Research On Dynamic Optimization Of Active Distribution Network Based On Power Electronic Transformer

With the rapid progress of new energy technology,the active distribution network with clean energy as the core is gradually becoming mature.The addition of distributed power generation has changed the form of power flow within the distribution network lines,transforming the traditional distribution network into an active distribution network with two-way power flow.Due to the large-scale access of distributed power generation,this poses a huge challenge to the smooth operation of the distribution network.The main performance is: voltage instability caused by grid connection of distributed power sources and insufficient means of active/reactive power regulation,greatly affecting the operation of the power grid,which greatly affects the operation of the power grid.Therefore,it is particularly important to consider how to effectively optimize the system after connecting distributed energy and loads in active distribution networks.Power electronic transformer is Compared to traditional on-load voltage regulating transformers,it have stronger control capabilities and more flexible regulation methods,which can reduce the cost of switching using parallel capacitor banks during operation,and also protect the system from pollution caused by excessive reactive power.Therefore,this article takes active distribution networks as the research object and combines the advantages of power electronic transformers to study the dynamic optimization process of distribution networks.The main research work includes the following aspects:Firstly,the research background and significance of dynamic optimization for active distribution networks are described,and the necessity of implementing dynamic optimization for active distribution networks is clarified.And summarizes the current research status of power electronic transformers and dynamic optimization,and describes the algorithms used in optimization.At the same time,the control modes of active distribution networks and the characteristics and mathematical models of various distributed power sources are analyzed,as well as the current popular power flow calculation methods are described,laying a theoretical foundation for studying the dynamic optimization of active distribution networks.Secondly,a mathematical model for reactive power optimization of active distribution networks is established with active power loss,voltage offset,and minimum node voltage as multiple objectives.This paper introduces the basic principle of standard particle swarm optimization algorithm,aiming at the possible problems of local convergence and premature convergence when dealing with complex problems with multiple targets.Using theconcept of population concentration to adjust the inertia weight value of the algorithm,and introducing sine and cosine control factors into the learning factors of the algorithm,an improved particle swarm optimization algorithm is proposed.The improved particle swarm optimization algorithm is applied to solve reactive power optimization in active distribution networks,and an example simulation is performed on an improved IEEE33 node system to prove the effectiveness and superiority of the improved particle swarm optimization algorithm proposed in this paper compared to other algorithms.Thirdly,considering the intermittency and volatility of load,distributed energy,and the economy and continuity of PET devices,a multi time scale dynamic reactive power optimization model for active distribution networks with PET is established.In the early stage,considering the constraints of discrete reactive power compensation equipment,taking voltage deviation and active network loss as objectives,an hour level optimization strategy is implemented,and heuristic spatiotemporal decoupling strategy and sensitivity analysis methods are used to process the constraints of equipment in each period,optimizing and adjusting the priority queue of equipment actions in each period,in order to obtain the optimal adjustment scheme;In the daytime stage,the adjustment capability of continuous reactive compensation equipment is considered,and the reactive output of distributed energy and PET devices is taken as control variables.The objective function is still the active network loss and voltage deviation.A minute level optimization strategy is implemented to ensure stable and reliable operation of the system in a short time.Finally,a dynamic active and reactive power coordination optimization model is established,which includes power storage devices(energy storage)and reactive power devices(PET).Through the charging and discharging strategies of energy storage units,voltage fluctuations are smoothed,load pressure on the power grid is alleviated,and PET devices are used to reduce the number of actions of voltage regulating equipment.This not only improves the operation level of the power grid,but also reduces the economic cost of the power grid.The improved particle swarm optimization algorithm is used to solve the established dynamic optimization model,and simulation is conducted on the improved IEEE33 node system to validate the dynamic optimization strategy for active distribution networks containing PET proposed in this paper.The results show that the proposed dynamic optimization strategy has certain theoretical significance and practical value for the economy,stability,and safety of active distribution networks.