基于PSO-SVM模型的理论线损率预测研究

Research on Theoretical Line Loss Rate Prediction Based on PSO-SVM Model

深入分析了线损率的影响因素,对现存的线损率预测方法进行了研究,采用粒子群算法对支持向量机进行参数寻优,建立基于粒子群优化的支持向量机预测模型对理论线损率进行预测仿真,为线损的降低和电能的高效利用提供保障;最后通过实例验证了该模型在理论线损率预测中的精度。

This paper deeply analyzes the influential factors for line loss rate, studies present line loss rate prediction methods, uses particle swarm algorithm to optimize the parameters of support vector machine, sets up support vector machine prediction model based on particle swarm optimization to simulate theoretical line loss rate prediction in order to provide guarantee for reducing line loss rate and highly-efficient utilization of power and finally uses sample experiment to verify the accuracy of this model in theoretical line loss rate prediction.