The proliferation of electric vehicles (EVs) causes a series of significant operational challenges for distribution system operators (DSOs) such as voltage control and power losses. This paper proposes a novel optimal charge scheduling method that balances the interests of both the DSO and the EV parking lot (EVPL) operator. Within the coordinated framework of Alternating Direction Method of Multipliers based distributed solution, the DSO aims to maximize the load factor, while the EVPL operator seeks to minimize charging costs. The proposed method avoids peak loading caused by the EVPL during low price time intervals, while it prevents the higher operation costs due to the high price time intervals caused by the DSO’s day ahead pricing scheme. Furthermore, the presented optimization model is experimentally tested for the individual operations, and coordinated operation.
{"title":"A new distributed charge approach for the electric vehicle parking lots considering coordination between DSO and EV operators","authors":"Tayfur Gökçek , Ali Rıfat Boynueğri , Sıtkı Güner , Ozan Erdinç , Jale Sadreddini","doi":"10.1016/j.apenergy.2025.125780","DOIUrl":"10.1016/j.apenergy.2025.125780","url":null,"abstract":"<div><div>The proliferation of electric vehicles (EVs) causes a series of significant operational challenges for distribution system operators (DSOs) such as voltage control and power losses. This paper proposes a novel optimal charge scheduling method that balances the interests of both the DSO and the EV parking lot (EVPL) operator. Within the coordinated framework of Alternating Direction Method of Multipliers based distributed solution, the DSO aims to maximize the load factor, while the EVPL operator seeks to minimize charging costs. The proposed method avoids peak loading caused by the EVPL during low price time intervals, while it prevents the higher operation costs due to the high price time intervals caused by the DSO’s day ahead pricing scheme. Furthermore, the presented optimization model is experimentally tested for the individual operations, and coordinated operation.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"390 ","pages":""},"PeriodicalIF":10.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-05DOI: 10.1016/j.apenergy.2025.125825
Daogui Tang , Hao Tang , Chengqing Yuan , Mingwang Dong , Cesar Diaz-Londono , Gibran David Agundis-Tinajero , Josep M. Guerrero , Enrico Zio
This paper proposes an economic and resilient operation architecture for a coupled hydrogen-electricity energy system operating at port. The architecture is a multi-objective optimization problem, which includes the energy system optimal economy as the goal orientation and the optimal resilience as the goal orientation. The optimal resilience orientation looks for the best resilience performance of the port through reasonable energy management including (1) reducing the amount of electricity purchased by the port power grid from the external power grid (2) improving the energy level of electric energy storage (3) improving the energy level of hydrogen energy storage. Taking the actual coupled hydrogen-electricity energy system of Ningbo-Zhoushan Port as an example, four typical scenarios were selected according to renewable generation and load characteristics, and a comparative analysis was carried out under the oriented operation. The results show that although the resilience orientation increases the operating cost compared with the economic orientation, the four scenarios reduce the load shedding by 44.84 %, 30.26 %, 48.49 % and 34.37 % respectively when the external power grid is disconnected. The impact of changes in resilience-oriented weight coefficients and hydrogen price on system resilience performance was investigated to provide more references for decision makers.
