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except with prior written consent of the “OffshoreGrid” consortium.

D6.1

Report describing the power market model, data requirements and results from analysis

of initial grid designs

Harald G Svendsen, Leif Warland, Magnus Korpås, Daniel Huertas-Hernando

SINTEF Energy Research

Jakob Völker

Deutsche Energie-Agentur GmbH (dena)

July 2010

Agreement n.: EIE/08/780/SI2.528573

Duration May 2009 – November 2011

Co-ordinator: European Wind Energy Association

Supported by:

Document Name: D6.1 – Offshore Power Market Modelling Final 28/07/2010 Document Number: Page: 2/33

Document informationDocument informationDocument informationDocument information

Document Name: D6.1 – Report describing the power market model, data requirements and results from analysis of initial grid designs

Document Number:

Author: Harald G Svendsen, Leif Warland, Magnus Korpås, Daniel Huertas-Hernando, Jakob Völker

Date: 28 July 2010

WP: WP6: Offshore Power Market Modelling

Task: Task 6.1: Market results and flows for initial grid designs

Revision: Frans Van Hulle, Achim Woyte

Approved: Sintef


SUMMARY

This report describes the power market model used to compute operational costs of the European power system in the OffshoreGrid project. The report aims to give a concise overview of the simulation program itself, the input data and the format of the output data. The actual simulation results have been made available to project partners separately as a number of data files, one for each case plus a summary file.

The simulation program, the SINTEF Power System Simulation Tool (PSST) has been developed previously to study effects of integrating large scale wind power into the European power grid. It combines physical power flow with a simplified electricity market, therefore a power market simulator. The simulation program computes the optimal generation dispatch for each hour, where optimum is defined as minimum total cost of generation, and hence represents the socio-economic optimum. The physical power flow equations are given as constraints to the optimisation problem, together with a number of other constraints such as e.g. cross-border trading limitations and cross-border line capacities. The PSST has previously been used in numerous projects, and recently in the European TradeWind project.

Input data required for these simulations are

• Grid data for Europe, including generation and demand distribution

• Demand forecasts and hourly demand profiles

• Forecasts for generator capacities and marginal costs (by type and country)

• Detailed data for offshore wind farms

• Region specific data for onshore wind generation

• Hydro reservoir data

• Net transfer capacities (country-to-country power trading limitations)

The grid data is collected from multiple sources and the model contains in total 1,494 generators, 4,836 buses, and 8,484 branches (connections between buses). A substantial amount of effort was put into the preparation of the grid data to make it consistent and with all the information required by the simulation program. A major task in this respect was to associate tabular data with geographical location for generators (i.e. power grid connection point).

Forecasts regarding demand and generation capacities, including onshore and offshore wind were provided by project partners. Other input data was largely taken from the TradeWind project.

The main output from the simulations is system cost, defined as the total annual operational costs of power generation. As total cost of generation defines the optimal point in the algorithm, it represents the most direct economic output and has the clearest interpretation. The simulations also give a number of additional output parameters that are used in the subsequent analysis of the results. These include technical and economical parameters such as

• Costs per country

• Cost variability (hour-by-hour)

• Cost difference between countries (hour-by-hour)

• Utilisation of offshore connections

• Wind power curtailment

The present report focuses on the approach and input data for the market modelling part. The final market modelling results will be published in February 2011.

The output data is provided in separate files in a tabular format. The explanation of this format, and definitions of the quantities reported are included in this report.

System cost results from these simulations are used together with investment cost calculations in work package 5 to form the scientific basis for policy recommendations in the final report (work package 8).


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SUMMARY ................................................................................................................................ 3

1 INTRODUCTION .............................................................................................................. 6

2 MARKET MODEL (POWER SYSTEM SIMULATION TOOL) ......................................... 7

2.12.12.12.1 The optimal power flow descriptionThe optimal power flow descriptionThe optimal power flow descriptionThe optimal power flow description ................................................................................................................................................................................................................................................................................................................................................................ 7777

Cost function............................................................................................................................................... 8

Optimal DC power flow description ........................................................................................................... 9

2.22.22.22.2 GenerationGenerationGenerationGeneration ........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................ 9999

2.32.32.32.3 Updating the constraints for a given hourUpdating the constraints for a given hourUpdating the constraints for a given hourUpdating the constraints for a given hour.................................................................................................................................................................................................................................................................................................................... 10101010

Demand 10

Wind generation ....................................................................................................................................... 10

Generation cost of hydro units ................................................................................................................ 10

3 EUROPEAN GRID MODEL............................................................................................ 12

3.13.13.13.1 Demand and generation scenariosDemand and generation scenariosDemand and generation scenariosDemand and generation scenarios............................................................................................................................................................................................................................................................................................................................................................ 13131313

3.23.23.23.2 Continental Europe (former UCTE)Continental Europe (former UCTE)Continental Europe (former UCTE)Continental Europe (former UCTE) ................................................................................................................................................................................................................................................................................................................................................................ 13131313

Production units in the power flow model............................................................................................... 13

Countries around the North and Baltic Seas where nodes are identified............................................. 14

Countries without geographical information........................................................................................... 14

3.33.33.33.3 Nordic region (former Nordel)Nordic region (former Nordel)Nordic region (former Nordel)Nordic region (former Nordel) ............................................................................................................................................................................................................................................................................................................................................................................................ 14141414

3.43.43.43.4 Great Britain and IrelandGreat Britain and IrelandGreat Britain and IrelandGreat Britain and Ireland ........................................................................................................................................................................................................................................................................................................................................................................................................................ 15151515

3.53.53.53.5 Baltic regionBaltic regionBaltic regionBaltic region ........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................ 15151515

3.63.63.63.6 ENTSOENTSOENTSOENTSO----E Net transfer CapacitiesE Net transfer CapacitiesE Net transfer CapacitiesE Net transfer Capacities ........................................................................................................................................................................................................................................................................................................................................................................ 16161616

3.73.73.73.7 Grid reinfoGrid reinfoGrid reinfoGrid reinforcementrcementrcementrcement................................................................................................................................................................................................................................................................................................................................................................................................................................................................ 17171717

3.83.83.83.8 Wind powerWind powerWind powerWind power ............................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................ 18181818

Onshore wind power................................................................................................................................. 18

Offshore wind power ................................................................................................................................ 20

4 INPUT DATA .................................................................................................................. 21

4.14.14.14.1 HVDC interconnectionsHVDC interconnectionsHVDC interconnectionsHVDC interconnections .................................................................................................................................................................................................................................................................................................................................................................................................................................... 21212121


4.24.24.24.2 Water values and inflowWater values and inflowWater values and inflowWater values and inflow................................................................................................................................................................................................................................................................................................................................................................................................................................ 22222222

4.34.34.34.3 Cost input dataCost input dataCost input dataCost input data .................................................................................................................................................................................................................................................................................................................................................................................................................................................................................... 23232323

5 RESULTS ....................................................................................................................... 26

5.15.15.15.1 Simulation casesSimulation casesSimulation casesSimulation cases ........................................................................................................................................................................................................................................................................................................................................................................................................................................................................ 26262626

5.25.25.25.2 Generation cost and electricity pricesGeneration cost and electricity pricesGeneration cost and electricity pricesGeneration cost and electricity prices............................................................................................................................................................................................................................................................................................................................................ 29292929

5.35.35.35.3 Reporting of simulation resultsReporting of simulation resultsReporting of simulation resultsReporting of simulation results.................................................................................................................................................................................................................................................................................................................................................................................... 29292929

Summary file ............................................................................................................................................. 29

Individual case result files ....................................................................................................................... 30


1 INTRODUCTION

This report describes the main activity of Work Package 6 in the OffshoreGrid project. The work package consists of the modelling and analysis of the offshore power market for Northern Europe, with the main objective to provide a scientific basis for further discussions and policy recommendations (Work package 8).

