摘要
功率存储为随机波动的风电功率适应确定性的电网调度决策提供了可能,而储能容量规划则必须兼顾对调度决策的适应性及包含储能系统的风电场运行的经济性。为此,以适应电网调度运行计划的风电场输出功率时段参考值为依据,以储能系统投资成本和风电场运行成本最小化为目标,构建了计及风电场弃风能量和储能系统损失能量的风电场储能容量优化计算模型。该模型可充分保障风电场储能系统运行的经济性,实现指定调度运行计划下风电场输出功率的不波动或极小概率波动,进而达到风功率调度与电网运行调度间的平稳、有效衔接。运用改进粒子群优化算法对所建模型进行算例求解,分析结果表明了该方法的有效性。
The energy storage system makes it possible for randomly fluctuated wind power to participate pre-determined power dispatching.However,both the adaptability of power dispatching decision and the economy of wind power system operation including storage system must be taken into account in the capacity planning.An optimization model for determining energy storage capacity is proposed,based on the reference value of wind farm output power suitable for power dispatching operation program.The optimization model aims to minimize the total cost of energy storage infrastructure and operation including loss of wind energy and storage system.The model can fully guarantee the economy of wind-storage system and minimize the probability of power fluctuation of wind farm in the power dispatching operation program,and achieve a stable and effective coordination between the wind power dispatch and main network dispatch.An improved particle swarm optimization(PSO) algorithm is used to calculate and analyze the example system,and the model is proved to be effective.
出处
《电力系统自动化》
EI
CSCD
北大核心
2013年第1期90-95,共6页
Automation of Electric Power Systems
基金
山东省自然科学基金资助项目(ZR2010EM055)
山东大学优秀研究生创新基金资助项目(yyx10115)~~
关键词
风力发电
储能容量
蓄电池
时段参考值
粒子群优化算法
wind power
energy storage capacity
storage battery
reference value
particle swarm optimization(PSO) algorithm