{"title":"Economic and resilience-oriented operation of coupled hydrogen-electricity energy systems at ports","authors":"Daogui Tang , Hao Tang , Chengqing Yuan , Mingwang Dong , Cesar Diaz-Londono , Gibran David Agundis-Tinajero , Josep M. Guerrero , Enrico Zio","doi":"10.1016/j.apenergy.2025.125825","DOIUrl":"10.1016/j.apenergy.2025.125825","url":null,"abstract":"<div><div>This paper proposes an economic and resilient operation architecture for a coupled hydrogen-electricity energy system operating at port. The architecture is a multi-objective optimization problem, which includes the energy system optimal economy as the goal orientation and the optimal resilience as the goal orientation. The optimal resilience orientation looks for the best resilience performance of the port through reasonable energy management including (1) reducing the amount of electricity purchased by the port power grid from the external power grid (2) improving the energy level of electric energy storage (3) improving the energy level of hydrogen energy storage. Taking the actual coupled hydrogen-electricity energy system of Ningbo-Zhoushan Port as an example, four typical scenarios were selected according to renewable generation and load characteristics, and a comparative analysis was carried out under the oriented operation. The results show that although the resilience orientation increases the operating cost compared with the economic orientation, the four scenarios reduce the load shedding by 44.84 %, 30.26 %, 48.49 % and 34.37 % respectively when the external power grid is disconnected. The impact of changes in resilience-oriented weight coefficients and hydrogen price on system resilience performance was investigated to provide more references for decision makers.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"390 ","pages":""},"PeriodicalIF":10.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-05DOI: 10.1016/j.apenergy.2025.125822
Mak Đukan, Bjarne Steffen
The cost of capital (CoC) is a critical parameter that significantly impacts the levelized costs of low-carbon energy technologies and cost-optimal decarbonization pathways. Nevertheless, empirical evidence on CoC differences between technologies and investor types is limited. Here, we study the heterogeneity among 11 technologies based on 193 CoC inputs from utilities, financial investors, and project developers in Switzerland. We find a wide range of CoC values across the technologies, averaging 3.6 % for small rooftop PV and 7.8 % for green hydrogen. Furthermore, we record an empirical variation of six percentage points even for assets of the same technology group, like solar PV, indicating differences between business models and investor types. Unlike neighboring countries that primarily rely on project finance for renewables, we find balance sheet financing to play an essential role for Swiss investors. Our results stress the need to differentiate CoC assumptions in energy system modeling and to consider not only technologies but also investor types and regional specificities as additional CoC dimensions.
{"title":"Cost of capital for renewables and enabling technologies: Measuring the multidimensional heterogeneity in Switzerland","authors":"Mak Đukan, Bjarne Steffen","doi":"10.1016/j.apenergy.2025.125822","DOIUrl":"10.1016/j.apenergy.2025.125822","url":null,"abstract":"<div><div>The cost of capital (CoC) is a critical parameter that significantly impacts the levelized costs of low-carbon energy technologies and cost-optimal decarbonization pathways. Nevertheless, empirical evidence on CoC differences between technologies and investor types is limited. Here, we study the heterogeneity among 11 technologies based on 193 CoC inputs from utilities, financial investors, and project developers in Switzerland. We find a wide range of CoC values across the technologies, averaging 3.6 % for small rooftop PV and 7.8 % for green hydrogen. Furthermore, we record an empirical variation of six percentage points even for assets of the same technology group, like solar PV, indicating differences between business models and investor types. Unlike neighboring countries that primarily rely on project finance for renewables, we find balance sheet financing to play an essential role for Swiss investors. Our results stress the need to differentiate CoC assumptions in energy system modeling and to consider not only technologies but also investor types and regional specificities as additional CoC dimensions.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"390 ","pages":"Article 125822"},"PeriodicalIF":10.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-05DOI: 10.1016/j.apenergy.2025.125769
Mo Sodwatana , Dimitri M. Saad , Mareldi Ahumada-Paras , Adam R. Brandt
Decarbonizing end-use appliances in homes and businesses is essential to meeting net-zero emissions targets. However, determining the best approach – whether through electrification or with net-zero emissions gas supplies – remains complex and highly dependent on regional demand patterns. This study explores optimal pathways for appliance decarbonization in California under various cost, technological, and regulatory constraints. The analysis was conducted using BRIDGES (Building Resilient Integrated Decarbonized Gas Electric Systems), a co-optimized gas and electric capacity expansion and dispatch model. We represented California as 16 interconnected nodes and tracked three key end-use technologies in the residential and commercial sectors for decarbonization (space heating, water heating, and kitchen ranges). We solved for five investment periods with a five-year interval from 2025 to 2045. To reach net-zero emissions by 2045 under current state plan, 92 % of water heaters and 60 % of kitchen ranges are electrified. 61 % of space heaters are electrified, with preferential electrification of coupled space heating and air conditioning. Our results show that the pace and extent of electrification vary by technology and geography, leading to between 45 % and 232 % increase in peak distribution-level demand and 1 %–17 % increase in peak system-level demand depending on the climate zone. Sensitivity analyses reveal that water heater electrification outcomes are largely insensitive to cost, technological, and regulatory constraints. However, policies around refrigerant leakage mitigation and offsets significantly influence electrification outcomes for space heating. These variations in electrification patterns lead to differing impacts on the grid, underscoring the importance of coordinated gas-electric optimization in regional decarbonization planning.
