Modeling solar power plant electricity supply chain toward renewable energy consumption

This paper aims to introduce a model of the solar plant electricity supply chain, encompassing mixed power plants, transmission lines, and consumers, with a focus on optimization and consideration of uncertainties. Within this article, the supply chain of solar power plants is delineated based on va...

Full description

Saved in:
Bibliographic Details
Main Authors: Mohammad Reza Eslami Rasekh, Farzad Mohammad Sharifi, Somaieh Alavi, Nassibeh Janatyan
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:e-Prime: Advances in Electrical Engineering, Electronics and Energy
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2772671125000142
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832583002355400704
author Mohammad Reza Eslami Rasekh
Farzad Mohammad Sharifi
Somaieh Alavi
Nassibeh Janatyan
author_facet Mohammad Reza Eslami Rasekh
Farzad Mohammad Sharifi
Somaieh Alavi
Nassibeh Janatyan
author_sort Mohammad Reza Eslami Rasekh
collection DOAJ
description This paper aims to introduce a model of the solar plant electricity supply chain, encompassing mixed power plants, transmission lines, and consumers, with a focus on optimization and consideration of uncertainties. Within this article, the supply chain of solar power plants is delineated based on various parameters. The quantities of power plants and solar panels are determined by different priorities, such as investment levels, pollution mitigation, and reduction of gas consumption by conventional power plants, utilizing the particle swarm algorithm for optimal outcomes. The proposed model addresses uncertainties related to electricity demand, solar radiation levels, and consequently, the power production of solar panels, through the application of type 2 fuzzy logic. The optimization of the model is done keeping in mind various constraints including the supply of electricity and the maximum allowed use of solar cells. The innovation of this article is in the design of the supply chain model from the point of view of the uncertainty of electric power production and the amount of consumer demand and the optimal selection of solar panels for solar power plants to minimize the electricity consumption of the gas power plant and the amount of pollution caused by it. Based on the results obtained from the simulation of this article, it has been shown that considering the maximum investment capacity, up to 76 % of the electric energy can be supplied by building five solar power plants at certain distances from the electric substations around the case study. Considering the maximum weight coefficients for CO2 plant emissions and gas consumption, five solar power plants are the optimal number that is achieved by proposed algorithm. The power capacity of five solar power plants is optimized 4.100,4.222,3.920,4.375and 3.991MW, respectively. To evaluation of the proposed model, PSO algorithm is compared to GA and the results show that cost function and convergence time in PSO is less than GA in the various weight coefficients scenarios. This optimal mode leads to the maximum reduction of gas consumption in the gas power plant, and on the other hand, the amount of pollution is minimized. The prediction of this number of power plants with different priorities is presented in this article and different policies can be considered strategically for this model of the supply chain.
format Article
id doaj-art-1df87dbe45114ad0892b8b12459c1b28
institution Kabale University
issn 2772-6711
language English
publishDate 2025-03-01
publisher Elsevier
record_format Article
series e-Prime: Advances in Electrical Engineering, Electronics and Energy
spelling doaj-art-1df87dbe45114ad0892b8b12459c1b282025-01-29T05:02:47ZengElseviere-Prime: Advances in Electrical Engineering, Electronics and Energy2772-67112025-03-0111100907Modeling solar power plant electricity supply chain toward renewable energy consumptionMohammad Reza Eslami Rasekh0Farzad Mohammad Sharifi1Somaieh Alavi2Nassibeh Janatyan3Department of Management and Industrial Engineering, Foolad Institute of Technology, Foolad shahr, Isfahan, IranUniversity of Isfahan, Department of Electrical Engineering, Isfahan, IranDepartment of Industrial Engineering, Faculty of Engineering and Technology, Shahid Ashrafi Esfahani University, Isfahan, Iran; Corresponding author.Quality management research group, Management institute, University of Isfahan, Isfahan, IranThis paper aims to introduce a model of the solar plant electricity supply chain, encompassing mixed power plants, transmission lines, and consumers, with a focus on optimization and consideration of uncertainties. Within this article, the supply chain of solar power plants is delineated based on various parameters. The quantities of power plants and solar panels are determined by different priorities, such as investment levels, pollution mitigation, and reduction of gas consumption by conventional power plants, utilizing the particle swarm algorithm for optimal outcomes. The proposed model addresses uncertainties related to electricity demand, solar radiation levels, and consequently, the power production of solar panels, through the application of type 2 fuzzy logic. The optimization of the model is done keeping in mind various constraints including the supply of electricity and the maximum allowed use of solar cells. The innovation of this article is in the design of the supply chain model from the point of view of the uncertainty of electric power production and the amount of consumer demand and the optimal selection of solar panels for solar power plants to minimize the electricity consumption of the gas power plant and the amount of pollution caused by it. Based on the results obtained from the simulation of this article, it has been shown that considering the maximum investment capacity, up to 76 % of the electric energy can be supplied by building five solar power plants at certain distances from the electric substations around the case study. Considering the maximum weight coefficients for CO2 plant emissions and gas consumption, five solar power plants are the optimal number that is achieved by proposed algorithm. The power capacity of five solar power plants is optimized 4.100,4.222,3.920,4.375and 3.991MW, respectively. To evaluation of the proposed model, PSO algorithm is compared to GA and the results show that cost function and convergence time in PSO is less than GA in the various weight coefficients scenarios. This optimal mode leads to the maximum reduction of gas consumption in the gas power plant, and on the other hand, the amount of pollution is minimized. The prediction of this number of power plants with different priorities is presented in this article and different policies can be considered strategically for this model of the supply chain.http://www.sciencedirect.com/science/article/pii/S2772671125000142Supply chainSolar power plantOptimizationUncertaintyType 2 fuzzy logicParticle swarm algorithm (PSO)
spellingShingle Mohammad Reza Eslami Rasekh
Farzad Mohammad Sharifi
Somaieh Alavi
Nassibeh Janatyan
Modeling solar power plant electricity supply chain toward renewable energy consumption
e-Prime: Advances in Electrical Engineering, Electronics and Energy
Supply chain
Solar power plant
Optimization
Uncertainty
Type 2 fuzzy logic
Particle swarm algorithm (PSO)
title Modeling solar power plant electricity supply chain toward renewable energy consumption
title_full Modeling solar power plant electricity supply chain toward renewable energy consumption
title_fullStr Modeling solar power plant electricity supply chain toward renewable energy consumption
title_full_unstemmed Modeling solar power plant electricity supply chain toward renewable energy consumption
title_short Modeling solar power plant electricity supply chain toward renewable energy consumption
title_sort modeling solar power plant electricity supply chain toward renewable energy consumption
topic Supply chain
Solar power plant
Optimization
Uncertainty
Type 2 fuzzy logic
Particle swarm algorithm (PSO)
url http://www.sciencedirect.com/science/article/pii/S2772671125000142
work_keys_str_mv AT mohammadrezaeslamirasekh modelingsolarpowerplantelectricitysupplychaintowardrenewableenergyconsumption
AT farzadmohammadsharifi modelingsolarpowerplantelectricitysupplychaintowardrenewableenergyconsumption
AT somaiehalavi modelingsolarpowerplantelectricitysupplychaintowardrenewableenergyconsumption
AT nassibehjanatyan modelingsolarpowerplantelectricitysupplychaintowardrenewableenergyconsumption