Renewable Energy Focus最新文献_第10页

Optimizing grid-connected battery energy storage systems: a comprehensive evaluation methodology 优化并网电池储能系统：一种综合评价方法

IF 4.2

Renewable Energy Focus Pub Date : 2025-09-01 Epub Date: 2025-05-28 DOI: 10.1016/j.ref.2025.100724

Mohammad Zain Ul Abideen, Abdulrahman Alassi, Santiago Bañales

引用次数: 0

Artificial neural network-based enhanced distance protection sensitivity in microgrids 基于人工神经网络的微电网距离保护灵敏度增强

IF 4.2

Renewable Energy Focus Pub Date : 2025-09-01 Epub Date: 2025-04-14 DOI: 10.1016/j.ref.2025.100710

Ahmed N. Sheta , Abdelfattah A. Eladl , Bishoy E. Sedhom , Magda I. El-Afifi , Padmanaban Sanjeevikumar , Mohamed Zaki

{"title":"Artificial neural network-based enhanced distance protection sensitivity in microgrids","authors":"Ahmed N. Sheta , Abdelfattah A. Eladl , Bishoy E. Sedhom , Magda I. El-Afifi , Padmanaban Sanjeevikumar , Mohamed Zaki","doi":"10.1016/j.ref.2025.100710","DOIUrl":"10.1016/j.ref.2025.100710","url":null,"abstract":"<div><div>The integration of distributed energy resources (DERs) into microgrids introduces dynamic operational challenges that conventional distance relays struggle to address, particularly under variable network topologies, load fluctuations, and DER intermittency. This paper proposes an artificial neural network (ANN)-enhanced distance protection scheme to improve fault detection accuracy, classification, and localization in DER-rich microgrids. A 20-layer ANN model, trained on 50 fault scenarios encompassing 11 fault types (including phase-to-phase, phase-to-ground, and high-impedance faults up to 50 Ω) and non-fault conditions, processes raw three-phase and ground impedance measurements directly. The ANN achieves a mean squared error (MSE) of 0.0143 at epoch 21, with binary outputs enabling rapid fault identification (within two power cycles) and classification. Validated under grid-connected and islanded modes with DER penetration levels of 20–80 %, the scheme demonstrates 98.7 % accuracy, 97 % noise resilience at 20 dB SNR, and precise localization of faults. Comparative analysis against traditional relays and AI-based methods (CNNs, DTs, and SVMs) reveals superior fault coverage, adaptability to DER variability, and elimination of preprocessing delays. By mitigating false tripping and DER-induced impedance errors, this ANN-based approach significantly enhances microgrid reliability, offering a robust solution for evolving power systems.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100710"},"PeriodicalIF":4.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143848142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Techno-economic viability of energy-sharing model for net-zero emissions in the Malaysian corporate sector 马来西亚企业部门实现净零排放的能源共享模式的技术经济可行性

IF 4.2

Renewable Energy Focus Pub Date : 2025-09-01 Epub Date: 2025-03-24 DOI: 10.1016/j.ref.2025.100704

