Pub Date : 2026-01-24DOI: 10.1016/j.cles.2026.100234
Sikandar Abdul Qadir , Amjad Ali , Md Tasbirul Islam , Muhammad Shahid , Shoaib Ahmed
Energy policies formulated after the Paris agreement place decarbonisation at the core of the energy system. The use of renewable energy resources has become imperative to combat the climate change. The global share of renewable electric capacity grew by 22% in 2024, dominated by solar capacity additions. Solar energy technologies are classified on various factors such as scale, application, technology, and installation. The most economical option is large-scale solar PV (LSPV). This work investigates the role of policies in ensuring LSPV projects’ success. A structured methodology is applied to determine the critical success factors for LSPV projects. Based on the empirical evidence and case studies across selected regions, the paper integrates policies supporting the commercial viability of these projects. It also discusses challenges, opportunities, and proposes recommendations for policymakers, investors, and stakeholders to maximise the potential of LSPV projects. Additionally, the paper presents the case of the Kingdom of Saudi Arabia, highlighting its LSPV potential and key insights from the analysis. A framework is proposed, incorporating successful design considerations from analysed cases to facilitate investment and improve project outcomes of LSPV projects.
{"title":"Critical success factors for large-scale solar projects: Insights for Saudi Arabia’s energy transition","authors":"Sikandar Abdul Qadir , Amjad Ali , Md Tasbirul Islam , Muhammad Shahid , Shoaib Ahmed","doi":"10.1016/j.cles.2026.100234","DOIUrl":"10.1016/j.cles.2026.100234","url":null,"abstract":"<div><div>Energy policies formulated after the Paris agreement place decarbonisation at the core of the energy system. The use of renewable energy resources has become imperative to combat the climate change. The global share of renewable electric capacity grew by 22% in 2024, dominated by solar capacity additions. Solar energy technologies are classified on various factors such as scale, application, technology, and installation. The most economical option is large-scale solar PV (LSPV). This work investigates the role of policies in ensuring LSPV projects’ success. A structured methodology is applied to determine the critical success factors for LSPV projects. Based on the empirical evidence and case studies across selected regions, the paper integrates policies supporting the commercial viability of these projects. It also discusses challenges, opportunities, and proposes recommendations for policymakers, investors, and stakeholders to maximise the potential of LSPV projects. Additionally, the paper presents the case of the Kingdom of Saudi Arabia, highlighting its LSPV potential and key insights from the analysis. A framework is proposed, incorporating successful design considerations from analysed cases to facilitate investment and improve project outcomes of LSPV projects.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"13 ","pages":"Article 100234"},"PeriodicalIF":0.0,"publicationDate":"2026-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037615","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}
Pub Date : 2026-01-20DOI: 10.1016/j.cles.2026.100232
Mahsa Mehrara , Jonas Zetterholm , Andrea Toffolo , Elisabeth Wetterlund
The transition to sustainable transportation fuels requires investment in emerging biomass-to-liquid production pathways under uncertain market and policy conditions. This study applies a real options analysis framework to evaluate the economic viability and timing of investments in biomass- and power-to-liquid pathways by identifying conditions where an investor should invest, defer, or abandon investments. The analysis is conducted for Sweden, reflected by its large biomass base and well-developed forest industry and ambitious defossilization policies. Results indicate that large price gaps between feedstock and produced fuels are not by themselves sufficient to trigger investment; in volatile markets, investors may still defer because the option to wait has economic value. Thus, even at identical price levels across scenarios, outcomes range from commitment to inaction depending on volatility. Moreover, when investments do occur, they are consistently deferred until the final year of the investment window. While modest subsidies may suffice under stable price conditions, volatile markets with high drifts require significantly greater support to counteract the incentive to defer investments. Electricity cost structures and carbon pricing must be targeted to support the transition toward electrified fuel production pathways. The insights from this study can inform the design of policy instruments that align investor incentives with global transition goals.