{"title":"Appliance decarbonization and its impacts on California’s energy transition","authors":"Mo Sodwatana , Dimitri M. Saad , Mareldi Ahumada-Paras , Adam R. Brandt","doi":"10.1016/j.apenergy.2025.125769","DOIUrl":"10.1016/j.apenergy.2025.125769","url":null,"abstract":"<div><div>Decarbonizing end-use appliances in homes and businesses is essential to meeting net-zero emissions targets. However, determining the best approach – whether through electrification or with net-zero emissions gas supplies – remains complex and highly dependent on regional demand patterns. This study explores optimal pathways for appliance decarbonization in California under various cost, technological, and regulatory constraints. The analysis was conducted using BRIDGES (Building Resilient Integrated Decarbonized Gas Electric Systems), a co-optimized gas and electric capacity expansion and dispatch model. We represented California as 16 interconnected nodes and tracked three key end-use technologies in the residential and commercial sectors for decarbonization (space heating, water heating, and kitchen ranges). We solved for five investment periods with a five-year interval from 2025 to 2045. To reach net-zero emissions by 2045 under current state plan, 92 % of water heaters and 60 % of kitchen ranges are electrified. 61 % of space heaters are electrified, with preferential electrification of coupled space heating and air conditioning. Our results show that the pace and extent of electrification vary by technology and geography, leading to between 45 % and 232 % increase in peak distribution-level demand and 1 %–17 % increase in peak system-level demand depending on the climate zone. Sensitivity analyses reveal that water heater electrification outcomes are largely insensitive to cost, technological, and regulatory constraints. However, policies around refrigerant leakage mitigation and offsets significantly influence electrification outcomes for space heating. These variations in electrification patterns lead to differing impacts on the grid, underscoring the importance of coordinated gas-electric optimization in regional decarbonization planning.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"390 ","pages":"Article 125769"},"PeriodicalIF":10.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-05DOI: 10.1016/j.apenergy.2025.125746
Hamed Faghihian, Arman Sargolzaei
Electric vehicles (EVs) are widely recognized as the future of mobility. Maximizing the energy efficiency of EVs reduces total energy consumption in transportation and addresses challenges related to future EV adoption. Regenerative braking is one of the most promising features for increasing the range and efficiency of EVs. However, the current implementation of regenerative braking relies on human drivers, which is not efficient. Additionally, these systems are not designed to provide efficient torque to maximize the energy efficiency of EVs. To address these challenges, this paper proposes an Eco-Regen system which is a novel, energy-efficient automated regenerative braking system (RBS) to increase the energy efficiency of EVs. The proposed system incorporates a continuously variable gear ratio to maximize recaptured energy during braking maneuvers, with a fuzzy logic controller designed to select the optimum gear ratio in the Eco-Regen system. Human driver behavior was measured to investigate its impact on total recaptured energy during braking, and the effect of average human driver behavior was also studied. Simulation-in-the-loop (SIL) and Hardware-in-the-loop (HIL) results show that the Eco-Regen system can significantly increase the total recaptured energy, by up to 61 % compared to an average human driver, especially in scenarios where vehicles operate in environments with frequent stops, such as urban areas or transit buses.