Nur Iqtiyani Ilham , Nofri Yenita Dahlan , Mohamad Zhafran Hussin

{"title":"Techno-economic viability of energy-sharing model for net-zero emissions in the Malaysian corporate sector","authors":"Nur Iqtiyani Ilham , Nofri Yenita Dahlan , Mohamad Zhafran Hussin","doi":"10.1016/j.ref.2025.100704","DOIUrl":"10.1016/j.ref.2025.100704","url":null,"abstract":"<div><div>Achieving net-zero emissions by 2050 requires a transformative approach, with the corporate sector playing one of the significant roles. Transitioning from brown to green energy through innovative solutions like energy-sharing is critical in this journey. Despite global interest in energy-sharing frameworks, detailed assessments of such strategies remain scarce in Southeast Asia, particularly in Malaysia. Previous studies in this country have focused on optimizing solar PV and storage systems, neglecting the potential of integrated energy-sharing model and the adoption of Renewable Energy Certificates (REC) for energy trading. This research addresses this gap by proposing a techno-economic and environmentally viable energy-sharing model tailored for Malaysian Corporate Consumers (MCC), aiming to maximize financial and environmental benefits. The HOMER grid software is used to develop and simulate energy-sharing configurations, including (i) grid-connected Solar-Power-Plant (SPP), (ii) grid-connected SPP with Battery-Energy-Storage-System (BESS), and (iii) grid-connected BESS. Technical analysis identifies optimal SPP capacities to reduce MCC utility dependency, highlighting the potential of integrating BESS with SPP. Economic outcomes are evaluated for varying SPP sizes and BESS capacities at real-time System Marginal Price (SMP) as green energy tariff rate. Results show that grid-connected SPP with BESS projects are profitable at 5% Energy-Storage-Output-to-SPP-Output-Ratio (<em>R</em>), with 25-MW achieving the highest Net Present Value (NPV). Integrating BESS enhances SPP’s environmental performance, reducing CO<sub>2</sub> emissions by up to 25% compared to grid-connected SPP configurations. This research serves as a crucial guide for stakeholders and policymakers by demonstrating net-zero emissions initiatives through REC implementation in the energy-sharing landscape.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100704"},"PeriodicalIF":4.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improved hybrid algorithm-based optimization for Integrated Energy Distribution Network System: minimizing voltage deviation, line losses, and costs 基于改进混合算法的综合配电网系统优化：最小化电压偏差、线路损耗和成本

IF 4.2

Renewable Energy Focus Pub Date : 2025-09-01 Epub Date: 2025-05-01 DOI: 10.1016/j.ref.2025.100716

Yixi Zhang, Heng Chen, Yue Gao, Jingjia Li, Peiyuan Pan

{"title":"Improved hybrid algorithm-based optimization for Integrated Energy Distribution Network System: minimizing voltage deviation, line losses, and costs","authors":"Yixi Zhang, Heng Chen, Yue Gao, Jingjia Li, Peiyuan Pan","doi":"10.1016/j.ref.2025.100716","DOIUrl":"10.1016/j.ref.2025.100716","url":null,"abstract":"<div><div>To address the siting and sizing of an integrated energy distribution network system incorporating PV, WT, EV, SVC, and BES, as well as the operational planning of SVC and BES, this paper proposes an improved hybrid algorithm. In the first stage, a multi-objective genetic algorithm is adopted to plan the siting and sizing of each device in the integrated energy distribution network. In the second stage, based on the siting and sizing results, an adaptive particle swarm optimization algorithm is utilized to schedule the daily energy storage dispatch and reactive power output. Through this two-stage optimization, the issues of unbalanced load distribution and voltage quality in the distribution network are resolved, while minimizing investment costs. The IEEE 69-node simulation results demonstrate that under the optimal scenario, the average voltage deviation of the distribution system remains stable at 1.0 p.u., the line loss rate decreases to 2.90 %, and the initial construction cost and operational cost reach 120,220,000 CNY and 16,923.88 CNY, respectively. Compared with similar algorithms, the proposed hybrid algorithm achieves a 34.5% improvement in loss reduction, significantly enhances voltage stability, and reduces daily operational costs by 9.91 %, demonstrating its effectiveness and superiority.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100716"},"PeriodicalIF":4.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143902605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Coordinated scheduling of renewable energy micro-grids through coupled energy flow and battery delivery logistics 基于能量流与电池配送物流耦合的可再生能源微电网协调调度

IF 4.2

Renewable Energy Focus Pub Date : 2025-09-01 Epub Date: 2025-05-29 DOI: 10.1016/j.ref.2025.100723

