Integración óptima de generadores fotovoltaicos en sistemas de distribución DC a través de la aplicación del algoritmo de optimización aritmética modificado

Abstract

The reduction of the annual installing and operating cost of PV sources for distribution networks will allow generating economically viable projects. In this research is proposed a solution methodology to place and size PV sources in direct current (DC) distribution networks. An objective function to minimize the total annual operating cost for a planning horizon of 2 decades is formulated. Is formed by adding the annual cost of purchasing energy at the substation and the cost of investment and annual maintenance of the PVs. Therefore, the mixed-integer nonlinear programming model (MINLP) emerges as an alternative to represent the optimization problem analyzed. This MINLP model is solved by applying a master-slave methodology. The master stage is a modified version of the arithmetic optimization algorithm, which includes an exploration and exploitation phase where the best current solution 𝓍𝑡𝑏𝑒𝑠𝑡 is obtained at each iteration 𝑡 and modified by implementing a Gaussian distribution operator that generates new candidate solutions with center at the best current solution 𝓍𝑡𝑏𝑒𝑠𝑡. The slave stage uses a specialized DC power flow approach to determine the value of the objective function for each solution provided by the master stage. The algorithm was programmed in MATLAB software, considering IEEE distribution networks of 33 nodes and 69 nodes. These test feeders corroborated that the proposed method represents a significant improvement over metaheuristic optimizers such as the discrete-continuous vortex algorithm and the original arithmetic optimization algorithm.