This work makes use of the SINTEF Power System Simulation Tool (PSST), which is an existing flow based power market simulator that was used e.g. in the TradeWind project [1]. A detailed model of the offshore grid developed in WP5 is implemented and merged with existing onshore power system data. To the extent possible the project made use of power system and power market data that was collected in the TradeWind project. In addition to ensuring efficiency in the often time consuming data collection task, this also contributes to consistency and confidence in the results obtained.

Different study cases have been simulated to analyse different offshore grid designs and sensitivities. These cases, in total 32, have been specified by project partners.

The main output from the simulations is system cost, i.e. the total annual operational costs of power generation. The simulations also give a number of additional output parameters that are used in the subsequent analysis of the results. These include technical and economical parameters such as

• Costs per country

• Cost variability (hour-by-hour)

• Cost difference between countries (hour-by-hour)

• Utilisation of offshore connections

• Wind power curtailment

The present report focuses on the approach and input data for the market modelling part. The final market modelling results will be published in February 2011.

The simulation cases are based on offshore grid designs specified in Work package 5, and scenario specifications from Work package 4. The grid model is more detailed than the one used in the TradeWind project mentioned above, as it uses the detailed UCTE study grid model for continental Europe. In total, the grid model contains 1,494 generators, 4,836 buses, and 8,484 branches (connections between buses).

As the input data was taken from numerous sources, a substantial amount of effort was required for preparation of the grid data to make it consistent and with all the information required by the simulation program. A major task in this respect was to associate tabular data with geographical location for generators (i.e. power grid connection point).

As part of this process, the simulation tool itself also had to be upgraded to meet the requirements of the OffshoreGrid project.

The main input data required by the simulation program is

• Grid data for Europe, including generation and demand distribution

• Demand forecasts and hourly demand profiles

• Forecasts for generator capacities and marginal costs (by type and country)

• Detailed data for offshore wind farms

• Region specific data for onshore wind generation

• Hydro reservoir data

• Net transfer capacities (country-to-country power trading limitations)


2 MARKET MODEL (POWER SYSTEM SIMULATION TOOL)

The structure of the computer program which is used for simulating the European power systems is shown in Figure 1. The inputs to the program are the grid model, time series for load, time series for wind, generation capacity forecast for all generator types and generation costs for all generator types. The load is given as relative hourly profiles for each country for a given reference year. The actual load in any given hour can then be found using the total load in GWh. The generation capacity forecast is given as total installed capacity for a given year and country. Wind power time series have been provided by project partners.

Figure 1.Figure 1.Figure 1.Figure 1. PSST main simulation structurePSST main simulation structurePSST main simulation structurePSST main simulation structure

For each hour the program will update the load, wind production and marginal cost of hydro units and run an optimal power flow, which determines the power output of all generators and the power flow on all lines. The free (controllable) variables in the optimal power flow problem are the power output of all generators and the flow on HVDC interconnections. The power output of the generators is dependent on the maximum and minimum capacity, the marginal cost relative to other generators and limitations of power flow on lines.

2.12.12.12.1 The optimal power flow descriptionThe optimal power flow descriptionThe optimal power flow descriptionThe optimal power flow description

The following description of the DC optimal power flow algorithm is only meant as a brief reminder for those already familiar with this type of analysis. A reference for both optimal and DC power flow is ref.[2-3] in addition to [2] for DC power flow.

The linear optimisation problem given below is solved for all iterations of the simulation loop in Figure 1.

Aggregate and present

hours==8760

hour +1

Year (hour=1)

Parameter updating

True

False

Solve DC optimal power flow External LP solvers from Coin (Clp)

- Power flow case description

- Generator cost curves (marginal cost) - Reservoir levels (hydro)

- Watervalues

- Load series

- Inflow (hydro)

- Generator capacities

Input data for given year

Time dependent

- Wind and load by hour

- Branch/hvdc flow

- Power exchange (countries)

- Sensitivities of constraints

- Cost of hydro production

- Total load and production

results

- Wind series


min ( ) subject to:T

x

eqeq

lower upper

F x c x

A x b

A x b

x x x

=

⋅ =

⋅ ≤≤ ≤

(1)

where : x is the state variable vector F(x) is the cost function to be minimized (total generation costs) c determine the cost of all the second and first order elements respectively in

the cost function A and b describe the transmission constraints between grid zones Aeq and beq are given by the power flow equations xlower and xupper the lower and upper bounds on the state variables

The state variables x include generator production, HVDC flow and voltage angles. The HVDC connections are modelled as loads with opposite sign on each side of the connections. Both elements of the cost function, c, are given by the generator cost curves. The elements of the cost function for voltage angles and HVDC part of the state variable x are zero. The equality and inequality constraints typically represent the power flow description and the branch flow limitations respectively. Through the lower and upper bound on the state variable x it is possible to limit the flow on the HVDC connections as well as including maximum and minimum generation levels.

Cost function

The cost function F(x) is in general a function of all state variables x. In our case it gives the total generation cost as indicated above. The aim of the optimal power flow algorithm is to find the power flow solution with the optimal (i.e. minimal) generation cost.

For each generator the total cost is given as piecewise linear to represent an approximation of quadratic cost, shown in Figure 2. The cost coefficient steps (MC1, MC2 and MC3 in Figure 2) together with the number of equally spaced intervals (3 in Figure 2) are specified explicitly in the program. In the current case, the cost coefficient ranges stepwise from 90% of marginal cost at zero production (P=0) to 100% of marginal cost at full production (P=Installed capacity) for all generators except wind, which has a constant cost coefficient (equal to the marginal cost).

The cost is the cost coefficient multiplied by production. For non-generator state variables, such as HVDC power flow and voltage angles, the cost coefficient (marginal cost) is zero and therefore their cost is always zero.

P [MW]

Marginal cost (P) [Euro/MW]

MC3

MC2

MC1

Installed capacityP1 P2

P [MW]

Cost(P) [Euro]

Installed capacityP1 P2

Figure 2.Figure 2.Figure 2.Figure 2. Example of pExample of pExample of pExample of piecewise linear cost functioniecewise linear cost functioniecewise linear cost functioniecewise linear cost function with t with t with t with three stepshree stepshree stepshree steps


Optimal DC power flow description

The DC power flow [2] is a linearization of the power flow description under the following assumptions:

1. The voltage angles differences ( δ∆ ) are small,

2. Line resistance is negligible, ri ≈ 0

3. Flat voltage profile, i.e. all voltage magnitudes are close to 1.0 pu

The DC power flow description can be generalized to:

inj G L hvdcG hvdcB P I P P I Pδ = = − + (2)

and

FlowfB Pδ = (3)

where: Pinj - Vector containing the power injected into buses. Sum of production, load and

HVDC power injected. PL - Load vector B - The nodal admittance matrix Bf - The flow admittance matrix IG - Connection matrix for generators containing ones where state variable for

given generator is connected into the system. Ihvdc - Connection matrix for HVDC links, containing plus/minus one depending on

the direction of flow on the connection.

The voltage angle vector δ includes all but the reference angle. If there are several synchronous areas separated by HVDC connections these will each have their own reference bus. The equality constraints can be found by rearranging the power flow balance as shown in Equation (4).

[ ] {

eq

G LG hvdc

hvdceq

B I I P P

bPA

x

δ − − = −

144424443

123

(4)

The branch flow limitations encoded in the inequality constraints of the optimization problem in equation (1) are:

,max

,max

0 0

0 0f Flow

Gf Flow

hvdc

B PP

B PP

bAx

δ ≤ − 142431442443

123

(5)

In addition, the sum of rows in A representing a net transfer capacity (NTC) can be limited by an NTC value, putting an upper bound on the flow between countries or areas.

2.22.22.22.2 Generation Generation Generation Generation

For all generation types, except Wind and Hydro, the capacity and marginal cost is kept constant in the simulation. These quantities are either known and explicitly given by the model, or specified as a scenario input where the total GW installed capacity as well as marginal cost for all generation types are given for every country in the model. This would be the case when studying future scenarios, where no detailed information regarding location, type and size of generator units, only assumptions on total values and targets are available.