{"title":"A novel energy-efficient automated regenerative braking system","authors":"Hamed Faghihian, Arman Sargolzaei","doi":"10.1016/j.apenergy.2025.125746","DOIUrl":"10.1016/j.apenergy.2025.125746","url":null,"abstract":"<div><div>Electric vehicles (EVs) are widely recognized as the future of mobility. Maximizing the energy efficiency of EVs reduces total energy consumption in transportation and addresses challenges related to future EV adoption. Regenerative braking is one of the most promising features for increasing the range and efficiency of EVs. However, the current implementation of regenerative braking relies on human drivers, which is not efficient. Additionally, these systems are not designed to provide efficient torque to maximize the energy efficiency of EVs. To address these challenges, this paper proposes an Eco-Regen system which is a novel, energy-efficient automated regenerative braking system (RBS) to increase the energy efficiency of EVs. The proposed system incorporates a continuously variable gear ratio to maximize recaptured energy during braking maneuvers, with a fuzzy logic controller designed to select the optimum gear ratio in the Eco-Regen system. Human driver behavior was measured to investigate its impact on total recaptured energy during braking, and the effect of average human driver behavior was also studied. Simulation-in-the-loop (SIL) and Hardware-in-the-loop (HIL) results show that the Eco-Regen system can significantly increase the total recaptured energy, by up to 61 % compared to an average human driver, especially in scenarios where vehicles operate in environments with frequent stops, such as urban areas or transit buses.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"390 ","pages":""},"PeriodicalIF":10.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-05DOI: 10.1016/j.apenergy.2025.125731
Tahsin Afroz Hoque Nishat , Jong-Hyun Jeong , Hongki Jo , Shenghao Xia , Jian Liu
Battery-powered wireless sensor networks (WSNs) provide an affordable and easily deployable option for Structural Health Monitoring (SHM). However, their long-term viability becomes challenging due to uneven battery wear across the sensor network, logistical planning difficulties for battery replacement, and maintaining the desired Quality of Service (QoS) for SHM. A system-level battery health management strategy is vital to extend the lifespan and reliability of WSNs, especially considering the expensive maintenance trips required for battery replacement. This study presents a reinforcement learning (RL) based framework to actively manage battery degradation at the system level while preserving SHM QoS. The framework focuses on group battery replacement, reducing logistical burdens, and enhancing WSN longevity without compromising desired QoS. To validate the RL framework, a detailed simulation environment was created for a real-world WSN setup on a cable-stayed bridge SHM. The simulation accounted for various environmental and operational factors such as weather-induced solar harvesting variability, communication uncertainties, lithium-ion battery degradation models, sensor power consumption, and duty cycle strategies etc. Additionally, a mode shape-based quality index was introduced for a SHM network. The RL agent was trained within this environment to learn optimal node selection for specific duty cycles. The results demonstrate the framework's effectiveness in optimizing battery replacement efforts by ensuring a similar end of lifetimes with more uniform battery degradation and allowing the longer and more reliable operation of WSNs under uncertainties.
{"title":"Reinforcement learning for adaptive battery management of structural health monitoring IoT sensor network","authors":"Tahsin Afroz Hoque Nishat , Jong-Hyun Jeong , Hongki Jo , Shenghao Xia , Jian Liu","doi":"10.1016/j.apenergy.2025.125731","DOIUrl":"10.1016/j.apenergy.2025.125731","url":null,"abstract":"<div><div>Battery-powered wireless sensor networks (WSNs) provide an affordable and easily deployable option for Structural Health Monitoring (SHM). However, their long-term viability becomes challenging due to uneven battery wear across the sensor network, logistical planning difficulties for battery replacement, and maintaining the desired Quality of Service (QoS) for SHM. A system-level battery health management strategy is vital to extend the lifespan and reliability of WSNs, especially considering the expensive maintenance trips required for battery replacement. This study presents a reinforcement learning (RL) based framework to actively manage battery degradation at the system level while preserving SHM QoS. The framework focuses on group battery replacement, reducing logistical burdens, and enhancing WSN longevity without compromising desired QoS. To validate the RL framework, a detailed simulation environment was created for a real-world WSN setup on a cable-stayed bridge SHM. The simulation accounted for various environmental and operational factors such as weather-induced solar harvesting variability, communication uncertainties, lithium-ion battery degradation models, sensor power consumption, and duty cycle strategies etc. Additionally, a mode shape-based quality index was introduced for a SHM network. The RL agent was trained within this environment to learn optimal node selection for specific duty cycles. The results demonstrate the framework's effectiveness in optimizing battery replacement efforts by ensuring a similar end of lifetimes with more uniform battery degradation and allowing the longer and more reliable operation of WSNs under uncertainties.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"390 ","pages":""},"PeriodicalIF":10.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-05DOI: 10.1016/j.apenergy.2025.125793
