Energies, Vol. 18, Pages 6552: Optimal Location and Sizing of BESS Systems with Inertia Emulation to Improve Frequency Stability in Low-Inertia Electrical Systems
Energies doi: 10.3390/en18246552
Authors:
Jorge W. Gonzalez-Sanchez
Jose Aparicio-Ruidiaz
Santiago Bustamante-Mesa
Juan D. Velásquez-Gómez
Traditionally, the dynamics of power systems have been governed by synchronous generators and their associated rotating masses. However, with the increasing penetration of renewable generation and power electronic interfaces, the inertia contributed by rotating machines has been gradually displaced. This makes it imperative to study alternative elements capable of mitigating the reduction in inertia in modern power systems. This article addresses the problem of optimal sizing and placement of Battery Energy Storage Systems to enhance frequency response in power grids through the application of optimization techniques such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). Several inertia scenarios are analyzed, where the algorithms determine the optimal locations for Battery Energy Storage Systems units while minimizing the total installed Battery Energy Storage Systems capacity. As key contributions, this study models Battery Energy Storage Systems units, which emulate inertial responses based on the system’s Rate of Change of Frequency, and evaluates the impact of Battery Energy Storage Systems on frequency stability by analyzing parameters such as the frequency nadir, zenith, and steady-state frequency according to the installed Battery Energy Storage System’s size and location. A comparative analysis of the optimization scenarios shows that the Particle Swarm Optimization algorithm with 50% rotational inertia is the most efficient, requiring the lowest total installed power (277.11 MW). It is followed by the Particle Swarm Optimization algorithm with 100% rotational inertia (285.79 MW) and Genetic Algorithms with 50% rotational inertia (285.57 MW). In contrast, Genetic Algorithms with 25% rotational inertia demand the highest total installed Battery Energy Storage Systems power (307.44 MW), a result directly associated with a significant reduction in system inertia. Overall, an inverse relationship is observed between the available inertia level and the required Battery Energy Storage Systems capacity: the lower the inertia, the greater the power that the Battery Energy Storage Systems must supply to keep the system frequency within acceptable operational limits.