Optimized Development Planning of Energy Storage System Capacity in Rural Power Grid

The rural distribution network with rich photovoltaic resources and sparse loads is prone to large-scale revere power flow, node overvoltage, and incomplete PV consumption. The traditional energy storage system (ESS) configuration schemes focus on the optimization of capacity within only one single year. To achieve optimized planning of a longer certain stage, this paper proposes a path planning method for energy storage capacity optimization in rural power grids based on improved particle swarm optimization (PSO) algorithm. First, considering the ability and cost of energy storage system to consume photovoltaics, an energy storage capacity path planning model with the objective of minimizing energy storage investment costs is constructed. The model takes account of typical constraints such as voltage limit and line capacity. Secondly, an optimization algorithm based on improved inertial weight PSO algorithm is proposed to solve the model, which provides both the global search and local search capabilities of the PSO. Finally, a typical rural power grid is analyzed. Under different photovoltaic penetration rates of 70%, 60% and 50%, the ESS capacity path planning method can be formulated. Under the obtained optimal ESS capacity configuration, the consumption rate of the distributed PV power reaches to 100%.