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A framework for time-stamping battery charging and pricing structure to enable equitable and efficient dispatch for microgrids in demand-side management environment

Author

Listed:
  • Mishra, Mrityunjay Kumar
  • Sumaiti, Ameena Al
  • El din, Hatem Zein
  • El-Saadany, Ehab Fahmy

Abstract

Microgrids rely on diverse energy sources such as photovoltaics (PV), fossil fuels, and microturbines to power their operations. However, compensating these generators for their services poses significant challenges. This work examines the intricacies of compensation for various energy sources within microgrids and explores pricing mechanisms for battery energy storage. We investigate the feasibility of differentiating battery power based on the sources employed for charging, and the use of this information in pricing battery discharge power. Furthermore, we explore the possibility of “time stamping” the battery charging power. The timestamped charging data allows to distinguish discharged power according to its historical charging sources. This information is utilized in pricing battery power. The formulation supports equitable compensation for each energy source and allows microgrid operator (MGO) to establish fair payment structures. The problem is modeled as a bilevel interaction between the MGO and consumers in demand-side management environment. The prosumers schedule their devices by responding to the price signal sent by MGO. The price per slot depends on the total load per slot. By rearranging the device schedule, consumers change the price per unit per slot of energy. The MGO utilizes this information to decide the generation, charging–discharging profile of battery and compensation of various energy sources. A comprehensive analysis is performed to provide valuable insights into compensation and pricing strategies for the efficient and effective operation of a microgrid. Simulation results show that the proposed approach reduces the average cost by 18%, lowers the peak-to-average ratio (PAR) by 9.11%, and increases battery revenue from DG charged energy by 35.68% compared to flat-rate pricing schemes.

Suggested Citation

  • Mishra, Mrityunjay Kumar & Sumaiti, Ameena Al & El din, Hatem Zein & El-Saadany, Ehab Fahmy, 2025. "A framework for time-stamping battery charging and pricing structure to enable equitable and efficient dispatch for microgrids in demand-side management environment," Energy, Elsevier, vol. 335(C).
  • Handle: RePEc:eee:energy:v:335:y:2025:i:c:s0360544225037193
    DOI: 10.1016/j.energy.2025.138077
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    References listed on IDEAS

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    1. MansourLakouraj, Mohammad & Shahabi, Majid & Shafie-khah, Miadreza & Catalão, João P.S., 2022. "Optimal market-based operation of microgrid with the integration of wind turbines, energy storage system and demand response resources," Energy, Elsevier, vol. 239(PB).
    2. Xin-gang, Zhao & Ze-qi, Zhang & Yi-min, Xie & Jin, Meng, 2020. "Economic-environmental dispatch of microgrid based on improved quantum particle swarm optimization," Energy, Elsevier, vol. 195(C).
    3. Jalali, Mehdi & Zare, Kazem & Seyedi, Heresh, 2017. "Strategic decision-making of distribution network operator with multi-microgrids considering demand response program," Energy, Elsevier, vol. 141(C), pages 1059-1071.
    4. Cagnano, A. & De Tuglie, E. & Mancarella, P., 2020. "Microgrids: Overview and guidelines for practical implementations and operation," Applied Energy, Elsevier, vol. 258(C).
    5. Rezaei, Navid & Pezhmani, Yasin & Khazali, Amirhossein, 2022. "Economic-environmental risk-averse optimal heat and power energy management of a grid-connected multi microgrid system considering demand response and bidding strategy," Energy, Elsevier, vol. 240(C).
    6. Wu, Qiong & Xie, Zhun & Ren, Hongbo & Li, Qifen & Yang, Yongwen, 2022. "Optimal trading strategies for multi-energy microgrid cluster considering demand response under different trading modes: A comparison study," Energy, Elsevier, vol. 254(PC).
    7. Yao, Wenliang & Wang, Chengfu & Yang, Ming & Wang, Kang & Dong, Xiaoming & Zhang, Zhenwei, 2023. "A tri-layer decision-making framework for IES considering the interaction of integrated demand response and multi-energy market clearing," Applied Energy, Elsevier, vol. 342(C).
    8. Wang, Xuebin & Song, Wenle & Wu, Haotian & Liang, Haiping & Saboor, Ahmed, 2022. "Microgrid operation relying on economic problems considering renewable sources, storage system, and demand-side management using developed gray wolf optimization algorithm," Energy, Elsevier, vol. 248(C).
    9. Li, Ling-Ling & Ji, Bing-Xiang & Liu, Guan-Chen & Yuan, Jian-Ping & Tseng, Shuan-Wei & Lim, Ming K. & Tseng, Ming-Lang, 2024. "Grid-connected multi-microgrid system operational scheduling optimization: A hierarchical improved marine predators algorithm," Energy, Elsevier, vol. 294(C).
    10. Babagheibi, Mahsa & Jadid, Shahram & Kazemi, Ahad, 2023. "An Incentive-based robust flexibility market for congestion management of an active distribution system to use the free capacity of Microgrids," Applied Energy, Elsevier, vol. 336(C).
    11. Saeian, Hosein & Niknam, Taher & Zare, Mohsen & Aghaei, Jamshid, 2022. "Coordinated optimal bidding strategies methods of aggregated microgrids: A game theory-based demand side management under an electricity market environment," Energy, Elsevier, vol. 245(C).
    12. Jafari, Amirreza & Ganjeh Ganjehlou, Hamed & Khalili, Tohid & Bidram, Ali, 2020. "A fair electricity market strategy for energy management and reliability enhancement of islanded multi-microgrids," Applied Energy, Elsevier, vol. 270(C).
    13. Zhang, Di & Samsatli, Nouri J. & Hawkes, Adam D. & Brett, Dan J.L. & Shah, Nilay & Papageorgiou, Lazaros G., 2013. "Fair electricity transfer price and unit capacity selection for microgrids," Energy Economics, Elsevier, vol. 36(C), pages 581-593.
    14. Wang, Dongxiao & Qiu, Jing & Reedman, Luke & Meng, Ke & Lai, Loi Lei, 2018. "Two-stage energy management for networked microgrids with high renewable penetration," Applied Energy, Elsevier, vol. 226(C), pages 39-48.
    15. Hwang Goh, Hui & Shi, Shuaiwei & Liang, Xue & Zhang, Dongdong & Dai, Wei & Liu, Hui & Yuong Wong, Shen & Agustiono Kurniawan, Tonni & Chen Goh, Kai & Leei Cham, Chin, 2022. "Optimal energy scheduling of grid-connected microgrids with demand side response considering uncertainty," Applied Energy, Elsevier, vol. 327(C).
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