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EURAC research WP 6 Synergy Grids guideline page 1 of 20

WP6 SYNERGY GRIDS

Guideline

MA 6.1 Analyses of actual building sites MA 6.2 Integration of buildings in Synergy Grids

MA 6.3 Integration of building clusters in Synergy Grids

Authors: Roberto Lollini, Roberta Pernetti (Eurac Bolzano), Sonja Geier (HSLU T&A – CCTP), Markus Berchtold (Nena Network), Andrea Moro (Regione Piemonte) Date: April 2014 Elaborated by: Roberta Pernetti EURAC research, T: +39 0471 055 645 [email protected] Viale Druso 1, I-39100 Bolzano



TableofContents

Introduction ................................................................................................................................................. 3

Summary ..................................................................................................................................................... 3

1. Nearly zero emission cluster evaluation ............................................................................................... 4

1.1. From the Enerbuild tool to the CABEE cluster tool .............................................................................. 4

1.2. Definition of a Synergy Grid ............................................................................................................... 5

1.3. Objectives .......................................................................................................................................... 6

1.4. Boundary ........................................................................................................................................... 6

1.5. Targeted synergies ............................................................................................................................. 7

1.6. Implementation strategies ................................................................................................................. 8

2. Action 6.1: Analyses of actual building sites ......................................................................................... 9

2.1. Framework for the selection of one or more building sites ............................................................... 10

2.2. Evaluation of synergies within the building clusters ......................................................................... 10 2.2.1 Analysis of energy indicators ....................................................................................................... 10 2.2.2 Analysis of common selected must‐indicators ............................................................................. 12 2.2.3 Analysis of potential synergies ..................................................................................................... 13 2.2.4 Elaboration of scenarios how nearly Zero Emission Buildings can be achieved ............................ 14 2.2.5 Discussion with local decision makers.......................................................................................... 14

3. Action 6.2: Integration of buildings in Synergy Grids ........................................................................... 15

4. Action 6.3: Integration of building clusters in Synergy Grids ............................................................... 17

Bibliography .............................................................................................................................................. 19

Appendix: CABEE Cluster Tool .................................................................................................................... 20



Introduction

With the adoption of the recast EPBD in 2010 (Directive 2010/31/EU), EU Member States faced new challenges. Foremost among them, moving towards new and retrofitted nearly-zero energy buildings, and the application of a cost-optimal methodology for setting min-imum requirements for both the envelope and the technical systems. In the Alpine Space Project Enerbuild, evaluation methods for ecological sustainable pub-lic buildings have been elaborate, including evaluation of energy consumption, of the lo-cation and facilities, process and planning quality, health and comfort. CABEE project goes one step further and has as an objective of work package 6 to focus not only on a single building, but to consider a whole building cluster for emission evalua-tion. The overall topic of the work package is to study opportunities, how at building clus-ter level or community scale a transformation of the building stock into nearly Zero Emission Building nZEB can be reached. The target for existing buildings to become nearly Zero Emission in most cases is very difficult to reach. By using concepts on community scale this transition can be realized more easily. The project is not entering the topic of urban planning and sustainable urban develop-ment. Other EU-projects investigate on this topic. Rather more arising from a bottom-up perspective, sustainable measures are investigated on building cluster scale, by taking into account the feasibility to extend the cluster boundary to other surrounding buildings and other clusters. One concept to reduce energy consumptions on community scale is the application of Mi-cro Smart Grids. They allow to manage electrical energy demands and consumptions effi-ciently and can have the positive effect to strengthen users awareness on energy consumption. Community-wide renewable energy or central plant applications on larger scale and higher efficiency give opportunities to reduce thermal energy consumptions [1]. Within a building cluster further synergies on ecological, social and economic level can be strived for. Exchangeable goods and services shall allow a building cluster to reach nZEB and sustainability targets.

Summary

The document gives an overview on work package 6, called Micro Smart Energy Grids in CABEE project. The purpose of the document is to develop work package subjects in detail by defining a guideline which allows project partners to proceed in a common way and to produce interchangeable outcomes. Although the focus in the application form was set to Smart Grids, a more holistic ap-proach was decided to apply. Instead of concentrating the WP-activities only on electric energy and Micro Smart Grids, groups of buildings (building clusters) and their potentials in acting as a whole by creating synergies, was defined as the main theme of the WP. The sustainability performance of a building cluster is assessed through environmental, social and economic indicators in accordance to CEN/TC 350 and EN 15643-11. As instru-ment for the assessment, the CABEE cluster tool was developed, including a series of indi-cators tailored to the assessment of building clusters and synergies for reaching nearly Zero Emission Clusters. The document gives further a definition of Synergy Grids, describes the assessment ap-proach, gives indications on the cluster boundary, on objectives, targets and on imple-mentation strategies for reaching the goals of the case studies on local level. The single actions are described with necessary tasks, timelines, deliverables and outputs.

1 CEN/TC 350 EN 15631: 2010 Sustainability of construction works - Sustainability assessment of buildings - Part 1: General framework



1. Nearly zero emission cluster evaluation

1.1. From the Enerbuild tool to the CABEE cluster tool

Within EB-project2 the Enerbuild tool was developed and established as evaluation tool for public buildings. Within CABEE project the tool was adopted to the evaluation of building clusters and integrated into CESBA framework3. Necessary modifications and adaptations were done in order to quantify emission on a chosen cluster boundary. Additional criteria in evaluation and projection were investigate, to acquire advantages created through the consideration of building clusters instead of single buildings.

Figure 1: Energy efficiency and sustainability evaluation on building scale and on cluster scale. Measures for improvements are carried out either on building or

on cluster scale. Measures at building scale not in all cases can reach sufficient high performances like from nZEBs required. Some buildings even through high refurbishments and implementation of renewable energies cannot achieve this requirement. In this case optimizations on build-ing cluster level with an evaluation on cluster level can bring to enhanced results.

2 http://www.enerbuild.eu/publications/2012-02_ENERBUILD-result_6_2-4.pdf 3 http://www.cesba.eu/

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Building evaluation

Measures at building scale

Cluster evaluation

Measures at cluster scale



Figure 2: Through measures at building scale not all buildings can reach the target to become a nZEB. Some buildings rest high emission buildings (hEB). By interventions on cluster level the nZEB target can be reached for the whole cluster.

The implementation of new technologies as Smart Grids or renewable energy production on building sites, take time to be set up on large scale. Therefore a bottom-up approach on small scale is applied to test new technologies and to prepare small building clusters for their integration into larger intelligent grids. Further than the application of state-of-the-art technologies, the exploitation of possible interactions and relationships at building cluster level in a more holistic approach are investigated trough Synergy Grids. This should aim at reaching nearly Zero Emission Clusters. Synergies go beyond exchange of energy and take into account all other possible goods, solutions and services which can be exchanged or synergically shared. Synergy grids can operate where other implemented grids on higher level (municipality distribution systems) do not act or do not operate advantageous in the perspective of a small building cluster.

1.2. Definition of a Synergy Grid

According to Oxford dictionary the definition of synergy is: the interaction or cooperation of two or more organizations, substances, or other agents to produce a combined effect greater than the sum of their separate effects [2].

Wikipedia describes a Synergy in the following way: “Synergy is two or more things func-tioning together to produce a result not independently obtainable. The term synergy comes from the Greek word synergia from synergos, meaning "working together". …In the context of organizational behavior, following the view that a cohesive group is more than the sum of its parts, synergy is the ability of a group to outperform even its best individ-

nZEB

nZEB

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hEB

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nZEB

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nZEB

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nZECluster

Measures at building scale Measures at cluster scale

n. Zero Emission Buildings n. Zero Emission Cluster



ual member. These conclusions are derived from the studies conducted by Jay Hall on a number of laboratory-based group ranking and prediction tasks” [3].

For the CABEE project the following definition is proposed:

“ A Synergy Grid allows a building cluster to develop and implement joint strategies in the area of sustainability and energy efficiency. It is originated by transformation strategies of the building cluster, considering synergies and system effects over the entire life-cycle of a building, in order to achieve a nearly Zero Emission Building cluster with environmental, economic and social added values.”

1.3. Objectives

Many building clusters could benefit from different optimizations which cannot be achieved by the single building within the cluster through individual action. Many optimi-zations and concepts require the cooperation and interaction of different actors on differ-ent matters, which in exchange allows to acquire a heightened value. As retrofit interventions and optimizations on buildings, which have many owners and us-ers are difficult to realize, the concept of synergies can give a contribution to explain the benefits for acting at building cluster scale. The objectives within WP6 CABEE project is the highlighting of possible synergies by:

providing a framework for introducing different synergies at building cluster level providing exemplary implementation studies of synergies providing a framework for developing strategies for neighborhood infill and renova-

tion programs providing cost-optimal energy efficient solutions providing support for decision-making providing proposal to adjust the legal framework (for example spatial laws, build-

ing laws...) for the implementation of Synergy Grids developing a common standard for design and illustration of Synergy Grids

1.4. Boundary

The boundaries for a Synergy Grid are not fixed. The borders are dynamic to give the building cluster the possibility to growth and to shrink. Especially when new buildings are erected, the incorporation of new buildings can be advantageous. Furthermore different evaluation categories may have different boundaries. This allows to give more flexibility to the system i.e green spaces may be outside the environmental boundary. Moreover the evaluated area must not correspond to a neighborhood or a dis-trict from the urban-sociological point of view. Within CABEE the decision was taken to investigate clusters with about 15 buildings in or-der to find comparable structures. To quantify the improvements through synergies, the boundary should possibly be same for all categories in the CABEE cluster tool.



