Research On Multi-Source Planning And Operation Of Active Distribution Network Based On Improved Particle Swarm Algorithm

Renewable distributed power sources will have a great impact on the stable operation of the system after being connected to the traditional distribution network.In order to improve the ability of the distribution network to accept renewable distributed power sources,the Active Distribution Network(ADN)with active management capabilities has attracted widespread attention,and its planning and operation issues have also become a hot issue.The study of active distribution network planning and operation mainly lies in the establishment of models and the selection of solving algorithms.Since the maximum utilization of renewable resources in the planning area is related to the economics of investment,it is particularly important to reasonably determine the total amount of renewable resources in the region.At present,there is no suitable model or method that can fully describe the uncertain changes in the output power of renewable distributed power sources.Different locations and capacities where Distributed Generation(DG)is connected to the distribution network have different impacts on the power flow of the system.Whether the selected solution algorithm can solve the optimal solution of multi-objective functions and has good convergence is also a problem that needs to be considered in the planning and operation of active distribution network.In response to the above-mentioned problems,this article mainly conducted the following research work:(1)In this thesis,the uncertainty of the output of renewable distributed power generation represented by wind turbine power generation and photovoltaic power generation is modeled,and its output power is simulated by Monte Carlo method based on the probability density curve.The regional resource assessment method is used to determine the total amount of solar and wind energy resources in the region,which shows its superiority compared with the previous methods of determining the available amount of solar and wind energy resources.(2)Propose a comprehensive ratio that considers the rate of change of the network loss after the renewable distributed power source is connected to the system and the load ratio of the connected node,so as to determine the best position for the renewable distributed power source to connect to the distribution network,And get the best capacity range of the access system according to the best location of the renewable distributed power access system.(3)Applying the active management of the active distribution network,a multi-objective bi-level programming model with the least annual comprehensive cost and the smallest network loss is proposed.The adaptive improved particle swarm algorithm and the tracking center trajectory of the particle swarm algorithm combined with the genetic algorithm are used respectively.Solve by interior point method.The IEEE 33-node distribution network is used as a simulation example to illustrate the feasibility of the proposed comprehensive ratio and the effectiveness of the improved algorithm.