Load control and management strategy for a microgrid by a genetic algorithm

Abstract

This research project proposes to develop a strategy for the energy management of a microgrid, known as Energy Management System (EMS), using a genetic algorithm. The energy management problem in a microgrid is related to the determination of the optimum (or near optimum) operation point of the distributed generation systems available to meet the operation requirement of the system. Within the common goals in operating a microrede, either isolated or connected to the main grid, must ensure compliance with energy demand while minimizing operating costs by reducing the energy extracted from the main grid and limiting the use of fossil fuels.In a microgrid by incorporating several distributed generations units, storage units and different types of consumption (loads), which can apply different control strategies, requires a centralized system that carries out the management and control of its operation, to ensure its optimum performance. This management unit is a system that predicts the microgrid's operation by sending the operating points of the generation and the amount of energy required in each moment, defining electrical parameters such as voltage and current for micro-generation systems, at the same time that ensures stability, voltage and frequency regulation, as well as reliability of supply demand.The main motivations for the study of these systems focus on the development of microgrids, which can be considered as emerging technologies which can ensure the future supply of energy and reduce the impact of the electricity generation in nature, while making use of renewable energy sources. On the other hand, microgrids can represent a solution for energy supply to non-interconnected zones in the country-side, because they are composed of systems that integrate different sources of distributed generation making use of renewable energy, emerge as a viable and sustainable solution, reducing costs in populations which depends of generation based on fossil fuels.Considering the number of recent publications related to this topic, it can be observed that the development of systems for energy management in microgrids has taken special interest in the scientific community lately, leading to the implementation of Intelligent Management Systems Demand (IDSME), responsible for the management of electricity and other sources (heating, water, fuel) in a microgrid with a multi-generation topology. Moreover, as the EMS aims to reduce grid energy consumption to the minimum, this will allow the development of new strategies to reduce peak demand, improving the quality of delivered power. In future, these systems will fulfill the function to optimize operation of the demand for electricity, heating and water supply, among other sources, complying with the objectives of minimizing costs and increasing efficiency.It is possible to consider the microgrid's operation as an optimization problem with multiple objectives, where the EMS should ensure local supplies, minimize economic factors of operation and maintenance (O&M), minimize the environmental impact of the operation (emissions, noise, waste), while limiting the maximum energy that is taken from the main grid and reducing transient periods of stabilization system, in the event of a service interruption. The development of an energy management system for microgrids formed by several distributed systems generation will be a first step towards the integration of microgrids in the current electrical system, without affecting its operation or require major changes in its architecture or operation.