摘要
讨论了具有混合储能的独立光伏风能供电系统的规模优化问题,提出了一种新的技术用于优化储能系统外的多源电力系统曲线,研究了各种能源的建模和构成,有效实现了能源的优化。本文的研究目标是最小化需求的供电概率损失(LPSP),此外,成本最小化也是本文的另一个研究目标。使用遗传算法解决了相关问题,实现了系统的可靠运行。通过实验验证了本文算法的有效性,并将其优化结果与多目标粒子群优化结果进行了比较。
This paper discusses the scale optimization problem of an independent photovoltaic wind power supply system with hybrid energy storage,proposes a new technology for optimizing the multi-source power system curve outside the energy storage system,studies the modeling and composition of various energy sources,and effectively achieves energy optimization.The research objective of this article is to minimize the power supply probability loss(LPSP)of demand,and the cost minimization is also another research objective of this paper.The genetic algorithm is used to solve the related problems and achieve the reliable operation of the system.The effectiveness of the algorithm proposed in this paper is verified by experiments,and its optimization results are compared with those of multi-objective particle swarm optimization.
作者
乔中亚
QIAO Zhongya(Nanjing Ninggao Xiexin Gas Turbine Thermal Power Co.,Ltd.,Nanjing 211300,Jiangsu,China)
出处
《电气传动自动化》
2024年第2期51-54,80,共5页
Electric Drive Automation
关键词
混合储能
光伏-风能
供电系统
优化分析
Hybrid energy storage
Photovoltaic wind energy
Power supply system
Optimization analysis
