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Distributed energy resource and network expansion planning of a CCHP based active microgrid considering demand response programs

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  • Varasteh, Farid
  • Nazar, Mehrdad Setayesh
  • Heidari, Alireza
  • Shafie-khah, Miadreza
  • Catalão, João P.S.

Abstract

This paper addresses the network expansion planning of an active microgrid that utilizes Distributed Energy Resources (DERs). The microgrid uses Combined Cooling, Heating and Power (CCHP) systems with their heating and cooling network. The proposed method uses a bi-level iterative optimization algorithm for optimal expansion and operational planning of the microgrid that consists of different zones, and each zone can transact electricity with the upward utility. The transaction of electricity with the upward utility can be performed based on demand response programs that consist of the time-of-use program and/or direct load control. DERs are CHPs, small wind turbines, photovoltaic systems, electric and cooling storage, gas fired boilers and absorption and compression chillers are used to supply different zones' electrical, heating, and cooling loads. The proposed model minimizes the system's investment, operation, interruption and environmental costs; meanwhile, it maximizes electricity export revenues and the reliability of the system. The proposed method is applied to a real building complex and five different scenarios are considered to evaluate the impact of different energy supply configurations and operational paradigm on the investment and operational costs. The effectiveness of the introduced algorithm has been assessed. The implementation of the proposed algorithm reduces the aggregated investment and operational costs of the test system in about 54.7% with respect to the custom expansion planning method.

