ALMEIDA, B. A. M.; http://lattes.cnpq.br/3357451799359491; ALMEIDA, Bruno Araújo Marques de.
Resumen:
This work carries out a comprehensive evaluation of the performance of Energy Storage Systems (ESS) in distribution networks with high penetration of renewable energy sources, particularly solar and wind energy. The significant increase in the share of these sources in the global energy matrix, driven by the need to transition to cleaner energy, presents new technical challenges, such as the intermittency and variability of energy generation, which directly affect the stability and reliability of distribution networks. In this context, the SAE system has been identified as one of the solutions to mitigate the effects of these variations, enabling the maintenance of a more stable and efficient network operation. This work seeks to explore, through technical analyses and computer simulations, the impact of SAE integration in different scenarios, considering benefits in terms of reducing technical losses, stabilizing voltage and optimizing costs associated with the installation and operation of systems. Using OpenDSS software to simulate network performance and applying a genetic algorithm to optimize the location and sizing of storage systems, the study proposes hybrid arrangements that combine renewable sources with SAE, suitable for distribution networks. In addition, an economic analysis will be carried out, assessing the financial viability of implementing SAE in different contexts, considering investment and maintenance costs, and possible savings resulting from improved energy efficiency. The work’s ultimate goal is to contribute to the development of innovative and economically viable solutions that can facilitate the transition to a more sustainable energy matrix. Finally, it is expected that the results obtained will assist in the formulation of public policies and regulatory strategies for the expansion of SAE in distribution networks, optimizing the integration of renewable energies and increasing the operational flexibility of the networks.