基于随机模拟粒子群算法的含风电场电力系统经济调度

Economic dispatch based on particle swarm optimization of stochastic simulation in wind power integrated system

由于风电具有随机性,目前尚无法较准确预测其出力,因此含有风电的电力系统经济调度不再是一个常规意义下的确定性问题。利用传统的方法也难获得既经济又有较高可靠性的解。本文建立了基于机会约束规划的含风电场的电力系统经济调度数学模型,以概率的形式描述相关约束条件,考虑了机组的爬坡约束、出力限制,线路潮流限制、备用约束及负荷平衡等约束条件,利用基于随机模拟的粒子群算法求解该问题。通过IEEE30节点系统的算例验证,表明该模型与算法的有效性。

Wind power can not be forecasted because of its randomness. So the economic dispatch in wind power integrated system is not a traditional determinate question. The solution which is economic and reliable is difficult to attain by traditional ways. This paper put forward a mathematical model of economic dispatch in wind power integrated system based chance constrained programming （CCP） and describes the related constrained conditions in probability form. These include ramp constraints of the generating units, output restricted zone, line transmission capacity, reserved capacity constraints, the balance of load and so on. The question is solved by particle swarm optimization （P SO） based stochastic simulation. The optimization algorithm is proved effective by IEEE30 testing.