Abstract Development of efficient multi-objective evolutionary algorithms (MOEAs) has
provided effective tools to solve environmental/economic dispatch (EED) problems. EED is a …

Power generation system largely depends on fossil fuels to generate electricity. Due to
various reasons, the reserves of fossil fuels are declining and will become too expensive in …

A player unknown's battlegrounds (PUBG) ranking based optimization (PRBO) algorithm is
proposed. It is based on the ranking scheme of a popular battle royale game PUBG where …

The upsurge in microgrid demand is an important aspect of imparting energy in future
primarily because of the involvement of renewable energy sources, which alleviates the …

In the past decade, deep learning models have shown to be promising tools for time series
forecasting. However, owing to significant differences in the volatility characteristics among …

Economic environmental dispatch (EED) is an important optimization task in fossil fuel fired
power plant operation for allocating generation among the committed units such that fuel …

In the near future, plug-in electric vehicles (PEVs) will dominate the car market. The peak-
valley difference would increase greatly due to the random nature of PEVs charging …

Home energy management (HEM) is one of the crucial requirements for future smart grid
environment. Usually, utility companies motivate residential consumers to participate in …

This paper presents a new multiobjective evolutionary algorithm for environmental/economic
power dispatch (EED) problem. The EED problem is formulated as a nonlinear constrained …

The potential and effectiveness of the newly developed Pareto-based multiobjective
evolutionary algorithms (MOEA) for solving a real-world power system multiobjective …