Wei Xu , Yufeng Guo , Yifei Liu , Xuechen Bai

{"title":"Coordinated scheduling of renewable energy micro-grids through coupled energy flow and battery delivery logistics","authors":"Wei Xu , Yufeng Guo , Yifei Liu , Xuechen Bai","doi":"10.1016/j.ref.2025.100723","DOIUrl":"10.1016/j.ref.2025.100723","url":null,"abstract":"<div><div>With the rapid penetration of new energy sources into urban distribution networks (DNs), the load curve of DNs is exhibiting a “valley” characteristic, placing higher grid connection requirements on market participants. This paper focuses on micro-grids (MGs) and, driven by the objectives of peak shaving and carbon reduction, proposes a joint scheduling model for multi-MGs based on battery distribution and circulation. The model aims to address the challenges of energy exchange and collaboration, which are caused by long distances between some MGs and the immature peer-to-peer trading mechanisms. Firstly, a dynamic electricity purchase and sale price mechanism is designed according to the next day’s peak shaving demand of the distribution grid, guiding the MG to enhance grid-friendly power integration. Secondly, we propose a joint optimization strategy for multiple MGs, achieving cross-regional energy exchange through the flow of batteries of MGs. To address the shortcomings in existing research regarding the coupling of energy scheduling and logistics scheduling, this paper considers the coupling relationship between the two in terms of energy and dispatch periods, optimizing both the day-ahead energy scheduling of each MG and the logistics strategy for battery delivery. Through case analysis, the proposed model is validated for its excellence in grid friendliness and carbon reduction.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100723"},"PeriodicalIF":4.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144212600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Active and Reactive Power Control in Three-Phase Grid-Connected Electric Vehicles using Zebra Optimization Algorithm and Multimodal Adaptive Spatio-Temporal Graph Neural Network 基于斑马优化算法和多模态自适应时空图神经网络的三相并网电动汽车有功与无功控制

IF 4.2

Renewable Energy Focus Pub Date : 2025-09-01 Epub Date: 2025-05-02 DOI: 10.1016/j.ref.2025.100715

E. Shiva Prasad , S.V. Evangelin Sonia , Kokkirapati Naga Suresh , T.G. Shivapanchakshari

{"title":"Active and Reactive Power Control in Three-Phase Grid-Connected Electric Vehicles using Zebra Optimization Algorithm and Multimodal Adaptive Spatio-Temporal Graph Neural Network","authors":"E. Shiva Prasad , S.V. Evangelin Sonia , Kokkirapati Naga Suresh , T.G. Shivapanchakshari","doi":"10.1016/j.ref.2025.100715","DOIUrl":"10.1016/j.ref.2025.100715","url":null,"abstract":"<div><div>Three-phase grid-connected Electric Vehicles (EVs) are critical for optimizing energy flow, managing Active Power (AP) for charging and discharging, and controlling Reactive Power (RP) to ensure voltage regulation. These features enhance grid reliability and support the seamless integration of large-scale EVs into power grids. However, the unpredictable frequency of charging sessions creates challenges such as voltage fluctuations and grid imbalances, adversely affecting power quality (PQ) and stability. To address these issues, this study proposes a hybrid approach for AP and RP control in three-phase grid-connected EVs. The novel ZOA-MASTGNN technique integrates the Zebra Optimization Algorithm (ZOA) with the Multimodal Adaptive Spatio-Temporal Graph Neural Network (MASTGNN). The ZOA dynamically optimizes system parameters, improving power management, reducing Total Harmonic Distortion (THD), and enhancing grid stability. Meanwhile, MASTGNN predicts optimal control actions, mitigating harmonics, regulating voltage dynamically, and adapting to changing operational conditions in grid-interactive EV systems. The suggested method was implemented on the MATLAB platform and evaluated with existing approaches, including Resiliency-Guided Physics-Informed Neural Networks (RPINN), Elman Neural Networks (ENN), Multilayer Feed Forward Neural Networks (ML-FFNN), Deep Neural Networks (DNN), and Particle Swarm Optimization-Artificial Neural Networks (PSO-ANN). Results showed significant improvements, achieving 19.36% load current THD and 3.52% source current THD, while outperforming other approaches in efficiency and effectiveness. This framework addresses key challenges in large-scale EV integration, offering scalable and practical solutions for sustainable power grid operations.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100715"},"PeriodicalIF":4.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143924631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comprehensive methodology for assessing the impact of vehicle-to-grid integration in power system expansion planning 评估电力系统扩展规划中车辆与电网整合影响的综合方法

IF 4.2

Renewable Energy Focus Pub Date : 2025-09-01 Epub Date: 2025-05-24 DOI: 10.1016/j.ref.2025.100718

Leonardo Bitencourt , Walquiria N. Silva , Bruno H. Dias , Tiago P. Abud , Bruno Borba , Pedro Peters

