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Electricity adjustment for capacity market auction by a district heating and cooling system

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  • Ito, Masakazu
  • Takano, Akihisa
  • Shinji, Takao
  • Yagi, Takahiro
  • Hayashi, Yasuhiro

Abstract

Power grids connected to renewable energy sources must cope with fluctuating output by those sources. One method to do so is for the power grid company to accept bids to increase grid stability. These bids are accepted via capacity market auction of increasing grid stability. These offers are to increase the maximum power capacity by using power stations (both utility and non-utility stations) and by reducing electricity consumption via demand response. One candidate for achieving this is a district heating and cooling (DHC) system installed with combined heat and power. However, the electricity adjustment (EA) operation needed by the DHC for the auction is complicated because the system consists of boilers, water heaters, chillers, generators, and other items. To investigate the possibility of using DHC systems for capacity market auctions, this paper proposes two models for operating a DHC system: electricity-adjustment capacity (EAC) provision and EA operation. In addition, to develop methods for evaluating the cost of the proposed operational methods, a model DHC system is formulated with an actual DHC system asa basis. Using the models, numerical simulations are conducted by particle swarm optimization. Then, the running costs of EAC, EA, and normal operation are calculated. The results show that the running costs of the proposed operations are relatively stable by day and season, not varying beyond the range of ±10%. Nevertheless, the running costs in spring and fall are be lower than those in summer and winter. The cost of providing EAC is no more than 1% the cost of normal operation, and the cost of EA itself is no more than 2% that of normal operation.

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  • Ito, Masakazu & Takano, Akihisa & Shinji, Takao & Yagi, Takahiro & Hayashi, Yasuhiro, 2017. "Electricity adjustment for capacity market auction by a district heating and cooling system," Applied Energy, Elsevier, vol. 206(C), pages 623-633.
    • Handle: RePEc:eee:appene:v:206:y:2017:i:c:p:623-633
    DOI: 10.1016/j.apenergy.2017.08.210
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    1. Stadler, Ingo, 2008. "Power grid balancing of energy systems with high renewable energy penetration by demand response," Utilities Policy, Elsevier, vol. 16(2), pages 90-98, June.
    2. Falke, Tobias & Krengel, Stefan & Meinerzhagen, Ann-Kathrin & Schnettler, Armin, 2016. "Multi-objective optimization and simulation model for the design of distributed energy systems," Applied Energy, Elsevier, vol. 184(C), pages 1508-1516.
    3. Casisi, M. & Pinamonti, P. & Reini, M., 2009. "Optimal lay-out and operation of combined heat & power (CHP) distributed generation systems," Energy, Elsevier, vol. 34(12), pages 2175-2183.
    4. Wang, Haichao & Yin, Wusong & Abdollahi, Elnaz & Lahdelma, Risto & Jiao, Wenling, 2015. "Modelling and optimization of CHP based district heating system with renewable energy production and energy storage," Applied Energy, Elsevier, vol. 159(C), pages 401-421.
    5. Aghaei, Jamshid & Alizadeh, Mohammad-Iman, 2013. "Multi-objective self-scheduling of CHP (combined heat and power)-based microgrids considering demand response programs and ESSs (energy storage systems)," Energy, Elsevier, vol. 55(C), pages 1044-1054.
    6. Alipour, Manijeh & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2014. "Short-term scheduling of combined heat and power generation units in the presence of demand response programs," Energy, Elsevier, vol. 71(C), pages 289-301.
    7. Powell, Kody M. & Kim, Jong Suk & Cole, Wesley J. & Kapoor, Kriti & Mojica, Jose L. & Hedengren, John D. & Edgar, Thomas F., 2016. "Thermal energy storage to minimize cost and improve efficiency of a polygeneration district energy system in a real-time electricity market," Energy, Elsevier, vol. 113(C), pages 52-63.
    8. Liu, Yingqi, 2017. "Demand response and energy efficiency in the capacity resource procurement: Case studies of forward capacity markets in ISO New England, PJM and Great Britain," Energy Policy, Elsevier, vol. 100(C), pages 271-282.
    9. Østergaard, Poul Alberg, 2006. "Ancillary services and the integration of substantial quantities of wind power," Applied Energy, Elsevier, vol. 83(5), pages 451-463, May.
    10. Bradley, Peter & Leach, Matthew & Torriti, Jacopo, 2013. "A review of the costs and benefits of demand response for electricity in the UK," Energy Policy, Elsevier, vol. 52(C), pages 312-327.
    11. Lund, Rasmus & Mathiesen, Brian Vad, 2015. "Large combined heat and power plants in sustainable energy systems," Applied Energy, Elsevier, vol. 142(C), pages 389-395.
    12. Franco, Alessandro & Versace, Michele, 2017. "Optimum sizing and operational strategy of CHP plant for district heating based on the use of composite indicators," Energy, Elsevier, vol. 124(C), pages 258-271.
    13. Mehleri, Eugenia D. & Sarimveis, Haralambos & Markatos, Nikolaos C. & Papageorgiou, Lazaros G., 2012. "A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level," Energy, Elsevier, vol. 44(1), pages 96-104.
    14. Pan, Zhaoguang & Guo, Qinglai & Sun, Hongbin, 2017. "Feasible region method based integrated heat and electricity dispatch considering building thermal inertia," Applied Energy, Elsevier, vol. 192(C), pages 395-407.
    15. Pudjianto, Danny & Djapic, Predrag & Aunedi, Marko & Gan, Chin Kim & Strbac, Goran & Huang, Sikai & Infield, David, 2013. "Smart control for minimizing distribution network reinforcement cost due to electrification," Energy Policy, Elsevier, vol. 52(C), pages 76-84.
    16. Sorknæs, Peter & Lund, Henrik & Andersen, Anders N., 2015. "Future power market and sustainable energy solutions – The treatment of uncertainties in the daily operation of combined heat and power plants," Applied Energy, Elsevier, vol. 144(C), pages 129-138.
    17. Strbac, Goran, 2008. "Demand side management: Benefits and challenges," Energy Policy, Elsevier, vol. 36(12), pages 4419-4426, December.
    18. Rolfsman, Björn, 2004. "Combined heat-and-power plants and district heating in a deregulated electricity market," Applied Energy, Elsevier, vol. 78(1), pages 37-52, May.
    19. Streckiene, Giedre & Martinaitis, Vytautas & Andersen, Anders N. & Katz, Jonas, 2009. "Feasibility of CHP-plants with thermal stores in the German spot market," Applied Energy, Elsevier, vol. 86(11), pages 2308-2316, November.
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