基于风险熵的增益配电网投资风险评估模型设计

Design of Investment Risk Assessment Model for Gain Distribution Network Based on Risk Entropy

为了实现对增益配电网投资风险因素的量化评估和自动预测,提出基于风险熵特征提取的增益配电网投资风险评估算法,并建立增益配电网投资风险大数据分析模型。采用统计量化分析的方法进行增益配电网投资风险评估的约束参数分析,提取增益配电网投资风险大数据的熵特征量,采用输出稳定性增益评估和模糊决策的方法对风险评估的约束参数进行配电网风险评估的优化决策和评估,建立增益配电网投资风险评估的专家系统分析模型,采用自适应的机器学习算法进行增益配电网投资风险评估的自适应寻优,采用最大似然估计和模糊多参数约束控制的方法实现配电网投资风险评估模型的优化设计。仿真结果表明,采用该方法进行配电网投资风险评估的准确度较高,置信度水平较好,提高了配电网投资风险评估效能。

In order to realize the quantitative evaluation and automatic prediction of the investment risk factors of the gain distribution network,an investment risk evaluation algorithm based on the feature extraction of risk entropy is proposed,and a big data analysis model of the investment risk of the gain distribution network is established.The method of statistical quantitative analysis is used to analyze the constraint parameters of the investment risk assessment of the gain distribution network,the entropy feature of the big data of the investment risk of the gain distribution network is extracted,the optimization decision and assessment of the constraint parameters of the risk assessment are carried out by the method of output stability gain assessment and fuzzy decision,and an expert system of the investment risk assessment of the gain distribution network is established.Unified analysis model,adaptive machine learning algorithm are used to optimize the gain distribution network investment risk assessment,and maximum likelihood estimation and fuzzy multi parameter constraint control are used to optimize the distribution network investment risk assessment model.The simulation results show that the accuracy and confidence level of this method are high,which improves the efficiency of distribution network investment risk assessment.