{"title":"Comprehensive methodology for assessing the impact of vehicle-to-grid integration in power system expansion planning","authors":"Leonardo Bitencourt , Walquiria N. Silva , Bruno H. Dias , Tiago P. Abud , Bruno Borba , Pedro Peters","doi":"10.1016/j.ref.2025.100718","DOIUrl":"10.1016/j.ref.2025.100718","url":null,"abstract":"<div><div>The increasing adoption of electric vehicles (EVs) emphasizes the critical need to assess their integration into the electricity grid for a sustainable energy transition. Existing literature lacks comprehensive vehicle-to-grid (V2G) impact analyses and methodologies for long-term integration, particularly in developing countries. Moreover, the absence of optimized short-term operational models for EV integration poses challenges in grid management. To bridge these gaps, this research proposes a socio-economic model to estimate EV sales based on the Bass diffusion model and macroeconomic regressions. Additionally, it integrates electricity system expansion planning using the OSeMOSYS tool with a short-term operational model based on unit commitment. In this context, this work endeavors to develop a methodology for estimating the impact of V2G technology, considering both the deployment and utilization of EVs in a Brazilian case study. Applying traditional methodologies that do not consider operational system models can lead to potential future load shedding. It may accentuate disparities between long-term and short-term outcomes, especially with EV and V2G integration. The proposed methodology corrected the overestimation of the energy injection potential of EVs by the traditional model, indicating the need to consider both the expansion and the operation of the electricity system when planning the integration of EVs.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100718"},"PeriodicalIF":4.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144135017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal planning of biogas production in a set of batch biodigesters 间歇式沼气池沼气生产的优化规划

IF 4.2

Renewable Energy Focus Pub Date : 2025-09-01 Epub Date: 2025-04-15 DOI: 10.1016/j.ref.2025.100706

Arthur Barreto , Sanja Petrovic , Edilaine Soler , Helenice Florentino , Adriana Cherri

{"title":"Optimal planning of biogas production in a set of batch biodigesters","authors":"Arthur Barreto , Sanja Petrovic , Edilaine Soler , Helenice Florentino , Adriana Cherri","doi":"10.1016/j.ref.2025.100706","DOIUrl":"10.1016/j.ref.2025.100706","url":null,"abstract":"<div><div>The use of organic wastes from industrial, agro-industrial, and household sources has become an essential strategy for generating renewable and sustainable energy. Organic materials processed in biodigesters offer two major benefits: the production of biogas (a renewable energy source) and the creation of biofertilizers (which can enhance agricultural productivity). These benefits increased the interest from both researchers and industry leaders in finding more efficient ways to manage biomass for energy production. One area that has not been thoroughly explored is the scheduling of biogas production in batch biodigesters to meet fluctuating energy demand over time. Biodigesters typically operate in batches, where the substrate is loaded into the system and left to digest for a set period. However, the timing and amount of substrate to be processed are critical issues as the energy demand may vary, and managing production surpluses or shortages is crucial. In this context, a novel integer linear mathematical model has been proposed to address the biogas production scheduling problem. The model focuses on balancing the biogas demand with the operational constraints of biodigesters, such as their availability and production cycles. Several experimental tests have been conducted to validate the model’s effectiveness. These tests varied parameters as the biogas demand type, the length of the planning horizon, and the number of biodigesters with different production cycles.The results demonstrate that the proposed model effectively supports decision-making processes for biogas production planning, contributing to cleaner energy systems and sustainable resource management.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100706"},"PeriodicalIF":4.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143844650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing smart nano grid control strategies through virtual environment and hybrid deep learning approaches 基于虚拟环境和混合深度学习方法的智能纳米电网控制策略优化

IF 4.2

Renewable Energy Focus Pub Date : 2025-09-01 Epub Date: 2025-04-21 DOI: 10.1016/j.ref.2025.100712