{"title":"Risk, flexibility, and investment in Fischer–Tropsch fuels: Insights from real options analysis","authors":"Mahsa Mehrara , Jonas Zetterholm , Andrea Toffolo , Elisabeth Wetterlund","doi":"10.1016/j.cles.2026.100232","DOIUrl":"10.1016/j.cles.2026.100232","url":null,"abstract":"<div><div>The transition to sustainable transportation fuels requires investment in emerging biomass-to-liquid production pathways under uncertain market and policy conditions. This study applies a real options analysis framework to evaluate the economic viability and timing of investments in biomass- and power-to-liquid pathways by identifying conditions where an investor should invest, defer, or abandon investments. The analysis is conducted for Sweden, reflected by its large biomass base and well-developed forest industry and ambitious defossilization policies. Results indicate that large price gaps between feedstock and produced fuels are not by themselves sufficient to trigger investment; in volatile markets, investors may still defer because the option to wait has economic value. Thus, even at identical price levels across scenarios, outcomes range from commitment to inaction depending on volatility. Moreover, when investments do occur, they are consistently deferred until the final year of the investment window. While modest subsidies may suffice under stable price conditions, volatile markets with high drifts require significantly greater support to counteract the incentive to defer investments. Electricity cost structures and carbon pricing must be targeted to support the transition toward electrified fuel production pathways. The insights from this study can inform the design of policy instruments that align investor incentives with global transition goals.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"13 ","pages":"Article 100232"},"PeriodicalIF":0.0,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146037616","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}
Pub Date : 2026-01-08DOI: 10.1016/j.cles.2026.100231
Oleg Gaidai , Tao Zhang , Shicheng He , Qianlong Ma , Salwa Noureldine
Thorough experimental research is necessary for the development of green Energy Harvesters (EH), in addition to appropriate safety and reliability studies. The dynamic behavior of a particular galloping EH was studied through a number of wind tunnel experiments, carried out at various realistic wind speeds. Utilizing recently developed multivariate statistical approach, an excessive multivariate dynamic response of an experimental galloping EH was investigated. Majority of existing piezoelectric wind EHs, utilize a cantilever beam support structure. The effective mass, damping coefficient, and cantilever beam stiffness were determined by free vibration tests. Stationary aerodynamic loads were generated through wind tunnel experiments. This case study benchmarks recently developed design concept for the structural reliability analysis of multi-dimensional, nonstationary nonlinear dynamic systems.
Presented case study demonstrates efficiency of combining recently developed multivariate Gaidai reliability method with an accurate deconvolution extrapolation scheme, allowing for accurate estimations of the likelihood of structural damage and dynamic system’s failure. The latter is a distinct practical benefit of the proposed multivariate methodology, since existing structural reliability methodologies often struggle to cope with dynamic system's high dimensionality, along with nonlinear cross-correlations across system parts/dimensions. The aim of this investigation was to establish a baseline for the proposed multivariate structural reliability concept, facilitating the effective retrieval of pertinent statistical information from the underlying measured dataset. System performance or limit state function depends on multiple random variables (e.g., load, resistance, environmental factors).
Engineering relevance: assessing the reliability of high-dimensional structures where failure probabilities are quite low (e.g., less than ). Presented study benchmarked novel multivariate structural reliability concept that is more conservative than existing univariate or bivariate reliability schemes. Proposed deconvolution extrapolation scheme enabled assessment of design valued with four decimal orders of magnitude lower that actually measured data permits, thus enabling device design with over one year service lifetime.
