Modelo agregador para la gestión de la demanda en grandes consumidores con la inclusión de generación distribuida en sistemas de distribución de energía eléctrica

Abstract

The accelerated technological evolution and the change in energy consumption patterns have led the electricity industry to thoroughly investigate the active management of demand and the generation of distributed renewable resources. This involves evaluating how consumers respond to variations in electricity prices, thus optimizing the technical and economic efficiency of the system. Smart grids technically manage energy and generate data that allows third parties to form technical and financial data management systems. However, demand response programs that lack accurate information about customer strategies are often designed by companies and regulators. This research analyzes demand response programs in developing countries, highlighting the lack of participation of large consumers in creating these programs. An innovative methodology that uses data analytics, optimization and mathematical model techniques to design and evaluate responses to demand is proposed. Order is stratified, considering manageable and non-manageable loads and the renewable distributed generation that large consumers can contribute. It is projected based on electricity market prices. It is resolved through a bi-level optimization approach that maximizes the aggregator's benefits and minimizes the real-time costs of balancing supply and demand. The research evaluates technical and operational constraints from the perspective of the distribution operator, seeking technically viable and profitable decisions for consumers and distributors in a smart grid environment.