When using scenario input for generation capacity, existing generators are scaled so that total capacity by country match that specified in the scenario. If the scenario specifies capacity for a generator type that is not present in the model for a given country, this generation capacity is ignored. Likewise, if the scenario does not specify capacity for a generator type that is present in the model, such generator units are removed before simulation starts.

2.32.32.32.3 Updating the constraints for a given hourUpdating the constraints for a given hourUpdating the constraints for a given hourUpdating the constraints for a given hour

For each hour the constraints that are time dependent, i.e. the load, available wind power and marginal cost of hydro units, are updated before running the optimal power flow. The marginal cost of hydro units is a function of the reservoir level. The available wind power, given as hourly profiles for each area (onshore wind) or node (offshore wind), is defined here as the wind power output that can be fed into the grid in a non-congested case

Demand

For each country in the model an hourly demand profile must be provided. The hourly demand profile together with distribution of demand in any given country is normalized as shown in the equation below:

{ } { }all nodes in country all hours in year

1.0 , 1.0i hi h

P P∈ ∈

= =∑ ∑

where Pi is the normalized demand at node i, and Ph is the normalized hourly value for given country. By multiplying with the total yearly demand for given country the demand on any given node in the country can be found for all hours simulated. The total yearly demand for each country is specified as scenario inputs to the market model.

Wind generation

Aggregated wind farms are modelled as generators with maximum power equal to the available wind power for the specific hour. The minimum production is set to zero so that it is possible to reduce the wind power output in constrained areas. The marginal cost is set low, so that wind power plants always will produce if not limited by grid constraints.

Generation cost of hydro units

Costs associated with hydro units require special care: If the cost function of any hydro unit with reservoir were given by a fixed marginal cost value, typically lower than any other generation types except wind power, the unit would produce at its maximum level until the reservoir was empty. This would have resulted in an unrealistic production profile over the year. Therefore, the marginal cost of hydro units is chosen to be a function of the reservoir level. Thus, the marginal cost reflects the value of saving the water for later use, referred to as the water value method (see ref. [4]). Typically, the marginal cost is low when the reservoir level is near its maximum and vice versa. The same water value function is used for pumping operation.

As an example, consider a system with only gas power and hydro power with reservoir and pumping capacity. If the water value is lower than the marginal cost of the gas power plant, the hydro unit will generate power and thus cause a reduction of the reservoir level and thereby an increase in the water value until it equals the gas marginal cost. If the water value is higher than the marginal cost of the gas power plant, the hydro unit will consume power by pumping water from a lower reservoir to a higher reservoir and thereby decreasing the water value until it equals the gas marginal cost. The energy consumption during pumping is recovered later when the pumped water is used to generate power. Losses in the process are ignored.

The reservoir level is updated each hour, according to the following equation:


The inflow is the flow of water into the reservoir, represented as an energy flow (MWh per time step dt). The production is negative for pumped hydro operation. It is also ensured that the maximum production capacity of the hydro unit is limited by the available energy:

( )( ) min , ( ) ( ) /max installedP t P Reservoirlevel t Inflow t dt= +

Run of river units are not implemented as a separate generator type in the present version of the model. Instead, by specifying a hydro unit with very low reservoir capacity, the production will follow the hydro inflow as would be the case for a run-of-river station. The marginal cost will then always be low, due to the rapid filling of the reservoir.


3 EUROPEAN GRID MODEL

The European grid model used in this project is divided into five synchronous regions: Continental Europe (former UCTE), Great Britain, Ireland, the Nordic region (former Nordel) and the Baltic region. The countries included in the model are shown in Figure 3, where the zones in countries are indicated by red dots and the connection between them as white lines. The countries included in the model are also listed in Table 1.

Figure 3.Figure 3.Figure 3.Figure 3. OffshOffshOffshOffshoreGrid zones in the European grid modeloreGrid zones in the European grid modeloreGrid zones in the European grid modeloreGrid zones in the European grid model

The power flow descriptions for each of these areas come from different sources, with different levels of details, or simplifications, e.g. in the Irish system there is just two nodes with a single fictitious impedance in between, while for Great Britain a detailed model is available. This simplification of the Irish system is not a problem as the power flow market simulator uses a linear approach where the size of the impedances on radials does not make any difference for the actual flow as seen by the market model.

Table 1.Table 1.Table 1.Table 1. Countries included in the OffshoreGrid studyCountries included in the OffshoreGrid studyCountries included in the OffshoreGrid studyCountries included in the OffshoreGrid study

Albania Finland Lithuania Russia

Austria France Macedonia Serbia

Belgium Germany Monte Negro Slovak Republic

Bosnia-Herzegovina Great Britain Morocco Slovenia

Bulgaria Greece Netherlands Spain

Croatia Hungary Norway Sweden

Czech Republic Ireland Poland Switzerland

Denmark Italy Portugal Ukraine

Estonia Latvia Romania


The total size of the model for each synchronous area, as they are implemented in the model, is shown in Table 2.

Table 2.Table 2.Table 2.Table 2. Size of model used for all synchronous areasSize of model used for all synchronous areasSize of model used for all synchronous areasSize of model used for all synchronous areas

# bus# bus# bus# bus # gen# gen# gen# gen # branch# branch# branch# branch

UCTE 3815 1175 6753

Nordel 42 33 58

Great Britain 971 269 1665

Ireland 2 6 1

Baltic 6 11 7

3.13.13.13.1 Demand and generation scenarDemand and generation scenarDemand and generation scenarDemand and generation scenarios ios ios ios

The scenarios for demand, generation and marginal cost data pr. country and fuel type was prepared in work package 2, and distributed in the model as described in Chapter 2.2 and 2.3.

3.23.23.23.2 ContineContineContineContinental Europe (ntal Europe (ntal Europe (ntal Europe (former former former former UCTE)UCTE)UCTE)UCTE)

The UCTE Study Model – Winter (16/01) and Summer (16/7) situation 2008, have been provided for the OffshoreGrid project by ENTSO-E. The two models are snapshots of the flow representative for that period of year. The difference between the two models, summer and winter, is the demand and generation, and as both demand and generation size and type is provided by other sources only one of the models is used (winter).

In order to do a power flow analysis it is essential to have a fair overview of the topology and the geographical location of main components of the system, especially for a large system encompassing as many countries as given in the UCTE model. However, the model, as delivered by ENTSO-E, does not provide geographical information nor do the node names used in the model clearly identify the location. For some countries, such as Portugal, it provides only a number, which requires detailed knowledge for that part of the system to make any assumptions regarding generation units.

Identifying every single node in the UCTE model with its geographical location was neither necessary nor possible within the scope of this project. It was, however, necessary to identify parts of the main transmission network and locations of production units in order to have correct cost data. The focus of the study is the offshore grid in the North and Baltic Seas both for interconnecting countries and injection of large amount of offshore wind power. Clear knowledge of connection points in the onshore grid is important for identifying the best suited point for connection and for identifying necessary grid upgrades to cope with the large amount of power injected into the onshore system. The main nodes in the countries surrounding the North and Baltic Seas have been identified by the project partners for as many nodes as possible. The countries where nodes have been identified are Poland, Denmark, Germany, The Netherlands, Belgium, France and Luxembourg.

Production units in the power flow model

The market model uses marginal cost on production units to determine the distribution of power generation for any given hour. The hours are only connected through the water inflow to and the reservoir levels of the Hydro units. The production profile is then selected from a merit order list, while the constraints of the network model are maintained. In this model it is essential to have a good estimate of marginal costs for each unit in order to get a realistic optimal power flow solution. To get the exact value for each unit is for all practical purposes impossible, thus the approach of this project is to base the marginal cost on production types, such as hydro, nuclear, wind and fossil units.