Figure 3: Building cluster boundary and neighborhood boundary

As buildings are connected to the public grid for water supply, electricity, thermal energy and waste management, national, regional and municipal regulations implicate whether synergies can be established and within which borders. Legal framework in each region will define in a first step preliminary boundaries, i.e.: in Germany electric energy can be distributed on neighborhood level if no “public” grid is used. Possible boundaries

Owner oriented boundary: cluster of public buildings, cluster of condomini-um ownerships, cluster of mixed public and private buildings

Technology oriented boundary: cluster of buildings connected to district heating, to smart grid

Mobility oriented boundary: cluster of buildings connected to public transport net (bus stop, cycle way)

Urban boundary: block of buildings, delimitation from streets, ways, build-ing typology

As spatial extension for the CABEE project a building cluster, forming a small group of buildings should be chosen. The building cluster should consist in at least two buildings, which lie close to one another and should include around 15 buildings. To have different customers (residential, commercial..) within the building cluster can be advantageous, but is not a precondition for the choice of the cluster.

1.5. Targeted synergies

Within CABEE project the CABEE Cluster tool was elaborate for evaluating weighty ecolog-ical, social and economic criteria for the construction and refurbishment of building clus-ters. By doing an ecological evaluation for a whole building cluster, above-average performances and below-average performances of buildings can be compensate. Building clusters benefit not only from optimization of supply and demand, but also from appropri-ate storage systems, controls and algorithms and distribution networks [4]. The calculation is balanced on all buildings within the set boundary and not only on single building level. In this way different strategies for building construction and refurbishment can be chosen: new buildings with highest performance, historic buildings with moderate performance,

Building cluster Neighborhood



general renovations with cost-effective or cost-optimal level. New high performance buildings which are integrated in existing clusters, allow to have surplus of energy & ser-vices, which can help buildings with lacks to enhance their performance. The assessment method explained in the CABEE cluster tool including assessment criteria and description of assessment of indicators, follows in a separate document.

1.6. Implementation strategies

The promotion of the concept of synergies in-between a building cluster can be developed on different levels:

economic advantages as sharing investments and maintaining costs environmental advantages as CO2 emission reduction social cohesion and good neighborhood relation

Good communication between the users and involved stake holders, collective interests and benefits should push building clusters to adapt energy optimization concepts.



2. Action 6.1: Analyses of actual building sites

Main Action 6.1 is focused on the analysis of a building cluster and the evaluation of possi-ble synergies within the cluster. The elaboration of different scenarios shall show, how nearly Zero Emission building clusters can be achieved. During the process, a discussion and consultation of decision makers is required for defining a common vision and objec-tives, considering the CESBA framework and in particular Enerbuild, Openhouse, Super-building projects approach towards sustainability issues. Depending on the chosen project, the decision makers can be public representatives of municipalities, private owners, ten-ants or investors. The objective is to provide good advices to decision-makers. Working tasks are structured in the following way: 1. elaboration of a common definition for synergy grids, including their features and per-

formance figures 2. evaluation of synergy grids on 10 building sites (private or public) including their sur-

roundings in a range of 200 metres. analysis of energy flows analysis of synergies

3. elaboration of 3 possible scenarios for showing ways how NZEBs together with their close neighbourhood can be achieved for each site / building

4. discussion of scenarios with responsible local bodies and site owners. One output of this action shall be a report/handbook with best practices of the different regions as well as the demonstration of possible synergies with required conditions for reaching them. Scenarios for 10 building sites how to transform building cluster into nearly Zero Emission neighborhoods are described.

Common definition

Analyses of actual building sites

MA 6.1 Duration09/2012 ‐ 12/2014

Scenarios forachiving nZEBs

Evaluation of synergy gridson 10 building sites

Output: Report on scenarios

Time schedule for actions 6.1 1. Identification and selection of one or

more building sites, in total 10 building sites (at least one per PP) for a synergy grid

LP(2), PP3(1), PP4(2), PP5 (1), PP6(1),PP7 (1), PP8(1), PP9(1), PP10(1), NMS1 (1)

30.06.2013

6.1 2. Assessment of 15 must indicators within the building cluster

LP, PP3, PP4, PP5, PP6, PP7, PP8, PP9, PP10, NMS1

31.03.2014

6.1. 2. Evaluation of synergies of 15 must indi-cators within the building cluster

LP, PP3, PP4, PP5, PP6, PP7, PP8, PP9, PP10, NMS1

31.03.2014



6.1 3. Elaboration of 3 scenarios/variants for showing ways, how NZEBs together with their close neighbourhood can be achieved for every synergy grid

LP, PP3, PP4, PP5, PP6, PP8, PP9, PP10

30.06.2014

6.1 4. discussion with responsible local bodies(end of the task) and delivery of filled tem-plate on MA 6.1.

LP, PP3, PP4, PP5, PP6, PP8, PP9, PP10

31.12.2014

2.1. Framework for the selection of one or more building sites

Each partner should investigate in its region on best practices on smart grids or smart building clusters. The relevance of the best practice in the region must be clear. Moreover following criteria must be taken into account:

reproducibility of the grid (in the own region/ in a partner region) adaptability of the grid (in the own region/ in a partner region) costs (of the investment/maintenance) benefits

By collecting the outstanding solutions and by making them easily accessible to other partners, good solutions should become easily transferable from one region to another. If no suitable smart grid best practice could be found, a building cluster with good poten-tials should be chosen to study the inclusion of a Smart Grid or the transformation of the building cluster in a synergy grid. The requirements for the building cluster should take into account, the availability of required data and the availability of cooperation by deci-sion makers. Required data are:

plan documentation of the building cluster and its surroundings energy data such as electrical and thermal energy consumption of different users,

grid relevant data energy characteristics of the buildings, energy certificates if available additional data such as mobility, water, waste.

2.2. Evaluation of synergies within the building clusters

For being able to evaluate if synergies can be applied to a building cluster, as a first step the assessment and analysis of indicators of the building cluster is necessary. The assess-ment will be done by applying the CABEE cluster tool. In total 15 indicators (must-indicators) are assessed by all partners. 5 must-indicators refer to the part sub-category energy, 10 other must-indicators were established through a common choice of all part-ners and are distributed on all other sub-categories. For the assessment of indicators, the quality of gathered information is crucial. Should the required documents prove to be insufficient for issuing, the assessor shall make assump-tions and exemplify.

2.2.1 Analysis of energy indicators

As first assessment part, the sub-category Energy and its 5 must-indicators should be ana-lyzed and assessed. They are listed under the category Environmental Quality and consist in the analysis of thermal and electrical energy of the cluster as well the analysis of the Virtual Power System (VPS), if the cluster is connected to one.



B Environment

Energy

B 5 Primary energy for heating

B 6 Primary energy for cooling

B 7 Primary energy for public lighting

B 8 Intensity of greenhouse emissions per capita

B 9 Electric energy optimization through Virtual Power System

Table 1: Five energy must-indicators

The building cluster should be analyzed in terms of: thermal energy consumption: space heating and cooling; thermal energy

generation within the cluster (GSHP, CHP or bio mass); thermal storage domestic hot water: occupancies with high demands (hotels, restaurants,

residential) and occupancies with little demand but high production (indus-try)

electric energy consumption of building cluster electric energy consumption of public lighting DC power generation: CHP; PV; wind; DC storage

The analysis of the Smart Grid includes the study of the different smart grid compo-nents such as the:

electrical distribution network energy generation sources network software that optimizes power demand and supply power use controllers [1]

Estimation of Energy indicators For the energetic indicators (B5-B8), energy certificates from certification programs can be help as input data for thermal and electric energy. Similarly the collection of the ener-gy bills can give a good overview on overall thermal energy consumption and electric en-ergy consumption of buildings. Estimation of Primary Energy for Heating / Cooling The primary energy can be estimated through energy simulation tools like Passive House Planning Package (PHPP), Minergie, ProCasaClima etc. With the help of these tools an es-timation of the energy performance and the energy demand (Kwh/m²a) for heating, cool-ing and Domestic Hot Water in a building can be done. To estimate the energy demand, certain minimum parameters like climate zone of the building, typology of the construction, type of heating system, usable floor area, heated area, enclosed volume, number of dwelling units, number of people living in the building, dispersant area are needed. Besides referring to the dispersant area, it is necessary to de-fine the U-value for walls, floors, basements, roofs and windows, as well as the g-value for windows.



