Aportaciones a la gestión óptima de los recursos de generación y almacenamiento en microrredes eléctricas

Resumen

The energy sector is transitioning from a centralized grid, comprised of large, controllable power plants, to a decentralized grid based on increased penetration of Distributed Energy Resources. This change towards a more sustainable model poses new technological challenges, associated with the intermittency of renewable energy sources affected by weather conditions, which makes them difficult to manage, and with negative impacts on the electrical network such as variation in magnitude supply voltage and increased imbalances in voltage and currents, among others. Within this context, microgrids provide a key solution for integrating renewable energy sources, controllable energy resources, flexible loads, and storage systems in grid-connected or isolated mode. Optimal energy management is crucial in developing strategies to improve the efficiency and reliability of these small electrical power systems. The main scientific contribution of this research work is to propose a methodology to optimally manage the energy of a microgrid using the Unit Commitment problem, in a stochastic environment, taking into account errors in the demand prediction. This Thesis provides two algorithms, one using mixed integer linear programming (MILP) and the other with a meta-heuristic approach, in this case, a genetic algorithm (AG). Both algorithms solve an objective function that is formulated to minimize the total cost of operating a microgrid, while satisfying technical, economic and environmental constraints. In particular, they consider the spinning reserve of controllable units capable of covering the error in estimating demand by 99.73%, which guarantees the reliability of the operation of the island microgrid. These algorithms are validated in a microgrid consisting of a diesel generator and a microturbine as controlled units, a wind turbine and a photovoltaic plant as uncontrolled renewable energy sources and a battery energy storage system. As a result of the research carried out, two articles were published in journals indexed in JCR, which have been used to write the Thesis as a compendium of articles.