Abstract
Planning the operation scheduling with optimization heuristic algorithms allows microgrids to have a convenient tool. The developments done in this study attain this scheduling taking into account the impact of energy storage useful life in the microgrid operation. The scheduling solutions, proposed for the answer of an optimization problem, are obtained by using a metaheuristic algorithm called Differential Evolutionary Particle Swarm Optimization (DEEPSO). Thanks to the optimization that is conducted in this study, it is possible to formulate dispatches of the existent microgrid (MG) by always looking for the ideal dispatch that implies a lower cost and provides a greater viability to any project related to renewable energy, electric vehicles and energy storage. These advances oblige the battery manufacturers to start looking for more powerful batteries, with lower costs and longer useful life. In this way, this paper proposes a scheduling tool considering the energy storage useful life.
Highlights
The engineering discipline does focus on the development of technologies and solutions for practical challenges, but it looks for the most optimal ones
Some researchers have considered electric vehicles in the MG, including the Vehicle2Grid option (V2G), a technology with the capability of being charged using the energy supplied from the grid and sometimes returning the stored energy to the grid
The use of the plug-in hybrid electric vehicles, the use of wind and solar renewable energies, the energy storage and the uncertainty modeling through uncertainty cost functions of the availability of solar and wind power will be considered in an optimization formulation
Summary
The engineering discipline does focus on the development of technologies and solutions for practical challenges, but it looks for the most optimal ones. The use of the plug-in hybrid electric vehicles, the use of wind and solar renewable energies, the energy storage and the uncertainty modeling through uncertainty cost functions of the availability of solar and wind power will be considered in an optimization formulation. All this optimization approach is solved using the DEEPSO algorithm, which has obtained recognition because it has been the best algorithm when solving problems regarding optional power-flows an energy management in electric grids [20,21,22,23].
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