Haotian Wu , Deping Ke , Lin Song , Jian Xu , Siyang Liao , Lei Wang
The decarbonization transition of the iron and steel industry (ISI) necessitates an overshooting of its energy mix from a predominantly coal-consuming to a predominantly renewable energy-consuming one, including wind and hydrogen. This also presents novel challenges to the energy economy, efficiency, and flexibility of low-carbon ISI. To overcome this challenge, this paper proposes a multi-objective and multi-stage planning (MSP) model for ISI coupled with multi-energy forms. The MSP strategy, which considers the stage-adjustable hydrogen proportion (H2-CO ratio) used in iron production, is proposed as a means of fully considering energy development at different stages to make optimal equipment configuration. Moreover, a multi-objective capacity planning model is developed to establish energy economic, efficiency and flexibility objectives based on the actual energy policies implemented in China. Finally, an enhanced AUGMECON-R algorithm (EARA) is devised to address the bilinear constraints inherent to the model, thereby facilitating an efficient solution process. The simulation results substantiate the efficacy of the MSP strategy, illustrate the substantial value of the stage-plannable H2-CO ratio for ISI's economy and flexibility enhancement, and demonstrate that EARA can markedly enhance solution efficiency while maintaining an acceptable level of accuracy.
{"title":"Multi-objective and multi-stage capacity planning for low-carbon iron and steel industry empowered by wind-gas‑hydrogen energy","authors":"Haotian Wu , Deping Ke , Lin Song , Jian Xu , Siyang Liao , Lei Wang","doi":"10.1016/j.apenergy.2025.125793","DOIUrl":"10.1016/j.apenergy.2025.125793","url":null,"abstract":"<div><div>The decarbonization transition of the iron and steel industry (ISI) necessitates an overshooting of its energy mix from a predominantly coal-consuming to a predominantly renewable energy-consuming one, including wind and hydrogen. This also presents novel challenges to the energy economy, efficiency, and flexibility of low-carbon ISI. To overcome this challenge, this paper proposes a multi-objective and multi-stage planning (MSP) model for ISI coupled with multi-energy forms. The MSP strategy, which considers the stage-adjustable hydrogen proportion (H<sub>2</sub>-CO ratio) used in iron production, is proposed as a means of fully considering energy development at different stages to make optimal equipment configuration. Moreover, a multi-objective capacity planning model is developed to establish energy economic, efficiency and flexibility objectives based on the actual energy policies implemented in China. Finally, an enhanced AUGMECON-R algorithm (EARA) is devised to address the bilinear constraints inherent to the model, thereby facilitating an efficient solution process. The simulation results substantiate the efficacy of the MSP strategy, illustrate the substantial value of the stage-plannable H<sub>2</sub>-CO ratio for ISI's economy and flexibility enhancement, and demonstrate that EARA can markedly enhance solution efficiency while maintaining an acceptable level of accuracy.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"390 ","pages":"Article 125793"},"PeriodicalIF":10.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-05DOI: 10.1016/j.apenergy.2025.125846
Yongsheng Yu , Weibo Zheng , Bing Li , Cunman Zhang , Pingwen Ming
Hydrogen energy, a clean and efficient power source, plays a crucial role in the global transition to sustainable energy. Among various hydrogen energy technologies, proton-exchange membrane fuel cells (PEMFCs) are highly promising owing to their high-power density and low-temperature operation. However, the cold-start performance of PEMFCs under subfreezing conditions remains a significant challenge. Ice formation obstructs transport pathways, disrupts electrochemical reactions, and hinders both thermal and water management. This review provides a comprehensive analysis of recent advancements in PEMFC cold-start research, particularly on material innovations, structural design optimizations, and multi-mode cold-start control strategies. Unlike previous reviews that focus on numerical modeling, experimental analysis, thermal management, or optimization strategies, this paper integrates key mechanisms influencing cold-start performance. These mechanisms include water content regulation, heat transfer enhancement, and ice mitigation techniques. Moreover, various cold-start strategies (including purge-assisted water removal, external load regulation, and hybrid heating) are compared to assess their effectiveness and feasibility in real-world applications. Additionally, the review highlights key challenges affecting cold-start efficiency and outlines future research directions. These include the development of self-regulating hydration membranes, advanced water transport structures, and adaptive multi-phase startup strategies. This paper integrates fundamental principles with practical engineering approaches to outline a roadmap for enhancing PEMFC cold-start technology, particularly for automotive and stationary power applications.