The needed parameters can vary substantially from one building to another in a cluster. Basically they are conditioned by the epoch of construction ( U-values, architectural char-acteristics), the typology of building (single-family house, terraced-house, multi-family house, apartment block…) and its final use (housing, public use, office, commerce…). The energetic legislation of each partner region, according to the year of construction, give indications on minimum U-values. On basis of on-site inspection with a photo- documentation and the study of construction plans, these fundamental information should be collected and used as input data for an estimation in PHPP. When dealing with several buildings of the same characteristics, data can be extrapolated to the overall surface and volume of the buildings. When building constructions and typol-ogies differ one from another a separate estimation for each building should be done. The more precise the building stock of the cluster is assessed, the more detailed feasibil-ity studies and future interventions can be planned and implemented.

2.2.2 Analysis of common selected must-indicators

Once the analysis of the sub-category Energy is done, a more enlarged analysis of ecologi-cal, social and economic indicators is elaborate.

The following 10 must indicators, distributed on different categories (Process Quality, En-vironmental Quality, Social Quality, Economic Quality) are assessed:

A Process

Quality of planning A 1 Process and planning quality

Cluster management A 3 Communication and information management

B Environment

Quality of site B 2 Preservation of land and soil

Water B 13 Intensity of rainwater usage

Waste B 14 Avoidance of waste, accessibility to waste sort-ing facilities

C Society

Facilities & services C 1 Proximity to services and leisure facilities

Mobility C 8 Access to public transport

Cluster activities C 11 Social gatherings and common cluster activities

Comfort C 14 Exploitation and optimization of local resources: sun, daylight, wind

D Economy

Market value D 4 Economic advantage of cluster in comparison to single buildings

Table 2: Ten must-indicators from different sub-categories



An optimal evaluation for the building cluster is reached by assessing all 40 indicators of the CABEE tool. Take into account, that for action 6.2 a building and for 6.3 at least 10 buildings have to be integrated into the cluster. The choice of the assessed indicators should reflect the potential for creating synergies and to improve the indi-cators in a next step.

2.2.3 Analysis of potential synergies

On a building cluster scale, an optimization of the energy consumption can be reached by creating synergies. Decision makers are involved through the ROC and updated on the analyzed building clus-ter. By including users/inhabitants in the decision-making process and informing them on sustainability issues, a better collaboration and better results in reduction of energy con-sumptions can be achieved. Educated and enlightened users contribute to the success of the established synergies and their maintenance.

Figure 4: Analysis of synergies of a building cluster with enlightened us-

ers/inhabitants on energy and sustainability issues for achieving nZEB clusters. 1. Synergies can concern applications for common energy generation (on-site generation

from on-site renewables & on-site generation from off-site renewables), energy stor-age and Virtual Power Systems (VPS). If a VPS does not exist within the cluster, a con-cept should be elaborated. Possible synergies are discussed and objectives set to achieve at least one nearly Zero Emission Building within the building cluster. To compare the effect and enhancement of the established synergies the 5 energy must-indicators (B5 - B9) from table Table 1 are reassessed.

2. Other potentially exchangeable goods and services in-between the cluster are investi-gated. They can concern process quality, environmental quality, social quality and economic quality, i.e.:

……

Assessment of clusterMeasures at clusterlevel; assessment

……

MA 6.1 Analyses of actual building sites



grey water: rain water capturing on new buildings; common grey water treatment, storage and redistribution systems

parking spaces green spaces waste: solid waste capture and storage; bio generation plant maintenance services: HVAC maintenance, green spaces transport: car sharing, bike sharing, electric vehicles [4] To compare the effect and enhancement of the established synergies the 10 must-indicators from different sub-categories of Table 2 have to be reassessed:

2.2.4 Elaboration of scenarios how nearly Zero Emission Buildings can be achieved

Possible scenarios are elaborated for showing ways how nearly Zero Emission Buildings can be achieved. The definition and calculation method of nearly Zero Emission Build-ing will be elaborated in main action 4.1 Development of an Alpine-wide Guideline on nearly Zero Emission buildings and integrated into CESBA. Scenarios include strategies for the reduction of energy consumption (ther-mal/electrical) as well as scenarios for power generation within the building cluster.

Reduction of electrical energy through usage of energy efficient appliances, lighting systems

Reduction of thermal energy through refurbishments of the building enve-lopes, exchange of obsolete thermal power plants

Better exploitation of natural sources for daylight, solar thermal gains and natural ventilation through neighborhood planning and managing

On-site power generation on local rooftop solar, small hydropower, wind projects

A total three scenarios or three variants of the same scenario must be elaborate dis-tinguishing themselves through intervention strategies for reaching the nZEB target. As an example the following structure can be used:

Scenario 1: optimization of building cluster with focus on thermal energy optimization (refurbishment, demolition and possible rebuild, on-site ther-mal energy generation)

Scenario 2: optimization of building cluster with focus on electric energy optimization (energy efficient appliances, artificial lighting, on-site electric energy production and storage)

Scenario 3: optimization of building cluster with mix of thermal and electri-cal energy optimization

2.2.5 Discussion with local decision makers

The 3 scenarios or variants are discussed with decision makers (investors, municipali-ties).



3. Action 6.2: Integration of buildings in Synergy Grids

Action 6.2 foresees the study of integration of an additional building into a synergy grid. If possible the building cluster of main action 6.1 should be used. The integration of school buildings/commercial buildings in a cluster with residential buildings can allow to have positive synergies.

1. The assessment of the integrated building has to be executed like in action 6.1 by applying the CABEE cluster tool. The additional building is taken into account for at least all 15 must indicators, which were assessed in 6.1. The new balance is cal-culated taking established new synergies into account.

2. Technical and economic feasibility for plugging a new building to a an existing building cluster with existing synergies are evaluated. feasibility study is done fore 10 building sites with existing or presumed

synergy grids (e.g. good-practice-examples from WP6.1), at least one per partner (LP,PP4, PP5,PP6, PP7, PP8, PP9, PP10).

Figure 5: Integration of one building into a synergy grid with enlightened us-ers/inhabitants on energy and sustainability issues.

Integration of buildings into synergy grids

……

MA 6.2 Integration of buildings in Synergy Grids



Time schedule for actions 6.2 1. Integration of one additional building

into building site LP(2), PP4(1), PP5 (2), PP6(1), PP7 (1), PP8(1), PP9(1), PP10(1)

30.06.2014

6.2 2. Evaluation of technical and economic feasibility for plugging a new building to a an existing building cluster

LP, PP4, PP5, PP6,PP7, PP8, PP9, PP10

31.12.2014

6.2 3. Delivery of filled template on MA 6.2 LP, PP4, PP5, PP6,PP7, PP8, PP9, PP10

31.12.2014



4. Action 6.3: Integration of building clusters in Synergy Grids

Some buildings cannot reach the goal of nearly zero emission. But they may reach it in co-operation with their neighbouring buildings (statistic evaluation, exchange of energy, en-ergy storage, economics of scale, economic advantages etc.). Action 6.3 foresees, for each for each participating region a feasibility study for the inte-gration of at least 10 buildings into building cluster for reaching nearly zero emission clus-ters.

1. The assessment of at least 10 surrounding buildings is executed by using the CABEE cluster tool. 15 must-indicators of new buildings have to be assessed and balanced with the cluster evaluation.

2. In a second step synergies are analyzed in-between the 10 new buildings, and between the new buildings and the building cluster (at least for 15-must indica-tors). The assessment of the overall cluster is executed taking into account all feasible synergies.

3. Solutions for integration of many buildings in Synergy Grids are elaborate and documented in a feasibility study.

Figure 6: Integration of several buildings into a synergy grid with enlightened

users/inhabitants on energy and sustainability issues.

