针对现有电能质量评估方法存在的不足,提出了一种新的粒子群优化算法和支持向量机理论相结合的智能电能质量综合评估方法.根据电能质量国家标准,确定了电能质量评估指标,并针对目前电能质量等级过于模糊的缺点,提出了区间化电能质量的细化措施.利用惯性权重自适应调节方法对粒子群算法进行了改进,在此基础上建立了基于粒子群优化支持向量机的电能质量综合评估模型.仿真实例的评估结果表明,所建立的综合评估模型是合理有效的,评估结论与其他评估方法相比更为合理可信.%To overcome the shortcomings of the existing power quality assessment methods,a new intelligent power quality comprehensive evaluation method based on particle swarm optimization(PSO) algorithm and support vector machine (SVM) theory was proposed.According to the national standards of power quality,the power quality evaluation index was determined,and the refinement measures of interval power quality were put forward.The PSO was improved by the inertia weight adaptive adjustment method,then a power pulity comprenensive evaluation model based on PSO-SVM was established.The evaluation results of simulation examples show that the comprehensive evaluation model is reasonable and effective,and the evaluation conclusion is more reasonable and credible than other evaluation methods.
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