Optimal Scheduling Strategy of Wind-Photo Voltaic-Storage Generation System Based on Chaotic-Adaptive Particle Swarm Optimization Algorithm

As the penetration rate of renewable energy increasing, the situation of new electric power system is now multiply. In order to improve power quality and supply reliability, the wind-photovoltaic-storage complementary power generation system should be effectively scheduled. In this paper, the schedu...

Full description

Saved in:
Bibliographic Details
Published in:2023 7th International Conference on Electrical, Mechanical and Computer Engineering (ICEMCE) pp. 16 - 22
Main Authors: Lei, Zhenhua, Lu, Li, Liu, Huan, Xiang, Nan, Wang, Hongkun, Yan, Dongmei
Format: Conference Proceeding
Language:English
Published: IEEE 20.10.2023
Subjects:
Adaptation models
Batteries
Costs
Economic Optimization
Mathematical models
Modified Particle Swarm Optimization
Optimal scheduling
Processor scheduling
System recovery
Time-sharing Scheduling Strategy
Wind-photovoltaic-storage Complementary Power Generation System
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:As the penetration rate of renewable energy increasing, the situation of new electric power system is now multiply. In order to improve power quality and supply reliability, the wind-photovoltaic-storage complementary power generation system should be effectively scheduled. In this paper, the scheduling strategy is firstly formulated with the aim as minimizing the cost of wind-photovoltaic-storage complementary power generation system. In the meanwhile, a mathematical model is established according to the strategy, and the particle swarm optimization algorithm (PSO) is applied to the model. Secondly, the PSO is improved from the aspects of initialization and adaptive algorithm parameters to improve its operation accuracy and reduce the probability of falling into local deadlock. Finally, combined with the actual data of cloudy days in winter, PSO and improved PSO are respectively used in the simulation software to solve the scheduling model, and the results are compared and analyzed, so as to achieve the optimal economy of the system.
DOI:10.1109/ICEMCE60359.2023.10491009