Sistema de gestión de energía para bancos de baterías en redes distribución activas empleando el algoritmo de optimización aritmética

Abstract

The issue of energy management in battery banks installed in active distribution networks, whether operating in isolation or connected to the grid, is the focus of this thesis. The goal is to improve financial, technical, and environmental indicators. To achieve this, a mathematical model was formulated with the objective functions of optimizing the network's operational costs, minimizing energy losses associated with energy transport, and reducing carbon dioxide (CO2) emissions related to energy generation. The mathematical model also considers a set of constraints involved in the operation of an active distribution network in an environment with distributed energy resources (battery storage systems and photovoltaic generators). A master-slave strategy was proposed as the solution methodology, combining the arithmetic optimization algorithm (AOA) and an hourly successive approximation power flow method (HSAPF). To create test scenarios, two test systems with 27 and 33 nodes documented in specialized literature were adapted to an isolated network and a distribution network connected to the local grid, using generation and demand data from an average day of operation in Capurganá-Chocó (Rural) and Medellín-Antioquia (Urban). Regarding distributed energy devices, the integration of three different types of lithium-ion batteries and three photovoltaic generators distributed across the electrical networks was considered. Additionally, the energy production costs and CO2 emissions from diesel fuel in Colombia and the local grid were determined, as well as the maintenance costs associated with the photovoltaic distributed generators and the batteries. To validate the effectiveness of the proposed method in terms of solution quality, repeatability, and processing times, three comparison methods (PPSO, PVSA and PALO) reported in the specialized literature were used to solve the problem addressed in this work. In the test networks studied, the proposed solution method achieved the best results in terms of solution quality, repeatability, and competitive processing times compared to the other methods.