Storage Allocation in Active Distribution Networks Considering Life Cycle and Uncertainty

The modern active distribution systems necessitate integrating storage systems, thereby facilitating the large-scale proliferation of photovoltaic (PV) energy resources. This further calls for the optimal planning of energy storage systems, satisfying all the operational and economic constraints. This article describes an exhaustive storage integration method, deeming the life cycle of the battery energy storage, the uncertainty of load and PV output, and the islanded mode of operation of the system. A two-stage mixed-integer linear programming problem is formulated that determines the capacity and the number of discharge cycles of the batteries in the first stage. The lifetime of the battery based on the partial depth of discharge is analyzed in the second stage. Furthermore, the uncertainty and variability of PV and demand are taken into account through probabilistic analysis and time-period clustering. The method is validated on a standard 33-bus radial distribution network for the allocation of distributed lithium-ion batteries. Also, the method's scalability is validated on a practical Indian distribution network and a 141-bus distribution network of metropolitan area of Caracas with distributed PV installations on various nodes.

Automated summary

This article presents a comprehensive method for integrating energy storage systems into modern active distribution systems with photovoltaic resources. The method takes into account battery life cycle, load and photovoltaic output uncertainty, and system operation in islanded mode. It formulates a two-stage mixed-integer linear programming problem to determine battery capacity and number of discharge cycles in the first stage, and analyzes battery lifetime based on partial depth of discharge in the second stage. Probabilistic analysis and time-period clustering are used to consider the uncertainty and variability of photovoltaic and demand. The method is validated on different distribution networks, demonstrating its feasibility and scalability.