摘要
针对微网中风能和太阳能等可再生能源具有随机性和波动性的特点,提出了一种考虑随机性的微网能量优化调度模型,用以降低可再生能源发电预测不确定性带来的微电网和主网连接点(Point of common coupling,PCC)处的功率波动,使得微网对于主网成为一个可调度的单元,同时实现微网的经济调度。首先,采用拉丁超立方采样法(Latin hypercube sampling,LHS)和同步回带削减(Simultaneous backward reduction,SBR)技术生成可能的出力场景来描述风电和太阳能光伏发电出力的随机性。然后将PCC处能量波动引入目标函数,使得在系统期望成本最小的同时减小风电和光伏出力波动性对电网的影响,采用遗传算法求解该问题。仿真结果表明,该模型对含风电和太阳能光伏发电的微网优化调度的合理性和有效性。
This paper proposes a stochastic optimization model considering the volatility of wind power and photovoltaic power in microgrid. The model optimizes the economic operation of a microgrid as well as minimizes the flow deviation at the point of common coupling (PCC) from scheduled values. First, the Latin hypercube sampling (LHS) and simultaneous backward reduction (SBR) technique are introduced to describe the stochastic nature of wind power and photovoltaic power. Then the random characteristic is introduced into the objective function of the stochastic model which is solved based on the genetic algorithm (GA). Simulation results demonstrate its rationality and effectiveness for day-ahead scheduling of a microgrid.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2014年第11期112-117,共6页
Power System Protection and Control
关键词
微电网
经济调度
随机优化
分布式电源
PCC
microgrid
economic dispatch
stochastic optimization
renewable energy
PCC