Efficient integration of PV sources in distribution networks to reduce annual investment and operating costs using the modified arithmetic optimization algorithm

The optimal integration of photovoltaic generation systems is a challenge for distribution utilities since these devices have a direct impact on company finances due to the large amount of investment required at the beginning of the planning project. In this investigation, the problem regarding the...

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Autores: Montoya, Oscar Danilo, Giral-Ramírez, Diego Armando, Hernández, Jesus C.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Universidad de Jaén
Repositorio:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
OAI Identifier:oai:ruja.ujaen.es:10953/6577
Acceso en línea:https://www.mdpi.com/2079-9292/11/11/1680
https://doi.org/10.3390/electronics11111680
https://hdl.handle.net/10953/6577
Access Level:acceso abierto
Palabra clave:arithmetic optimization algorithm
distribution networks
solar PV generation
cost minimization
master-slave optimization
621.35
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spelling Efficient integration of PV sources in distribution networks to reduce annual investment and operating costs using the modified arithmetic optimization algorithmMontoya, Oscar DaniloGiral-Ramírez, Diego ArmandoHernández, Jesus C.arithmetic optimization algorithmdistribution networkssolar PV generationcost minimizationmaster-slave optimization621.35The optimal integration of photovoltaic generation systems is a challenge for distribution utilities since these devices have a direct impact on company finances due to the large amount of investment required at the beginning of the planning project. In this investigation, the problem regarding the optimal siting and sizing of photovoltaic resources in medium-voltage levels is addressed from an economical point of view, where the optimization model that represents said problem corresponds to a mixed-integer nonlinear programming model. The maximum allowed size for single photovoltaic units in the distribution network is set at 2400 kW. The investment costs, energy purchase costs and maintenance costs for photovoltaic units, are considered in the objective function. Typical constraints such as power balance, generation capacities, voltage regulation, among others, are considered in the mathematical formulation. The solution of the optimization model is addressed by implementing a modified version of the Arithmetic Optimization Algorithm, which includes a new exploration and exploitation characteristic based on the best current solution in iteration t, i.e., best. This improvement is based on a Gaussian distribution operator that generates new candidate solutions with the center at best, which are uniformly distributed. The main contribution of this research is the proposal of a new hybrid optimization algorithm to solve the exact optimization model, which is based on a combination of the Arithmetic Optimization algorithm with the Vortex Search algorithm and showed excellent numerical results in the IEEE 34-bus grid. The analysis of quantitative results allows us to conclude that the strategy proposed in this work has a greater effectiveness with respect to the General Algebraic Modeling System software solvers, as well as with metaheuristic optimizers such as Genetic Algorithms, the Newton–Metaheuristic Algorithm, and the original Arithmetic Optimization Algorithm. MATLAB was used as a simulation tool.MDPI202520252022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://www.mdpi.com/2079-9292/11/11/1680https://doi.org/10.3390/electronics11111680https://hdl.handle.net/10953/6577reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaéninstname:Universidad de JaénInglésElectronicsAttribution 3.0 Spainhttp://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:ruja.ujaen.es:10953/65772026-06-24T12:41:07Z
dc.title.none.fl_str_mv Efficient integration of PV sources in distribution networks to reduce annual investment and operating costs using the modified arithmetic optimization algorithm
title Efficient integration of PV sources in distribution networks to reduce annual investment and operating costs using the modified arithmetic optimization algorithm
spellingShingle Efficient integration of PV sources in distribution networks to reduce annual investment and operating costs using the modified arithmetic optimization algorithm
Montoya, Oscar Danilo
arithmetic optimization algorithm
distribution networks
solar PV generation
cost minimization
master-slave optimization
621.35
title_short Efficient integration of PV sources in distribution networks to reduce annual investment and operating costs using the modified arithmetic optimization algorithm
title_full Efficient integration of PV sources in distribution networks to reduce annual investment and operating costs using the modified arithmetic optimization algorithm
title_fullStr Efficient integration of PV sources in distribution networks to reduce annual investment and operating costs using the modified arithmetic optimization algorithm
title_full_unstemmed Efficient integration of PV sources in distribution networks to reduce annual investment and operating costs using the modified arithmetic optimization algorithm
title_sort Efficient integration of PV sources in distribution networks to reduce annual investment and operating costs using the modified arithmetic optimization algorithm
dc.creator.none.fl_str_mv Montoya, Oscar Danilo
Giral-Ramírez, Diego Armando
Hernández, Jesus C.
author Montoya, Oscar Danilo
author_facet Montoya, Oscar Danilo
Giral-Ramírez, Diego Armando
Hernández, Jesus C.
author_role author
author2 Giral-Ramírez, Diego Armando
Hernández, Jesus C.
author2_role author
author
dc.subject.none.fl_str_mv arithmetic optimization algorithm
distribution networks
solar PV generation
cost minimization
master-slave optimization
621.35
topic arithmetic optimization algorithm
distribution networks
solar PV generation
cost minimization
master-slave optimization
621.35
description The optimal integration of photovoltaic generation systems is a challenge for distribution utilities since these devices have a direct impact on company finances due to the large amount of investment required at the beginning of the planning project. In this investigation, the problem regarding the optimal siting and sizing of photovoltaic resources in medium-voltage levels is addressed from an economical point of view, where the optimization model that represents said problem corresponds to a mixed-integer nonlinear programming model. The maximum allowed size for single photovoltaic units in the distribution network is set at 2400 kW. The investment costs, energy purchase costs and maintenance costs for photovoltaic units, are considered in the objective function. Typical constraints such as power balance, generation capacities, voltage regulation, among others, are considered in the mathematical formulation. The solution of the optimization model is addressed by implementing a modified version of the Arithmetic Optimization Algorithm, which includes a new exploration and exploitation characteristic based on the best current solution in iteration t, i.e., best. This improvement is based on a Gaussian distribution operator that generates new candidate solutions with the center at best, which are uniformly distributed. The main contribution of this research is the proposal of a new hybrid optimization algorithm to solve the exact optimization model, which is based on a combination of the Arithmetic Optimization algorithm with the Vortex Search algorithm and showed excellent numerical results in the IEEE 34-bus grid. The analysis of quantitative results allows us to conclude that the strategy proposed in this work has a greater effectiveness with respect to the General Algebraic Modeling System software solvers, as well as with metaheuristic optimizers such as Genetic Algorithms, the Newton–Metaheuristic Algorithm, and the original Arithmetic Optimization Algorithm. MATLAB was used as a simulation tool.
publishDate 2022
dc.date.none.fl_str_mv 2022
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://www.mdpi.com/2079-9292/11/11/1680
https://doi.org/10.3390/electronics11111680
https://hdl.handle.net/10953/6577
url https://www.mdpi.com/2079-9292/11/11/1680
https://doi.org/10.3390/electronics11111680
https://hdl.handle.net/10953/6577
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Electronics
dc.rights.none.fl_str_mv Attribution 3.0 Spain
http://creativecommons.org/licenses/by/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution 3.0 Spain
http://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
instname:Universidad de Jaén
instname_str Universidad de Jaén
reponame_str RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
collection RUJA. Repositorio Institucional de la Producción Científica de la Universidad de Jaén
repository.name.fl_str_mv
repository.mail.fl_str_mv
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