Integration of clusters into synergy grids

……

MA 6.3 Integration of neighboorhoods in Synergy Grids



Time schedule for actions 6.3 1. Integration of 10 buildings into building

site (assessment of synergies of 15 must indicators)

LP(2), PP5 (1), PP6(1), PP7 (1), PP8(1), PP9(1), PP10(1), NMS1 (1)

30.06.2014

6.3 2. Feasibility study for the integration of building clusters in synergy grids

LP, PP5, PP6, PP7, PP8, PP9, PP10, NMS1

31.12.2014

6.3 3. Delivery of filled template on MA 6.2 LP, PP5, PP6, PP7, PP8, PP9, PP10, NMS1

31.12.2014



Bibliography

[1]. Ekanayake, Janaka. Smart Grid: Technology and Application. United Kingdom : John Wiley & Sons, 2012. [2]. Dictionary, Oxford. http://oxforddictionaries.com/; accessed on 12/2013. [3]. Wikipedia. Accessed on 12/2013. [4]. Nils Larsson, Serge Salat, Loeiz Bourdic, Frank Hovorka. Synergy Zones for provision of technical services to small urban areas. s.l. : iiSBE, 2012. [5]. N.Becker. Forum Resourcen Effizienz. Ressourceneffizienz im Bauwesen. s.l. : VDI Zentrum Ressourceneffizienz, 2011. [6] European Commission (2006) European Smart Grids Technology Platform: Vision and Strategy for Europe's Electricity, http://ec.europa.eu/research/energy/pdf/ smart-grids_en.pdf (accessed on 4 August 2011). [7] Department of Energy and Climate Change, UK, Smarter Grids: The Opportunity, De-cember 2009, http://www.decc.gov.uk/assets/decc/what%20we%20do/uk%20 ener-gy%20supply/futureelectricitynetworks/1_20091203163757_e_@@_smartergrid sopportunity.pdf (accessed on 4 August 2011). [8] U.S. Department of Energy, Smart Grid System Report, July 2009, http://www.oe .energy.gov/sites/prod/files/oeprod/DocumentsandMedia/SGSRMain_090707_lowres.pdf (accessed on 4 August 2011). [9] A Compendium of Modern Grid Technologies, July 2009, http://www.netl.doe.gov/ smartgrid/referenceshelf/whitepapers/Compendium_of_Technologies_APPROVED _2009_08_18.pdf (accessed on 4 August 2011). [10] European Commission, ICT for a Low Carbon Economy: Smart Electricity Distribution Networks, July 2009, http://ec.europa.eu/information_society/activities/sustainable_growth/docs/sb_publications/pub_smart_edn_web.pdf (accessed on 4 Au- gust 2011) [11] World Economic Forum (2009) Accelerating Smart Grid Investments, http:// www.weforum.org/pdf/SlimCity/SmartGrid2009.pdf (accessed on 4 August 2011). [12] DKE Normungsroadmap E-Energy / Smart Grids 2010 [13]. (EPRI), Electric Power Research Institute. Smart Grid Demonstration Initiative. Two Year Update. California : s.n., 2010. [14] DGNB Neubau Stadtquartiere. DGNB Handbuch für nachhaltiges Bauen. Deutsche Ge-sellschaft für Nachhaltiges Bauen e.V., 2012 [15] La démarche HQE –Aménagement. Pour la réalisation d’opérations d’aménagement durable. HQE Association, Novembre 2011 [16] SBTool Urban Indicators. iiSBE,June 2012 [17] Leed 2009 for neighborhood development rating system. Congress for the New Ur-banism, Natural Resources Defense Council, and the U.S. Green Building Council, April 2012 [18] Nachhaltige Quartiere. SMEO. Herausforderung und Chancen für die urbane Entwick-lung, Bundesamt für Raumentwicklung ARE, Bundesamt für Energie BFE, [19]2000-Watt-Gesellschaft.Bilanzierungskonzept. EnergieSchweiz für Gemeinden, Stadt Zürich, SIA Schweizerischer Ingenieur- und Architekten verein, März 2012



Appendix: CABEE Cluster Tool



CABEE Cluster Tool for existing building clusters CABEE CLUSTER TOOL, version April 2013 Created by Roberta Pernetti, Roberto Lollini (Eurac research), Giulia Barbano (iISBE Italia), Andrea Moro (Regione Piemonte), Markus Berchtold (NENA Network) Content

General Remarks 3 Assessment structure 3 Assessment indicators 4 Must indicators 5

A Process quality 6 Quality of Planning 6

A 1 Process and planning quality 6 A 2 Risk management 7

Cluster management 7 A 3 Communication and information management 7 A 4 Synergy management 8

B Environmental quality 8 Quality of site 8

B 1 Continuity of urban areas 8 B 2 Preservation of land and soil 9 B 3 Preservation of the existing built environment 9 B 4 Impact on surrounding buildings 10

Energy 10 B 5 Primary energy for heating 10 B 6 Primary energy for cooling 11 B 7 Primary energy for public lighting 11 B 8 Intensity of GHG emissions 12 B 9 Electric energy and Virtual power systems (VPS) 12

Building materials 13 B 10 Building materials and construction (OI3 index) 13

Water 14 B 11 Permeability of land 14 B 12 Intensity of grey‐water treatment 14 B 13 Intensity of rainwater usage 15

Waste management 15 B 14 Avoidance of waste, accessibility to waste sorting facilities 15

C Social quality 16 Facilities and services 16

C 1 Proximity to services and leisure facilities 16 C 2 Collective facilities and outsourcing of services 17 C3 Flexibility of residential buildings 17 C 4 Flexibility of use of nonresidential spaces 17 C 5 Availability of green spaces 18 C 6 Access to a broadband communication network 18

Mobility 19 C 7 Contiguity of bicycle and car routes 19



C 8 Access to public transport 19 C 9 Accessibility of pedestrian spaces 20 C10 Shared mobility 21

Cluster activities 21 C 11 Social gatherings and common cluster activities 21 C 12 Local production of food 21 C 13 Objective/ subjective safety measures 22

Comfort 22 C 14 Exploitation of local resources: sun, daylight, wind 22 C 15 Thermal comfort of outdoor areas 23 C 16 Prevention of noise 24 C 17 Air quality monitoring 24 C 18 Light pollution 24

D Economic Quality 25 Equity 25

D 1 Affordability of housing property 25 D2 Affordability of housing rental 25

Economy 26 D3 Life cycle cost 26

Market value 26 D4 Economic advantage of cluster in comparison to single buildings 26



General Remarks

CABEE Cluster Tool assists to document and assesse the energetic and ecological quality of a building cluster. By creating synergies, building clusters become more sustainable than their initial situation. The performance is assessed through a series of indicators, which are chosen to provide information for understanding and enhancing the relationships be-tween, energy use, environmental, social and economic elements in long-term sustainabil-ity. Overall objective is to transform building clusters into Nearly Zero Emission Cluster. The boundary of the cluster can be flexible and dynamic in order to give the building clus-ter the possibility to growth and to shrink. Furthermore different evaluation categories may have different boundaries. This allows to give more flexibility to the system i.e green spaces may be outside the environmental boundary.

Assessment structure

In total 40 indicators, assigned to the main categories Process Quality, Environmental Quality, Social Quality and Economic Quality, allow to demonstrate quantitative improve-ments by assessing indicators before and after the consideration of potential improve-ments and especially of synergies within a building cluster. PROCESS QUALITY A 100 points

ENVIRONMENTAL QUALITY B 400 points

SOCIAL QUALITY C 400 points

ECONOMIC QUALITY D 100 points Table 3: Assessment categories with maximum point distribution The assignment of indicators is related to the location of the cluster to be assessed. De-pending on the determination of rural, urban and metropolitan areas. Some indicators have not to be assessed for rural areas, whereat for urban and metropolitan areas they are required.



Assessment indicators

40 indicators enable to measure the progress of a building cluster towards a Nearly Zero Emission Cluster. The indicators include several topics such as quality of planning, cluster management, quality of site, energy, building materials, water, waste, facilities & services, mobility, cluster activities, com-fort, equity, economy and market value.

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A Process 100A 1 Process and planning quality M 25 x x xA 2 Risk management 25 x x xA 3 Communication and information management M 25 x x xA 4 Synergy management 25 x x x

B Environment 400B 1 Continuity of urban areas 15 x xB 2 Preservation of land and so il M 15 x x xB 3 Preservation of the buit environment 15 x x xB 4 Impact on other sourrounding buildings 15 x xB 5 Primary energy for heating M 40 x x xB 6 Primary energy for cooling M 40 x x xB 7 Primary energy for public lighting M 40 x x xB 8 Intensity of greenhouse emissions per capita M 40 x x xB 9 Electric energy optimization through Virtual Power System (VPS) M 20 x x x

Building materials B 10 OI3 index (building materials and construction) 100 x x xB 11 Permaeability of land 15 x x xB 12 Intensity of greywater treatment 15 x x xB 13 Intensity of rainwater usage M 15 x x x

Waste B 14 Avoidance of waste, accessibility to waste sorting facilit ies M 15 x x x

C Society 400C 1 Proximity to services and le isure facilit ies M 20 x x xC 2 Collective facilities and outsourcing of services 20 x x xC 3 Flexibility of residential buildings 20 x x xC 4 Flexibility of use of non residential spaces 20 x x xC 5 Availability of green spaces 20 x x xC 6 Access to broadband communication network 20 x x xC 7 Contiguity of bicycle and car routes 20 x x xC 8 Access to public transport M 20 x x xC 9 Accessibility of pedestrian spaces 20 x x xC 10 Shared mobility 20 x x xC 11 Social gatherings and common cluster activities M 25 x x xC 12 Local production of food 25 x x xC 13 Objective / subjective safety 25 x x xC 14 Exploitaton and optimization of local resources: sun, daylight, wind M 25 x x xC 15 Thermal comfort of outdoor areas 25 x x xC 16 Prevention of noise 25 x x xC 17 Air quality monitoring 25 x xC 18 Light pollution 25 x x x

D Economy 100D 1 Affordability of housing property 25 x x xD 2 Affordability of housing rental 25 x x x

Economy D 3 Life cycle cost 25 x x xMarket value D 4 Economic advantage of cluster in comparision to single buildings M 25 x x x

CABEE Cluster Tool

ECONOMIC QUALITY

Quality of planning

Cluster managementPROCESS QUALITY

ENVIRONMENTAL QUALITY

Quality of site

SOCIAL QUALITY

Comfort

Mobility

Facilities & services

Energy

Water

Cluster activities

Equity

Table 4: Assessment indicators of CABEE Cluster Tool



Must indicators

Each sub-category has one or more must indicators. There are a total of 15 must indica-tors, 2 must indicators from the category energy, 8 from the category environmental qual-ity, 4 from social quality and 1 from the category economic quality.

