Emission/Reliability-Aware Stochastic Optimization of Electric Bus Parking Lots and Renewable Energy Sources in Distribution Network: A Fuzzy Multi-Objective Framework Considering Forecasted Data.
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| Title: | Emission/Reliability-Aware Stochastic Optimization of Electric Bus Parking Lots and Renewable Energy Sources in Distribution Network: A Fuzzy Multi-Objective Framework Considering Forecasted Data. |
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| Authors: | ur Rehman, Masood, Shirode, Ujwal Ramesh, Pawar, Aarti Suryakant, Wong, Tze Jin, Khudaynazarov, Egambergan, Arabi Nowdeh, Saber |
| Source: | World Electric Vehicle Journal; Nov2025, Vol. 16 Issue 11, p624, 53p |
| Subject Terms: | STOCHASTIC programming, RENEWABLE energy sources, FORECASTING, ELECTRIC vehicle charging stations, RELIABILITY in engineering, EMISSION exposure, MATHEMATICAL optimization |
| Abstract: | In this paper, an emission- and reliability-aware stochastic optimization model is proposed for the economic planning of electric bus parking lots (EBPLs) with photovoltaic (PV) and wind-turbine (WT) resources in an 85-bus radial distribution network. The model simultaneously minimizes operating, emission, and energy-loss costs while increasing system reliability, measured by energy not supplied (ENS), and uses a fuzzy decision-making approach to determine the final solution. To address optimization challenges, a new multi-objective entropy-guided Sinh–Cosh Optimizer (MO-ESCHO) is proposed to efficiently mitigate premature convergence and produce a well-distributed Pareto front. Also, a hybrid forecasting architecture that combines MO-ESCHO and artificial neural networks (ANN) is proposed for accurate prediction of PV and WT power and network loading. The framework is tested across five cases, progressively incorporating EBPL, demand response (DR), forecast information, and stochastic simulation of uncertainties using a new hybrid Unscented Transformation–Cubature Quadrature Rule (UT-CQR) method. Comparative analyses against conventional methods confirm superior performance in achieving better objective values and ensuring computational efficiency. The outcomes indicate that the combination of EBPL with RES reduces operating costs by 5.23%, emission costs by 27.39%, and ENS by 11.48% compared with the base case with RES alone. Moreover, incorporating the stochastic model increases operating costs by 6.03%, emission costs by 5.05%, and ENS by 7.94% over the deterministic forecast case, reflecting the added complexity of uncertainty. The main contributions lie in coupling EBPLs and RES under uncertainty and proposing UT-CQR, which exhibits robust system performance with reduced variance and lower computational effort compared with Monte Carlo and cloud-model approaches. [ABSTRACT FROM AUTHOR] |
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| Database: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: Emission/Reliability-Aware Stochastic Optimization of Electric Bus Parking Lots and Renewable Energy Sources in Distribution Network: A Fuzzy Multi-Objective Framework Considering Forecasted Data. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22ur+Rehman%2C+Masood%22">ur Rehman, Masood</searchLink><br /><searchLink fieldCode="AR" term="%22Shirode%2C+Ujwal+Ramesh%22">Shirode, Ujwal Ramesh</searchLink><br /><searchLink fieldCode="AR" term="%22Pawar%2C+Aarti+Suryakant%22">Pawar, Aarti Suryakant</searchLink><br /><searchLink fieldCode="AR" term="%22Wong%2C+Tze+Jin%22">Wong, Tze Jin</searchLink><br /><searchLink fieldCode="AR" term="%22Khudaynazarov%2C+Egambergan%22">Khudaynazarov, Egambergan</searchLink><br /><searchLink fieldCode="AR" term="%22Arabi+Nowdeh%2C+Saber%22">Arabi Nowdeh, Saber</searchLink> – Name: TitleSource Label: Source Group: Src Data: World Electric Vehicle Journal; Nov2025, Vol. 16 Issue 11, p624, 53p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22STOCHASTIC+programming%22">STOCHASTIC programming</searchLink><br /><searchLink fieldCode="DE" term="%22RENEWABLE+energy+sources%22">RENEWABLE energy sources</searchLink><br /><searchLink fieldCode="DE" term="%22FORECASTING%22">FORECASTING</searchLink><br /><searchLink fieldCode="DE" term="%22ELECTRIC+vehicle+charging+stations%22">ELECTRIC vehicle charging stations</searchLink><br /><searchLink fieldCode="DE" term="%22RELIABILITY+in+engineering%22">RELIABILITY in engineering</searchLink><br /><searchLink fieldCode="DE" term="%22EMISSION+exposure%22">EMISSION exposure</searchLink><br /><searchLink fieldCode="DE" term="%22MATHEMATICAL+optimization%22">MATHEMATICAL optimization</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In this paper, an emission- and reliability-aware stochastic optimization model is proposed for the economic planning of electric bus parking lots (EBPLs) with photovoltaic (PV) and wind-turbine (WT) resources in an 85-bus radial distribution network. The model simultaneously minimizes operating, emission, and energy-loss costs while increasing system reliability, measured by energy not supplied (ENS), and uses a fuzzy decision-making approach to determine the final solution. To address optimization challenges, a new multi-objective entropy-guided Sinh–Cosh Optimizer (MO-ESCHO) is proposed to efficiently mitigate premature convergence and produce a well-distributed Pareto front. Also, a hybrid forecasting architecture that combines MO-ESCHO and artificial neural networks (ANN) is proposed for accurate prediction of PV and WT power and network loading. The framework is tested across five cases, progressively incorporating EBPL, demand response (DR), forecast information, and stochastic simulation of uncertainties using a new hybrid Unscented Transformation–Cubature Quadrature Rule (UT-CQR) method. Comparative analyses against conventional methods confirm superior performance in achieving better objective values and ensuring computational efficiency. The outcomes indicate that the combination of EBPL with RES reduces operating costs by 5.23%, emission costs by 27.39%, and ENS by 11.48% compared with the base case with RES alone. Moreover, incorporating the stochastic model increases operating costs by 6.03%, emission costs by 5.05%, and ENS by 7.94% over the deterministic forecast case, reflecting the added complexity of uncertainty. The main contributions lie in coupling EBPLs and RES under uncertainty and proposing UT-CQR, which exhibits robust system performance with reduced variance and lower computational effort compared with Monte Carlo and cloud-model approaches. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of World Electric Vehicle Journal is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/wevj16110624 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 53 StartPage: 624 Subjects: – SubjectFull: STOCHASTIC programming Type: general – SubjectFull: RENEWABLE energy sources Type: general – SubjectFull: FORECASTING Type: general – SubjectFull: ELECTRIC vehicle charging stations Type: general – SubjectFull: RELIABILITY in engineering Type: general – SubjectFull: EMISSION exposure Type: general – SubjectFull: MATHEMATICAL optimization Type: general Titles: – TitleFull: Emission/Reliability-Aware Stochastic Optimization of Electric Bus Parking Lots and Renewable Energy Sources in Distribution Network: A Fuzzy Multi-Objective Framework Considering Forecasted Data. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: ur Rehman, Masood – PersonEntity: Name: NameFull: Shirode, Ujwal Ramesh – PersonEntity: Name: NameFull: Pawar, Aarti Suryakant – PersonEntity: Name: NameFull: Wong, Tze Jin – PersonEntity: Name: NameFull: Khudaynazarov, Egambergan – PersonEntity: Name: NameFull: Arabi Nowdeh, Saber IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20326653 Numbering: – Type: volume Value: 16 – Type: issue Value: 11 Titles: – TitleFull: World Electric Vehicle Journal Type: main |
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