hydrogen energy system with renewables for isolated households: the optimal system design, numerical...

Accepted Manuscript

Title: Hydrogen energy system with renewables for isolatedhouseholds: The optimal system design, numerical analysisand experimental evaluation

Author: Rok Lacko Bostjan Drobnic Mihael Sekavcnik MitjaMori

PII: S0378-7788(14)00309-0DOI: http://dx.doi.org/doi:10.1016/j.enbuild.2014.04.009Reference: ENB 4973

To appear in: ENB

Received date: 23-1-2014Revised date: 2-4-2014Accepted date: 6-4-2014

Please cite this article as: R. Lacko, B. Drobnic, M. Sekavcnik, M. Mori, Hydrogenenergy system with renewables for isolated households: The optimal system design,numerical analysis and experimental evaluation, Energy and Buildings (2014),http://dx.doi.org/10.1016/j.enbuild.2014.04.009

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http://dx.doi.org/doi:10.1016/j.enbuild.2014.04.009

http://dx.doi.org/10.1016/j.enbuild.2014.04.009

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Hydrogen energy system with renewables for isolated households: The

optimal system design, numerical analysis and experimental evaluation

Rok Lackoa, Boštjan Drobničb,c, Mihael Sekavčnikb,c, Mitja Morib,c,*

a INEA d.o.o., Stegne 11, 1000 Ljubljana, Slovenia

b Faculty of mechanical engineering, University of Ljubljana, Aškerčeva 6, 1000 Ljubljana, Slovenia

c Centre of Excellence for Low‐Carbon Technologies, Hajdrihova 19, 1000 Ljubljana, Slovenia

*Corresponding author. Tel +386 1 4771715; fax: +386 1 2518567. E‐mail address:

[email protected]‐lj.si (M. Mori)

Abstract

One potential solution for stand‐alone power generation is to use hybrid energy systems

with hydrogen storage. In this paper, the physical behaviour of a hydrogen energy system

with renewables has been numerically simulated and experimentally re‐enacted. A reference

household in Slovenia’s coastal region was used to identify the optimal energy system

design, by considering the geographical location, availability of energy sources, actual load

dynamics, and components’ technical and economical characteristics. The results show that

optimal electricity supply is technically feasible with a 100% renewable system, consisting of

wind turbines and solar photovoltaic arrays, including hydrogen technologies (electrolyser,

hydrogen tank, fuel cell). The optimal feasible system capacity (33 kW), with the lowest total

net present cost (€136,063), is approximately eight times larger than the peak power

demand (3.8 kW). The experimental work was performed at hydrogen laboratory facilities.

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Experiments proved the possibility of alternative uses of existing industrial hydrogen

technology for balancing power supply and demand, with a mere 3% deviation from

numerical results. Keywords: Experimental validation; Hydrogen technologies; Reference

household; Renewable energy sources; Self‐sufficient energy system.

1. Introduction

The increasing needs for energy and the uncertain costs of future fossil fuel supplies, along

with the mitigation of climate change effects and natural environment preservation, are the

reasons for the increasing interest in renewable (RES), local and distributed energy sources,

as opposed to centralised fossil primary energy usage. While fully energy self‐sufficient

dwellings are still rare, solar and wind power units have been widely adopted for private

family homes. The introduction of RES into the energy supply, however, raises certain issues

in balancing energy demand and supply due to their variable and non‐storable nature. This

especially applies to wind and solar energy, and (to a lesser respect) to other RES, such as

geothermal energy, hydropower and biomass. Furthermore, a single stand‐alone user

presents the most challenging case of RES integration, due to its inability to import and

export surplus energy.

In coping with the misalignment of energy production and demand, the use of energy

storage is usually required [1]. Hydrogen technology is a technically viable storage solution

especially in energy systems with high shares of renewables [2–4]. Several technical and

economic numerical simulations of stand‐alone RES energy systems with hydrogen storage

have already been discussed [5–11]. Such hybrid energy systems have also been

experimentally demonstrated [12–15] or partially experimentally validated [16].

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Although stand‐alone RES‐hydrogen energy systems have been proposed and studied,

common shortcomings of those analyses include (a) a pre‐determined system design, (b)

optimization of system’s performance without preliminary optimising its configuration or

design, (c) overgeneralised input parameters, such as using typical daily consumption data

sets only, (d) short term simulation only (day, week) and finally (e) numerical models and

simulation results not being experimentally evaluated and verified. Studies also show that

results are highly dependent on numerous local factors, e.g. meteorological conditions;

therefore, a site‐specific analysis is needed for credible results [17].