{"title":"A comprehensive review of cold start in proton-exchange membrane fuel cells: Challenges, strategies, and prospects","authors":"Yongsheng Yu , Weibo Zheng , Bing Li , Cunman Zhang , Pingwen Ming","doi":"10.1016/j.apenergy.2025.125846","DOIUrl":"10.1016/j.apenergy.2025.125846","url":null,"abstract":"<div><div>Hydrogen energy, a clean and efficient power source, plays a crucial role in the global transition to sustainable energy. Among various hydrogen energy technologies, proton-exchange membrane fuel cells (PEMFCs) are highly promising owing to their high-power density and low-temperature operation. However, the cold-start performance of PEMFCs under subfreezing conditions remains a significant challenge. Ice formation obstructs transport pathways, disrupts electrochemical reactions, and hinders both thermal and water management. This review provides a comprehensive analysis of recent advancements in PEMFC cold-start research, particularly on material innovations, structural design optimizations, and multi-mode cold-start control strategies. Unlike previous reviews that focus on numerical modeling, experimental analysis, thermal management, or optimization strategies, this paper integrates key mechanisms influencing cold-start performance. These mechanisms include water content regulation, heat transfer enhancement, and ice mitigation techniques. Moreover, various cold-start strategies (including purge-assisted water removal, external load regulation, and hybrid heating) are compared to assess their effectiveness and feasibility in real-world applications. Additionally, the review highlights key challenges affecting cold-start efficiency and outlines future research directions. These include the development of self-regulating hydration membranes, advanced water transport structures, and adaptive multi-phase startup strategies. This paper integrates fundamental principles with practical engineering approaches to outline a roadmap for enhancing PEMFC cold-start technology, particularly for automotive and stationary power applications.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"390 ","pages":""},"PeriodicalIF":10.1,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-04DOI: 10.1016/j.apenergy.2025.125814
Nayeem Rahman , Rodrigo Rabetino , Arto Rajala , Hannu Makkonen
Energy ecosystems increasingly embrace prosumer flexibility to integrate intermittent renewable sources into the energy mix. However, our understanding of actor roles, interactions, and market dynamics related to prosumer flexibility integration remains limited. We address this gap by exploring how prosumer flexibility can facilitate value co-creation among ecosystem actors and the resources necessary for effective integration within the Finnish electricity ecosystem. To this end, we conducted an exploratory single case study in Finland, involving 24 semi-structured interviews, 18 with key stakeholders and six with flexibility platform operators active in various European markets. Our results reveal several challenges in implementing prosumer flexibility, including barriers to integrating novel actors such as aggregators in the value chain, limitations of rural distribution networks in supporting large-scale flexibility operations, and gaps in energy literacy programs. Despite these challenges, there is a generally optimistic outlook toward prosumer flexibility adoption. We further contribute to the energy prosumption literature by incorporating the Service-Dominant Logic concept into prosumer driven value co-creation. We identify a critical phase of ‘resource harmonization,’ where emerging and incumbent actors align their resources to adopt novel energy technologies and provide a comprehensive framework for facilitating value co-creation through integrating these technologies.