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A Process 100Quality of planning A 1 Process and planning quality M 25

Cluster management A 3 Communication and information management M 25

B Environment 400Quality of site B 2 Preservation of land and soil M 15

B 5 Primary energy for heating M 40B 6 Primary energy for cooling M 40B 7 Primary energy for public lighting M 40B 8 Intensity of greenhouse emissions per capita M 40B 9 Electric energy optimization through Virtual Power System (VPS) M 20

Water B 13 Intensity of rainwater usage M 15

Waste B 14 Avoidance of waste, accessibility to waste sorting facilities M 15

C Society 400Facilities & services C 1 Proximity to services and leisure facilities M 20

Mobility C 8 Access to public transport M 20

Cluster activities C 11 Social gatherings and common cluster activities M 25

Comfort C 14 Exploitaton and optimization of local resources: sun, daylight, wind M 25

D Economy 100Market value D 4 Economic advantage of cluster in comparision to single buildings M 25

SOCIAL QUALITY

ECONOMIC QUALITY

CABEE Cluster Tool

EnergyENVIRONMENTAL QUALITY

PROCESS QUALITY

Table 5: Must indicators Assessment process CABEE For the evaluation of building clusters within WP6 of CABEE not all indicators have to be assessed. Partners assess obligatory the 15 must indicators and add further add relevant indicators for their building cluster. Indicators are assessed before and after the establishment of synergies. The assessment within CABEE allows to test the tool, which shall become in a long-term perspective an Input for CESBA. Scoring Each indicator has a score and a fixed benchmark explained in this guideline. Generally, a maximum and a minimum score have been established, and the other scores have to be assigned proportionally. For some indicators, the scores are determined by summing up separated points according to specific criteria. If it is not possible to collect all the useful data, which allow an accurate evaluation of one indicator or if the information are incomplete, assign zero points



A Process quality

Quality of Planning

A 1 Process and planning quality (M)

For the improvement of the sustainability of a building cluster, a diagnosis of the situation succeeded by an evaluation of the performance is necessary. During the conception of the project objectives and measurable goals have to be defined for future interventions and planning phases (planned- versus actual-comparison). They can concern refurbishments and new constructions within the cluster boundary as well as services during the operational phase of the cluster. The development of scenarios of the area can help to identify short-term, medium-term and long-term priorities to enhance social, environmental and economic quality of the cluster. As user acceptance is a highly important issue, the participation of the inhabitants and us-ers during the planning phase and implementation of actions should be striven. Sensitiza-tion and participation should be facilitated by giving the possibility in participation in the decision-making process. The effects and consequences of planned measures should be transparent for cluster members. Economic, social and environmental benefits should become comprehensible i.e. by explaining effects on basis of the indicators calculation. Intent: Improvement of environmental, social, economic quality of a building cluster Indicator: Document with planned quantitative and qualitative objectives, as a result of a participative planning process. Unit of measure: - Assessment method: As a basis, a detailed program should be elaborate by distinguishing environmental, social, economic improvements with goals tailored to the respective cluster. Life time of the buildings and users types (occupant, tenant, resident, commercial user) should be taken into account. Urgent interventions should become visible and become priority. Constraints, information on sustainability, sensitization of the users, consultation of the inhabitants, negotiation with the inhabitants, cooperation of the users are important pro-cesses which lead to common objectives and a project which is supported by the cluster inhabitants. Incentive schemes from national and regional programs (renovation of building stock, use of renewable energies, optimization of mobility) should be pointed out and made accessi-ble for the cluster community. Clusters should attract the interest of buildings outside of the boundary and facilitated their integration into the cluster.



Score: The maximum score for this indicator is 25. Assign:

10 points if a documentation of the decision making process exists and it is availa-ble;

15 points if planning variants were considered. 0 points otherwise

A 2 Risk management

Risk Management is an important requirement for all planning activities. Often planning and execution is not in line, because of changed framework conditions, which can be re-lated to timelines, founding, conflicting interest of stakeholders, executional works. The cluster should not fall into difficulties, when such unforeseeable circumstances occur. Intent: Limit the risk to achieve the established objectives Indicator: Risk management plan for each synergy with long time prediction during lifecy-cle Unit of measure: - Assessment method: A risk management plan should be elaborate for each planned improvement and each planned synergy within the cluster. Alternative solutions should limit the risk of losing im-portant synergies. Score: The maximum score for this indicator is 25. Assign 25 points if 100% of the synergies have a risk management plan and 0 points if none of the synergies has a risk management plan. Determine the other scores proportionally.

Cluster management

A 3 Communication and information management (M)

Intent: Ensure communication and information exchange to guarantee correct operation of the buildings and functioning of synergies within the cluster. Indicator: Percentage of trained users with access to information. Unit of measure: % Assessment method: Inhabitants should be continuously informed on on-going activities and on taken decisions. Identified needs by the inhabitants should be discussed and future actions adjusted ac-cordingly. As the actual performance of the cluster depends heavily on the users’ behaviour, a dis-tributed information grid should provide users with content, tailored for their needs and responsibilities.



In order to ensure the functioning of this information system, users need to be trained on its features, and on how to act when interventions are necessary. Score: The maximum score for this indicator is 25. Assign 25 points if all the adult inhabitants (100%) are trained or have access to the important Information of the building cluster and 0 points if no inhabitants are informed (0%). Determine the other scores proportionally.

A 4 Synergy management

Intent: Provide maintenance of operation of established services and synergies. Indicator: Maintenance plan Unit of measure: - Assessment method: Different services may need a management for being initiated, maintained and closed. Maintenance of operation in most cases will take the biggest effort and should therefore be organized in a structured way. For each synergy operational requirements are established and responsible persons named. Score: The maximum score for this indicator is 25. Assign 25 points if all the synergies have a management plan, and 0 points if none of the synergies has a management plan. Deter-mine the other scores proportionally.

B Environmental quality

Quality of site

B 1 Continuity of urban areas

Intent: Fill the gaps in the urban fabric and reduce sprawl. Indicator: Adjacency to urban areas. Unit of measure: % Assessment method: To assess this criterion, calculate the length of the cluster perimeter that is directly adja-cent to other urban clusters, and divide it for the length of the entire cluster perimeter. A cluster that fills completely a gap in the urban fabric would thus achieve a value of 100%.



Score: The maximum score for this indicator is 15. Assign 15 points if the calculated value is equal to 100% and 0 if it is equal to 0%. Determine the other scores proportionally.

B 2 Preservation of land and soil (M)

Intent: Reduce land consumption. Indicator: Re-use of previously occupied and contaminated land for buildings and infra-structure. Unit of measure: Assessment method: To assess this criterion, assign to each homogeneous part of the cluster a weight as fol-lows:

- undisturbed land weight = -1 - agricultural land weight = 0 - occupied land weight = 3 - contaminated land weight = 5

Multiply each surface area by its weight and sum the weighted values. Divided the weighted sum by the total area of the cluster. The result will be a number between -1 and 5. Score: The maximum score for this indicator is 15. Assign 15 points if the calculated value is equal or higher than 4 and 0 points if it is equal or less than 1. Determine the other scores proportionally.

B 3 Preservation of the existing built environment

Intent: Preserve the existing urban form, reduce the consumption of land and construction materials. Indicator: Percentage of preserved existing surface over the total. Unit of measure: % Assessment method: To assess this criterion, calculate the area of all the existing surfaces in the cluster (build-ing floors and street networks). Identify all of the surfaces that are preserved in the pro-ject, and divide their overall area by the total of the existing surfaces. Do not consider in the total all the surfaces which are not feasibly reusable. Score: The maximum score for this indicator is 15. Assign 15 points if the calculated value is



equal to 100% and 0 points if it is equal to 0%. Determine the other scores proportionally.

