Abstract
In the revolution of green energy development, microgrids with renewable energy sources such as solar, wind and fuel cells are becoming a popular and effective way of controlling and managing these sources. On the other hand, owing to the intermittency and wide range of dynamic responses of renewable energy sources, battery energy-storage systems have become an integral feature of microgrids. Intelligent energy management and battery sizing are essential requirements in the microgrids to ensure the optimal use of the renewable sources and reduce conventional fuel utilization in such complex systems. This paper presents a novel approach to meet these requirements by using the grey wolf optimization (GWO) technique. The proposed algorithm is implemented for different scenarios, and the numerical simulation results are compared with other optimization methods including the genetic algorithm (GA), particle swarm optimization (PSO), the Bat algorithm (BA), and the improved bat algorithm (IBA). The proposed method (GWO) shows outstanding results and superior performance compared with other algorithms in terms of solution quality and computational efficiency. The numerical results show that the GWO with a smart utilization of battery energy storage (BES) helped to minimize the operational costs of microgrid by 33.185% in comparison with GA, PSO, BA and IBA.
Highlights
With the ever-growing energy demand, greenhouse gas (GHG) emission reductions, energy-efficiency improvements, and adequate clean power have become major challenges in the energy sector
The effectiveness of the developed grey wolf algorithm is demonstrated in this paper by utilizing it to solve different non-linear parameters and complex problems by considering the load dispatch issues in the microgrid
The feeders supplying distributed loads from the generators have a relatively short distance which does not have a significant impact on the voltage profile, and the power losses are neglected in this study
Summary
With the ever-growing energy demand, greenhouse gas (GHG) emission reductions, energy-efficiency improvements, and adequate clean power have become major challenges in the energy sector. A promising solution to this issue is the development of microgrids with renewable energy sources such as solar, wind and fuel cells. The microgrids can be self-sufficient power grids (standalone microgrids) working with local sources or grid-connected microgrids attached to the conventional utility grid. Irrespective of the microgrids’ form, they have succeeded in reducing the CO2 amount and cutting energy costs [1,2]. Due to the fluctuations and intermittency of renewable-energy sources such as wind turbines (WTs) and photovoltaic (PV) units, the utilization of storage devices has become crucial in the microgrids [3].
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