Power Quality Evaluation Based On The Variable Weighted Synthesis

We study the issues of power quality comprehensive evaluation,three kinds of variable weight synthesis based power quality evaluation models are established.The main contents includes:First,a Maximum Entropy Programming based comprehensive evaluation method is set up for the problem of electric power quality comprehensive evaluation with partial uncertainty index weight information.Firstly,the known index weight information,such as the judgments on the weight range or relative importance relationship of partial indexes,index reasonable constraints and the common specification regulations etc,are expressed as equality or inequality constraints by using mathematical modeling method.Then,a Maximum Entropy Programming model is set up to find the optimal index weight distribution by maximizing the entropy of comprehensive evaluation vector under the constraints of known index weight information.Finally,the comprehensive evaluation value is calculated by using the optimal index weight.The analysis of an electric power quality evaluation example verifies the validity of given method.Second,for the problem of traditional entropy-weight methods may occurs an unreasonable phenomenon that small changes of entropy value can cause dramatic changes in corresponding weight when all of the entropy values are approaching to 1,a new modified entropy weight method is proposed by introducing an adjustment parameter ?.Then,a variable weight synthesis power quality evaluation method based on the modified entropy weight method is given.The example analysis shows that the modified entropy weight methods can obtain a more reasonable result comparing with popularly used RSR,TOPSIS and Catastrophe decision method etc.Third,considering the effect of marginal cost increasing for index improvement,a variable weight synthesis model with incentive effect is introduced.First,the axiomatic definition of excellent degree operator and several construction method based on typical elementary function and their combinations were proposed to depict the excellent degree of an alternative according to single factor evaluation.Then,the concept of state based incentive weight adapter is introduced considering the excellence incentive effects.In addition,a new mode for variable weightconstruction is given based on the superposition of the factor importance related normal weight and the state based weight adapter which was set up by using excellent degree.In the following,a nonlinear programming model to determine the unknown normal weight is set up by using the principle of deviation maximization.Finally,the validity of the new model is examined by an example of electricity quality evaluation.