基于自适应差分算法的电力系统稳定器参数设计

Parameter Design of Power System Stabilizer Based on Self-adaptive Differential Evolution Algorithm

自适应差分算法强大高效,是一种基于群体的随机搜索技术,一般用于连续空间优化问题求解,被广泛应用于科学和工程领域。自适应差分算法是在差分进化算法基础上经过改进得到的算法,其实验向量生成策略及其相关的控制参数值拥有自适应能力,这种能力是通过从前期生成可能解的过程中学习得来的。在利用S imu link建立起单机无穷大系统仿真模型的基础上,根据时间乘绝对误差积分准则(ITAE准则)设计寻优问题的目标函数,将电力系统稳定器的参数设计问题转化为最小化问题,并用自适应差分算法求解。最后在单机无穷大系统上进行仿真实验,结果表明经过优化设计的电力系统稳定器拥有良好性能。

Differential evolution（DE） algorithm is an efficient and powerful population-based stochastic search technique for solving the optimization problems over continuous space,which has been widely applied to the scientific and engineering fields.Self-adaptive differential evolution（SaDE） algorithm is the improved algorithm,in which both trial vector generation strategies and their associated control parameter values are gradually self-adapted by learning from their previous experiences in generating promising solutions.Based on the simulation model of single machine infinite bus system,the objective function of optimization issue is designed according to the time by absolute error integral criterion（ITAE criterion）.The parameter design issue of power system stabilizer is converted to the minimization issue.Finally,the simulation test is carried out on a single machine infinite bus system,and the results show that the power system stabilizer has a good performance after the design optimization.