While for the Nordic, British and Irish regions it was fairly easy to identify the production units given by type and size, based on publicly available information as well as the knowledge of the project partners, this was not the case for the Continental (UCTE) system. In the model received from ENTSO-E [5] there is no information regarding generator type or size, only an indication


whether or not there is production available for any node in the power flow model. The model received is structurally identical to the model received from ENTSO-E at the end of the TradeWind project, thus the work done in the Master thesis of Beharrysingh [6] was used as starting point for further improvements to the allocation of size and type to generator units in the model.

Countries around the North and Baltic Seas where nodes are identified

For the countries where nodes had been identified and assigned geographical information (longitude and latitude), the Platts database [7] was used for generators. The Platts database provides detailed information on size, type and geographical location. The generators from the Platts database were placed on the node in the model closest to its actual location as described by Platts. Only nodes with existing generation capacity in the original models were considered when placing the generators from Platts.

Countries without geographical information

For the countries where the nodes have not been identified geographically, the generators of all types, including wind, were allocated to nodes as given in references [6, 8]. Here, data available from IEAE [9] and INSC [10] as well as the ENTSO-E grid map [5] was used to trace each generator within the detailed model to identify the node name referring to the nuclear power plants. All nuclear plants were explicitly assigned. The network map also identifies the hydro power plants within each country. Firstly, the total number of hydro plants in each country was found. Then, nodes referring to substations located in close proximity to these individual hydro plants or clusters of plants were also identified by tracing through the detailed model. Of the 24 UCTE countries in which hydro power was represented, 17 countries were fully described – with all hydro plants or clusters of hydro plants explicitly assigned.

After the assignment of nuclear and hydro power stations as described in the previous section, a list of unassigned generators was created per country. The generation type and size of these were then assigned according to an algorithm described in detail in ref. [6, 8]. Also, wind generators were distributed based on a wind injection dispersion algorithm, see ref. [6, 8] for further details.

3.33.33.33.3 Nordic region (Nordic region (Nordic region (Nordic region (former former former former Nordel)Nordel)Nordel)Nordel)

The basis for all calculations performed for the Nordic power system is the 21 generator model of the Northern European system. The 21 generator model determines the topology of the grid, and the distribution of loads and generation units except wind. The original development of this model is described in [11], and further model developments in [12] . The model has been developed through several steps and updated with recent grid and generation data for the use in the TradeWind project. The original Nordic model includes a bus representing Denmark West and a bus representing Germany. These buses have been removed from the Nordic grid used here, since they are parts of the UCTE grid model. The grid model is visualised in Figure 4.

In the context of the OffshoreGrid project, the 21 generator model is suitable as it represents the power flow of the system well. This has been demonstrated previously through comparisons with a full scale model of the Nordic system. For analyses related to active power flow the reduced size and good accuracy makes the 21 generator model favourable.

In the 21 generator model of Northern Europe the lines and generators are located and adjusted in such a way that they reflect the real production and the most important bottlenecks in the Nordic power system. The impedances are adjusted in such a way that the power flow corresponds to the flow using a full-scale model. HVDC-links that are not modelled (for instance Finland–Russia) can be treated as loads in the model, although not included in the data set used here.


Figure 4.Figure 4.Figure 4.Figure 4. Nodes and connections in the Nodes and connections in the Nodes and connections in the Nodes and connections in the 21 generator model for 21 generator model for 21 generator model for 21 generator model for the Nordic regionthe Nordic regionthe Nordic regionthe Nordic region

3.43.43.43.4 Great BritainGreat BritainGreat BritainGreat Britain and Ireland and Ireland and Ireland and Ireland

Great Britain and Ireland in this context refer to the two geographical islands.

Network data describing transmission system, demand and generation by type, for Great Britain, is available from the 2009 Seven Year Statement at the National Grid website [13]. The model has been updated with some missing information, such as missing transmission lines splitting the system into several islands, based on knowledge of the system by project partners Senergy Econnect. For Ireland no data describing the network has been made available for the project. However, as this is a fairly small network, a two bus equivalent, one for the Republic of Ireland and the other for Northern Ireland, was assumed to be adequate for the purpose of the market study within this project. With only two buses in the system the value of the impedance between them does not influence the result of the market model since it is assumed lossless. In other words, this part of the system is modelled as a pure transport model.

3.53.53.53.5 BalticBalticBalticBaltic region region region region

For the Baltic countries Estonia, Latvia and Lithuania a reduced equivalent model as shown in Figure 5 is used. The demand is equally distributed between the four nodes in Estonia, while the main generation is in Tallinn with hydro, Tartu with lignite coal and Narva with gas, hard coal and renewable sources other than wind.


Tallinn

Parnu Tartu

Narva

Latvia

Lithuania

Estonia

2000 MW

700 MW

1200 MW

1200 MW

1200 MW

2000 MW

750 MW

Figure 5.Figure 5.Figure 5.Figure 5. Baltic reduced network equivalentBaltic reduced network equivalentBaltic reduced network equivalentBaltic reduced network equivalent

There is also a 350 MW HVDC connection between Finland (node 7000 in the Nordel model) and Tallinn connecting the Nordic countries and the Baltic area.

3.63.63.63.6 ENTSOENTSOENTSOENTSO----EEEE Net transfer C Net transfer C Net transfer C Net transfer Capacitiesapacitiesapacitiesapacities

The DC power flow model is a linear model which does not capture stability constraints such as voltage, transient and angular stability. Based on more detailed studies, maximum transfer capacities can be established which account for these stability issues. Such detailed studies are not a part of this project. Instead, net transfer capacities (NTC) which also include political constraints for allowable power flow between the countries have been included in the model. These NTC values are available from ENTSO-E [5], The values used in this project are based on the Winter 2010 values, except for the Nordic region, where instead more detailed NTC values on zone level from the TradeWind project have been used. In reality, the NTC values vary throughout the year, but in the current model only one set of NTC values are used. These are shown in Table 3 and Table 4. The model does not include HVDC connections in the NTC, so the total transfer capacity between two countries is equal to the sum of the NTC and all HVDC capacities.


Table 3.Table 3.Table 3.Table 3. NTC values for NTC values for NTC values for NTC values for Nordic regionNordic regionNordic regionNordic region

Country/regionCountry/regionCountry/regionCountry/region Capacity [MW]Capacity [MW]Capacity [MW]Capacity [MW] CoCoCoCountry/Regionuntry/Regionuntry/Regionuntry/Region Capacity [MW]Capacity [MW]Capacity [MW]Capacity [MW]

NO_3 NO_2 600 600 SE_3 SF_2 1600 1200 NO_3 SE_3 600 700 SE_3 SE_2 7000 7000 NO_2 SE_3 600 500 SE_1 SE_2 4000 4000 NO_2 NO1 300 300 SE_1 DK_E 1350 1750 NO_1 NO2 2050 1850

Table 4.Table 4.Table 4.Table 4. NTC values for NTC values for NTC values for NTC values for other regionsother regionsother regionsother regions

Country/regionCountry/regionCountry/regionCountry/region CapaCapaCapaCapacity [MW]city [MW]city [MW]city [MW] Country/RegionCountry/RegionCountry/RegionCountry/Region Capacity [MW]Capacity [MW]Capacity [MW]Capacity [MW]

AT SI 900 900 ES FR 500 1300

AT IT 220 285 ES PT 1500 1300

AT DE 2000 2200 FR IT 2650 995

AT CH 1200 1200 GR BG 300 600

AT HU 400 800 GR MK 300 350

AT CZ 1200 2180 GR AL 200 150

BE FR 2300 3400 IT SI 650 650

BE NL 2400 2400 RO HU 1400 600

BA HR 700 570 RO BG 600 600

BA RS 480 400 RO RS 600 300

BA ME 500 380 RS MK 350 350

CH IT 4240 1810 RS BG 300 350

CH DE 3200 1500 RS HU 600 600

CH FR 2300 3200 RS ME 400 400

HR SI 1000 1000 RS AL 200 200

HR HU 1500 1000 ME AL 250 250

HR RS 400 350 MK BG 250 450

CZ DE 2300 800 SK HU 1250 600

CZ PL 800 2000 SK PL 500 600

CZ SK 1700 1000 UA SK 400 400

DE FR 3050 2800 UA HU 800 800

DE PL 1200 1100 UA RO 550 400

DE NL 3850 3000 DK DE 1500 950 3.73.73.73.7 Grid reinforcementGrid reinforcementGrid reinforcementGrid reinforcement

In an analysis of future scenarios with increased power demand and generation it is generally important to include reinforcements in the grid to avoid an unrealistic amount of grid bottlenecks constraining the power flow in the system.

