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Energy Procedia 99 (2016) 292 - 297
10th International Renewable Energy Storage Conference, IRES 2016, 15-17 March 2016,
Düsseldorf, Germany
Prospective Integration of Renewable Energies with High Capacities Using Combined Heat and Power Plants (CHP) with
Thermal Storages
Dr.-Ing. Tim Schmidlaa*, Prof. Dr.-Ing. habil. Ingo Stadlera
University of Applied Sciences, Institute of Electrical Engineering, Betzdorfer Straße 2, Cologne 50679, Germany
Abstract
The increasing use of fluctuating generation plants like wind turbines and solar power systems makes new demands on the existing power grid. Aiming at the expand of renewable energies in our electrical power supply system and their implementation as a basic grid component will lead to an increasing demand of operating reserve and balancing energy due to the stochastic feed in character. At the same time also a strong increase of efficient CHP systems in the current supply structure will be aspired. Regarding this context decentralized plants like combined heat and power (CHP) can be used in our present power supply system in such a way, that a future electricity supply with high fraction of fluctuating renewable energies as wind power and photovoltaics could be possible. In connection with enlarged thermal storages, their specific application can add a substantial contribution in combination with an aimed electricity supply of 80 % renewable energy. According to the heat demand also this form of generation indicates a stochastic feed in or consumption behavior. The integration of thermal energy storages can decouple the production of electricity and heat from time to time. Seeing that on one side the fraction of CHP systems can be developed clearly and on the other side this kind of plant configuration makes a contribution to a functioning future power supply. The paper will describe the integration of such cogeneration systems on basis of the German supply system. To combine heat and power operated solutions the operation schedule of the system and his participants is calculated by a linear optimization tool. Based on a high fraction of those combined systems, a functioning future power supply is possible basically also without intense use of battery storages.
© 2016 The Authors. Published by ElsevierLtd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.Org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of EUROSOLAR - The European Association for Renewable Energy
* tim.schmidla1@th-koeln.de
1876-6102 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.Org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of EUROSOLAR - The European Association for Renewable Energy doi: 10.1016/j.egypro.2016.10.119
Tim Schmidla and Ingo Stadler /Energy Procedía 99 (2016) 292 — 297 Keywords: Distributed generation, combined heat and power (CHP), optimization, virtual power plant, thermal storages, energy management
1. Introduction
In the course of the German "Energiewende" there should be a power supply with 80 % of renewable energy in 2050 [1] [2]. A power supply with such a high fraction of renewable energy has considerable fluctuations between electrical production and electrical demand. At the same time the removal of the present residential building stock up to passive house standard will be implemented and the local heat demand will decrease significantly.
The current analysis deals with a power supply based on 100 % of renewable energy and aims on the detection of useful compensation strategies for this application case (Fig. 1). The investigation shows on one side, that our actual heat supply can be increasingly moved by the conventional heat production to a supply with CHP systems and otherwise that a partly separation of heat and power production is possible for the provision of balancing energy (see also [3], [4], [5]).
Energy supply and demand in 2010 and 2050
time [m]
Fig. 1. Half year comparison between 2010 and a 100 % renewable supply in 2050
The efficiency of conventional centralized power systems is generally low in comparison with combined heat and power (CHP) technologies which produce electricity or mechanical power and recover waste heat for process use (cogeneration). CHP systems can deliver energy with efficiencies exceeding 90%, while significantly reducing the emissions of greenhouse gases and other pollutants. Generally residential CHP systems or cogeneration power plants connected to a district heating network are heat operated. That means the operation control of the CHP system mainly follows the heat demand of the consumer. In order to integrate residential CHP systems into energy management a mixed control strategy is needed combining both heat and power operated solutions. Based on a forecast of the power and heat demand the operation schedule of the distributed system will be calculated by an energy management optimizer (presented in [6] and [7]). In the next sections a procedure is described to find a functional configuration of the CHP units and enlarged thermal storages within a virtual plant structure. Such a virtual plant can be used for the substitution of missing wind and solar energy. Thereby the demand of heat and electricity of the buildings can be covered and guaranteed.
2. Methodology
A potential analysis delivered the required time series for the simulation scenarios in 2050. For the calculation the electrical generation by water power, biomass and geothermal energy was constantly considered with 50,1 TWh per year and an equipartition of the installed capacity concerning solar and wind power was also assumed. Based on five reference years (the definition is listed below) the generation of wind and solar power has been incremented until a specific coverage of the confronted electrical load was reached.
• 1994: solar and wind proposition above average
• 1996: solar and wind proposition below average
• 1998: solar proposition ^ below average; wind proposition above average
• 1999: solar- and wind proposition average
• 2003 : solar proposition ^ above average; wind proposition below average
In this case the overall electrical load was presumed with 525 TWh per year, composed of the single sectoral demands from households, trade and commerce plus the industry. Starting from generation coverage by renewable energy of 60 %, 80 %, 100 % and 120 %, the comparison with the electrical load led finally to several residual load profiles (Fig. 2).
Residual load (reference year 1996)
Fig. 2. Residual load profile in 2050 based on the case study assumptions
Thermal load of the household sector (reference year 1994)
3.0 --
Fig. 3. Example of a thermal load profile for a single household in 2050
Calculated energy amounts which exceeded the grid capacity limit of 200 GW were strictly bolted and the residual load was further brought to a demand side management analysis. The resulting deficit periods inside the electrical load profiles built together with the different sectoral thermal demands (exemplary displayed in Fig. 3) the framework conditions for the simulation of CHP and thermal storage configurations and feasible operating modes. Equations and formulae should be typed in Mathtype, and numbered consecutively with Arabic numerals in parentheses on the right hand side of the page (if referred to explicitly in the text). They should also be separated from the surrounding text by one space.
