摘要
由于可再生能源发电自身存在的高度间歇性、波动性和随机性特点,考虑光照辐射、温度等天气因素影响,制定满足经济性与可靠性要求的微网优化调度策略值得深入研究。该文首先构建考虑源荷不确定性的光伏发电系统经济调度模型,定义平均调整成本;其次,综合运用基于粒子群算法的调度和基于两点估计的概率性实时最优潮流,生成日前调度的示例场景,并评估实时平均调整成本以实现系统最优化运行;最后,基于IEEE30节点系统的仿真结果验证所提调度策略的有效性和可行性。
The renewable energy generation has characteristics of such the high degree of intermittent,fluctuation and randomness.This paper takes into account the impact of solar irradiation,temperature and other weather factors to make the optimal scheduling strategy for the satisfy the economic and reliability requirements of microgrid.Firstly,the economic dispatch model is constructed for a photovoltaic generation system which consider the uncertainty in source and load and determine the optimum mean adjustment cost.Furthermore,the PSO-based schedule and two-point estimate-based probabilistic real-time optimal power flow is employed.The sample scenarios for a DA schedule are generated and the evaluation of MAC in RT is made to reach an optimal operation of system.Lastly? the simulation for the IEEE 30-bus system is simulated to test the effectiveness and feasibility of proposed scheduling strategy.
作者
宫娅宁
秦红
付洪斌
江月
黎敏
GONG Ya-ning;QIN Hong;FU Hong-bin;JIANG Yue;LI Min(Economic Research Institute of State Grid Jiangxi Electric Power Company, Nanchang 330043, China;Jiangxi Vocational &Technical College of Electricity,Nanchang 330029, China;Electric Engineering & Renewable Energy School, China Three Gorges University, Yichang 443002, China)
出处
《电力科学与技术学报》
CAS
北大核心
2019年第2期112-118,共7页
Journal of Electric Power Science And Technology
基金
国家自然科学基金(51537003)
关键词
光伏发电
日前调度
两点估计法
粒子群算法
概率最优潮流
photovoltaic generation
day-ahead scheduling
two-point estimate method
particle swarm optimization
probabilistic optimal power flow