Optimal Commissioning of Power Plant Units by Including an Energy Storage System and Demand-Side Program Using a Hybrid Bacterial Foraging and Honey Bee Optimization Method
Unit commitment (UC) programming is a critical task in power system operations, which faces problems such as uncertainty in generation and loads with the significant rise in the generation of electrical energy through renewable energy sources (RES) such as wind and responsive load programs. The prob...
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2022-10-01
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| Series: | Advances in Engineering and Intelligence Systems |
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| Online Access: | https://aeis.bilijipub.com/article_158303_4eeface6c0213d34683ba287f63be065.pdf |
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| author | Afshar Shokri Hamid Shakibi Behrooz Sobhani |
| author_facet | Afshar Shokri Hamid Shakibi Behrooz Sobhani |
| author_sort | Afshar Shokri |
| collection | DOAJ |
| description | Unit commitment (UC) programming is a critical task in power system operations, which faces problems such as uncertainty in generation and loads with the significant rise in the generation of electrical energy through renewable energy sources (RES) such as wind and responsive load programs. The problem of UC, or the unit commissioning problem, is a major optimization problem, the exact solution of which can lead to a significant reduction in costs. In this article, smart grids are considered which aim to reduce costs and environmental problems. Thus, this paper solves the UC problem in smart grids by considering the emission of generation units, resulting in a multi-objective function for minimization. With the introduction of smart grids, energy storage systems (ESS) have also been considered in the grid. This paper proposes the optimal charging and discharging of ESS. Another problem modeled in this article is that of demand response (DR) in smart grids. To validate the performance of the proposed model, it is tested on a 4-unit system with ESS and the results show its optimal performance. To solve the problem of UC programming, a hybrid honey bee mating and bacterial foraging algorithm are used to reduce the complexity of the problem and achieve optimal results. |
| format | Article |
| id | doaj-art-dd004890ab244ee29999f5d5695f6c77 |
| institution | Kabale University |
| issn | 2821-0263 |
| language | English |
| publishDate | 2022-10-01 |
| publisher | Bilijipub publisher |
| record_format | Article |
| series | Advances in Engineering and Intelligence Systems |
| spelling | doaj-art-dd004890ab244ee29999f5d5695f6c772025-02-12T08:46:30ZengBilijipub publisherAdvances in Engineering and Intelligence Systems2821-02632022-10-0100103546510.22034/aeis.2022.359515.1039158303Optimal Commissioning of Power Plant Units by Including an Energy Storage System and Demand-Side Program Using a Hybrid Bacterial Foraging and Honey Bee Optimization MethodAfshar Shokri0Hamid Shakibi1Behrooz Sobhani2Department of Mechanical Engineering, Iran University of Science and Technology (IUST), Tehran, 1684613114, IranDepartment of Mechanical Engineering, Faculty of Engineering, Urmia University, Urmia, 5756151818, IranDepartment of Electrical Engineering, University of Mohaghegh Ardabili, Ardabil, 5619911367, IranUnit commitment (UC) programming is a critical task in power system operations, which faces problems such as uncertainty in generation and loads with the significant rise in the generation of electrical energy through renewable energy sources (RES) such as wind and responsive load programs. The problem of UC, or the unit commissioning problem, is a major optimization problem, the exact solution of which can lead to a significant reduction in costs. In this article, smart grids are considered which aim to reduce costs and environmental problems. Thus, this paper solves the UC problem in smart grids by considering the emission of generation units, resulting in a multi-objective function for minimization. With the introduction of smart grids, energy storage systems (ESS) have also been considered in the grid. This paper proposes the optimal charging and discharging of ESS. Another problem modeled in this article is that of demand response (DR) in smart grids. To validate the performance of the proposed model, it is tested on a 4-unit system with ESS and the results show its optimal performance. To solve the problem of UC programming, a hybrid honey bee mating and bacterial foraging algorithm are used to reduce the complexity of the problem and achieve optimal results.https://aeis.bilijipub.com/article_158303_4eeface6c0213d34683ba287f63be065.pdfunit commitment programenergy storagerenewable energy resourcesmart griddemand side management |
| spellingShingle | Afshar Shokri Hamid Shakibi Behrooz Sobhani Optimal Commissioning of Power Plant Units by Including an Energy Storage System and Demand-Side Program Using a Hybrid Bacterial Foraging and Honey Bee Optimization Method Advances in Engineering and Intelligence Systems unit commitment program energy storage renewable energy resource smart grid demand side management |
| title | Optimal Commissioning of Power Plant Units by Including an Energy Storage System and Demand-Side Program Using a Hybrid Bacterial Foraging and Honey Bee Optimization Method |
| title_full | Optimal Commissioning of Power Plant Units by Including an Energy Storage System and Demand-Side Program Using a Hybrid Bacterial Foraging and Honey Bee Optimization Method |
| title_fullStr | Optimal Commissioning of Power Plant Units by Including an Energy Storage System and Demand-Side Program Using a Hybrid Bacterial Foraging and Honey Bee Optimization Method |
| title_full_unstemmed | Optimal Commissioning of Power Plant Units by Including an Energy Storage System and Demand-Side Program Using a Hybrid Bacterial Foraging and Honey Bee Optimization Method |
| title_short | Optimal Commissioning of Power Plant Units by Including an Energy Storage System and Demand-Side Program Using a Hybrid Bacterial Foraging and Honey Bee Optimization Method |
| title_sort | optimal commissioning of power plant units by including an energy storage system and demand side program using a hybrid bacterial foraging and honey bee optimization method |
| topic | unit commitment program energy storage renewable energy resource smart grid demand side management |
| url | https://aeis.bilijipub.com/article_158303_4eeface6c0213d34683ba287f63be065.pdf |
| work_keys_str_mv | AT afsharshokri optimalcommissioningofpowerplantunitsbyincludinganenergystoragesystemanddemandsideprogramusingahybridbacterialforagingandhoneybeeoptimizationmethod AT hamidshakibi optimalcommissioningofpowerplantunitsbyincludinganenergystoragesystemanddemandsideprogramusingahybridbacterialforagingandhoneybeeoptimizationmethod AT behroozsobhani optimalcommissioningofpowerplantunitsbyincludinganenergystoragesystemanddemandsideprogramusingahybridbacterialforagingandhoneybeeoptimizationmethod |