Title A Hybrid Approach Based on SOCP and the Discrete Version of the SCA for Optimal Placement and Sizing DGs in AC Distribution Networks
Authors Montoya, Oscar Danilo , Molina-Cabrera, Alexander , Chamorro, Harold R. , ALVARADO BARRIOS, LÁZARO, Rivas-Trujillo, Edwin
External publication No
Means Electronics (Switzerland)
Scope Article
Nature Científica
JCR Quartile 3
SJR Quartile 2
JCR Impact 2.69000
SJR Impact 0.59000
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098797282&doi=10.3390%2felectronics10010026&partnerID=40&md5=fd53554e65bab306df1c4e26a227716b
Publication date 01/01/2021
ISI 000605924500001
Scopus Id 2-s2.0-85098797282
DOI 10.3390/electronics10010026
Abstract This paper deals with the problem of the optimal placement and sizing of distributed generators (DGs) in alternating current (AC) distribution networks by proposing a hybrid master-slave optimization procedure. In the master stage, the discrete version of the sine-cosine algorithm (SCA) determines the optimal location of the DGs, i.e., the nodes where these must be located, by using an integer codification. In the slave stage, the problem of the optimal sizing of the DGs is solved through the implementation of the second-order cone programming (SOCP) equivalent model to obtain solutions for the resulting optimal power flow problem. As the main advantage, the proposed approach allows converting the original mixed-integer nonlinear programming formulation into a mixed-integer SOCP equivalent. That is, each combination of nodes provided by the master level SCA algorithm to locate distributed generators brings an optimal solution in terms of its sizing; since SOCP is a convex optimization model that ensures the global optimum finding. Numerical validations of the proposed hybrid SCA-SOCP to optimal placement and sizing of DGs in AC distribution networks show its capacity to find global optimal solutions. Some classical distribution networks (33 and 69 nodes) were tested, and some comparisons were made using reported results from literature. In addition, simulation cases with unity and variable power factor are made, including the possibility of locating photovoltaic sources considering daily load and generation curves. All the simulations were carried out in the MATLAB software using the CVX optimization tool.
Keywords distributed generation; mixed-integer nonlinear programming; optimal power flow; second-cone programming; discrete-sine cosine algorithm; metaheuristic optimization
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