Apresenta-se neste artigo um método de detecção automática de faltas baseado na análise da energia janelada dos coeficientes wavelet das tensões e correntes de fase. O método é capaz de detectar faltas evolutivas e de múltiplos distúrbios transitórios, a exemplo de uma falta seguida por um religamento automático, capturados no mesmo registro oscilográfico. O método também consegue distinguir faltas de algumas ocorrências relacionadas à qualidade da energia elétrica, tais como afundamento de tensão e transitórios de chaveamento. O método é eficaz na identificação dos instantes inicial e final da falta, além de conseguir analisar sinais referentes a linhas de transmissão de diferentes classes de tensão e que tenham sido registrados com frequências de amostragem diversas. Em avaliação de desempenho com registros oscilográficos simulados e reais, o método apresentou bons resultados.

By considering technical, economic, and socio-environmental criteria, in addition to the natural resources of each location, the assessment of wind and photovoltaic generation potential provides an opportunity for the conception, adaptation, and improvement of methods and models, preventing severe compromises to the realism of problem solutions regarding: i) the siting of a new hybrid energy generation power plant, and ii) the sizing of the power plant and its connection to the grid. The proposal is to integrate these problems into a model that preserves their nature, allowing them to be solved by distinct methods that are best suited to each. The sizing and connection problem is a mixed-integer optimization problem to be solved by MILP. A metaheuristic is applied to solve the siting subproblem and process the optimization as a whole. The Differential Evolution metaheuristic was tested to validate the model and applied to a real-world case study for prospecting renewable energy sources (RES) to be harnessed with an optimal return on investment. In practice, the proposal allows for a much more realistic model of the problem by considering, for example, the connection costs of the new power plants. The results found herein confirm the viability of the proposal.

Wind power expansion in the Brazilian Northeast faces two mutually reinforcing difficulties: the best-resource areas are progressively being occupied by operating projects, and the grid-connection cost has become comparable to the cost of the turbines themselves. Treating site selection and layout optimization as separate problems, which is the dominant practice in the literature, leads to suboptimal solutions under these conditions. This paper proposes Wind Farm Swarm Optimization (WFSO), a bi-level formulation based on Particle Swarm Optimization that unifies both problems in a single search loop: the outer level moves the centroids of candidate farms in continuous space, while the inner level optimizes the turbine layout of each candidate. Both levels share the levelized cost of energy (LCOE), which endogenously incorporates the connection cost, automatically selecting from among the available scenarios, and the interference zones of existing wind turbines. The methodology was validated on a benchmark case with a known optimum and applied to a 3500 km² region in Rio Grande do Norte, Brazil, using real resource, constraint, and infrastructure data. Four outer-PSO settings, spanning 1300 to 20,200 objective-function evaluations, converged to the same region and connection point, with a reference LCOE of 249.64 R$/MWh under a common seed. Repeated runs with independent seeds reveal a bimodal objective landscape whose success rate is governed by the evaluation budget: from about 11,400 evaluations, every seed reaches the best basin, and a configuration that is executable in 3.6 h stays within 0.27% of the 38.6 h reference. A sequential siting-then-layout baseline built with the same inner optimizer reaches an LCOE 9.4% higher, and on a reduced benchmark the method matches the optimum verified by exhaustive enumeration in 10 out of 10 seeds, which makes the tool practical for prospecting campaigns covering multiple areas.

The selection of georeferenced meteorological databases is a critical technical and financial factor in photovoltaic (PV) system sizing. This study evaluates how database choice affects PV generation estimates and economic feasibility by combining bibliometric screening, technical validation, financial indicators, and multicriteria analysis. A bibliometric review of 5658 documents indexed in Scopus and Web of Science supports the selection of seven databases, compared across ten Brazilian locations. PV generation is estimated using both a simplified sizing approach and a higher-temporal-resolution model based on hourly irradiance, ambient temperature, and module thermal coefficients, enabling comparison with measured generation in a three-year case study in João Pessoa. Performance is assessed using MAE, MAPE, RMSE, $R^2$, NPV, payback and the Analytic Hierarchy Process. Under the adopted PV model and AHP weighting structure, NASA POWER shows the strongest overall multicriteria performance in the analyzed Brazilian sample, ranking first in seven locations. Database choice causes variations of up to 4.70 years in payback and BRL 105,709.36 in NPV, equivalent to USD 21,082.84 at the 22 May 2026 exchange rate. The simplified CRESESB-based method overestimates annual generation by 6.79–12.64%, whereas NASA POWER reaches a best annual deviation of $-1.66\%$ in 2024.

Optimal sizing of energy storage system to be installed in a grid-connected hybrid generation plant. The optimization considers dispatch expectations and reliability indicators. The irradiation and wind database were obtained from INMET. Demand curves were generated based on the actual demand curve at the output of a 69/13.8 kV distribution substation in the city of Campina Grande. For a powerplant with 75 MW of wind power and 25MW of photovoltaic, a storage system of 35.45 MWh was sized, resulting in a 21% increase in reliability and a 3-fold reduction in the reference factor. Another positive effect was in the grid’s power flows, with a 10 MW reduction in the import amplitude of the balance bus.