However, accessible information regarding planned reinforcements is only patchy, and it has proven infeasible to include this project by project in the current study. A related problem is lacking information on the geographical location of future increases in demand and generation. Demand and generation scenarios are specified per country, and a uniform scaling is applied to all generators and loads. Various approaches were tested, such as to apply a uniform up-scaling of capacities of bottleneck lines (i.e. lines with very high utilisation) in line with increased generation.

In fact, even the original 2010 case, where all or most of the demand was given in the original model, proved to give solutions with unrealistic grid constraints (apparent in the simulation results as high amount of load shedding).

The approach to handling grid reinforcements that was adopted was to remove capacity constraints within zones, but retain them on zone-to-zone lines. This way, the most important capacity constraints would be incorporated at the same time as most of the load shedding was avoided.


It is worth emphasising that removing capacity constraints does not reduce the model to a simple transport model, as impedances on the lines are still included. (A transport model has effectively zero impedance.) Setting the capacity to infinite is equivalent to the ideal situation where all lines have been upgraded such that they never represent a bottleneck. Then power flow is only dependent on impedances.

3.83.83.83.8 Wind powerWind powerWind powerWind power

Wind power time series is provided by work package 3. Onshore wind power

For the onshore wind hourly values of the power is given as a total pr. country or zones in country as given in Table 5. The wind units in each country are scaled such that the total production within a country/zone is equal to that given by the scenario for a specified hour. The table and the scenarios Italy consist of two zones, though as it not possible to identify the location of nodes from Italy the scenario wind data for Italy was merged to one value for the entire country. Wind production in Ireland was split between the Republic and Northern Ireland using the same split as in TradeWind.

Table 5.Table 5.Table 5.Table 5. Onshore wOnshore wOnshore wOnshore wind zonesind zonesind zonesind zones

Area Zone Country/Region Description

Node

Coordinates

Capacity

2020

(MW)

Capacity

2030

(MW)

AT AT Austria 47,4 N 14,6 E 3500 4300

BE BE Belgium 50,5 N 4,4 E 2100 2500

BG BG Bulgaria 42,3 N 25,1 E 3000 3550

CH CH Switzerland 47,2 N 7,2 E 300 600

CZ CZ Czech Republic 49,5 N 17,4 E 1600 1920

DK DK_E Denmark East East 55,2 N 11,6 E 820 900

DK DK_W Denmark West West 56,3 N 9,2 E 3000 3380

DE DE_1 Germany 1 East 51,6 N 12,1 E 16407 17000

DE DE_2 Germany 2 North-West 53,4 N 9,0 E 9601 10000

DE DE_3 Germany 3 Centre 51,4 N 9,3 E 4007 6000

DE DE_4 Germany 4 South-East 49,2 N 11,3 E 515 1000

DE DE_5 Germany 5 West 50 N 7,3 E 9730 12000

DE DE_6 Germany 6 South West 48,3 N 9,2 E 736 1000

EE EE Estonia 58,9 N 25,7 E 500 1200

ES ES Spain 39000 47666

FI SF_1 Finland 1 South 62,3 N 22,0 E 660 860

FI SF_2 Finland 2 North 66,1 N 26,5 E 840 1500

FR F1 France 1 North West 48,7 N 0,5 E 10050 20370

FR F2 France 2 North East 47,6 N 5,2 E 4021 8315

FR F3 France 3 South East 45 N 5 E 1300 1830

FR F4 France 4 South West 44,4 N 0,6 E 3619 7484

GB GB-1 UK South

England,

Wales 2600 3870

GB GB-2 UK Scotland Scotland 10400 15490

GR GR Greece 6500 12000

HR HR Croatia Coastal 44,6 N 15,2 E 1400 3000

HU HU Hungary 47,2 N 18,1 E 900 1600

IE IE Republic of Ireland and Northern Ireland 5000 5400

IT IT1 Italy North 950 1150

IT IT2 Italy South 14820 17940

LT LT Lithuania 55,5 N 23,8 E 1000 1570

LU LU Luxembourg 49,7 N 6,1 E 300 700


LV LV Latvia 57,1 N 25,5 E 200 500

NL NL Netherlands 52,4 N 4,7 E 5000 6000

NO NO1 Norway 1 South 59,5 N 5,5 E 420 1060

NO NO2 Norway 2 Middle 62,5 N 7,4 E 1350 1500

NO NO3 Norway 3 North 1410 3220

PL PL Poland 1 11000 16000

PT PT Portugal 7572 9412

RO RO Romania 3000 3900

RS RS Serbia 42,4 N 21,3 E 80 200

SE SE_1 Sweden 1 South 56,5 N 14,0 E 2000 2500

SE SE_2 Sweden 2 Centre 61,0 N 16,4 E 1330 1500

SE SE_3 Sweden 3 North 2660 3000

SK SK Slovakia 800 1100

SI SI Slovenia Coastal 500 860

MT MT Malta 100 200

Figure 6 and Figure 7 show the wind regions in both Germany and France.

Figure 6.Figure 6.Figure 6.Figure 6. Zones in GermanyZones in GermanyZones in GermanyZones in Germany


Area 1Area 2

Area 4Area 3

Figure 7.Figure 7.Figure 7.Figure 7. Zones in FranceZones in FranceZones in FranceZones in France

Offshore wind power

For the offshore wind farms, hourly wind power values (potential production) was provided by work package 3 for each individual wind farm.


4 INPUT DATA

This chapter includes specifications of input data used in the market model simulations that has not already been discussed in the previous chapter.

4.14.14.14.1 HVDC interconnectionsHVDC interconnectionsHVDC interconnectionsHVDC interconnections

HVDC connections that are included in the model are listed in Table 6. This list was updated to agree with the list provided by project partner Senergy Econnect. Figure 8 shows a map with the HVDC links plotted in.

Table 6.Table 6.Table 6.Table 6. HVDC interconnectionsHVDC interconnectionsHVDC interconnectionsHVDC interconnections

Node ANode ANode ANode A NoNoNoNode Bde Bde Bde B CapacityCapacityCapacityCapacity (MW)(MW)(MW)(MW) 2010201020102010 2020202020202020 2030203020302030 NameNameNameName

KTJE__1 Nordel: 5604 275 Yes Yes Yes Skagerrak 1



KNVV__1 Nordel: 3361 300 Yes Yes Yes Kontiskan 2 / Kattegat

KFGD__1 Nordel: 8501 600 Yes Yes Yes Great Belt / DK E–W

ZSLK5412 Nordel: 3300 600 Yes Yes Yes SwePol / SE–PL

D8BW__21 Nordel: 8501 600 Yes Yes Yes Kontek / DE–DK E

D2HWBC11 Nordel: 3300 600 Yes Yes Yes Baltic cable / DE–SE

Nordel: 5605 NEEM-E1 700 Yes Yes Yes NorNed

FMANDA11 SELL40 2000 Yes Yes Yes Cross Channel / FR–GB

NMVL-G1 GRAI41 1290 Yes Yes Yes BritNed

IGLNN111 GARACH11 500 Yes Yes Yes Italy–Greece

AUCH20 IE: 2 500 Yes Yes Yes Moyle / Scotland–NI

DEES41 IE: 1 500 Yes Yes Yes East West / Wales–IE

Baltic: Tallin Nordel: 7001 350 Yes Yes Yes Estlink

Nordel: 3001 Nordel: 7001 550 Yes Yes Yes Fenno–Skan

Nordel: 3001 Nordel: 7001 800 Yes Yes Fenno–Skan 2

KTJE__1 Nordel: 5604 700 Yes Yes Skagerrak 4

Baltic: Tallin Nordel: 7001 650 Yes Yes Estlink 2

IBRIN111 AKOMAN2 500 Yes Yes Italy–Albania

Nordel: 5605 NEEM-E1 700 Yes Yes NorNed2

KEDR__1 NEEM-E1 700 Yes Yes Cobra (DK–NL)