This paper aims to overcome the detected shortcomings by considering the topics of optimal

hydrogen‐RES system design based on relevant, site specific and actual measured input data,

hourly system’s dynamics analysis for a period of one year, including experimental

evaluation of numerical results. An RES‐hydrogen energy system for a self‐sufficient power

supply of a single household is described and analysed in this study, as shown schematically

in Fig. 1. In this example, hydrogen is produced (and stored in a tank) by an electrolyser,

which is powered by the surplus electricity from renewable energy sources, using solar and

wind technologies (specifically at summer daytime). When RES are scarce, or demand is high,

additional power is needed; therefore, the fuel cell converts the chemical energy of the

stored hydrogen gas directly into electricity (usually at night and in winter).

2. Methodology

The scope of this work is, first, to find an optimal feasible configuration of a self‐sufficient

energy system based on RES and hydrogen technologies for a remote household located in

Slovenia and to numerically model its physical behaviour and, second, to experimentally

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validate the results of the system’s operation. In this study, only electricity is considered.

Experimentally, only hydrogen technologies are validated, while renewables are only

simulated. A demonstration laboratory system with hydrogen technologies was used for

experimental evaluation of the numerical results; its photograph is shown in Fig. 6.

2.1 Numerical model and simulation

The optimal RES‐hydrogen energy system structure was determined using the HOMER

numerical simulation software, based on the lowest net present cost. The energy system’s

physical behaviour and its life‐cycle cost, which is the total cost of installation and operation

over its life span, have been modelled. HOMER is a deterministic input/output model making

annual analyses in steps of one hour. The general inputs are the demands, capacities,

component technical characteristics and costs. Outputs or results are the energy balances,

capacities, resulting annual production and life‐cycle costs.

In this paper, the power supply of a stand‐alone household, located in Slovenia, is

considered. In the model (Fig. 1), AC electrical load is supplied, via DC‐AC inverter, primarily

by wind turbine and photovoltaic array. Excess electricity produced from RES is stored as

electrolytically produced hydrogen. When primary RES are scarce or unavailable, the fuel cell

system produces power from stored hydrogen.

Here, mathematical models of energy systems are not based on differential equations;

instead, a quasi‐dynamic approach has been used, and stationary conditions within each

hourly interval have been assumed. For each time interval, an energy balance has been

calculated, presented in general by Eq. (1),

(1)

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where E denotes the total energy at time interval t.

For the conversion of solar radiation to electrical energy, a photovoltaic array (PV) has been

used. The power output of the PV array depends on the amount of radiation striking its

surface, which is generally not horizontal. Thus, in each time step, the model calculates the

global solar irradiation on the surface of the PV array. In the calculation of the PV’s power

output, its rated capacity, de‐rating factor, solar irradiation, temperature coefficient of

power and PV cell temperature are considered. For converting wind kinetic energy into

electricity, a wind turbine (WT) was used. Its power depends on wind speed, adjusted to hub

height, and its power curve [18]. The cut‐in wind speed of the chosen wind turbine equals 3

m/s, and it reaches peak output power at wind speeds of 13 m/s. The hydrogen production

rate is defined by the electrolyser’s efficiency and minimum load ratio (technical minimum).

Experimentally determined values 72 and 50%, respectively, were used [19]. A hydrogen

container is used to store produced hydrogen for later use. A fuel cell system re‐powers

stored hydrogen when there is not enough RES. Fuel cell hydrogen consumption depends on

the fuel curve, shown in Fig. 2, which was experimentally defined [20]. The fuel cell’s electric

efficiency is based on a lower heating value (LHV): 120 MJ/kg (maximum efficiency is 48%).

The DC/AC power converter’s energy efficiency of 0.9 has been used in the calculation.

The model simulates different system configurations with several combinations of

components (and their sizes), which are specified in the components’ inputs. All feasible

system configurations are then listed in order from most cost‐effective to least cost‐

effective, based on their net present cost (NPC).

The project’s lifetime is assumed to be 20 years, as well as all components’ lifetime, except

for the fuel cell, which has to be replaced every 20,000 operating hours. The annual real

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interest rate considered in the model was 6%. Table 1 shows components’ parameters as

boundary conditions of the model, considered in optimising the configuration of the system.

The sizes of the PV array and wind turbine considered in calculation were 10 to 30 and 5 to

20 kW, respectively. The electrolyser, fuel cell and converter sizes between 1 and 6 kW were

considered. The capital costs of investment are based on invoices acquired within this

project. Operation and maintenance (O&M) costs are based on [7]. The minimum and

maximum sizes of components were chosen in an iterative process to ensure that the

optimum lies within spans presented in Table 1.

