基于节点不平衡功率的粒子群潮流转移控制算法

通过将潮流转移的校正控制转化为非线性规划问题,提出了基于节点不平衡功率的潮流转移控制算法。首先将常规优化问题中的功率平衡等式转化为节点不平衡功率,作为优化目标处理,避免了常规人工智能优化算法中必须先满足潮流等式后再优化求解的弊端,提高了计算速度;然后应用信息充分交流的粒子群优化方法求解该模型。为了克服粒子群算法的早熟,采用混沌序列初始化粒子位置,发生早熟停滞时进行混沌寻优,以增强搜索多样性。该方法可同时计及实施过程中的各种约束。系统负荷较重时,常规方法无法使用,但文中所述算法依然有效。利用新英格兰39节点系统验证了该方法的有效性。

A Power Flow Transferring Control Algorithm Based on Node Lopsided Powers Using Particle Swarm Optimization

By turning the power security control of power transfer into non-linear programming,a new power flow transferring control algorithm based on node lopsided powers is proposed.The equality constraints are transformed into power mismatch and processed as the optimization target.It avoids the drawback of the conventional intelligent optimization algorithm that optimal solution must succeed to the satisfaction of power flow equations,thus improving the computing speed.Then a particle swarm optimization(PSO) algorithm with fully communicated information is utilized to solve the optimization problem.In order to avoid premature in PSO optimization process,chaotic sequence is used to initiate individual position,so as to strengthen the diversity of searching.Constraints of the optimization problem can be effectively handled by the proposed method.When system is heavily loaded,conventional methods cannot be used,but the algorithm proposed is still valid.New England 39-bus system is employed to verify the effectiveness of the proposed method.