Stationary and mobile storages-based renewable off-grid system planning considering storage degradation cost based on information-gap decision theory optimization
This paper presents the planning of a hybrid renewable system with wind turbines and bio-waste energy units along with stationary (i.e., batteries) and mobile (i.e., electric vehicles) energy storage. This model minimizes the cost of construction, maintenance and storage degradation. In this model,...
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| Veröffentlicht in: | Journal of energy storage Jg. 58; S. 106389 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Elsevier Ltd
01.02.2023
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| ISSN: | 2352-152X, 2352-1538 |
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| Abstract | This paper presents the planning of a hybrid renewable system with wind turbines and bio-waste energy units along with stationary (i.e., batteries) and mobile (i.e., electric vehicles) energy storage. This model minimizes the cost of construction, maintenance and storage degradation. In this model, the energy supply priority is given to renewable sources. Then the mentioned storage devices are used to cover the gap between the load profile and the renewable generation power. The proposed scheme addresses the uncertainties of loads, renewable power and energy consumption of mobile storage devices. Therefore, robust optimization based on information-gap decision theory (IGDT) is utilized to obtain a robust solution against the prediction error of the aforementioned uncertainties. Also, the hybrid optimization algorithm of honey bee mating and artificial bee colony is derived, showing the optimal solution with low dispersion in the final response. The proposed design is applied to the data of the city of Espoo, Finland. The obtained numerical results show the capability of the proposed design in deriving robust economic planning for the proposed hybrid system. So, the used hybrid solution algorithm is able to obtain the best solution in a lower computation time compared to non-hybrid solvers, and it has a low standard deviation around 0.94 % in the final response. The presence of the aforementioned renewable sources leads to attaining an environment-friendly hybrid system. The optimal performance of the storage devices leads to the robustness of the optimal solution against the maximum error of 18.19 % in the prediction of uncertainties. This occurs considering the smart charging management of mobile storage, but the maximum uncertainty level of 11.12 % holds to non-smart management of these storage devices in the proposed scheme. The energy management of mobile storage devices based on smart (non-smart) charging strategy also reduces (increases) the planning cost of the off-grid system by 7.62 % (39.68 %) compared to their absence.
•Planning an off-grid system with 100% renewable sources such as WT, BEU and stationery and mobile storage devices.•Formulating the function of aggregating EVs in an island hybrid system to minimize planning cost.•Deriving robust planning of off-grid system against forecasting error using IGDT model of uncertainties.•Obtaining optimal solution in low computing time with low dispersion in final solution by HBMO+ABC algorithm. |
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| AbstractList | This paper presents the planning of a hybrid renewable system with wind turbines and bio-waste energy units along with stationary (i.e., batteries) and mobile (i.e., electric vehicles) energy storage. This model minimizes the cost of construction, maintenance and storage degradation. In this model, the energy supply priority is given to renewable sources. Then the mentioned storage devices are used to cover the gap between the load profile and the renewable generation power. The proposed scheme addresses the uncertainties of loads, renewable power and energy consumption of mobile storage devices. Therefore, robust optimization based on information-gap decision theory (IGDT) is utilized to obtain a robust solution against the prediction error of the aforementioned uncertainties. Also, the hybrid optimization algorithm of honey bee mating and artificial bee colony is derived, showing the optimal solution with low dispersion in the final response. The proposed design is applied to the data of the city of Espoo, Finland. The obtained numerical results show the capability of the proposed design in deriving robust economic planning for the proposed hybrid system. So, the used hybrid solution algorithm is able to obtain the best solution in a lower computation time compared to non-hybrid solvers, and it has a low standard deviation around 0.94 % in the final response. The presence of the aforementioned renewable sources leads to attaining an environment-friendly hybrid system. The optimal performance of the storage devices leads to the robustness of the optimal solution against the maximum error of 18.19 % in the prediction of uncertainties. This occurs considering the smart charging management of mobile storage, but the maximum uncertainty level of 11.12 % holds to non-smart management of these storage devices in the proposed scheme. The energy management of mobile storage devices based on smart (non-smart) charging strategy also reduces (increases) the planning cost of the off-grid system by 7.62 % (39.68 %) compared to their absence.
•Planning an off-grid system with 100% renewable sources such as WT, BEU and stationery and mobile storage devices.•Formulating the function of aggregating EVs in an island hybrid system to minimize planning cost.•Deriving robust planning of off-grid system against forecasting error using IGDT model of uncertainties.•Obtaining optimal solution in low computing time with low dispersion in final solution by HBMO+ABC algorithm. |
| ArticleNumber | 106389 |
| Author | Le, Binh Nguyen Mohammed, Adil Hussein Jokar, Mohammad Reza Foong, Loke Kok Shahmoradi, Saeid Pirouzi, Sasan |
| Author_xml | – sequence: 1 givenname: Mohammad Reza surname: Jokar fullname: Jokar, Mohammad Reza email: m.mohamadreza.jokar@gmail.com organization: Faculty of Electrical and Computer Engineering, University of shahed, Tehran, Iran – sequence: 2 givenname: Saeid surname: Shahmoradi fullname: Shahmoradi, Saeid email: saeedsh61@yahoo.com organization: Khuzestan Water and Power Authority, Ahvaz, Iran – sequence: 3 givenname: Adil Hussein surname: Mohammed fullname: Mohammed, Adil Hussein email: adil.mohammed@cihanuniversity.edu.iq organization: Department of Communication and Computer Engineering, Faculty of Engineering, Cihan University-Erbil, Kurdistan Region, Iraq – sequence: 4 givenname: Loke Kok surname: Foong fullname: Foong, Loke Kok email: lokekokfoong@duytan.edu.vn organization: Institute of Research and Development, Duy Tan University, Da Nang, Vietnam – sequence: 5 givenname: Binh Nguyen surname: Le fullname: Le, Binh Nguyen email: bnlnguyen@duytan.edu.vn organization: Institute of Research and Development, Duy Tan University, Da Nang, Vietnam – sequence: 6 givenname: Sasan surname: Pirouzi fullname: Pirouzi, Sasan email: s.pirouzi@sutech.ac.ir organization: Department of Engineering, Semirom Branch, Islamic Azad University, Semirom, Iran |
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| Keywords | Hybrid solution algorithm Stationary and mobile storage Bio-waste energy unit Storage degradation cost Information-gap decision theory Off-grid system |
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| SubjectTerms | Bio-waste energy unit Hybrid solution algorithm Information-gap decision theory Off-grid system Stationary and mobile storage Storage degradation cost |
| Title | Stationary and mobile storages-based renewable off-grid system planning considering storage degradation cost based on information-gap decision theory optimization |
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