B 4 Impact on surrounding buildings

Intent: Quantify the impact on surrounding buildings. Indicator: Percentage of quality reduction of neighbouring buildings and areas. Unit of measure: % Assessment method: Environmental measures should not have negative effects on sur-rounding buildings and clusters. The impacts of shading, wind, vegetation, transport through established synergies should not influence negatively neighbouring buildings and areas outside the cluster boundary. Score: The maximum score for this indicator is 15. Assign:

15 if the cluster does not affect the comfort of surrounding area 7 if the cluster slightly affects the comfort of surrounding area 0 if the cluster influences negatively the existing surroundings

Energy

Besides the energy and economic criteria for evaluating the "sustainability" of heating buildings, environment-related criteria have importance. The overall assessment of heat-ing systems refers mainly to its efficiency and the use of energy sources with climate-relevant emissions for production and use. Efficiency can be increased by plant size. Therefore substitutions of outdated heating- and distribution systems, need to be re-thought not only on building level, but on neighborhood level where decentralized plants can be applied. Primary energy factors and CO2 emission factors accounts the depletion of energy sources within their life cycle, but also the renewability of energy. Therefore an increased use of renewable energies should be striven for.

B 5 Primary energy for heating (M)

Intent: Reduce the need of energy for heating. Indicator: Percentage of primary energy under the limit. Unit of measure: % Assessment method: To assess this criterion, estimate (via project assumptions, or via actual data if available) the heating primary energy requirement of every building in the cluster [kWh/m2]. Aggre-gate these values through a weighted mean over the floor surfaces, to obtain a cluster value. Divide the cluster heating primary energy requirement by the local limit and multiply by



100 to obtain the performance as a percentage ratio. Score: The score for this indicator is 40. Assign 40 points if the results evaluated through the as-sessment method is equal or less than the 25% of the local limit. For example, if the limit is 100 kWh/m2, to reach the maximum score, the cluster energy performance have to be equal or lower than 25 kWh/m2. Assign 0 points if the cluster en-ergy performance is equal of higher than the local limit. Determine the other scores pro-portionally.4

B 6 Primary energy for cooling (M)

Intent: Reduce the need of energy for cooling. Indicator: Percentage of primary energy over the limit. Unit of measure: % Assessment method: To assess this criterion, estimate (via project assumptions, or via actual data if available) the cooling primary energy requirement of every building in the cluster [kWh/m2]. Aggre-gate these values through a weighted mean over the floor surfaces, to obtain a cluster value. Divide the cluster cooling primary energy requirement by the local limit and multiply by 100 to obtain the performance as a percentage ratio. Score: The score for this indicator is 40. Assign 40 points if the results evaluated through the as-sessment method is equal or less than the 25% of the local limit. For example, if the limit is 100 kWh/m2, to reach the maximum score, the cluster energy performance have to be equal or lower than 25 kWh/m2. Assign 0 points if the cluster en-ergy performance is equal of higher than the local limit. Determine the other scores pro-portionally

B 7 Primary energy for public lighting (M)

Intent: Reduce the need of energy for public lighting. Indicator: Percentage of primary energy over the limit. Unit of measure: % Assessment method: To assess this criterion, estimate (via project assumptions, or via actual data if available) the public lighting primary energy requirement of all public areas in the cluster [kWh/m2]. Aggregate these values through a weighted mean over the floor surfaces, to obtain a clus-ter value. Divide the cluster public lighting primary energy requirement by the local limit and multi- 4 The target percentage for the cluster energy performances is set according to the objectives pro-moted by the European Commission within the Program Horizon 2020



ply by 100 to obtain the performance as a percentage ratio. Score: The score for this indicator is 40. Assign 40 points if the results evaluated through the as-sessment method is equal or less than the 25% of the local limit. For example, if the limit is 100 kWh/m2, to reach the maximum score, the cluster energy performance have to be equal or lower than 25 kWh/m2. Assign 0 points if the cluster en-ergy performance is equal of higher than the local limit. Determine the other scores pro-portionally

B 8 Intensity of GHG emissions (M)

Intent: Reduce the per capita emission of CO2. Indicator: Percentage of GHG emissions over the average. Unit of measure: % Assessment method: To assess this criterion, estimate (via project assumptions, or via actual data if available) the overall energy demand of the cluster as per the previous criteria. Associate each com-ponent to the CO2 emission factor corresponding to its vector [kg CO2 / kWh]. For each component, multiply the energy demand [kWh / m2] for its emission factor, to obtain the amount of CO2 emissions [kg CO2 / m2]. Sum all emissions from all components to obtain the overall CO2 emissions of the cluster. To obtain a relative performance, calculate the comparison metric as the average CO2 emissions as follows: Consider as energy demands the local limits as defined by laws, and define a credible sce-nario for the energy vectors (as the common choices available in the region). Calculate as average the amount of CO2 emissions the cluster would have if its energy demands corre-sponded to the limits, using the common energy vectors (and their emission factors), as above. The relative performance is thus calculated by dividing the actual performance by the emissions of the average scenario, and multiplying by 100 to obtain a percentage value. Score: The score for this indicator is 40. Assign 40 points if the results evaluated through the as-sessment method is equal or less than the 25% of the local limit. For example, if the limit is 100 kg CO2/m2, to reach the maximum score, the cluster green house emissions have to be equal or lower than 25 kg CO2/m2. Assign 0 points if the cluster energy performance is equal of higher than the local limit. Determine the other scores proportionally.

B 9 Electric energy and Virtual power systems (VPS) (M)

Intent: Optimize electric energy management within the building cluster. Indicator: Percentage of electric appliances connected to the VPS Unit of measure: %



Assessment method: A Virtual Power Systems integrates two existing concepts of Virtual Power Plant (VPP) and Virtual Power Load (VPL). It combines load, storages and genera-tions into a single aggregation. For the documentation of the VPS use the template from Alpenergy project (www.alpenergy.eu). Score: The score for this indicator is 20. Assign 20 points if all of the electric appliances are con-nected to the VPS and 0 points if none of them is connected. Determine the other scores proportionally.

Building materials

B 10 Building materials and construction (OI3 index)

The Eco- index 3 of the whole building illustrates the ecological optimization process In a simplified way. The lower the value of the OI3- index of a building, the less non-renewable energy resources are used and the less greenhouse gases and other emissions are produced in the production of construction materials, for the building under construc-tion and for rehabilitation and maintenance work. Out of a large number of environmental- and substance categories, the OI3 index uses the following three: - Global Warming Potential (100 years related to 1994) - Acidification potential - The demand for non-renewable energy resources Definitions: OI3- Guideline 20115 Intent: Assess the ecological quality of building materials Indicator: OI3 index Unit of measure: Assessment method: To calculate the OI3 points of a building a determination of the the weighted mean values of OI3-points of all construction is required. Assessment software: EcoSoft, Archiphysik. Documentation available in Enerbuild-tool from Enerbuild project. Score: The score for this indicator is 100. The reference value are included in the interval be-tween 38 and 295. Then, assign 0 point if the OI3 is equal or higher than 295 and 100 if OI3 is equal to 38. To determine the scores for other OI3 values apply the following equation: Score = 2 * (0,0007 * OI32

– 0,623 * OI3 + 123)

5 O3.-Indicator. IBO-Guidelines for calculating the OI3 indicators for buildings. Version 2.2, 2011



Water

B 11 Permeability of land

Intent: Minimize the interruption and pollution of natural water flows. Indicator: Percentage of permeable area over the total. Unit of measure: % Assessment method: To assess this criterion, calculate the area of all the permeable surfaces in the cluster (in-cluding street networks, public spaces, private gardens, and roofs). Identify all of the sur-faces that are permeable in the project, and divide their overall area by the total surface of the cluster. For semi-permeable surfaces, apply a permeability factor to account for the reduction in performance. Do not consider the surfaces that cannot be permeable (by laws and standards). Score: The score for this indicator is 15. Assign 15 points if the percentage of permeable soil is 0% and 0 points if the percentage is 100%. Determine the other scores proportionally.

B 12 Intensity of grey-water treatment

Grey water, which is water coming from domestic equipment other than toilets (e.g., bathtubs, showers, sinks, washing machines), can be recycled on-site for uses such as WC flushing, laundry, landscape irrigation. Intent: Maximize the potential for the use of grey-water instead using potable water when possible. Indicator: Rate of wastewater collection and treatment. Unit of measure: % Assessment method: To assess this criterion, calculate the volume of wastewater collected (and treated for re-use in the cluster (as a project estimate or through actual data, if available). Divide this amount by the overall water consumption in the cluster. Score: The score for this indicator is 15. Assign 15 points if the percentage of wastewater col-lected and treated is equal to 100% and 0 points if the percentage is 0%. Determine the other scores proportionally.



B 13 Intensity of rainwater usage (M)

Intent: Maximise the use of rainwater. Indicator: Rainwater collected in the zone for landscape irrigation and WC flushing and laundry. Unit of measure: % Assessment method: To assess this criterion, calculate the volume of rain water storage tanks (as a project es-timate or through actual data, if available). Divide this amount by the maximal storage tank volume for all cluster necessities. Score: The score for this indicator is 15. Assign 15 points if the results of the evaluation is equal to 100%, and if it is equal to 0%, assign 0 points. Determine the other scores proportional-ly.