2.2 Model input data

The input data time series (hourly averages) needed for the analysis were obtained from

actual measurements. Electricity consumption data (Fig. 3) were taken from the MeRegio

and Mirabel projects [21]. A single load with average electricity consumption of 11 kWh/day

and a 3.8 kW hourly averaged maximum peak has been chosen. Its annual electricity

consumption amounts to 4,160 kWh.

Meteorological data (solar irradiation, wind speed) for renewable energy source

determination were acquired from ARSO’s1 meteorological test reference year (synthetically

constructed time series based on a multiple year historical digital data set that is typical for a

specific location). Fig. 4 shows reference hourly averaged global solar irradiation (left) and

wind speed (right) in Slovenia’s coastal region, with annual average daily global horizontal

irradiation 3.9 kWh/m² and wind speed of 2.8 m/s, peaking at 10.6 m/s [22].

1 Slovenian Environment Agency

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2.3 Experimental hydrogen energy system

The hydrogen energy system set for experimental and technology demonstration purpose is

installed at the Šoštanj thermal power plant in Slovenia. The facilities were used to provide

experimental evaluation of the use of hydrogen technology for energy storage and balancing

in a RES‐rich system. The schematic of the experimental set‐up is shown in Fig. 5 and its

photograph in Fig. 6. It is composed of alkaline electrolyser (Hydrogenics HySTAT) with 120

kWe nominal capacity and hydrogen production rate up to 15 Nm³/hr at 25 bar. The

hydrogen tank size is 20 m³. The low temperature PEM‐type fuel cell UPS system (Future‐E

Jupiter) delivers 6 kWe of power. Additional equipment consists of an electronic load (Amrel

PLW) with cooling unit (Hidros LSK), measuring instrumentation (hydrogen mass flow

meters, electric meters, pressure gauges, etc.), PLC (Mitsubishi Q series) and a computer

control system with remote access. This system has been fully‐instrumented to accurately

determine energy and hydrogen mass balances.

3. Results and discussion

3.1 Numerical simulation results

A feasible system is defined as a hybrid system configuration that is capable of meeting the

required load. Under given conditions, one system configuration was found to be feasible. It

has a total of 102 different combinations of size or number of components. The optimal

combination, with the lowest total net present cost (€136,063), is presented in Table 2. The

(levelised) cost of energy for optimal system combination is €2.8/kWh. The current

electricity grid purchase price in Slovenia for households is approximately €0.15/kWh. The

combined nominal primary (RES) and secondary (fuel cell) power source capacity is 33 kW,

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while peak demand is 3.8 kW. The optimal electrolyser and converter size is 4 kW, each, with

tank capacity being 30 kg of hydrogen.

Fig. 7–Fig. 9 show the principal components’ operating characteristics: electrolyser input

power, fuel cell output power and their duration curves and hydrogen storage level,

respectively. Hydrogen energy storage shows the ability to store inter‐seasonal fluctuations

of RES availability. Summers’ higher RES energy density is stored to be used during the

colder half of the year (Fig. 9). Unlike the fuel cell (Fig. 8), the electrolyser (Fig. 7) operates

during 74% of the operation time at nominal power (Fig. 9). In Fig. 9, the difference between

electrolyser electricity consumption and fuel cell electricity production, which represents the

overall efficiency of hydrogen energy storage (averaging 26%) is also shown.

Table 3 presents an optimal system’s electrical production and consumption values. The PV

arrays produce 75%, while the secondary power source (fuel cell) produces 10% of the

electricity. The electrolyser’s electricity consumption rate is 69%, while the household

consumes 31%. All electric load was met throughout the year, and the excess electricity is

42% of overall production.

Table 4 lists optimal system configuration characteristics, reflected in low mean outputs and

low capacity factors. Capacity factors vary from 3.4% to 12.1%, except for the electrolyser

being 26.5%. The average power of production, from primary and secondary power sources,

exceeds the average household load by 588%, the largest contribution being from

photovoltaic arrays (PV) with 447% penetration. The results show similar operation times of

PV and wind turbine (WT), 3,873 and 3,556 hours per year, respectively. In contrast, the

electrolyser (EL) operates less frequently (2,507 hours/year) than the fuel cell (4,771

hours/year), which is also demonstrated by fewer start‐ups. The fuel cell’s (FC) life span of

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20,000 operating hours means that replacement is necessary after every 4.14 years. The

average fuel cell’s electric efficiency is 42.9%. The electrolyser produces 170 kg of hydrogen,

while the fuel cell consumes 167 kg annually, which enables the start of the following year

with sufficient supplies of hydrogen.

