Considering the intermittent nature of renewable energy,a storage system to reserve power in off-peak hours and then to supply it during peak hours is necessary.However,if these storage devices in a network are not pl...Considering the intermittent nature of renewable energy,a storage system to reserve power in off-peak hours and then to supply it during peak hours is necessary.However,if these storage devices in a network are not placed in an appropriate manner,the advantages can never be achieved.In this study,the allocation and sizing strategies of a battery energy-storage system(BESS)in an optimal way are proposed to improve the performance of the radial distribution networks.The test network adopted is a standard IEEE 33 bus network that is integrated with solar power.Simulations are carried out in DIgSILENT PowerFactory for the distribution network model and the process of optimization is done through MATLAB®.The optimization algorithm adopted is the genetic algorithm.The system is studied for 24 hours with a step size of 15 minutes,employing a time-sweep analysis of dynamic load.It is studied under three different scenarios and the results are compared.The results illustrate a considerable reduction in power losses in the case of the optimized BESS.The total losses before the optimization process are 16365.57 kW.The total losses after the employment of the proposed solution are 10246.5 kW,which means that the losses are reduced by≤62%.展开更多
文摘Considering the intermittent nature of renewable energy,a storage system to reserve power in off-peak hours and then to supply it during peak hours is necessary.However,if these storage devices in a network are not placed in an appropriate manner,the advantages can never be achieved.In this study,the allocation and sizing strategies of a battery energy-storage system(BESS)in an optimal way are proposed to improve the performance of the radial distribution networks.The test network adopted is a standard IEEE 33 bus network that is integrated with solar power.Simulations are carried out in DIgSILENT PowerFactory for the distribution network model and the process of optimization is done through MATLAB®.The optimization algorithm adopted is the genetic algorithm.The system is studied for 24 hours with a step size of 15 minutes,employing a time-sweep analysis of dynamic load.It is studied under three different scenarios and the results are compared.The results illustrate a considerable reduction in power losses in the case of the optimized BESS.The total losses before the optimization process are 16365.57 kW.The total losses after the employment of the proposed solution are 10246.5 kW,which means that the losses are reduced by≤62%.