Waste management

B 14 Avoidance of waste, accessibility to waste sorting facilities (M)

Intent: It aims to increase recycling quota and raise residents' awareness of source separa-tion and recycling. Indicator: Percentage of users located at less than 50 m from waste sorting facilities. Unit of measure: % Assessment method: To assess this criterion, calculate the amount of users who have access to waste sorting facilities in the same building or in its immediate vicinity. Consider only waste sorting fa-cilities which are connected to a waste management plan at cluster scale or wider. Quantify also efforts relating to waste avoidance and recycling through information and educational campaigns. Score: The score for this indicator is 15. Assign 15 points if the results of the evaluation is equal to 100% and 0 points if none of the inhabitants has easy access to waste sorting. Deter-mine the other scores proportionally.



C Social quality

Facilities and services

C 1 Proximity to services and leisure facilities (M)

Intent: To reduce the need for vehicular transport outside the cluster. Indicator: Percentage of users located at less than 300 m from the main services. For rural cluster villages, the score is assigned according to the available services and facilities within the cluster boundaries. Unit of measure: - Assessment method: To assess this criterion, it is necessary to identify all the main services located in the clus-ter and outside of it (only the nearest instance). Graphically, overlay to each of these ser-vices a circle with a 300 m radius. Calculate how many users are served by these services, by verifying which buildings are included in the radius of all the services. Possible services include: primary schools, health facilities (primary care, emergency ser-vices, pharmacies), grocery shopping, public services (post office, libraries) Possible leisure facilities include: theaters, museums, port halls. Calculate the percentage of service users of all the considered services For rural village cluster consider all the services within the analysed boundary and assign a score according to the classes reported in Table 6. Score: The maximum score for this indicator is 20. If the considered service supplies all of the cluster inhabitants assign:

8 points for each service belonging to Class 1 (Table 6) 6 points for each service belonging to Class 2 (Table 6)

If the service does not serve all the cluster inhabitants, assign a score proportional to the percentage of served users. Sum all the scores obtained by all the services up to the max-imum score. Class 1 Class 2

Local food shop Children's play area

Primary school Postal facility

Outdoor public access area Bank/cash machine

Leisure centre/sport centre Pharmacy

Medical centre/doctor

Table 6: Service Classes6 For rural village cluster, assign the points according to the classes reported in Table 6 if the service is included within the cluster boundary (do not consider the percentage of 6 Project LENSE - Stepping Stone 2 - Methodology Development towards a Label for Environmental, Social and Economic Buildings.



served users).

C 2 Collective facilities and outsourcing of services

Intent: To reduce housing costs for all users, and to maximize resource consumption in the cluster. Indicator: Percentage of users located at less than 50 m from communal housing services. Unit of measure: % Assessment method: Several household services can be moved from the private dwellings to communal areas, in order to reduce the square footage needed by the inhabitants and to optimize the con-sumption of soil, energy, and water in the cluster. This criterion allows to verify the amount of users who have access to communal facilities in the same building or in its immediate vicinity. Some example facilities include: laundry, meeting rooms, co-working office space, leisure time areas, dining hall, kitchen, gym. Score: The score for this indicator is 20. Assign 20 points if all the inhabitants have communal housing services located at less than 50 m, assign 0 points if none of them has easy access to common facilities. Determine the other scores proportionally.

C3 Flexibility of residential buildings

Intent: Provide functional flexibility for residential buildings, in order to adapt them to living changes and to age of inhabitants. Growing and shrinking of families as well as mul-tigenerational living arrangements should be taken into account. Indicator: Percentage of living surface with flexible floor plans and foreseen adaptable spaces. Unit of measure: % Assessment method: When dealing with major interventions (new construction and refurbishment), functional flexibility has to be taken into account. Floor plans with multi- generational concepts (i.e. adaptation of floor plan depending on family size, separate access for apartments, barrier free accesses and sanitary installation) allow a long term usage of apartments and con-tribute to a sustainable living concept. To assess this criterion, identify residential areas with adaptable floor planes and calcu-late the percentage of the total living area. Score: The score for this indicator is 20. Assign 20 points if all the residential areas have adapta-ble floor planes and 0 points if there are no spaces with adaptable plan. Determine the other scores proportionally.



C4 Flexibility of use of non-residential spaces

Intent: To encourage the constant use of non-residential buildings and public facilities. Indicator: Percentage of occupied hours over the average day. Unit of measure: % Assessment method: To assess this criterion, identify all the non-residential (public and private) buildings and facilities on the site, and evaluate the number of planned hours of daily operations. Calcu-late the percentage of occupied hours over the 24 hour day. Score: The score for this indicator is 20. Assign 20 points if the occupied hours over the day are equal to 16 hours, and 0 if the public and private non-residential spaces are not occupied. Determine the other scores proportionally.

C 5 Availability of green spaces

Intent: Increase the availability of green spaces for to the occupants. Indicator: Green fabric quota. Unit of measure: % Assessment method: To assess this criterion, calculate the surface of accessible green spaces per occupant (m²/person) in the cluster and divide it by the per capita value of the city. Subtract one, and multiply the result by 100 to obtain a percentage. This metric therefore evaluates the increase or decrease in green fabric availability as compared to the urban context. Score: The score for this indicator is 20. Assign 20 points if the index is equal to 100% (it means that the cluster has double the green spaces of the city) and 0 points if the cluster has the same green spaces of the city. Determine the other scores proportionally.

C 6 Access to a broadband communication network

Intent: To ensure occupants access to high-speed Internet connections. Indicator: Percentage of population with access to broadband communication. Unit of measure: % Assessment method: To assess this criterion, identify all the dwellings that have access to high-speed Internet



connection, estimate the occupancy, and divide the value for the overall population of the cluster. Score: The score for this indicator is 20. Assign 20 points if all the population in the cluster has access to broadband communication and 0 points if none of them has the access. Assign the other scores proportionally.

Mobility

C 7 Contiguity of bicycle and car routes

Intent: Allow the use of bicycles as a viable option for transport. Indicator: Percentage of car routes with adjacent bicycle routes in the cluster. Unit of measure: % Assessment method: To assess this criterion, consider all car routes which have adjacent and safe bicycle routes which connect to the urban cycling network. Count all the routes between two in-tersections. Divide the number for the total number of car route segments between inter-sections. Score: The score for this indicator is 20. Assign 20 points if all the car routes have an adjacent bike line, that is the index is equal to 100%; assign 0 points if the index is 0%. Determine the other scores proportionally.

C 8 Access to public transport (M)

Intent: Reduce the use of private vehicles. Indicator: Accessibility to public transport index. Unit of measure: - Assessment method7: For each building in the cluster, calculate the accessibility index as follows [LEnSE meth-odology]. Then, calculate the average accessibility index of the cluster as a weighted av-erage on the number of users per building. Step 1: Walking distance to public transport nodes Determine the walking distance from the building’s main entrance to each public transport node served by rail, bus or tram. Use a notional walking speed of 80 metres per minute. Do not consider nodes that are further than a 500m radius of the building for bus/tram and 1000m for rail. Note: 1. For nodes within the radius that are served by the same service/route consider only the 7 Project LENSE – Stepping Stone 2 - Methodology Development towards a Label for Environmental, Social and Economic Buildings.



closest node, i.e. do not consider multiple nodes which are on the same route. 2. The distance must be measured as it would be travelled on foot, i.e. do not measure in a straight line over inaccessible objects such as buildings or rivers. Step 2: Frequency of service at each node ■ For each node that meets the requirements in step 1, determine the total number of services departing/arriving at each node in the following periods for a typical weekday: AM 08.00 – 10.00 PM 17.00 – 19.00 ■ For domestic buildings, consider the number of services departing/arriving at each node in the following periods for a typical weekday and on a Saturday: Weekday: AM 08.00 – 10.00 PM 17.00 – 19.00 Saturday: 08.00AM – 19.00PM Note: 1. For nodes that have multiple routes, determine the frequency of service for each route and not a collective nodal frequency. 2. It is likely that each route at a node will be bi-directional, consider only the route in the direction with the highest frequency of service. 3. For trains consider only those routes that have at least two stops within a 20km radius of the development (Including the stop nearest to the building). Step 3: Calculating the accessibility index For each node and route: 1. Determine the walk time = Distance to node (m) / notional walk speed (80 m/min) 2. Determine the service waiting time = 0.5*(60/(No. of services during peak time/4)) 3. Add a reliability factor to the service waiting time: Bus/trams=2,Train = 0.75 4. Determine total access time = walk time + service wait time 5. Determine the Equivalent Building Entrance (EBE) frequency = 30/ total access time. Then; 6. For each public transport type calculate the accessibility index = EBEmax + (0.5 * all other EBE). Then; 7. Sum the accessibility index of all public transport types. Score: The maximum score for this indicator is 20. Assign the score according to the benchmark reported in Table 7.

