Optimal Integration of Photovoltaic Sources in DC Distribution Networks through the Application of The Modified Arithmetic Optimization Algorithm
Abstract
This paper addresses the problem regarding the optimal siting and sizing of photovoltaic (PV) generators in direct current (DC) networks, with the purpose of minimizing the network’s investment and operation costs assumed by the energy distribution company for a planning horizon of 20 years. This problem is presented by means of a mixed-integer nonlinear programming (MINLP) mathematical model, which is solved by implementing a master-slave optimization methodology. The master stage corresponds to an improved version of the arithmetic optimization algorithm, which includes a solution space exploration and exploitation phase that involves generating new solutions based on applying Gaussian distribution functions around the current in each iteration t. The slave stage employs a power flow algorithm specialized for DC grids, which allows evaluating each possible solution obtained in the master stage with regard to PV generator siting (nodes) and sizing, as well as verifying that all constraints associated with the MINLP model are fulfilled. The main result of this research corresponds to an improved methodology that is based on combining the arithmetic optimization algorithm and the Gaussian distribution functions in order to improve the solution space exploration and exploitation phases and find solutions with better quality than those reported in the specialized literature. In conclusion, the numerical results obtained in the IEEE 33- and IEEE 69-node test systems demonstrated that the proposed optimization algorithm improved the results of the specialized literature with regard to the location and sizing of PV sources in DC distribution systems, which sets a new point of reference for future research on this subject.
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