HAWP20 PEHE11 1800 Yes Yes East Coast / GB

DEES41 HUNF30 2000 Yes Yes West Coast / GB

CHIC41 FMENUE11 1000 Yes Yes Enlgand France 2

ICANR111 HKONJS2 1000 Yes Yes Italy–Croatia

IVLLR111 0PODG12 1000 Yes Yes Italy–Montenegro

IGLNN111 GARACH11 500 Yes Yes Italy–Greece 2

Nordel: 5605 D2BRUN11 1400 Yes Yes Nordlink /NO–DE

SELL40 BSLYKE31 1000 Yes Yes Nemo / GB–BE

Nordel: 6000 GRIW40 1400 Yes Yes BritNor / GB–NO


Figure 8.Figure 8.Figure 8.Figure 8. HVDC interconnections in 2030 around the North and Baltic SeasHVDC interconnections in 2030 around the North and Baltic SeasHVDC interconnections in 2030 around the North and Baltic SeasHVDC interconnections in 2030 around the North and Baltic Seas

4.24.24.24.2 Water values and inflowWater values and inflowWater values and inflowWater values and inflow

Reservoir capacity, pumping capacity and water inflow is specified for each country. Values used in this project are identical to those used in the TradeWind project, and are shown in Table 7.

Water values are also based on values used in the TradeWind project, but for non-Nordic countries (i.e. all countries except NO, SE, FI) modified with an upper cap such that they never exceed 100 €/MWh. This was done to avoid that the electricity price, defined as the cost of the most expensive generator in operation, would be set by the water value. For the generation dispatch this has very little effect due to relatively low reservoir capacities. For the Nordic countries, (NO, SE, FI) however, the hydro reservoirs play the dominant role in the generator dispatch computation, and such a modification is not justifiable. For these the original water value profile is kept (the maximum value, for very low reservoir level, is for these countries 674 €/MWh.)

Table 7.Table 7.Table 7.Table 7. Hydro input dataHydro input dataHydro input dataHydro input data

Country Country Country Country codecodecodecode

Reservoir Reservoir Reservoir Reservoir capacity capacity capacity capacity (TWh)(TWh)(TWh)(TWh)

Pumping Pumping Pumping Pumping capacity capacity capacity capacity (GW)(GW)(GW)(GW)

Reservoir Reservoir Reservoir Reservoir start level start level start level start level (%)(%)(%)(%)

Inflow Inflow Inflow Inflow 2010 2010 2010 2010 (TWh)(TWh)(TWh)(TWh)



AL 0.45 0 60 4.5 5.25 6

AT 3.2 2.9 50 36.5 37.5 37.5

BA 1.44 0 50 6 6 6

BE 0.312 1.3 50 0.3 0.3 0.3

BG 0.984 0.6 50 3.3 4.5 5.2

CH 8.6 1.6 50 33 33 33

CZ 0.542857 1.1 50 1.8 1.8 1.6

DE 0.3 3.8 50 23 25 25

DK 0 0 50 0.023 0.023 0.023

EE 0.001 0.2 60 0 0 0

ES 18.4 3.3 50 35 37 39

FI 5 0 60 13.3 14 14

FR 9.8 4.3 50 62 62 62

GB 0.4 2.8 50 1.6 1.6 1.6

GR 2.4 0.7 50 3.7 3.9 3.9

HR 1.44 0 50 6.3 6.3 6.3

HU 0 0 50 0.3 0.5 0.6

IE 0.04 0.3 50 0.16 0.16 0.16


IT 7.9 4.2 50 45 50 50

LT 0.0049 0.9 60 0 0 0

LU 0.264 1.1 50 0.1 0.1 0.1

LV 0.00942 0 60 3.046 3.046 3.046

MK 0 0 50 1.4 1.4 1.4

NL 0 0 50 0.1 0.1 0.1

NO 82 0 60 121.5 122.7 125.5

PL 0.408 1.7 50 2.5 2.9 2.9

PT 2.6 0.8 50 12 15 16

RO 4.296 0 50 17.8 20.3 22

RS 2 0 50 13.2 13.2 13.2

SE 34 0 60 67 68.4 69.7

SI 0.0009 0 50 4 4 4

SK 0.63 0.9 50 4.1 4.1 4.1

4.34.34.34.3 Cost input dCost input dCost input dCost input dataataataata

The total generation cost is computed from marginal costs for all generators which are producing power. The marginal costs are defined per generator type for each country according to:

Marginal cost = fuel cost/fuel efficiency + CO2 tax + non-fuel cost.

The CO2 tax on electricity, measured in €2007/MWh, is computed for each fuel type according to

CO2 tax = CO2 price × CO2 content /fuel efficiency.

The tables below specify the values of the various marginal cost components used in this project. This data has been provided by Work package 3.

Table 8.Table 8.Table 8.Table 8. SpecificSpecificSpecificSpecific fuel fuel fuel fuel cost cost cost cost –––– lignite coal ( lignite coal ( lignite coal ( lignite coal (€€€€2007200720072007/MWh)/MWh)/MWh)/MWh)

CountryCountryCountryCountry 2010201020102010 2020202020202020 2030203020302030

AL 5.08 5.08 5.08

GR 4.40 4.40 4.40

PL 4.69 4.69 4.69

Others 4.20 4.20 4.20

Table 9.Table 9.Table 9.Table 9. Specific Specific Specific Specific fuel fuel fuel fuel cost cost cost cost –––– oil and hard coal ( oil and hard coal ( oil and hard coal ( oil and hard coal (€€€€2007200720072007/MWh)/MWh)/MWh)/MWh)

Fuel typeFuel typeFuel typeFuel type 2012012012010000 2020202020202020 2030203020302030

Crude oil 35.37 44.87 53.79

Hard coal 11.06 10.75 10.13

Table 10.Table 10.Table 10.Table 10. Specific Specific Specific Specific fuel fuel fuel fuel cost cost cost cost –––– gas ( gas ( gas ( gas (€€€€2007200720072007/MWh)/MWh)/MWh)/MWh)

CountryCountryCountryCountry 2010201020102010 2020202020202020 2030203020302030

(LU) 21.47 23.80 24.63

(MA) 21.47 23.80 24.63

AL 21.47 23.80 24.63

AT 21.47 23.80 24.63

BA 21.47 23.80 24.63

BE 17.64 20.83 22.48

BG 13.10 17.31 19.93

CH 21.47 23.80 24.63

CZ 17.55 20.75 22.42

DE 26.53 27.73 27.48

DK 14.34 18.26 20.62


EE 11.11 15.76 18.81

ES 21.47 23.80 24.63

FI 17.18 20.47 22.22

FR 21.47 23.80 24.63

GB 25.80 27.16 27.07

GR 21.47 23.80 24.63

HR 19.08 21.95 23.29

HU 21.47 23.80 24.63

IE 21.47 23.80 24.63

IT 21.47 23.80 24.63

LT 16.10 19.63 21.61

LV 14.81 18.64 20.89

ME 21.47 23.80 24.63

MK 21.47 23.80 24.63

NL 21.47 23.80 24.63

NO 21.47 23.80 24.63

PL 18.65 21.61 23.04

PT 16.09 19.62 21.60

RO 19.79 22.50 23.69

RS 21.47 23.80 24.63

SE 21.47 23.80 24.63

SI 19.57 22.33 23.56

SK 22.07 24.26 24.97

UA 23.97 25.74 26.04

Table 11.Table 11.Table 11.Table 11. COCOCOCO2222 prices ( prices ( prices ( prices (€€€€2007200720072007/t/t/t/tonne COonne COonne COonne CO2222))))

