Multi-objective optimal scheduling of wind-photoelectric-storage virtual power plants considering demand response

Jingshu Zhang; Xinhui Du; Wei Zhao; Zhishuo Zhang; Yaoke Shang; Tao Su

doi:10.1117/12.3024321

13 May 2024 Multi-objective optimal scheduling of wind-photoelectric-storage virtual power plants considering demand response

Jingshu Zhang, Xinhui Du, Wei Zhao, Zhishuo Zhang, Yaoke Shang, Tao Su

Author Affiliations +

Proceedings Volume 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023); 131590I (2024) https://doi.org/10.1117/12.3024321
Event: Eighth International Conference on Energy System, Electricity and Power (ESEP 2023), 2023, Wuhan, China

Abstract

In this paper, a multi-objective optimal scheduling model of wind-photovoltaic storage virtual power plant with demand response is established. Under system constraints, an economical and environmentally friendly virtual power plant integrated optimization scheduling model was proposed to minimize the total cost of virtual power plant and maximize the utilization rate of wind power and photovoltaic. At the same time, this paper improves MOPSO optimization algorithm, and uses nonlinear exponential decline function to obtain the algorithm inertia, which effectively improves the algorithm convergence performance and the distribution characteristics of pareto frontier. The simulation results show that the model can guide the multi-objective optimal scheduling of virtual power plant to a certain extent.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jingshu Zhang, Xinhui Du, Wei Zhao, Zhishuo Zhang, Yaoke Shang, and Tao Su "Multi-objective optimal scheduling of wind-photoelectric-storage virtual power plants considering demand response", Proc. SPIE 13159, Eighth International Conference on Energy System, Electricity, and Power (ESEP 2023), 131590I (13 May 2024); https://doi.org/10.1117/12.3024321

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