{"title":"Prosumer flexibility as an enabler for ecosystem value co-creation: A resource integration approach from the Finnish electricity markets","authors":"Nayeem Rahman , Rodrigo Rabetino , Arto Rajala , Hannu Makkonen","doi":"10.1016/j.apenergy.2025.125814","DOIUrl":"10.1016/j.apenergy.2025.125814","url":null,"abstract":"<div><div>Energy ecosystems increasingly embrace prosumer flexibility to integrate intermittent renewable sources into the energy mix. However, our understanding of actor roles, interactions, and market dynamics related to prosumer flexibility integration remains limited. We address this gap by exploring how prosumer flexibility can facilitate value co-creation among ecosystem actors and the resources necessary for effective integration within the Finnish electricity ecosystem. To this end, we conducted an exploratory single case study in Finland, involving 24 semi-structured interviews, 18 with key stakeholders and six with flexibility platform operators active in various European markets. Our results reveal several challenges in implementing prosumer flexibility, including barriers to integrating novel actors such as aggregators in the value chain, limitations of rural distribution networks in supporting large-scale flexibility operations, and gaps in energy literacy programs. Despite these challenges, there is a generally optimistic outlook toward prosumer flexibility adoption. We further contribute to the energy prosumption literature by incorporating the Service-Dominant Logic concept into prosumer driven value co-creation. We identify a critical phase of ‘resource harmonization,’ where emerging and incumbent actors align their resources to adopt novel energy technologies and provide a comprehensive framework for facilitating value co-creation through integrating these technologies.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"390 ","pages":"Article 125814"},"PeriodicalIF":10.1,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-04DOI: 10.1016/j.apenergy.2025.125800
Jihan Zhuang , Amadeus Bach , Bruis H.C. van Vlijmen , Stefan J. Reichelstein , William Chueh , Simona Onori , Sally M. Benson
The growth of electric vehicles (EVs) has raised concerns about the disposition of their batteries once they reach the end of their life. Currently, recycling is regarded as the potential solution for retired Li-ion batteries (LIBs). However, these LIBs can still be repurposed for other energy storage system (ESS) applications in their “second life” before recycling. Yet, there is no guidance for deciding whether to reuse or recycle them. Here, a technoeconomic decision support model is proposed to evaluate retired batteries from both technical and economic perspectives. Data-driven models are developed and combined with an equivalent circuit model (ECM) to build module-level aging models. Simulations show that limiting the State of Charge (SOC) operating range and charge current in second life applications can extend the lifetime of LIBs. Depending on when and how to use the battery in its second life, the simulated lifetime is between 1–6 years. From an economic perspective, the most profitable application is frequency regulation, which has a value of /kWh. A comprehensive comparison of different end-of-life strategies is presented to demonstrate the most economically way to handle a retired battery.
{"title":"Technoeconomic decision support for second-life batteries","authors":"Jihan Zhuang , Amadeus Bach , Bruis H.C. van Vlijmen , Stefan J. Reichelstein , William Chueh , Simona Onori , Sally M. Benson","doi":"10.1016/j.apenergy.2025.125800","DOIUrl":"10.1016/j.apenergy.2025.125800","url":null,"abstract":"<div><div>The growth of electric vehicles (EVs) has raised concerns about the disposition of their batteries once they reach the end of their life. Currently, recycling is regarded as the potential solution for retired Li-ion batteries (LIBs). However, these LIBs can still be repurposed for other energy storage system (ESS) applications in their “second life” before recycling. Yet, there is no guidance for deciding whether to reuse or recycle them. Here, a technoeconomic decision support model is proposed to evaluate retired batteries from both technical and economic perspectives. Data-driven models are developed and combined with an equivalent circuit model (ECM) to build module-level aging models. Simulations show that limiting the State of Charge (SOC) operating range and charge current in second life applications can extend the lifetime of LIBs. Depending on when and how to use the battery in its second life, the simulated lifetime is between 1–6 years. From an economic perspective, the most profitable application is frequency regulation, which has a value of <span><math><mrow><mo>$</mo></mrow></math></span>/kWh. A comprehensive comparison of different end-of-life strategies is presented to demonstrate the most economically way to handle a retired battery.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"390 ","pages":"Article 125800"},"PeriodicalIF":10.1,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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