ScenarioScenarioScenarioScenario 2010201020102010 2020202020202020 2030203020302030

Base case 14.18 36.03 44.39

Higher price 42.59 64.86 100.00

Lower price 15.00 20.00 25.00

Table 12.Table 12.Table 12.Table 12. Fuel efficiencyFuel efficiencyFuel efficiencyFuel efficiency and CO and CO and CO and CO2222 content content content content (tonne CO (tonne CO (tonne CO (tonne CO2222/MWh fuel)/MWh fuel)/MWh fuel)/MWh fuel)

Fuel typeFuel typeFuel typeFuel type 2010201020102010 2020202020202020 2030203020302030 COCOCOCO2222 content content content content

Hydro 1 1 1 0

Wind 1 1 1 0

Other renewable 0.29 0.33 0.34 0

Nuclear 1 1 1 0

Lignite coal 0.34 0.37 0.41 0.425

Hard coal 0.34 0.37 0.41 0.32637

Gas 0.46 0.49 0.50 0.20374

Oil 0.37 0.38 0.42 0.27927

Oil/gas mix 0.35 0.36 0.40 0.26542

NA 0.33 0.34 0.38 0.26


Table 13.Table 13.Table 13.Table 13. NonNonNonNon----fuel cost (fuel cost (fuel cost (fuel cost (€€€€2007200720072007/MWh)/MWh)/MWh)/MWh)

Fuel typeFuel typeFuel typeFuel type 2010201020102010 2020202020202020 2030203020302030

Hydro 3.00 3.00 3.00

Wind 0.50 0.50 0.50

Other renewable 3.00 3.00 3.00

Nuclear 6.00 6.00 6.00

Lignite coal 2.00 2.00 2.00

Hard coal 2.00 2.00 2.00

Gas 1.70 1.70 1.70

Oil 5.00 5.00 5.00

Oil/gas mix 5.00 5.00 5.00

NA 5.00 5.00 5.00


5 RESULTS

5.15.15.15.1 Simulation casesSimulation casesSimulation casesSimulation cases

Table 14 gives an overview of the cases that have been simulated. Figure 9 shows offshore wind farms and offshore grid in the North Sea region for the direct links case (08) and the hubs case (09). Table 15 contains an overview of key results for each simulation case.

Table 14.Table 14.Table 14.Table 14. Simulation casesSimulation casesSimulation casesSimulation cases

CaseCaseCaseCase DescriptionDescriptionDescriptionDescription

01 Base case 2030

02 Base case 2020

03 Base case 2010

04 T-connection – BritNor/Dogger 1




08 Case 01 + Direct links

09 Case 01 + Hubs

10 Meshed UK-NO: Case 01 + direct (line 2)

11 Meshed UK-NO: Case 01 + hubs (line 1)

12 Meshed UK-NO: Case 01 + hubs (line 1) – BritNor (UK-NO)

13 Meshed UK-NO: Case 01 + hubs (line 1) + extra UK-NO

14 Meshed UK-DE: Case 01 + direct (line 4)

15 Meshed UK-DE: Case 01 + hubs (line 3)

16 Meshed UK-DE: Case 01 + hubs (line 3) – Nemo (UK-BE)

17 T-connection – Nordlink/DanTysk 1 ( = Case 01)

18 T-connection – Nordlink/DanTysk 2



21 Sensitivity – Case 08 with higher CO2 prices


23 Sensitivity – Case 05 + extra UK-NO (line 2)



26 Sensitivity – Case 04 with 500 MW wind farm





31 Sensitivity – Case 01 with lower CO2 prices

32 (Sensitivity Nordlink connection point – only in preliminary simpulations)

33 Sensitivity – Case 01 – BritNor (UK-NO)


Table 15.Table 15.Table 15.Table 15. Results Results Results Results –––– key numbers key numbers key numbers key numbers

CaseCaseCaseCase

Total Total Total Total generation generation generation generation cost (Mcost (Mcost (Mcost (M€)€)€)€)

Difference Difference Difference Difference from base from base from base from base case (Mcase (Mcase (Mcase (M€)€)€)€)

Specific Specific Specific Specific generation generation generation generation cost (cost (cost (cost (€/MWh)€/MWh)€/MWh)€/MWh)

Price Price Price Price ((((€/MWh)€/MWh)€/MWh)€/MWh)

01 108 309 0.0 25.669 61.666

02 113 288 4 979.8 29.153 64.008

03 87 749 -20 559.5 25.744 65.961

04 108 309 0.1 25.669 61.664

05 108 333 24.1 25.675 61.742

06 108 312 3.6 25.670 61.683

07 108 284 -24.8 25.663 61.690

08 108 163 -145.2 25.635 61.477

09 108 227 -81.9 25.650 61.628

10 108 235 -73.5 25.652 61.572

11 108 270 -38.4 25.660 61.652

12 108 391 82.0 25.689 61.777

13 108 202 -106.9 25.644 61.561

14 108 254 -54.7 25.656 61.566

15 108 279 -29.8 25.662 61.630

16 108 339 30.7 25.677 61.736

17 108 309 0.0 25.669 61.666

18 108 312 3.8 25.670 61.648

19 108 308 -0.7 25.669 61.639

20 108 296 -12.3 25.666 61.658

21 147 459 39 150.3 34.955 86.189

22 147 539 39 230.8 34.974 86.205

23 108 254 -55.0 25.656 61.652

24 108 238 -70.8 25.652 61.596

25 108 215 -94.0 25.647 61.596

26 108 323 14.7 25.673 61.674

27 108 335 26.3 25.675 61.709

28 108 323 14.5 25.673 61.677

29 108 287 -21.2 25.664 61.664

30 147 647 39 338.8 35.000 86.152

31 90 225 -18 084.1 21.391 53.350

33 108 439 130.7 25.700 61.793


(a)

(b)

Figure 9.Figure 9.Figure 9.Figure 9. Offshore grid Offshore grid Offshore grid Offshore grid –––– a) hubs case (ca) hubs case (ca) hubs case (ca) hubs case (case 09)ase 09)ase 09)ase 09),,,, b) direct case (case 08) b) direct case (case 08) b) direct case (case 08) b) direct case (case 08)

Wind HydroOther

renewableNuclear

Lignite

coalHard coal Gas Other

case 3 (2010) 146 541 2 971 483 545 704 15

case 2 (2020) 589 564 267 921 409 449 675 11

case 1 (2030) 1 062 548 359 892 342 519 486 11

0

200

400

600

800

1 000

1 200

An

nu

al p

rod

uct

ion

(T

Wh

)

Energy mix of power generation

Figure 10.Figure 10.Figure 10.Figure 10. Energy mix in the 2010, 2020 and 2030 base casesEnergy mix in the 2010, 2020 and 2030 base casesEnergy mix in the 2010, 2020 and 2030 base casesEnergy mix in the 2010, 2020 and 2030 base cases

Total generation for the three cases shown in Figure 10 is

• 2010: 3409 (case 3)

• 2020: 3886 (case 2)

• 2030: 4219 (case 1)


5.25.25.25.2 Generation cost and electricity pricesGeneration cost and electricity pricesGeneration cost and electricity pricesGeneration cost and electricity prices

The simulation program runs an optimal power flow analysis for each hour, where the objective function is the total generation cost. In other words, the program computes the generation cost as part of the optimisation process. Generation cost is computed as the sum of power output times marginal cost for all generators (see chapter 2.1). The main factors that determine the total generation cost is therefore the marginal costs and the energy mix (see Figure 10).

