| The large-scale access of distributed power supplies has brought certain adverse effects to the power distribution network,and the proposal of virtual power plant provides new ideas and methods for solving this problem.As one of the core equipment of virtual power plant,energy storage device's can effectively improve the economics of virtual power plants through rational allocation.However,the main factor limiting its large-scale application is the relatively high cost.Configuring energy storage capacity and reducing investment cost of energy storage system have become one of the key issues in the planning process of virtual power plants.Firstly,the distributed photovoltaic,gas turbine and multi-type energy storage system(lithium titanate battery,all-vanadium liquid battery and super capacitor)and load are selected to from virtual power plants.Under the condition of ensuring that all PVs are consumed,the output strategies of each component are analyzed,and an optimization model with the objective of maximum net revenue of virtual power plants that takes into account the time-of-use electricity price is established,the output of the energy storage system is solved by the particle swarm optimization algorithm,and then the power and capacity of different types of energy storage are obtained by the signal decomposition of the energy storage system through the fast Fourier transform according to different characteristics of each energy storage unit in the energy storage system.In addition,it is verified that the combination of three types of energy storage is better than the combination of two types.Secondly,the improved quantum-behaved particle swarm algorithm is put forward to improve the absorber in particle position.Under the premise that the light is allowed to be abandoned,the revenue optimization model of virtual power plant is established,and it is solved by the improved quantum-behaved particle swarm algorithm to obtain the configuration capacity of the energy storage system.At the same time,the superiority of the improved quantum-behaved particle swarm algorithm is verified through the computational time and iterative convergence of the quantum-behaved particle swarm algorithm and improved quantum-behaved particle swarm algorithm.Finally,in order to facilitate the calculation of the capacity configuration of energy storage system in the virtual power plant under different scenarios,the MATLAB is called by C# language to build a multi-type energy storage capacity configuration platform for the virtual power plant.The platform can select the PV and load data and change the parameter information of each energy storage unit in the energy storage system according to the requirements,and can not only change the data and parameter,but also make the calculation of the capacity configuration of the energy storage system more simple and convenient,and improve the work efficiency. |
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