Optimizing day-ahead power scheduling: A novel MIQCP approach for enhanced SCUC with renewable integration
•This paper introduces an innovative methodology aimed at enhancing day-ahead power system scheduling by incorporating adaptable technologies within the framework of security-constrained unit commitment.•The main objective is to reducing operational expenses linked to energy storage systems, demand...
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| Abstract | •This paper introduces an innovative methodology aimed at enhancing day-ahead power system scheduling by incorporating adaptable technologies within the framework of security-constrained unit commitment.•The main objective is to reducing operational expenses linked to energy storage systems, demand response initiatives, solar power curtailment, and load shedding.•a mixed-integer quadratically-constrained programming model, which guarantees globally optimal solutions for intricate, real-world applications.•Results highlights the model's effectiveness in improving operational efficiency and cost savings for power systems with high renewable energy penetration, establishing it as an essential tool for sustainable management of power systems.
This paper introduces an innovative methodology aimed at enhancing day-ahead power system scheduling by incorporating adaptable technologies within the framework of security-constrained unit commitment. The methodology is tailored for power systems characterized by significant integration of photovoltaic energy, with the goal of reducing operational expenses linked to energy storage systems, demand response initiatives, solar power curtailment, and load shedding. The scheduling issue is structured as a mixed-integer quadratically-constrained programming model, which guarantees globally optimal solutions for intricate, real-world applications. The developed model has been implemented using the GAMS and tested through extensive case studies on the IEEE 24-bus system. The findings reveal that the strategic coordination of flexible resources leads to a 5.6 % reduction in scheduling costs compared to traditional methods. This result highlights the model's effectiveness in improving operational efficiency and cost savings for power systems with high renewable energy penetration, establishing it as an essential tool for sustainable management of power systems. |
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| AbstractList | •This paper introduces an innovative methodology aimed at enhancing day-ahead power system scheduling by incorporating adaptable technologies within the framework of security-constrained unit commitment.•The main objective is to reducing operational expenses linked to energy storage systems, demand response initiatives, solar power curtailment, and load shedding.•a mixed-integer quadratically-constrained programming model, which guarantees globally optimal solutions for intricate, real-world applications.•Results highlights the model's effectiveness in improving operational efficiency and cost savings for power systems with high renewable energy penetration, establishing it as an essential tool for sustainable management of power systems.
This paper introduces an innovative methodology aimed at enhancing day-ahead power system scheduling by incorporating adaptable technologies within the framework of security-constrained unit commitment. The methodology is tailored for power systems characterized by significant integration of photovoltaic energy, with the goal of reducing operational expenses linked to energy storage systems, demand response initiatives, solar power curtailment, and load shedding. The scheduling issue is structured as a mixed-integer quadratically-constrained programming model, which guarantees globally optimal solutions for intricate, real-world applications. The developed model has been implemented using the GAMS and tested through extensive case studies on the IEEE 24-bus system. The findings reveal that the strategic coordination of flexible resources leads to a 5.6 % reduction in scheduling costs compared to traditional methods. This result highlights the model's effectiveness in improving operational efficiency and cost savings for power systems with high renewable energy penetration, establishing it as an essential tool for sustainable management of power systems. This paper introduces an innovative methodology aimed at enhancing day-ahead power system scheduling by incorporating adaptable technologies within the framework of security-constrained unit commitment. The methodology is tailored for power systems characterized by significant integration of photovoltaic energy, with the goal of reducing operational expenses linked to energy storage systems, demand response initiatives, solar power curtailment, and load shedding. The scheduling issue is structured as a mixed-integer quadratically-constrained programming model, which guarantees globally optimal solutions for intricate, real-world applications. The developed model has been implemented using the GAMS and tested through extensive case studies on the IEEE 24-bus system. The findings reveal that the strategic coordination of flexible resources leads to a 5.6 % reduction in scheduling costs compared to traditional methods. This result highlights the model's effectiveness in improving operational efficiency and cost savings for power systems with high renewable energy penetration, establishing it as an essential tool for sustainable management of power systems. |
| ArticleNumber | 101022 |
| Author | Shirini, Kimia Abdollahi, Arya Gharehveran, Sina Samadi Khavar, Selma Cheshmeh |
| Author_xml | – sequence: 1 givenname: Sina Samadi orcidid: 0000-0001-5442-2485 surname: Gharehveran fullname: Gharehveran, Sina Samadi email: s.samadi@tabrizu.ac.ir organization: Department of Computer & Electrical Engineering, Tabriz University, Tabriz, , Iran – sequence: 2 givenname: Kimia surname: Shirini fullname: Shirini, Kimia organization: Department of Computer & Electrical Engineering, Tabriz University, Tabriz, , Iran – sequence: 3 givenname: Selma Cheshmeh surname: Khavar fullname: Khavar, Selma Cheshmeh organization: Department of Electrical Engineering, Amir Kabir University of technology, Tehran, Iran – sequence: 4 givenname: Arya surname: Abdollahi fullname: Abdollahi, Arya organization: Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran |
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| Cites_doi | 10.1007/s11227-024-06407-z 10.1109/TPWRS.2017.2756074 10.1109/TSTE.2018.2806444 10.1016/j.rser.2022.112095 10.1016/j.est.2020.101335 10.1049/iet-rpg.2018.6018 10.1016/j.ijepes.2018.07.013 10.1109/TPWRS.2015.2475700 10.1016/j.ijepes.2020.106473 10.1109/TSTE.2017.2748463 10.1016/j.rser.2013.09.020 10.1016/j.est.2022.106467 10.1016/j.apenergy.2021.117837 10.1016/j.asoc.2021.107243 10.1049/iet-gtd:20080064 10.1007/s10107-018-1337-6 10.1016/j.scs.2022.103952 10.1007/s11227-024-06806-2 10.1016/j.epsr.2024.110856 10.1109/TPWRS.2016.2593422 10.1016/j.ijepes.2014.10.049 10.1049/iet-gtd.2016.0704 10.1016/j.est.2023.108263 10.1049/smt2.12067 10.1049/iet-gtd.2019.0330 10.1016/j.energy.2022.124918 10.1109/59.918295 10.1016/j.ijepes.2016.01.041 10.1007/s11227-024-06385-2 10.1016/j.rser.2017.01.008 10.1016/j.ijepes.2018.04.026 10.1016/j.est.2024.111024 10.1109/TPWRS.2018.2834502 |
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| Keywords | Renewable energy management Security-constrained unit commitment Day-ahead scheduling Mixed-integer quadratically-constrained programming Demand-side management |
| Language | English |
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