Allocation of Energy Storage Systems in a Hydro-Thermal-Wind System

Abstract

Abstract Strong concerns over greenhouse gas emissions have required the construction of non-polluting energy sources such as wind farms and photovoltaic plants. This need, combined with recent technological developments, has enabled the global installed capacity of wind farms in particular to grow from a negligible level in 2001 to more than 900 GW in 2023. However, due to the high variability of wind, this energy source is non-dispatchable, i.e., it cannot be controlled by operators to meet demand in a short amount of time. This problem can be mitigated by the allocation of energy storage systems (ESSs) to appropriate buses. This paper proposes an optimization model for the allocation of large-scale ESSs using a genetic algorithm (GA) and a linear multi-period optimal power flow (LMOPF). The GA enables the best allocation of the ESS to buses, their dimensions (i.e., selection of the power and energy of the ESS) and four types of technology. The LMOPF is used to perform system planning for a horizon of np periods, and to carry out the generation dispatch of a high voltage hydro-thermal-wind system and the charging and discharging processes of the ESS allocated by the GA. Due to the large size of the system and the complexity of resolution, a single-phase network model was chosen, and reactive power was disregarded. The model was tested using a system in the south of Brazil. The results showed that the optimal allocation of ESSs allowed for a hydroelectric energy time-shift, reducing the daily costs of operation.

Keywords

• Allocation of energy storage systems
• arbitrage
• energy time-shift
• genetic algorithms
• linear multi-period optimal power flow.