计及可靠性成本的风光储微电网储能容量协同优化

汪宇航; 李琰; 应飞祥; 徐天奇; 田华; 贾鉴

汪宇航,李琰,应飞祥,徐天奇,田华,贾鉴.计及可靠性成本的风光储微电网储能容量协同优化[J].电测与仪表,2023,60(5):59-65.
Wang Yu Hang,Li Yan,Ying Feixiang,Xu Tianqi,Tian Hua,Jia Jian.The collaborative optimization of energy storage capacity ofmicro grid considering reliability cost includes wind power[J].Electrical Measurement & Instrumentation,2023,60(5):59-65.

计及可靠性成本的风光储微电网储能容量协同优化

The collaborative optimization of energy storage capacity ofmicro grid considering reliability cost includes wind power

DOI：10.19753/j.issn1001-1390.2023.05.008

中文关键词: 强不确定性微电网可靠性成本改进二阶振荡粒子群算法配置成本寻优

英文关键词:strong uncertainty, microgrid, reliability cost, improved second-order oscillating particle swarm optimization algorithm, configuration cost optimization

基金项目:国家自然科学基金项目（ 61761049）；云南省教育厅科学研究基金项目(2019Y0169)；云南省教育厅科学研究基金项目(2020Y0241)；云南省教育厅科学研究基金项目(2020Y0240).

作者中文名	作者英文名	单位
汪宇航	Wang Yu Hang	云南民族大学电气信息工程学院
李琰	Li Yan	云南民族大学电气信息工程学院
应飞祥	Ying Feixiang	云南民族大学电气信息工程学院
徐天奇	Xu Tianqi	云南民族大学电气信息工程学院
田华	Tian Hua	昆明电器科学研究所
贾鉴	Jia Jian	中国能源建设集团云南省电力设计院有限公司

摘要点击次数: 1674

中文摘要:

对比常规能源，新能源具备可再生、污染低、资源丰富的优势，其中风光发电被大规模引入到微电网系统，但由于其发电量具有较强的不确定性，这使如何提高新能源消纳水平、提升电力系统运行稳定性以及降低微电网配置成本成为了充满挑战性的重要问题。针对上述问题，文章提出一种计及可靠性成本，同时考虑风、光资源多时间尺度不确定性的风光储互补微电网系统储能容量协同优化的方法。该方法首先采用自回归滑动平均模型和Homer软件仿真离散的风速、光辐照度序列，构建出风机、光伏发电机的出力模型；其次采取电量不足期望值为评估指标建立可靠性成本函数，构建出微电网配置成本模型；最后使用改进二阶振荡粒子群算法求解系统最优配置成本。算例结果表明了该方法的可行性及经济性，可为实际风光储互补微电网系统配置规划提供参考。

英文摘要:

Compared to conventional energy, new energy has the advantages of renewable low pollution resources, including scenery power generation by large-scale introduction to the micro grid system, but its generating capacity has the defects of strong uncertainty, which how to improve the level of new energy given improve power system stability and reduce the micro grid configuration cost has become an important problem challenging.According to the above problem,This paper presents a fully gauge and reliability cost, at the same time, considering the wind light resources multiple time scale uncertainty of scenery complementary micro grid storage system energy storage capacity of the collaborative optimization method this method first USES the autoregressive moving average model and Homer software simulation of discrete sequence of wind speed light irradiance, build out fan pv generator output model; Secondly, the expected value of power shortage is used as the evaluation index to establish the reliability cost function, and the cost model of micro-grid configuration is constructed. Finally, the improved second-order oscillation particle swarm optimization algorithm is used to calculate the optimal value of the wind-storage-complementary microgrid system capacity. The results show that the method is feasible and economical, which can provide a reference for the configuration planning of the wind-storage-complementary microgrid system.

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