3.2 Experimental results

The fact that the given experimental system configuration is unalterable prevents the

recreation of an exact experimental match to different numerical model designs. In order to

conduct an experiment in which the model and real system capacity do not match, scaling

has to be applied. For the purpose of this experiment, capacity (input power), hydrogen

production rate and time scaling were applied. The fuel cell system’s modular design (3 ×

2 kW) enabled the direct transfer of the numerical model results to be replicated in the

experiment. In contrast, the electrolyser prevents any capacity adjustment; therefore, linear

scaling was performed. After consulting electrolyser system operators, the maximum input

power in the experiment was set to 72 kWe.

The electrolyser’s experimental operation program was acquired using numerical simulation

results, multiplied by 72/4. For analogue‐to‐input power, the hydrogen production

measurements during the experiment were multiplied by 4/72. On the basis of previous

experimental work, the fast electrolyser system operation response to power changes and

relatively fast start‐up times (less than 10 seconds) were observed. For that reason, and due

to relatively long simulation period (hourly steps in one year), the experiment’s duration was

limited to a period of one week in summer and scaled so that one hour in the model

corresponds to one minute in the experiment. Furthermore, due to frequent start‐up

limitations, the electrolyser was not shut down during the experiment, but its power was

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reduced, as seen in Fig. 10. For the analysis, data (power and hydrogen production rate)

from that period were not taken into consideration (used as zero), which is also shown in Fig.

10. Fig. 11 and Fig. 12 present the chosen one‐week period with both numerical and

experimental results of device power and hydrogen flow rate, respectively. Both the

electrolyser and the fuel cell typically start once per day. The electrolyser operates in periods

of excess electricity production during the daylight. In contrast, the fuel cell mostly operates

during the night, acting as a substitute for the missing solar irradiation. A comparison of

integral parameters, both simulation and experiment, presented in Table 5, shows

remarkably good matches of both results, with differences of less than 3%.

3.3 Error analysis and validation of results

The analyses in this paper have been conducted using the HOMER model, which is a leading

micro‐power optimisation tool for off‐grid and grid‐connected hybrid renewable energy

systems; it has been used for a large number of analyses published in peer‐reviewed journal

articles, including [6,8,10,23–32]. The model has been validated through its ability to

replicate existing energy systems, such as calculating the same fuel demands as revealed by

energy statistics.

Experimental studies usually involve some unpredictable and uncertain factors that occur

due to instrumental manufacturing errors, calibration errors and human mistakes. The

measurement uncertainty has been calculated based on the instruments’ documentation

and calibration data sheets. The instruments accuracy, the maximum absolute error and a

type B uncertainty of direct or indirect measurements for each individual component in the

instrumental chain are presented in Table 6. In general, industrial Class 1 measuring

instruments have been used with a 1% accuracy, or better. Alongside measurement

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uncertainty, some error can be attributed to the generalised modelling of the devices; the

fuel cell UPS system also contains a battery for quick power response due to slow core (fuel

cell stack) ramping dynamics, which have been modelled as one single device. Furthermore,

the actual electrolyser efficiency is not constant, but has been modelled as such.

Additionally, other dynamic characteristics of the electrolyser have been ignored, e.g.

internal pressure buffer, hydrogen filtering discharge and power ramping. Due to the fact

that the electrolyser operates at nominal power the majority of time (74%) and only starts

once per day on average, the model using a single operating point proves sufficient for the

scope of this research.

Scaling the results of a fuel cell or electrolyser linearly, raises a question of accuracy. Some

errors in results and reduced relevance could rightly be recognised. Arguments in favour of

this method (linear scaling) are that (a) fuel cells (and electrolysers, since it is essentially the

same process) are unique as energy converters, i.e. their range of application (in terms of

power and use) far exceeds all other types [33], (b) most auxiliary power is used for cooling

which is proportional to power, (c) one large unit in the model can in reality be substituted

by several smaller ones (dispersed or centralised), and (d) EL and FC are in essence both

already composed of multiple individual cells (forming stack), implying their fundamental

ability to scale.

The experimental results presented in this paper indicate that previously described

shortcomings only have a minor effect since the deviation to the calculations is small. Thus,

the results additionally validate (in addition to the literature) the numerical structure of the

tool itself, as well as the specific model that we have designed, specifically in part of the

hydrogen technology. Furthermore, the results of this analysis show that (a) the electrolyser

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mostly operates at daytime, while the fuel cell at night; (b) in any case, they do not operate

simultaneously; and (c) integrating RES for an isolated and self‐sufficient household in

Slovenia requires the use of seasonal energy storage, which is in accordance with

expectations. Additionally, the results show that a 100% renewable energy system is

feasible, which is in accordance with [8,10,30,34–38].

