Stochastic Day-ahead Optimal BESSs' Allocation in T&D Systems: Co-Optimization Based Approach with Uncertainties

With the growth of emerging new technologies in distribution networks, such as wind power, photovoltaic or DGs, the need for simultaneously investigation of these networks alongside transmission networks is highly important. In this paper, an efficient framework is proposed to understand seamlessly transmission and distribution (T&D) interactions while including detailed models for distributed energy resources. Wind power, photovoltaic and load are investigated according to their 24h profile. Besides, wind power uncertainty is considered via scenario based method. Finally, Battery Energy Storage Systems (BESSs‘) are used to track probabilistic renewable generation and minimize the total system power losses. The modified IEEE 9-bus test system is selected as a transmission network and 3 simple 8-bus radial feeders are selected as the distribution side networks. The problem modeled as a mixed integer nonlinear programming (MINLP) optimization problem and handled via GAMS programming language. The results show that with high penetration of renewable sources at distribution level, rescheduling main generators increases system energy efficiency. Moreover, BESS mitigates the impact of renewable sources volatility on both transmission and distribution levels while reducing power losses during peak hours.