RESUMO
Developing a reliable power grid and investing in non-conventional renewable energy resources pose problems for low- and medium-income countries. Frequently, maintaining a robust power grid infrastructure can present challenges in terms of reliability, resilience, and flexibility. This article presents a methodology for improving power flexibility in susceptible power systems through the utilization of Battery Energy Storage Systems (BESS). The methodology entails the examination of power stability, operating conditions, and security criteria in order to identify suitable locations for storage allocation. A study was conducted utilizing the Electrical Transient and Analysis Program (ETAP®) software to simulate the Central American power transmission grid. The results of the study indicate that including storage systems to offer virtual inertia and backup during emergency situations is a recommended strategy for mitigating potential challenges. The study suggests that applying specific criteria for allocation and sizing at critical points in sensitive systems can enhance power transfer flexibility, eliminating potential constraints. The Central American electrical Power System, which faces power transfer limitations, is well-suited for BESS. In severe contingencies, such as when the system frequency drops to 58.75 Hz and power transfer between Mexico and Central America exceeds 300 MW with voltage levels below 0.97 pu, BESS can help mitigate these issues. The solution involves deploying BESS both centrally and distributively. Results show decreased instability, with power increases not exceeding 300 MW for more than 11 study cycles in all scenarios. The approach includes a BESS with an installed capacity of 1,060 MWh/160 MW and a virtual inertia of H=6s.
RESUMO
This paper proposes a time-series stochastic socioeconomic model for analyzing the impact of the pandemic on the regulated distribution electricity market. The proposed methodology combines the optimized tariff model (socioeconomic market model) and the random walk concept (risk assessment technique) to ensure robustness/accuracy. The model enables both a past and future analysis of the impact of the pandemic, which is essential to prepare regulatory agencies beforehand and allow enough time for the development of efficient public policies. By applying it to six Brazilian concession areas, results demonstrate that consumers have been/will be heavily affected in general, mainly due to the high electricity tariffs that took place with the pandemic, overcoming the natural trend of the market. In contrast, the model demonstrates that the pandemic did not/will not significantly harm power distribution companies in general, mainly due to the loan granted by the regulator agency, named COVID-account. Socioeconomic welfare losses averaging 500 (MR$/month) are estimated for the equivalent concession area, i.e., the sum of the six analyzed concession areas. Furthermore, this paper proposes a stochastic optimization problem to mitigate the impact of the pandemic on the electricity market over time, considering the interests of consumers, power distribution companies, and the government. Results demonstrate that it is successful as the tariffs provided by the algorithm compensate for the reduction in demand while increasing the socioeconomic welfare of the market.