Public transport accessibility index - benchmark

Points Capital/regional centre or inner city

Capital/regional city dis-trict centre or district

town/city

Small/medium town or city suburb

Rural

20 22.5 13.5 9.0 4.5

0 2.5 1.5 1.0 0.5

Table 7: Benchmark for public transport accessibility (Project LENSE)

C 9 Accessibility of pedestrian spaces

Intent: Provide equal access to all the population of the cluster. Indicator: Percentage of accessible pedestrian paths. Unit of measure: %



Assessment method: To assess this criterion, calculate the amount of pedestrian paths that follow the Design For All principles and divide it by the total pedestrian area in the cluster. Score: The score for this indicator is 20. Assign 20 points if the index is equal to 100% and 0 points if none of the pedestrian paths follow the Design For All principles (index = 0%). Determine the other scores proportionally.

C10 Shared mobility

Intent: Enhance shared mobility concepts. Indicator: Percentage of people who have access to shared mobility initiatives. Unit of measure: % Assessment method: To assess this criterion, calculate the amount of people who have access to shared mobili-ty initiatives (car-sharing, bike-sharing, e-bike sharing, e-car sharing). Score: The score for this indicator is 20. Assign the maximum score if the percentage of inhabit-ants who have access to shared mobility is 100%, and 0 points if the percentage is equal to 0%. Determine the other scores proportionally.

Cluster activities

C 11 Social gatherings and common cluster activities (M)

Intent: Establish common services and social gatherings. Indicator: Number of established services and social gatherings. Unit of measure: Assessment method: The criterion evaluates the number of services and activities which have been established for the cluster. Mobility concepts like car sharing, bike sharing are taken into account, sustainable food acquisition, time bank activities for providing coop-eration between neighbors. Score: The score for this indicator is 25. Assign 5 points for each service and activity.

C 12 Local production of food

Intent: Encourage the production of fresh fruit and vegetables



Indicator: Surface of garden areas per capita. Unit of measure: m²/family unit Assessment method: To assess this criterion, calculate the surface of vegetable gardens available to the users in the clusters and divide it by the number of inhabitants. Score: The score for this indicator is 25. Assign 25 points if the surface of the vegetable garden area is 10 m2 for each family unit and 0 if the there are no green area. Determine the oth-er scores proportionally.

C 13 Objective/ subjective safety measures

Intent: Provide objective and subjective safety to cluster users. Indicator: Number of established safety measures. Unit of measure: no Assessment method: To assess this criterion, count established safety measures which can be related to auton-omous energy supply, fire alarm systems, alarm system with presence detectors. Score: The score for this indicator is 25. Assign 5 points for each safety measure.

Comfort

C 14 Exploitation of local resources: sun, daylight, wind (M)

Overheating of buildings can be avoided by detailed planning and appropriate dimensions of transparent surface, glazing properties and shading systems. Within a building cluster the erection of new buildings, enlargements of buildings or demolition of building parts can change the solar radiation on surrounding buildings. Trees can provide shading on buildings and should be planned in accordance with the whole building cluster. Vegetation can alleviate the urban heat island effect, and reduce functioning of air-conditioning and energy consumption. Energy refurbishments and extension can have influences on daylight availability of neigh-boring buildings too. Mostly daylight is reduced when new construction are erected, but also positive effect can be reached. Thus, for example, application of an external thermal insulation on a building with application of a new light colored plaster can have increased light reflection on neighboring buildings and allow better daylight conditions. When new buildings are erected, based on the local dominant wind direction, ventilation corridors or ventilation barriers can appear. The artificial surfaces affect urban natural ventilation and the formation of urban wind environment. Therefore, observations of the



local climate conditions should be done, the wind direction and wind speed in planning considered. Natural ventilation is a simple and way to alleviate urban heat island effect. Intent: Exploit the local resources and predict the effects interventions into the building cluster. Indicator: Numerical simulation of cluster for urban interventions and building design. Unit of measure: Assessment method: Elaboration of a digital model of the building cluster with analysis of shadings, daylight, natural ventilation, and effects of interventions like erections of new buildings or planting trees. Score: The score for this indicator is 25. Assign points if a numerical simulation model of the building cluster was elaborated:

- 10 points for daylighting and shadings model - 10 points for natural ventilation simulation - 5 points for simulations related to the effects of interventions

If there are no simulation, assign 0 points.

C 15 Thermal comfort of outdoor areas

Buildings in the city are mostly built of concrete, stone, metal and asphalt, which have low albedo (reflectivity), so can only reflect little of the sun’s energy. The materials tend to absorb heat energy and, with their low heat capacities, temperatures rise. If buildings are made of such materials, temperatures in nearby areas are naturally elevated. We may try to raise the albedo of the construction materials. For instance, it is possible to make the building surfaces paler or even white. Intent: Reduce the discomfort at ground level during summer. Indicator: Albedo of outdoor areas. Unit of measure: % Assessment method: To assess this criterion, calculate the area of all the surfaces in the cluster. Assign to each surface an albedo value, considering green areas and areas that are shaded in summer days as having an albedo of 1. Multiply all surfaces for their albedo value, and divide their sum area by the total area of all surfaces of the cluster. Score: The score for this indicator is 25. Assign the maximum score if the average albedo is equal or higher than 0.8 and 0 points if the value is equal or lower than 0.2. Assign the other score proportionally.



C 16 Prevention of noise

Centralized ventilation machines, installed in multifamily houses should consider noise emission to all apartments. Decentralized machines installed during renovations on balco-nies, verandas or on external walls should planned in order to avoid noise for neighboring apartments and buildings. Intent: Prevent noise from ventilation machines and other plant systems. Indicator: Unit of measure: Assessment method: Measurement of noise level. Score: The score for this indicator is 25. Assign 25 points if the measured noise level respects the law limits, otherwise assign 0 points.

C 17 Air quality monitoring

Intent: Ensure the constant monitoring of air quality in the area. Indicator: Density of monitoring stations over the average. Unit of measure: % Assessment method: To assess this criterion, calculate the density of air quality monitoring stations in the clus-ter [n / m2] and divide it by the density value of the city. Subtract one, and multiply the result by 100 to obtain a percentage. Consider only those stations connected to a monitoring and alert system at cluster scale or larger. Score: The score for this indicator is 25. Assign 25 points if the index is equal to 100%, and 0 points if its value accounts for 0. Assign the other scores proportionally.

C 18 Light pollution

Intent: Reduce sky glow, glare and over-illumination at night. Indicator: Quota of light sent above the horizontal plane. Unit of measure: % Assessment method: To assess this criterion, count the number of outdoor fixtures with no light intensity above the horizontal plane and divide it by the total number of outdoor fixtures in the cluster. Subtract one, and multiply the result by 100 to obtain a percentage.



Score: The score for this indicator is 25. Assign 25 points if the index is equal to 100%, and 0 points if its value accounts for 0. Assign the other scores proportionally.

D Economic Quality

Equity

D 1 Affordability of housing property

Intent: Reduce the barrier to home ownership. Indicator: Surface of housing affordable to the yearly salary in the lowest quintile. Unit of measure: m2 Assessment method: To assess this criterion, divide the average yearly salary of the lowest quintile of the population in the region by the average price per square meter of housing in the cluster. Score: The score for this indicator is 25. Assign 25 points if the maximum score is equal or higher than 10 m2 and 0 points if the index is equal or lower than 5. Assign the other scores pro-portionally

D2 Affordability of housing rental

Intent: Reduce the financial load of housing. Indicator: Percentage of yearly income in the lowest quintile for rental costs. Unit of measure: % Assessment method: To assess this criterion, divide the average yearly rent for housing in the cluster by the av-erage yearly salary of the lowest quintile of the population in the region. Score: The score for this indicator is 25. Assign 25 points if the index is equal or lower than 30% and 0 points if the index is equal or higher than 50%. Assign the other scores proportional-ly.



Economy

D3 Life cycle cost

For evaluating the costs and benefits of energy and water conservation and renewable en-ergy a life cycle costs assessment is useful. It helps to determine which interventions have the lowest LCC and are therefore most economical. Intent: Life Cycle Cost assessments over specific period of time. Indicator: Life Cycle Cost Unit of measure: - Assessment method: according to Standard ISO 15686-5. (Documentation available in En-erbuild-tool from Enerbuild project http://wiki.cesba.eu/wiki/Simplified_calculation_of_efficiency) Score: The score for this indicator is 25. Assign 25 points if a Life Cycle Cost Analysis was per-formed according to the Standard ISO 15686-5 or with the simplified method defined with-in the Project ENERBUILD, otherwise assign 0 points. (http://wiki.cesba.eu/wiki/Simplified_calculation_of_efficiency)

Market value

D4 Economic advantage of cluster in comparison to single buildings (M)

Intent: Evaluation of economic advantages of the building cluster Indicator: Cost reduction through common investments and usage of common facilities. Unit of measure: Assessment method: Assess the cost benefit gathered through common actions in process quality, environmental and social quality. Score: The score for this indicator is 25. Assign 25 points if the cost reduction accounts for the 40% and 0 points if there is no cost reduction. Assign the other scores proportionally.