Distribution Network Planning Based On Uncertainty Theory

Distribution network planning in power system is a complex system problem with multi-objective and uncertainty.There are many uncertain factors in the power system,such as the uncertainty of equipment failure,the access of distributed power supply,and the uncertainty of load prediction.It is very important to solve the influence of uncertain factors on the reliability,security,stability and reliability of distribution network planning.Therefore,based on the uncertainty theory,this paper makes an in-depth study on the distribution network planning.The specific work of this study includes the following aspects:(1)expound the theory of uncertain planning.The concepts of fuzzy set and fuzzy expected value are analyzed and the two concepts are simulated.The concepts of random variable and random expected value are expounded,and the mathematical principle of random chance constraint in random programming is expounded.(2)study uncertain power flow calculation and optimize related algorithms.Considering the characteristics of load power and distributed power generation,fuzzy power flow is calculated by fuzzy programming and random power flow is calculated by random programming.The fuzzy increment of the state variable is calculated by using Taylor series on the basis of nou-rafa.The power probability distribution of each branch and each node of the variable to be solved is calculated by using random power flow and semi-invariant method.Then,the paper mainly introduces,summarizes and compares the application characteristics of adaptive genetic algorithms.(3)the distribution network planning model is established based on the uncertainty theory.The uncertain quantity in the distribution network planning is modeled,including load uncertainty,wind power generation,photovoltaic power generation,and the corresponding opportunity constraint planning model and fuzzy expectation planning model are established.In the two models,in the fuzzy expectation programming model,the minimum objective function is the fuzzy expectation of the investment and construction cost,and the trapezoidal fuzzy number is used to simulate the load uncertainty.In the other model,chance constraint programming mainly considers the confidence level of branch convention and node voltage constraint condition.(4)verify the validity of the above two models by analyzing and verifying a node system,and optimize the solution based on adaptive genetic algorithm.According to the principle of minimum construction investment cost and network loss cost,the research shows that the influence of uncertain factors on the distribution network can be effectively reduced by using the uncertain planning theory,and the uncertain planning theory can also reduce the network planning cost and effectively promote the improvement of economic benefits.