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  • Varasteh, Farid & Nazar, Mehrdad Setayesh & Heidari, Alireza & Shafie-khah, Miadreza & Catalão, João P.S., 2019. "Distributed energy resource and network expansion planning of a CCHP based active microgrid considering demand response programs," Energy, Elsevier, vol. 172(C), pages 79-105.
  • Handle: RePEc:eee:energy:v:172:y:2019:i:c:p:79-105
    DOI: 10.1016/j.energy.2019.01.015
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    as
    1. Jun, Zeng & Junfeng, Liu & Jie, Wu & Ngan, H.W., 2011. "A multi-agent solution to energy management in hybrid renewable energy generation system," Renewable Energy, Elsevier, vol. 36(5), pages 1352-1363.
    2. 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.
    3. Carvalho, Monica & Serra, Luis Maria & Lozano, Miguel Angel, 2011. "Optimal synthesis of trigeneration systems subject to environmental constraints," Energy, Elsevier, vol. 36(6), pages 3779-3790.
    4. Roberto Aringhieri & Federico Malucelli, 2003. "Optimal Operations Management and Network Planning of a District Heating System with a Combined Heat and Power Plant," Annals of Operations Research, Springer, vol. 120(1), pages 173-199, April.
    5. Kia, Mohsen & Setayesh Nazar, Mehrdad & Sepasian, Mohammad Sadegh & Heidari, Alireza & Catalão, João P.S., 2017. "New framework for optimal scheduling of combined heat and power with electric and thermal storage systems considering industrial customers inter-zonal power exchanges," Energy, Elsevier, vol. 138(C), pages 1006-1015.
    6. Ju, Liwei & Tan, Zhongfu & Li, Huanhuan & Tan, Qingkun & Yu, Xiaobao & Song, Xiaohua, 2016. "Multi-objective operation optimization and evaluation model for CCHP and renewable energy based hybrid energy system driven by distributed energy resources in China," Energy, Elsevier, vol. 111(C), pages 322-340.
    7. Shaban Boloukat, Mohammad Hadi & Akbari Foroud, Asghar, 2016. "Stochastic-based resource expansion planning for a grid-connected microgrid using interval linear programming," Energy, Elsevier, vol. 113(C), pages 776-787.
    8. Lozano, Miguel A. & Ramos, Jose C. & Serra, Luis M., 2010. "Cost optimization of the design of CHCP (combined heat, cooling and power) systems under legal constraints," Energy, Elsevier, vol. 35(2), pages 794-805.
    9. Hemmati, Reza & Saboori, Hedayat & Siano, Pierluigi, 2017. "Coordinated short-term scheduling and long-term expansion planning in microgrids incorporating renewable energy resources and energy storage systems," Energy, Elsevier, vol. 134(C), pages 699-708.
    10. Mehleri, E.D. & Sarimveis, H. & Markatos, N.C. & Papageorgiou, L.G., 2013. "Optimal design and operation of distributed energy systems: Application to Greek residential sector," Renewable Energy, Elsevier, vol. 51(C), pages 331-342.
    11. Weber, C. & Shah, N., 2011. "Optimisation based design of a district energy system for an eco-town in the United Kingdom," Energy, Elsevier, vol. 36(2), pages 1292-1308.
    12. Li, Miao & Mu, Hailin & Li, Nan & Ma, Baoyu, 2016. "Optimal design and operation strategy for integrated evaluation of CCHP (combined cooling heating and power) system," Energy, Elsevier, vol. 99(C), pages 202-220.
    13. Chicco, Gianfranco & Mancarella, Pierluigi, 2009. "Distributed multi-generation: A comprehensive view," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(3), pages 535-551, April.
    14. Kia, Mohsen & Setayesh Nazar, Mehrdad & Sepasian, Mohammad Sadegh & Heidari, Alireza & Siano, Pierluigi, 2017. "An efficient linear model for optimal day ahead scheduling of CHP units in active distribution networks considering load commitment programs," Energy, Elsevier, vol. 139(C), pages 798-817.
    15. Sakawa, Masatoshi & Kato, Kosuke & Ushiro, Satoshi, 2002. "Operational planning of district heating and cooling plants through genetic algorithms for mixed 0-1 linear programming," European Journal of Operational Research, Elsevier, vol. 137(3), pages 677-687, March.
    16. Sanaye, Sepehr & Khakpaay, Navid, 2014. "Simultaneous use of MRM (maximum rectangle method) and optimization methods in determining nominal capacity of gas engines in CCHP (combined cooling, heating and power) systems," Energy, Elsevier, vol. 72(C), pages 145-158.
    17. Bracco, Stefano & Dentici, Gabriele & Siri, Silvia, 2013. "Economic and environmental optimization model for the design and the operation of a combined heat and power distributed generation system in an urban area," Energy, Elsevier, vol. 55(C), pages 1014-1024.
    18. Zheng, Xuyue & Wu, Guoce & Qiu, Yuwei & Zhan, Xiangyan & Shah, Nilay & Li, Ning & Zhao, Yingru, 2018. "A MINLP multi-objective optimization model for operational planning of a case study CCHP system in urban China," Applied Energy, Elsevier, vol. 210(C), pages 1126-1140.
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    5. Pinto, Rafael S. & Unsihuay-Vila, Clodomiro & Tabarro, Fabricio H., 2021. "Coordinated operation and expansion planning for multiple microgrids and active distribution networks under uncertainties," Applied Energy, Elsevier, vol. 297(C).
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    10. Tabar, Vahid Sohrabi & Banazadeh, Hamidreza & Tostado-Véliz, Marcos & Jordehi, Ahmad Rezaee & Nasir, Mohammad & Jurado, Francisco, 2022. "Stochastic multi-stage multi-objective expansion of renewable resources and electrical energy storage units in distribution systems considering crypto-currency miners and responsive loads," Renewable Energy, Elsevier, vol. 198(C), pages 1131-1147.
    11. Liu, Wenxia & Huang, Yuchen & Li, Zhengzhou & Yang, Yue & Yi, Fang, 2020. "Optimal allocation for coupling device in an integrated energy system considering complex uncertainties of demand response," Energy, Elsevier, vol. 198(C).
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    13. Adrian Tantau & András Puskás-Tompos & Laurentiu Fratila & Costel Stanciu, 2021. "Acceptance of Demand Response and Aggregators as a Solution to Optimize the Relation between Energy Producers and Consumers in order to Increase the Amount of Renewable Energy in the Grid," Energies, MDPI, vol. 14(12), pages 1-19, June.
    14. Yuwei Wang & Yuanjuan Yang & Liu Tang & Wei Sun & Huiru Zhao, 2019. "A Stochastic-CVaR Optimization Model for CCHP Micro-Grid Operation with Consideration of Electricity Market, Wind Power Accommodation and Multiple Demand Response Programs," Energies, MDPI, vol. 12(20), pages 1-33, October.
    15. Liu, Zuming & Zhao, Yingru & Wang, Xiaonan, 2020. "Long-term economic planning of combined cooling heating and power systems considering energy storage and demand response," Applied Energy, Elsevier, vol. 279(C).
    16. Xu, Weiwei & Zhou, Dan & Huang, Xiaoming & Lou, Boliang & Liu, Dong, 2020. "Optimal allocation of power supply systems in industrial parks considering multi-energy complementarity and demand response," Applied Energy, Elsevier, vol. 275(C).
    17. Bostan, Alireza & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2020. "An integrated optimization framework for combined heat and power units, distributed generation and plug-in electric vehicles," Energy, Elsevier, vol. 202(C).
    18. Armioun, Majid & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Siano, Pierluigi, 2023. "Optimal scheduling of CCHP-based resilient energy distribution system considering active microgrids' multi-carrier energy transactions," Applied Energy, Elsevier, vol. 350(C).
    19. Ma, Ning & Fan, Lurong, 2023. "Double recovery strategy of carbon for coal-to-power based on a multi-energy system with tradable green certificates," Energy, Elsevier, vol. 273(C).
    20. Mahyar Lasemi Imeni & Mohammad Sadegh Ghazizadeh & Mohammad Ali Lasemi & Zhenyu Yang, 2023. "Optimal Scheduling of a Hydrogen-Based Energy Hub Considering a Stochastic Multi-Attribute Decision-Making Approach," Energies, MDPI, vol. 16(2), pages 1-23, January.
    21. Mohseni, Soheil & Brent, Alan C. & Kelly, Scott & Browne, Will N. & Burmester, Daniel, 2021. "Strategic design optimisation of multi-energy-storage-technology micro-grids considering a two-stage game-theoretic market for demand response aggregation," Applied Energy, Elsevier, vol. 287(C).
    22. Miao Li & Yiran Feng & Maojun Zhou & Hailin Mu & Longxi Li & Yajun Wang, 2019. "Economic and Environmental Optimization for Distributed Energy System Integrated with District Energy Network," Energies, MDPI, vol. 12(10), pages 1-19, May.
    23. Mukhopadhyay, Bineeta & Das, Debapriya, 2021. "Optimal multi-objective expansion planning of a droop-regulated islanded microgrid," Energy, Elsevier, vol. 218(C).

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