Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Algorithm
<p dir="ltr">Coordinated energy scheduling and management strategies in the energy hub plan are essential to achieve optimal economic performance. In this paper, the scheduling and management framework of an energy hub (EH) is presented with the aim of energy profit maximization in p...
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2023
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| author | Ali S. Alghamdi (12722891) |
| author2 | Mohana Alanazi (17541558) Abdulaziz Alanazi (9509776) Yazeed Qasaymeh (17541561) Muhammad Zubair (728141) Ahmed Bilal Awan (17250952) Muhammad Gul Bahar Ashiq (17541564) |
| author2_role | author author author author author author |
| author_facet | Ali S. Alghamdi (12722891) Mohana Alanazi (17541558) Abdulaziz Alanazi (9509776) Yazeed Qasaymeh (17541561) Muhammad Zubair (728141) Ahmed Bilal Awan (17250952) Muhammad Gul Bahar Ashiq (17541564) |
| author_role | author |
| dc.creator.none.fl_str_mv | Ali S. Alghamdi (12722891) Mohana Alanazi (17541558) Abdulaziz Alanazi (9509776) Yazeed Qasaymeh (17541561) Muhammad Zubair (728141) Ahmed Bilal Awan (17250952) Muhammad Gul Bahar Ashiq (17541564) |
| dc.date.none.fl_str_mv | 2023-03-09T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.3390/app13063526 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Energy_Hub_Optimal_Scheduling_and_Management_in_the_Day-Ahead_Market_Considering_Renewable_Energy_Sources_CHP_Electric_Vehicles_and_Storage_Systems_Using_Improved_Fick_s_Law_Algorithm/24717258 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Electrical engineering Electronics, sensors and digital hardware Information and computing sciences Theory of computation optimal energy hub planning scheduled and multi-energy management energy profit improved Fick’s law algorithm Rosenbrock’s direct rotational method |
| dc.title.none.fl_str_mv | Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Algorithm |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Coordinated energy scheduling and management strategies in the energy hub plan are essential to achieve optimal economic performance. In this paper, the scheduling and management framework of an energy hub (EH) is presented with the aim of energy profit maximization in partnership with electricity, natural gas, and district heating networks (EGHNs) considering the coordinated multi-energy management based on the day-ahead market. The optimum capacity of EH equipment, including photovoltaic and wind renewable energy sources, a combined heat and power system (CHP), a boiler, energy storage, and electric vehicles is determined in the day-ahead market using the improved Fick’s law algorithm (IFLA), considering the energy profit maximization and also satisfying the linear network and hub constraints. The conventional FLA is inspired by the concept of Fick’s diffusion law, and, in this study, its performance against premature convergence is improved by using Rosenbrock’s direct rotational method. The performance of the IFLA when applied to EH coordinated scheduling and management problems with the aim of profit maximization is compared with the conventional FLA, particle swarm optimization (PSO), and manta ray foraging optimization (MRFO) methods. The results show that the proposed scheduling and multi-energy management framework achieves more energy profit in the day-ahead electricity, gas, and heating markets by satisfying the operation and EH constraints compared to other methods. Furthermore, according to the findings, the increased (decreased) demand and the forced outage rate caused a decrease (increase) in the EH profit. The results show the effectiveness of the proposed framework to obtain the EH maximum energy profit in the day-ahead market.</p><h2>Other Information</h2><p dir="ltr">Published in: Applied Sciences<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/app13063526" target="_blank">https://dx.doi.org/10.3390/app13063526</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_6a0d0f9b3973616732a86f5b7a2e1171 |
| identifier_str_mv | 10.3390/app13063526 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24717258 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law AlgorithmAli S. Alghamdi (12722891)Mohana Alanazi (17541558)Abdulaziz Alanazi (9509776)Yazeed Qasaymeh (17541561)Muhammad Zubair (728141)Ahmed Bilal Awan (17250952)Muhammad Gul Bahar Ashiq (17541564)EngineeringElectrical engineeringElectronics, sensors and digital hardwareInformation and computing sciencesTheory of computationoptimal energy hub planningscheduled and multi-energy managementenergy profitimproved Fick’s law algorithmRosenbrock’s direct rotational method<p dir="ltr">Coordinated energy scheduling and management strategies in the energy hub plan are essential to achieve optimal economic performance. In this paper, the scheduling and management framework of an energy hub (EH) is presented with the aim of energy profit maximization in partnership with electricity, natural gas, and district heating networks (EGHNs) considering the coordinated multi-energy management based on the day-ahead market. The optimum capacity of EH equipment, including photovoltaic and wind renewable energy sources, a combined heat and power system (CHP), a boiler, energy storage, and electric vehicles is determined in the day-ahead market using the improved Fick’s law algorithm (IFLA), considering the energy profit maximization and also satisfying the linear network and hub constraints. The conventional FLA is inspired by the concept of Fick’s diffusion law, and, in this study, its performance against premature convergence is improved by using Rosenbrock’s direct rotational method. The performance of the IFLA when applied to EH coordinated scheduling and management problems with the aim of profit maximization is compared with the conventional FLA, particle swarm optimization (PSO), and manta ray foraging optimization (MRFO) methods. The results show that the proposed scheduling and multi-energy management framework achieves more energy profit in the day-ahead electricity, gas, and heating markets by satisfying the operation and EH constraints compared to other methods. Furthermore, according to the findings, the increased (decreased) demand and the forced outage rate caused a decrease (increase) in the EH profit. The results show the effectiveness of the proposed framework to obtain the EH maximum energy profit in the day-ahead market.</p><h2>Other Information</h2><p dir="ltr">Published in: Applied Sciences<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/app13063526" target="_blank">https://dx.doi.org/10.3390/app13063526</a></p>2023-03-09T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3390/app13063526https://figshare.com/articles/journal_contribution/Energy_Hub_Optimal_Scheduling_and_Management_in_the_Day-Ahead_Market_Considering_Renewable_Energy_Sources_CHP_Electric_Vehicles_and_Storage_Systems_Using_Improved_Fick_s_Law_Algorithm/24717258CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/247172582023-03-09T03:00:00Z |
| spellingShingle | Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Algorithm Ali S. Alghamdi (12722891) Engineering Electrical engineering Electronics, sensors and digital hardware Information and computing sciences Theory of computation optimal energy hub planning scheduled and multi-energy management energy profit improved Fick’s law algorithm Rosenbrock’s direct rotational method |
| status_str | publishedVersion |
| title | Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Algorithm |
| title_full | Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Algorithm |
| title_fullStr | Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Algorithm |
| title_full_unstemmed | Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Algorithm |
| title_short | Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Algorithm |
| title_sort | Energy Hub Optimal Scheduling and Management in the Day-Ahead Market Considering Renewable Energy Sources, CHP, Electric Vehicles, and Storage Systems Using Improved Fick’s Law Algorithm |
| topic | Engineering Electrical engineering Electronics, sensors and digital hardware Information and computing sciences Theory of computation optimal energy hub planning scheduled and multi-energy management energy profit improved Fick’s law algorithm Rosenbrock’s direct rotational method |