To ensure that a solution can be found in all situations, a simple version of load shedding (rationing) is included in the model, i.e. the ability to reduce the demand. This has a cost associated with it that is always higher than the cost of the most expensive generator. In general, load shedding occurs if there is a mismatch between demand/generation and grid capacity. The overall load shedding in the 2030 base case is less than 0.2% of the total demand, when internal constrains within zones are not included. See chapter 3.7.

The electricity price (‘wholesale price’) is computed as a derived quantity during the post-processing of the simulation results, and therefore does not affect the power flow. The price is computed for each country for each hour, and is defined as the marginal cost (as defined in chapter 4.3) of the most expensive generator in operation within the given country and hour. For hydro plants outside the Nordic countries (NO, SE, FI), this cost does not include the water values (i.e. equals the base price 3 €/MWh). To further filter out water value influence on the electricity price, prices for the Nordic countries (NO, SE, FI) have not been included, i.e. the same prices have been used in all cases (computed as the highest marginal cost in the base case). This definition of price does not take into account the price of imported/exported power.

In general it is the most expensive generator type that sets the price. In most cases this is gas generators, which for e.g. Germany 2030 has a marginal cost 74.7 €/MWh. Unless water values are higher, and assuming at least one gas generator is in operation, the price for Germany will then be 74.4 €/MWh. The annual average should be expected to be of this order.

5.35.35.35.3 Reporting of simulation resultsReporting of simulation resultsReporting of simulation resultsReporting of simulation results

The results from the simulations have been collected and presented as Excel files. There is one report file per simulation case, and a summary file. The files have been made available to project partners via the project website. Below are descriptions of the content of these files. Summary file

The summary file contains key numbers taken from the individual case result files (see below). The format of the file is explained in Table 16.

Table 16.Table 16.Table 16.Table 16. Summary fileSummary fileSummary fileSummary file

ColumnColumnColumnColumn DescriptionDescriptionDescriptionDescription

A Case number

B Total generation cost for entire system

C Difference in generation cost (column C) from base case

D Specific generation cost (=total cost /total generation) for entire system

E Average price (Country average of annual average for each country. Price is computed for each hour for each country and equals the marginal cost of the most expensive generator in operation. Cost of hydro generation is treated in a special way. And variations in price time series for NO,SE,FI are not included – prices for these countries are kept equal to the base case )

F Difference in price (column E) from base case

G Average absolute bilateral price difference. The price difference is computed hour by hour and then averaged for each country pair. (cf. case report worksheet called 'abspricediff') The countries AL, MA, ME, RU, UA are not included in the average.

H Difference in column G from base case

I+J As columns G&H, but based on absolute cost differences (worksheet 'abscostdiff')


Individual case result files

Detailed results for each simulation case are given in separate spreadsheet files with the following worksheets:

Sheet ‘generation’Sheet ‘generation’Sheet ‘generation’Sheet ‘generation’: See Table 17.

Sheet ‘price’Sheet ‘price’Sheet ‘price’Sheet ‘price’: See Table 18.

Sheet ‘cosSheet ‘cosSheet ‘cosSheet ‘cost’t’t’t’: The ‘cost’ sheet is identical to the ‘price’ sheet except specific generation cost is used instead of price.

Sheet ‘Weighted_price’Sheet ‘Weighted_price’Sheet ‘Weighted_price’Sheet ‘Weighted_price’: Price per country based on an alternative price calculation using the weighted average of the nodal prices within each country, weighted by the demand at the node. The nodal price is defined by sensitivity: The increase in total cost of generation if one MWh of demand is added at the specific node.

Sheet ‘abspricediff'Sheet ‘abspricediff'Sheet ‘abspricediff'Sheet ‘abspricediff': A cross-table with the average absolute price difference between countries. The absolute price difference is computed hour-by-hour, and then averaged over the year.

Sheet ‘abscostdiff'Sheet ‘abscostdiff'Sheet ‘abscostdiff'Sheet ‘abscostdiff': As 'abspricediff' but with specific cost instead of price.

Sheet ‘interconnectors’Sheet ‘interconnectors’Sheet ‘interconnectors’Sheet ‘interconnectors’: Includes all HVDC connections in the model. See Table 19.

Sheet ‘wind’Sheet ‘wind’Sheet ‘wind’Sheet ‘wind’: Information on onshore and offshore wind power production. See Table 20. Note: The report does not include an estimate for downtime that would reduce potential wind production. The export cable capacity constraint is in reality therefore less than indicated in column J.

Table 17.Table 17.Table 17.Table 17. Report file Report file Report file Report file –––– sheet ‘ sheet ‘ sheet ‘ sheet ‘generationgenerationgenerationgeneration’’’’


A Country code

B Total met demand

C Total unmet demand, i.e. Load shed. In principle this should be zero

D Total generation

E Net import = column B - column D

F Total generation cost. Sum of hour-by-hour values

G Specific generation cost = column F/column D

Table 18.Table 18.Table 18.Table 18. Report file Report file Report file Report file –––– sheet ‘ sheet ‘ sheet ‘ sheet ‘pricepricepriceprice’ (and ‘cost’)’ (and ‘cost’)’ (and ‘cost’)’ (and ‘cost’)

ColumnColumnColumnColumn DescriDescriDescriDescriptionptionptionption

A Country code

B Price calculated as explained above

C Number of hours when no price could be computed. This should be zero

D Maximum price during the whole year

E Minimum price during the whole year

F Standard deviation of price time series

G Average absolute price change from hour to hour

H Maximum price change (max rise) form hour to hour

I Minimum price change (max drop) from hour to hour

J,K,L As column G-I, but comparing hour to 5 hours later

M,N,O As column G-I, but comparing hour to 10 hours later

P,Q,R As column G-I, but comparing hour to 24 hours later

S,T,U As column G-I, but comparing hour to 48 hours later

V-AS Hourly profile, i.e. annual average price for each hour of the day

Table 19.Table 19.Table 19.Table 19. Report file Report file Report file Report file –––– sheet ‘interconnectors’ sheet ‘interconnectors’ sheet ‘interconnectors’ sheet ‘interconnectors’

ColumnColumnColumnColumn DeDeDeDescriptionscriptionscriptionscription

A Name of first node.(‘O: ’ signifies offshore node)

B Name of second node


C Country code for first node

D Country code for second node

E Value of the interconnections, calculated as follows: Hour-by-hour value is computed as price difference (€/MWh) multiplied by flow (MWx1h). If the flow is opposite direction of price difference, zero value for that hour is used instead. Hour-by-hour values are then summed up to get total value.

F As column E except specific cost difference has been used instead of price difference.

G Capacity of line in direction of first to second node

H Capacity of line in direction of second to first node

I Mean flow in direction first to second node

J Mean flow in direction second to first node

K Percentage of the time the flow is in direction first to second node

L Percentage of time the flow is in direction second to first node (K+L is not necessarily 100% as sometimes there may be no flow at all)

M Utilisation of line = mean flow/capacity

Table 20.Table 20.Table 20.Table 20. Sheet ‘wind’Sheet ‘wind’Sheet ‘wind’Sheet ‘wind’


A Country code

B Onshore wind capacity

C Onshore potential wind production

D Onshore actual wind production (possibly less than column B due to grid constraints)

E Constrained production due to grid = column C - column D

F Offshore wind capacity

G Offshore potential wind production

H Offshore potential wind export (=potential wind production capped to 90% of capacity due to export cable capacity limitation)

I Offshore actual wind export (possibly less than column H due to grid constraints)

J Constrained production due to export cable capacity = column G - column H

K Constrained production due to grid = column H - column I


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AppendixAppendixAppendixAppendix Simulation case report files and summary file in XLS spreadsheet format, bundled as a ZIP file and available through the project internal website.

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