Signaling Game Approach for Energy Scheduling in the Community Microgrid
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-1027-4_129
Reference20 articles.
1. Luo, X., Shi, W., Jiang, Y., et al.: Distributed peer-to-peer energy trading based on game theory in a community microgrid considering ownership complexity of distributed energy resources. J. Clean. Prod. 351, 131573 (2022)
2. Shen, Y., Hu, W., Liu, M., et al.: Energy storage optimization method for microgrid considering multi-energy coupling demand response. J. Energy Storage 45, 103521 (2022)
3. Wu, J., Xing, X., Liu, X., et al.: Energy management strategy for grid-tied microgrids considering the energy storage efficiency. IEEE Trans. Ind. Electron. 65(12), 9539–9549 (2018)
4. Han, L., Morstyn, T., McCulloch, M.: Incentivizing prosumer coalitions with energy management using cooperative game theory. IEEE Trans. Power Syst. 34(1), 303–313 (2018)
5. Zhang, M., Eliassen, F., Taherkordi, A., et al.: Demand-response games for peer-to-peer energy trading with the hyperledger blockchain. IEEE Trans. Syst., Man, Cybern.: Syst. 52(1), 19–31 (2021)
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