Cluster Operation Optimization Of Active Distribution Network Based On Distributed Energy Storage Location And Capacity Determination

In order to reduce carbon emissions,it has become a consensus to use clean energy more and more.Large-scale clean energy power supply is bound to bring uncertainty to the distribution network.In order to improve the safety and reliability of distribution network operation,traditional distribution network has gradually developed into an active distribution network.Energy storage and other adjustable resource optimization can enhance the absorption capacity of distributed power supply in the distribution network,and ensure the safe and stable operation of the power system.In addition,clustering of distribution network nodes with high-scale photovoltaic access facilitates energy storage configuration planning to better meet the challenges of power system management after large-scale distributed power supply is connected to low-voltage distribution network.Under this background,this paper studies the optimal operation method of active distribution network cluster based on distributed energy storage location and capacity selection,and the specific work is as follows:First,in order to maximize the consumption level of renewable energy,clusters are divided according to the degree of electrical coupling.In order to measure the degree of coupling between nodes,this paper divides the proposed indicators into two categories according to the logical,structural and functional principles.Among them,the logical and structural principles emphasize the structural strength between nodes,so the modularity index based on electrical distance is used to indicate the degree of electrical coupling between nodes in each cluster.Functional principle pays attention to the balance between source and load as well as the power regulation ability.Therefore,this paper uses reactive power balance and active power balance index to represent the source and load coordination ability of nodes in the cluster.Based on this,a comprehensive electrical distance index composed of modularity,reactive power balance and active power balance is presented.Secondly,based on the traditional community discovery algorithm,an improved community discovery algorithm is proposed,which makes up for the shortcomings of the traditional algorithm in global optimization ability.Finally,an example of IEEE 33-node distribution network is used to demonstrate that the clustering method proposed in this chapter has stronger electrical coupling and source-load coordination ability,and the algorithm proposed has better clustering effect.Secondly,under the scenario of determining the photovoltaic output,the energy storage location and capacity planning model of active distribution network based on cluster partition is established,which is optimized by double-layer particle swarm optimization algorithm.The upper target considers the annual integrated cost of installation and maintenance costs of energy storage system(ESS),photovoltaic power subsidy and the main network purchase cost,while the lower target considers the total power loss under the distribution network access to energy storage and photovoltaic.The upper and lower models need to work together to exchange information between layers through parameter transfer.The upper model transfers the decision variables it obtains to the lower model.The lower model obtains the corresponding constraints and initial state based on this value.The lower model optimizes the ESS charging and discharging power based on this state,and then calculates the distribution network loss corresponding to the optimal value and transfers it back to the upper model.The upper model calculates the annual integrated cost of the distribution network through this value of the total model.Based on the results of cluster partitioning in Chapter II,this chapter proves that cluster-based configuration has better economy,lower network loss and greater voltage stability than traditional centralized configuration.Thirdly,the two-stage robust optimal operation of active distribution network considering the uncertainty of distributed photovoltaic output is studied.A two-stage robust operation model is used to consider the random uncertainty of distributed photovoltaic output.The proposed twophase robust method determines the power interaction with the upper power grid in the first phase,and in the second phase,reschedules the charging and discharging plans of the storage devices according to the actual photovoltaic output to satisfy all photovoltaic output scenarios within the robust and uncertain set.Then the two-stage optimization problem is solved by C&CG algorithm,and the economic and security balance of the active distribution system is achieved by solving the two-stage problem cooperatively.