Figure 4 summarizes the basic simulation or rather calculation procedure. In any simulation cases the use of long time storage systems like pumped hydro or methane and thermal peak load vessels was needed to ensure a balanced energy system on both - electric and thermic - sides.
electric demand
electric supply
thermal supply
thermal demand
electric load
electric load
thermal storage
balanced energy system
balanced energy system
Fig. 4. Basic overview of simulation respectively calculation procedure
3. Results
Outgoing from the previous assumptions the following results and conclusions were mentioned. With an assumed shifting potential about 20 GWh per activation period and a maximal number of those single operations about 348 an overall energy compensation of more than 1.000 hours with a common energy content up to 23 TWh could be realized in each simulation based on a 100 % renewable coverage scenario.
Figure 5 shows the calculated deficit times and energy contents of each reference year based on the various renewable coverage rates. In case of the 100 % scenarios a mean deficit about 155 TWh and over 5.000 hours could be monitored; by deducting the demand side management values in a next step more than 130 TWh and 4.000 hours remained for the profitable CHP operation in deficit time periods. In fact the optimizer (described in [6] and [7]) was used for calculating the CHP and thermal storage configuration and operation schedules for all plant sections on the basis of the different system information.
Overall energy content
renewable coverage [%]
45,00 -40,00 Maximal energy content in one period
■ 1691 ■ 1996 ■ 1998 ■ 1999 2003
— 30,00 ^ 25,00 - ■g 20,00 IS -a 10,00 5,00 0,00 - 1
1 ■ 1
1 I iîïnF^^ff I
60 00 100 120 renewable coverage [%]
Fig. 5. Basic simulation results concerning deficit period behavior
Fig. 6. Key figures of CHP operation with an enlarged thermal storage system
Figure 6 displays the results which were achieved depending on the stepwise enlargement of the thermal storage oriented on the mean daily maximum thermal load in the reference years 1996 and 2003. Based on an assumed real market penetration of 50 % and herein an installed thermal capacity about 40 % of the yearly maximum thermal
load, a possible electric deficit reduction of nearly 20 GWh on average was pointed out by an enlargement of two storable daily maximum loads.
The most ideal overall performance has been reached with inserted CHP coefficients between a = 0,4 and 0,6. Over 60 % operating time of the CHP proportional to the peak load vessel system could be achieved with more than 4.000 full-load hours. Seeing that instead of 130 TWh less than 50 TWh must be balanced by long time storage systems or energy imports.
4. Discussion
The integration of thermal energy storages decouples the production of electricity and heat from time to time. Seeing that on one side the fraction of CHP systems can be developed clearly and on the other side this kind of plant configuration makes a contribution to a functioning future power supply. The disadvantage of today's power supply, that the production has to follow the load, means also that the overall capacity of our power plants must directly correspond to the peak load level even though the operational demand is temporary. Storages charged in low load periods and discharged in peak load periods decouple production and consumption profitable.
Acting on the suggestion of price incentive the generation of electrical power operates proportional to the given superordinate electrical load profile and leads to an optimal capping. Separation of heat production and power production using the thermal storage system permits a current operation mode with simultaneous covering of local heat load profile at plant location. The potential of such a high fraction of CHP generation systems already exists and can be seen at the development of the energy supply system of Denmark. [8]
5. Conclusion
The concept makes an integration of CHP plants into a future grid system possible and under convenient framework conditions, which means particularly suitable incentives for the prosumers (producer/ consumer) such as [3], also economic viable. Herein the most efficient operation mode is calculated using a linear algorithm structure involving actual and forecast data for solving the existing optimization problem. Decentralized produced energy is used directly at the place of production. In the described scenario the virtual plant is used for the substitution of missing wind and solar energy. Under the use of thermal storage systems thereby the heat demand of each building can be covered and guaranteed providing the maximization of contribution margin.
References
[1] www.bundesregierung.de/Content/DE/StatischeSeiten/Breg/Energiekonzept/auftakt.html (accessed January 2016)
[2] The German Roadmap E-Energy/ Smart Grid, German Commission for Electrical, Electronic & Information Technologies of DIN and VDE, Published by VDE Association for Electrical, Electronic & Information Technologies, Frankfurt am Main, Germany, 2010
[3] Merkblatt Erneuerbare Energien, KfW-Programm Erneuerbare Energien "Premium", KfW Palmengartenstr. 5-9, 60325 Frankfurt, www.kfw.de (accessed January 2016)
[4] Energy Management in the Low-Voltage Supply by means of Decentralized Decision, D. Nestle; Renewable Energies and Energy Efficiency Vol. 7, Kassel, 2008
[5] Demand Response, state doctorate, Prof. Dr.-Ing. habil. I. Stadler, Kassel, 2005
[6] Integration of Cogeneration Systems into Smart Grids, SPEEDAM 2012, Schellong W. / Schmidla T. / Stadler I. / Strumpler F.; International Symposium on Power Electronics, Electrical Drives, Automation and Motion, 21st Edition - June 20 - 22, 2012, Sorrento / Italy, IEEE-Explore Digital Library, August 2012, ISBN: 978-1-4673-1299-8
[7] Optimization of distributed cogeneration systems, Schellong, W.; Schmidla, T., Industrial Technology (ICIT), 2013 IEEE International Conference on Year: 2013 Pages: 879 - 884, DOI: 10.1109/ICIT.2013.6505787
[8] Our Future Energy - The Danish Government; The Danish Ministry of Climate, Energy and Buildings; Stormgade 2-6, 1470 Copenhagen K, Denmark; November 2011;ISBN 978-87-7844-915-3