Designing Multi-Objective Optimization Model of Electricity Market Portfolio for Industrial Consumptions under Uncertainty
In deregulated electricity markets, the electricity consumer should distribute his required electricity optimally between different markets including spots markets with instantaneous price and bilateral contract markets. The present study is aimed to design a model for selecting the optimal electric...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Amirkabir University of Technology
2021-12-01
|
| Series: | AUT Journal of Electrical Engineering |
| Subjects: | |
| Online Access: | https://eej.aut.ac.ir/article_4395_9ed5fec5e5dfb7724428b812b9241d4c.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849434108662382592 |
|---|---|
| author | Saeed Khalili Ebrahim Abbasi Bardia Behnia Mohammad Amirkhan |
| author_facet | Saeed Khalili Ebrahim Abbasi Bardia Behnia Mohammad Amirkhan |
| author_sort | Saeed Khalili |
| collection | DOAJ |
| description | In deregulated electricity markets, the electricity consumer should distribute his required electricity optimally between different markets including spots markets with instantaneous price and bilateral contract markets. The present study is aimed to design a model for selecting the optimal electricity market portfolio, so the purchase costs can be minimized by considering a risk level. For this purpose, an optimization approach based on random planning was proposed to minimize costs and reduce power supply risk. Conditional value at risk was used as an appropriate and well-known factor for reducing unfavorable situations in decision-making under uncertain conditions. For simulations, the real information of Iran in 2018 was used as much as possible. Due to the small number of industrial subscribers, the whole population was studied. A genetic algorithm has been used to solve this optimization problem. In addition, MATLAB software was used for implementing the proposed model. The efficiency of the proposed model was proved by analyzing different sensitivities and the best components of the risk-averse decision-making purchasing portfolio in β=5 included from the energy exchange, then from the energy pool, and finally from bilateral contracts. |
| format | Article |
| id | doaj-art-0b806f07c3fc46c0891d7955f8af91a3 |
| institution | Kabale University |
| issn | 2588-2910 2588-2929 |
| language | English |
| publishDate | 2021-12-01 |
| publisher | Amirkabir University of Technology |
| record_format | Article |
| series | AUT Journal of Electrical Engineering |
| spelling | doaj-art-0b806f07c3fc46c0891d7955f8af91a32025-08-20T03:26:48ZengAmirkabir University of TechnologyAUT Journal of Electrical Engineering2588-29102588-29292021-12-0153217118810.22060/eej.2021.19236.53874395Designing Multi-Objective Optimization Model of Electricity Market Portfolio for Industrial Consumptions under UncertaintySaeed Khalili0Ebrahim Abbasi1Bardia Behnia2Mohammad Amirkhan3Department of Industrial Management, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, IranAssociate professor at Alzahra University Tehran, IranDepartment of Industrial Engineering and Management, Rouzbahan Institute of Higher Education, Sari, IranDepartment of Industrial Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, IranIn deregulated electricity markets, the electricity consumer should distribute his required electricity optimally between different markets including spots markets with instantaneous price and bilateral contract markets. The present study is aimed to design a model for selecting the optimal electricity market portfolio, so the purchase costs can be minimized by considering a risk level. For this purpose, an optimization approach based on random planning was proposed to minimize costs and reduce power supply risk. Conditional value at risk was used as an appropriate and well-known factor for reducing unfavorable situations in decision-making under uncertain conditions. For simulations, the real information of Iran in 2018 was used as much as possible. Due to the small number of industrial subscribers, the whole population was studied. A genetic algorithm has been used to solve this optimization problem. In addition, MATLAB software was used for implementing the proposed model. The efficiency of the proposed model was proved by analyzing different sensitivities and the best components of the risk-averse decision-making purchasing portfolio in β=5 included from the energy exchange, then from the energy pool, and finally from bilateral contracts.https://eej.aut.ac.ir/article_4395_9ed5fec5e5dfb7724428b812b9241d4c.pdfportfolio optimizationelectricity energy marketuncertaintystochastic optimizationconditional value at risk |
| spellingShingle | Saeed Khalili Ebrahim Abbasi Bardia Behnia Mohammad Amirkhan Designing Multi-Objective Optimization Model of Electricity Market Portfolio for Industrial Consumptions under Uncertainty AUT Journal of Electrical Engineering portfolio optimization electricity energy market uncertainty stochastic optimization conditional value at risk |
| title | Designing Multi-Objective Optimization Model of Electricity Market Portfolio for Industrial Consumptions under Uncertainty |
| title_full | Designing Multi-Objective Optimization Model of Electricity Market Portfolio for Industrial Consumptions under Uncertainty |
| title_fullStr | Designing Multi-Objective Optimization Model of Electricity Market Portfolio for Industrial Consumptions under Uncertainty |
| title_full_unstemmed | Designing Multi-Objective Optimization Model of Electricity Market Portfolio for Industrial Consumptions under Uncertainty |
| title_short | Designing Multi-Objective Optimization Model of Electricity Market Portfolio for Industrial Consumptions under Uncertainty |
| title_sort | designing multi objective optimization model of electricity market portfolio for industrial consumptions under uncertainty |
| topic | portfolio optimization electricity energy market uncertainty stochastic optimization conditional value at risk |
| url | https://eej.aut.ac.ir/article_4395_9ed5fec5e5dfb7724428b812b9241d4c.pdf |
| work_keys_str_mv | AT saeedkhalili designingmultiobjectiveoptimizationmodelofelectricitymarketportfolioforindustrialconsumptionsunderuncertainty AT ebrahimabbasi designingmultiobjectiveoptimizationmodelofelectricitymarketportfolioforindustrialconsumptionsunderuncertainty AT bardiabehnia designingmultiobjectiveoptimizationmodelofelectricitymarketportfolioforindustrialconsumptionsunderuncertainty AT mohammadamirkhan designingmultiobjectiveoptimizationmodelofelectricitymarketportfolioforindustrialconsumptionsunderuncertainty |