4. Conclusions

In this paper, an optimal RES‐hydrogen system was analysed and designed. A numerical

model of an RES‐hydrogen energy system was experimentally recreated and compared to

numerical results.

The analyses are based on historically relevant, site‐specific and actual measured input data,

hourly system dynamics for a period of one year, which were used as inputs for modelling

and simulation using commercial software and for conducting the experiment.

The results illustrate that the discussed energy system requires large production capacity,

which results in considerable excess electricity production (almost 50%) and low energy

utilisation (low capacity factor). Due to low resource availability and intermittent seasonal

energy, large seasonal storage of hydrogen is required. Furthermore, the results of this

analysis show that the electrolyser mostly operates at daytime with nominal power, while

the fuel cell operates highly variably at night; they never operate simultaneously.

Additionally, the results show that a 100% renewable power supply of a household, using

hydrogen storage is feasible, although costly. Experiments have confirmed the numerical

results with a mere 3% deviation. In addition, the experiments proved possible the

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alternative use of existing industrial hydrogen technology: as the storage and balancing of

energy in a stand‐alone household powered from fluctuating renewable energy sources.

Acknowledgements

This operation has been partly financed by the European Union, the European Social Fund.

The part of presented work has been accomplished within the Centre of Excellence for Low‐

Carbon Technologies (CONOT), Hajdrihova 19, 1000 Ljubljana, Slovenia. This work was

supported by INEA d.o.o., Stegne 11, 1117 Ljubljana, Slovenia and Šoštanj thermal power

plant, Cesta Lole Ribarja 18, 3325 Šoštanj.

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Fig. 1. A schematic of the numerical model of a stand-alone energy system with

renewables and hydrogen storage.

Fig. 2. Experimentally determined fuel cell’s fuel curve (left); corresponding

maximum efficiency of the fuel cell is 48% (right) [20].

Fig. 3. A one-year (left) and a one-day section (right) of hourly averaged electricity

consumption of a reference household [21].

Fig. 4. Reference hourly averaged solar irradiation (left) and wind speed (right) in

Portorož. Meteorological data were acquired from ARSO [22].

Fig. 5: General scheme of experimental system with hydrogen technologies.

Fig. 6: Photograph of the outside of the hydrogen technology testing facilities, which

consist of container units with electrolyser and fuel cell systems, and a hydrogen

storage.

Fig. 7. The result of annual simulation of electrolyser’s input power in steps of one

hour.

Fig. 8. The result of a simulation of fuel cell’s output power: full year scale (left),

one-week section (right).

Fig. 9: Electrolyser and fuel cell duration curves (left) and hourly averaged hydrogen

storage content (right).

Fig. 10. Correction of experimental results by neglecting values in periods of

simulated turn-off.

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Fig. 11. Simulation and experimental power distribution of a 1-week period in

summer. Electrolyser mostly operates with its nominal power, while the fuel cell’s

operation is highly variable. Typically both devices start once per day (electrolyser at

daytime, fuel cell at night).

Fig. 12. Simulation and experimental hydrogen flow rate distribution of a 1-week

period in summer. Deviations in results are the consequence of the UPS’s battery

charging even after the demand reduces and of the electrolyser’s internal pressure

buffer and hydrogen filtering discharge.

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Table 1 Considered input parameters of the components used for optimising the system configuration. Size spans were determined iteratively; capital cost estimations are based on invoices; O&M costs are based on [7].

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Table 2 Optimal system configuration, based on lowest net present cost. Significant production capacities (33 kW) are needed in order to meet the load (3.8 kW hourly averaged peak).

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Table 3 Optimal system configuration electrical production and consumption.

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Table 4 Optimal system configuration characteristics.

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Table 5 Simulation and experiment results comparison. Small deviation (3%) experimentally validates the numerical model design and the possibility of alternative use of the currently available industrial hydrogen technology for balancing power production and demand.

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Table 6 The accuracy, maximum absolute error and the measurement uncertainty for each individual component in the chain of measurements, as well as the combined measurement uncertainty of the experimental hydrogen energy system, located in Šoštanj.

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Highlights

We model the self‐sufficient energy system with renewables and hydrogen storage.

Required large renewable production capacities result in low capacity factors.

The electrolyser operates mostly with its nominal power, while fuel cell’s varies.

Hydrogen energy seasonal storage enables 100% renewable power supply.

Experiment validates model design and alternative use of hydrogen technologies.

hydrogen energy system with renewables for isolated households: the optimal system design, numerical...

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