基于EWM-AHP-BP神经网络的地区电网电压无功组合评价

Voltage and Reactive Power Combinational Evaluation of Regional Power Grid Based on EWM-AHP-BP Neural Network

为量化评估新能源接入对地区电网电压无功运行状态的影响,提出一种基于EWM-AHP-BP(entropy weight method-analytic hierarchy process-BP)神经网络的地区电网电压无功组合评价方法。建立考虑电压合格率、电压波动、功率因数合格率、无功储备4项指标的电压无功综合评价模型,通过新能源与负荷运行数据聚类划分典型场景,采用熵权-层次分析组合方法对多场景下的评价模型打分,评价结果作为BP神经网络的样本进行训练。提出的组合评价方法简化了多目标评价的指标权重计算过程,实现了权重随数据变化的自适应调整,有效提升了计算效率。以某实际地区电网为例进行仿真,对历史数据进行样本训练和评价分析,验证了该方法的有效性。

In order to quantitatively evaluate the influence of renewable energy access on voltage and reactive power operation,a combinational evaluation method of voltage and reactive power based on EWM-AHP-BP neural network is proposed to carry out the multi-objective evaluation weight calculation.Considering voltage qualified rate,voltage fluctuation,power factor qualified rate and reactive power reserve,the comprehensive evaluation model is established.The operation data of renewable energy and power load are clustered to divide the typical scenarios and the evaluation model under multiple scenarios is scored by the combination method of entropy weight method and analytic hierarchy process.The evaluation results are trained as samples of BP neural network.The proposed method simplifies the weight calculation process of multi-objective evaluation,realizes the adaptive adjustment of weight with the change of samples and effectively improves the calculation efficiency.The effectiveness of the proposed method is verified by the simulation on an actual regional power grid and the sample training and evaluation analysis of historical data.