Modelo de optimización para la gestión colectiva de la demanda de energía en hogares inteligentes

Power systems are evolving towards smart grids to improve their efficiency and reliability through demand response and management strategies. This study presents the Multi-User Model of Controllable Electric Loads (MUMCEL), an optimization model developed to collectively manage the residential demand of multiple users, through Controllable Electric Load Scheduling (CELS). The objective of the model was to minimize the cost of energy and achieve a more uniform distribution of the electric load, taking into account dynamic pricing rates and specific constraints. The methodology was based on classical optimization techniques in two stages. The first stage focused on the single user level using the exhaustive search method to select solutions that minimize the cost of each user's bill. The second stage employed the local search method for multi-user optimization to find a flatter demand curve. For this purpose, an algorithm was designed in MATLAB® that simulated a scenario with 60 users for 24 hours, scheduling the most appropriate on/off periods of controllable loads. Two scenarios were compared: one where users manage their loads at their convenience and the other where the proposed model was applied. The results indicated a decrease in peak demand, with an average savings of 4.94 % on the electricity bill for all users and up to 12.34 % individually. The simulation achieved this optimal solution in 25 minutes, despite the computational complexity involved in managing the demand of 60 users. Therefore, the model used simple methods to optimize multiple variables, providing better performance compared to processing that would require a more complex algorithm. Los sistemas eléctricos están evolucionando hacia redes inteligentes para mejorar su eficiencia y confiabilidad mediante estrategias de gestión y respuesta a la demanda. Este estudio presenta el Modelo Multiusuario de Cargas Eléctricas Controlables (MMCEC), un modelo de optimización desarrollado para gestionar colectivamente la demanda residencial de múltiples usuarios mediante la Programación de Cargas Eléctricas Controlables (PCEC). El objetivo del modelo fue minimizar el costo de la energía y lograr una distribución más uniforme de la carga eléctrica, teniendo en cuenta tarifas dinámicas de precios y restricciones específicas. La metodología se basó en técnicas clásicas de optimización en dos etapas. La primera se enfocó a nivel de único usuario utilizando el método de búsqueda exhaustiva para selecci