| Reactive power optimization is a significant control means to realize safe and stable operation of distribution network.Flexible scheduling of reactive power control equipment can efficiently decrease system loss and increase voltage quality.As an energy storage device that can be flexibly transferred in both space and time dimensions,mobile energy storage brings effective power support to distribution network and improve power flow distribution in the system.The current research on mobile energy storage participating in reactive power optimization of distribution network mainly focuses on the collaborative optimization of mobile energy storage and on-load tap changer,shunt capacitor,distributed generation and other fixed reactive power equipment to realize voltage control or economic dispatch of distribution network.However,the current research usually only considers the single optimization objective of improving the voltage quality of the system or decreasing the network loss,or using a coupling method to convert multiple optimization indicators into single-objective optimization,and does not use multi-objective optimization methods to study the reactive power optimization of active distribution network with mobile energy storage participation.Therefore,a multiobjective optimization method based on mobile energy storage is applied to reactive power optimization of distribution network.The voltage excursion and network active loss of system are taken as the optimization target,and the multi-objective comprehensive control process of active distribution network is carried out.This paper mainly completed the following work:Firstly,the properties of various reactive power devices used for voltage control in power system are analyzed.The basic reactive power control principle of some common reactive power control devices used for power system is introduced and analyzed.These devices include on-load tap changer,shunt capacitor,distributed generation and energy storage.Then,the relevant mathematical model is established as the basis for reactive power optimization configuration of active distribution network.Secondly,the validity of the widely used reactive power optimization method for active distribution network is studied.Firstly,the operation and control characteristics of reactive power equipment connected to the grid are analyzed from a theoretical perspective.Secondly,the scheduling strategy of reactive power equipment participating in system optimization control is studied.Finally,the IEEE33-bus system is used as the calculation example for optimization simulation to verify the effectiveness of the above reactive power optimization method.Thirdly,a single objective reactive power optimization method for active distribution network with mobile energy storage is analyzed.Using the characteristics of flexible deployment of mobile energy storage,the reactive power flow distribution of the system is more balanced,so that the power system can runs safely and stably when reactive power is insufficient or excessive in some areas.Firstly,the composition structure and basic characteristics of mobile energy storage are introduced.Secondly,the operation constraints and output constraints of the moving path of the mobile energy storage are mathematically described,and the mathematical model of reactive power optimization scheduling of active distribution network is established.Finally,IEEE33-bus system is used as an example to verify the correctness of the established model and the effectiveness of the solution algorithm.Fourthly,a multi-objective reactive power optimization model of active distribution network with mobile energy storage is established.Firstly,the active distribution network with mobile energy storage participation is modeled according to the optimization principle of multiobjective function.Secondly,the multi-objective particle swarm optimization algorithm is used to solve the established model,and then the Pareto solution set of the objective function containing node voltage excursion and line active power loss is obtained.Then,the fuzzy membership method is used to select the comprehensive optimal solution in the Pareto solution set.Finally,IEEE33-bus system is used as an example to verify the correctness of the established model and the effectiveness of the solution algorithm. |
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