Ibrahim Sinneh Sinneh, Yanxia Sun Yanxia

{"title":"Optimizing smart nano grid control strategies through virtual environment and hybrid deep learning approaches","authors":"Ibrahim Sinneh Sinneh, Yanxia Sun Yanxia","doi":"10.1016/j.ref.2025.100712","DOIUrl":"10.1016/j.ref.2025.100712","url":null,"abstract":"<div><div>Smart nano grids face enormous challenges stemming from variations in time demand and risks from cyber threats, which lead to their inefficiency and unstable operation. To overcome these difficulties, this study presents a novel “Federated Reinforced LSTM-Crayfish Whale Optimization Detection (FRLC-WOD)” procedure. The system proposed here integrates Reinforcement-LSTM-Crayfish Optimization Technique (RL-LSTM-CAO) and Federated Graph Whale Optimization Intrusion Detection (FG-WOA-ID) to improve adaptability, efficiency, and security. The RL-LSTM-CAO methodology employs Bi-directional Long Short-Term Memory (Bi-LSTM) for accurate forecasting, Reinforcement Learning-based Power Distribution (RL-PD) for real-time adaptability, and Crayfish Optimization Algorithm (CAO) for optimal energy management. On the other hand, FG-WOA-ID employs Federated Learning for decentralized anomaly detection, Graph Neural Networks for intrusion detection, and Whale Optimization Algorithm for cybersecurity measures adaptation. The results of the experiments achieved a grid stability improvement of 95 %, an energy efficiency improvement of 92 %, a response time of 1.5 s, and a 95 % improved cyber threat resistance, outperforming existing standard methodologies such as EMS GWO-OSA, RNN, and MPPT. This will show how the proposed method significantly upgrades the delivery of reliable and optimized operations for smart nano grids.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100712"},"PeriodicalIF":4.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Techno-economic analysis of integrated PV/Biogas/Wind/Hydrogen polygeneration energy systems for green transportation in Bangladesh context 孟加拉国绿色交通一体化光伏/沼气/风能/氢气多联产能源系统的技术经济分析

IF 4.2

Renewable Energy Focus Pub Date : 2025-09-01 Epub Date: 2025-04-05 DOI: 10.1016/j.ref.2025.100707

Shemanto Saha , Abu Kowsar , Sumon Chandra Debnath , Kawsar Ahmed , Firoz Alam

{"title":"Techno-economic analysis of integrated PV/Biogas/Wind/Hydrogen polygeneration energy systems for green transportation in Bangladesh context","authors":"Shemanto Saha , Abu Kowsar , Sumon Chandra Debnath , Kawsar Ahmed , Firoz Alam","doi":"10.1016/j.ref.2025.100707","DOIUrl":"10.1016/j.ref.2025.100707","url":null,"abstract":"<div><div>The global transportation system is currently experiencing a notable shift towards the prominence of fully electric, hybrid, and hydrogen-fuelled vehicles to reduce the environmental consequences of fossil fuels. Developing countries, including Bangladesh, promote renewable energy-based power generation to foster the uptake of green transportation solutions. However, the implementation of such a solution poses significant economic, technical, and affordability challenges. This study explores the techno-economic viability of four potential options (Models): photovoltaic (PV), biogas, wind, and hydrogen energy within a net-metering scheme, an area not previously well explored for developing countries. The study findings reveal that Model 1 (PV/biogas) featuring electric vehicles (EVs) bears a cost of US$ 0.0141/km and demonstrates higher economic viability than the other three models. From an environmental standpoint, Model 3 (PV/biogas-powered hydrogen refuelling stations—HRFS) emerges as the optimal choice, characterised by a CO<sub>2</sub> emission of 1.83 g/km and the levelized cost of hydrogen (LCOH) and hydrogen production (LCOH<sub>P</sub>) values of US$ 13.4 and US$ 8.93, respectively. A sensitivity analysis of the PEM electrolyser price and gasification ratio estimates the LCOHp at US$ 8.63 to US$ 9.90. Environmental evaluations show that Models 3 and 4 can reduce CO<sub>2</sub> emissions from diesel, petrol, and CNG in Bangladesh’s transportation sector by approximately 99.5%. The study further reveals that EVs are deemed more economical than hydrogen fuel cell vehicles for green transportation for developing nations under the current cost structure.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"54 ","pages":"Article 100707"},"PeriodicalIF":4.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0