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Academic Journal of Energy, 2022, 3(2); doi: 10.38007/RE.2022.030203.

Optimal Scheduling of Park Integrated Energy System Based on Dynamic Game Method


Haotian Wu

Corresponding Author:
Haotian Wu

Shanghai Investigation, Design & Research Institute Co., Ltd, Shanghai 200335, China


Recently, the energy crisis and deterioration have seriously restricted the improvement of our country. It is urgent to build a safe energy system. The emergence of the integrated energy system is a breakthrough and reform of the traditional energy system. The system is one of the main forms of the system. The purpose of this paper is to analyze the electricity demand and cooling demand of consumer energy based on the dynamic game method of the scheduling of the system, and the motion dynamic game method. The results show that the electrical trading volume and wholesale price of the electricity grid and the natural gas network, that is, the difference in their respective production costs, are the main factors that cause the profit gap between them.


Dynamic Game Method, Integrated Energy System, Integrated Energy in the Park, System Optimal Dispatch

Cite This Paper

Haotian Wu. Optimal Scheduling of Park Integrated Energy System Based on Dynamic Game Method. Academic Journal of Energy (2022), Vol. 3, Issue 2: 20-28. https://doi.org/10.38007/RE.2022.030203.


[1] Aiello G , Valavanis K P , Rizzo A . Fixed-Wing UAV Energy Efficient 3D Path Planning in Cluttered Environments. Journal of Intelligent & Robotic Systems, 2022, 105(3):1-13. https://doi.org/10.1007/s10846-022-01608-1

[2] Yammani C , Prabhat P , Dahal K . Optimal Dispatch of Vehicle-to-Grid (V2G) Battery Storage Using p-ELECTRE Method and Its Impact on Optimal Scheduling of DGs in Distribution System. Electric Power Components and Systems, 2019, 47(2):1-13.

[3] Ghofrane R , Hamza G , Samir B A . New optimal solutions for real-time scheduling of reconfigurable embedded systems based on neural networks with minimisation of power consumption. International Journal of Intelligent Engineering Informatics, 2018, 6(6):569-585. https://doi.org/10.1504/IJIEI.2018.096581

[4] Ae A , Amsb C . Optimal Scheduling of Interconnected AC/DC Combined Heat and Power System Microgrids with Multiple Fuel Options - ScienceDirect. Energy Procedia, 2019, 162(1):285-295. https://doi.org/10.1016/j.egypro.2019.04.030

[5] Pathak D P , Khatod D K . Development of Integrated Renewable Energy System Based on Optimal Operational Strategy and Sizing for an Un-Electrified Remote Area. IETE Journal of Research, 2020,2021(1):1-20.

[6] Paliwal N K . A day-ahead Optimal Scheduling Operation of Battery Energy Storage with Constraints in Hybrid Power System. Procedia Computer Science, 2020, 167(1):2140-2152. https://doi.org/10.1016/j.procs.2020.03.263

[7] Gazijahani F S , Salehi J . Integrated DR and reconfiguration scheduling for optimal operation of microgrids using Hong's point estimate method. International Journal of Electrical Power & Energy Systems, 2018, 99(7):481-492.

[8] Bornapour M , Hooshmand R A , Parastegari M . An Efficient Scenario-Based Stochastic Programming method for Optimal Scheduling of CHP-PEMFC, WT, PV and Hydrogen Storage Units in Micro Grids. Renewable Energy, 2018, 130(1):1049-1066.

[9] Capdeboscq Y , Vogelius M S . On optimal cloaking-by-mapping transformations. ESAIM: Mathematical Modelling and Numerical Analysis, 2022, 56(1):303-316. https://doi.org/10.1051/m2an/2022004

[10] Amroune M . Wind integrated optimal power flow considering power losses, voltage deviation, and emission using equilibrium optimization algorithm. Energy, Ecology and Environment, 2022, 7(4):369-392.

[11] Grami M . An energy-aware scheduling of dynamic workflows using big data similarity statistical analysis in cloud computing. The Journal of Supercomputing, 2022, 78(3):4261-4289. https://doi.org/10.1007/s11227-021-04016-8

[12] Hemmati M , Mohammadi-Ivatloo B , Ghasemzadeh S , et al. Risk-based optimal scheduling of reconfigurable smart renewable energy based microgrids. International Journal of Electrical Power & Energy Systems, 2018, 101(1):415-428.

[13] Tsang-Kai, Chang, Ankur, et al. Optimal Scheduling for Resource-Constrained Multirobot Cooperative Localization. IEEE Robotics and Automation Letters, 2018, 3(3):1552-1559. https://doi.org/10.1109/LRA.2018.2801467

[14] Lendvai A Z , Barta Z , Liker A , et al. The effect of energy reserves on social foraging: hungry sparrows scrounge more.. Proceedings. Biological sciences, 2018, 271(1556):2467-72.

[15] Levin B E . Metabolic imprinting: critical impact of the perinatal environment on the regulation of energy homeostasis. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2019,361(1471):1107-21. https://doi.org/10.1098/rstb.2006.1851

[16] Goran M I . Energy metabolism and obesity. The Medical clinics of North America, 2019,84(2):347-62.

[17] Emrani-Rahaghi P , Hashemi-Dezaki H , Hasankhani A . Optimal Stochastic Operation of Residential Energy Hubs Based on Plug-in Hybrid Electric Vehicle Uncertainties Using Two-point Estimation Method. Sustainable Cities and Society, 2021, 72(4):103059-103059. https://doi.org/10.1016/j.scs.2021.103059

[18] Rambabu C , Prasad V V K D V , Prasad K S . A New Version of Energy-Efficient Optimization Protocol Using ICMA-PSOGA Algorithm in Wireless Sensor Network. SN Computer Science, 2022, 3(5):1-12. https://doi.org/10.1007/s42979-022-01232-8