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Feasible region method based integrated heat and electricity dispatch considering building thermal inertia

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  • Pan, Zhaoguang
  • Guo, Qinglai
  • Sun, Hongbin

Abstract

Integrated heat and electricity dispatch is crucial to exploit synergistic benefits from integrated energy systems. However, this requires information from both electricity systems and district heating systems (DHSs), which are managed by an electricity control center (ECC) and district heating control centers (DHCCs), respectively. For reasons pertaining to privacy, communication, dimension, and compatibility, it is not practical for DHCCs to send detailed models to the ECC. Therefore, a new feasible region method is proposed for formulation of new DHS models, which exploit the flexibility of DHSs with consideration of building thermal inertia. A greedy method is developed to solve the new modified feasible region models by calculating a series of linear programming problems efficiently. Then the new models are sent to the ECC to be used in central dispatch considering DHS operation constraints, i.e. integrated heat and electricity dispatch. The modified models are similar to conventional power plants and storages, and are thus compatible with current dispatch programs. Case studies verify the effectiveness of the method. Although some conservativeness exists, the total cost and wind energy curtailment are both decreased compared to conventional decoupled dispatch.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:appene:v:192:y:2017:i:c:p:395-407
    DOI: 10.1016/j.apenergy.2016.09.016
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    1. Mahmoudi, Nadali & Saha, Tapan K. & Eghbal, Mehdi, 2014. "Modelling demand response aggregator behavior in wind power offering strategies," Applied Energy, Elsevier, vol. 133(C), pages 347-355.
    2. Brange, Lisa & Englund, Jessica & Lauenburg, Patrick, 2016. "Prosumers in district heating networks – A Swedish case study," Applied Energy, Elsevier, vol. 164(C), pages 492-500.
    3. Pan, Zhaoguang & Guo, Qinglai & Sun, Hongbin, 2016. "Interactions of district electricity and heating systems considering time-scale characteristics based on quasi-steady multi-energy flow," Applied Energy, Elsevier, vol. 167(C), pages 230-243.
    4. Colmenar-Santos, Antonio & Rosales-Asensio, Enrique & Borge-Diez, David & Collado-Fernández, Eduardo, 2016. "Evaluation of the cost of using power plant reject heat in low-temperature district heating and cooling networks," Applied Energy, Elsevier, vol. 162(C), pages 892-907.
    5. Zamani, Ali Ghahgharaee & Zakariazadeh, Alireza & Jadid, Shahram, 2016. "Day-ahead resource scheduling of a renewable energy based virtual power plant," Applied Energy, Elsevier, vol. 169(C), pages 324-340.
    6. Li, Jinghua & Fang, Jiakun & Zeng, Qing & Chen, Zhe, 2016. "Optimal operation of the integrated electrical and heating systems to accommodate the intermittent renewable sources," Applied Energy, Elsevier, vol. 167(C), pages 244-254.
    7. Yang, Hongming & Xiong, Tonglin & Qiu, Jing & Qiu, Duo & Dong, Zhao Yang, 2016. "Optimal operation of DES/CCHP based regional multi-energy prosumer with demand response," Applied Energy, Elsevier, vol. 167(C), pages 353-365.
    8. 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.
    9. Kensby, Johan & Trüschel, Anders & Dalenbäck, Jan-Olof, 2015. "Potential of residential buildings as thermal energy storage in district heating systems – Results from a pilot test," Applied Energy, Elsevier, vol. 137(C), pages 773-781.
    10. Jin, Xiaolong & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Xu, Xiandong & Yu, Xiaodan, 2016. "Optimal day-ahead scheduling of integrated urban energy systems," Applied Energy, Elsevier, vol. 180(C), pages 1-13.
    11. Jiang, X.S. & Jing, Z.X. & Li, Y.Z. & Wu, Q.H. & Tang, W.H., 2014. "Modelling and operation optimization of an integrated energy based direct district water-heating system," Energy, Elsevier, vol. 64(C), pages 375-388.
    12. Duquette, Jean & Rowe, Andrew & Wild, Peter, 2016. "Thermal performance of a steady state physical pipe model for simulating district heating grids with variable flow," Applied Energy, Elsevier, vol. 178(C), pages 383-393.
    13. Bai, Linquan & Li, Fangxing & Cui, Hantao & Jiang, Tao & Sun, Hongbin & Zhu, Jinxiang, 2016. "Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 270-279.
    14. Wei, Dajun & Chen, Alian & Sun, Bo & Zhang, Chenghui, 2016. "Multi-objective optimal operation and energy coupling analysis of combined cooling and heating system," Energy, Elsevier, vol. 98(C), pages 296-307.
    15. 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.
    16. Nuytten, Thomas & Claessens, Bert & Paredis, Kristof & Van Bael, Johan & Six, Daan, 2013. "Flexibility of a combined heat and power system with thermal energy storage for district heating," Applied Energy, Elsevier, vol. 104(C), pages 583-591.
    17. Conejo, Antonio J. & Nogales Martín, Francisco Javier & Prieto Fernández, Francisco Javier, 2001. "A decomposition procedure based on approximate newton directions," DES - Working Papers. Statistics and Econometrics. WS ws010906, Universidad Carlos III de Madrid. Departamento de Estadística.
    18. Liu, Xuezhi & Mancarella, Pierluigi, 2016. "Modelling, assessment and Sankey diagrams of integrated electricity-heat-gas networks in multi-vector district energy systems," Applied Energy, Elsevier, vol. 167(C), pages 336-352.
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