{"title":"Nonstationary multivariate structural damage risk evaluation method for green energy harvesters","authors":"Oleg Gaidai , Tao Zhang , Shicheng He , Qianlong Ma , Salwa Noureldine","doi":"10.1016/j.cles.2026.100231","DOIUrl":"10.1016/j.cles.2026.100231","url":null,"abstract":"<div><div>Thorough experimental research is necessary for the development of green Energy Harvesters (EH), in addition to appropriate safety and reliability studies. The dynamic behavior of a particular galloping EH was studied through a number of wind tunnel experiments, carried out at various realistic wind speeds. Utilizing recently developed multivariate statistical approach, an excessive multivariate dynamic response of an experimental galloping EH was investigated. Majority of existing piezoelectric wind EHs, utilize a cantilever beam support structure. The effective mass, damping coefficient, and cantilever beam stiffness were determined by free vibration tests. Stationary aerodynamic loads were generated through wind tunnel experiments. This case study benchmarks recently developed design concept for the structural reliability analysis of multi-dimensional, nonstationary nonlinear dynamic systems.</div><div>Presented case study demonstrates efficiency of combining recently developed multivariate Gaidai reliability method with an accurate deconvolution extrapolation scheme, allowing for accurate estimations of the likelihood of structural damage and dynamic system’s failure. The latter is a distinct practical benefit of the proposed multivariate methodology, since existing structural reliability methodologies often struggle to cope with dynamic system's high dimensionality, along with nonlinear cross-correlations across system parts/dimensions. The aim of this investigation was to establish a baseline for the proposed multivariate structural reliability concept, facilitating the effective retrieval of pertinent statistical information from the underlying measured dataset. System performance or limit state function depends on multiple random variables (e.g., load, resistance, environmental factors).</div><div><em>Engineering relevance</em>: assessing the reliability of high-dimensional structures where failure probabilities <span><math><msub><mi>P</mi><mi>F</mi></msub></math></span> are quite low (e.g., less than <span><math><msup><mrow><mn>10</mn></mrow><mrow><mo>−</mo><mn>6</mn></mrow></msup></math></span>). Presented study benchmarked novel multivariate structural reliability concept that is more conservative than existing univariate or bivariate reliability schemes. Proposed deconvolution extrapolation scheme enabled assessment of design valued with <span><math><msub><mi>P</mi><mi>F</mi></msub></math></span> four decimal orders of magnitude lower that actually measured data permits, thus enabling device design with over one year service lifetime.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"13 ","pages":"Article 100231"},"PeriodicalIF":0.0,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926482","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}
Pub Date : 2026-01-01DOI: 10.1016/j.cles.2025.100230
Ade Gafar Abdullah , Samsu Arif , Muhammad Kunta Biddinika , Farsha Sabilla Rahman , Mita Maylani , Dadang Mohamad
The accelerating adoption of electric vehicles (EVs) has created an urgent demand for efficient and sustainable charging infrastructure. Among the viable alternatives, photovoltaic (PV)-powered electric vehicle charging stations (EVCS) stand out for their alignment with global decarbonization and renewable energy targets. However, determining optimal EVCS locations requires integrating diverse criteria, including spatial suitability, technical feasibility, environmental impact, socio-economic considerations, and grid connectivity. This study presents a systematic literature review (SLR) of 43 peer-reviewed articles published between 2010 and 2024, applying the PRISMA methodology to examine the use of geographic information systems (GIS) and multi-criteria decision-making (MCDM) approaches in PV-based EVCS site selection. The analysis is structured around five key themes: analytical frameworks, dominant MCDM methods, artificial intelligence (AI) integration, spatial data utilization, and methodological challenges. Results indicate that AHP and TOPSIS are the most widely applied MCDM techniques, enabling structured evaluation of multiple criteria, while GIS is extensively used for spatial visualization, overlay analysis, and suitability mapping. Emerging studies demonstrate the incorporation of AI and machine learning (ML) methods such as Improved whale optimization algorithm (IWOA), particle swarm optimization (PSO), and random forest to enhance site prediction accuracy, adaptability, and planning under uncertainty. Despite methodological progress, gaps remain in the consistent integration of social sustainability dimensions, dynamic real-time data, and empirical model validation. This review contributes by synthesizing current trends, identifying research limitations, and proposing a hybrid GIS–MCDM–AI framework to support future decision-making processes. The insights generated offer practical implications for infrastructure planners and policymakers aiming to scale up context-sensitive, intelligent, and sustainable EVCS deployment worldwide.
{"title":"Geographic information system–based multi-criteria decision framework for siting photovoltaic-powered electric vehicle charging stations","authors":"Ade Gafar Abdullah , Samsu Arif , Muhammad Kunta Biddinika , Farsha Sabilla Rahman , Mita Maylani , Dadang Mohamad","doi":"10.1016/j.cles.2025.100230","DOIUrl":"10.1016/j.cles.2025.100230","url":null,"abstract":"<div><div>The accelerating adoption of electric vehicles (EVs) has created an urgent demand for efficient and sustainable charging infrastructure. Among the viable alternatives, photovoltaic (PV)-powered electric vehicle charging stations (EVCS) stand out for their alignment with global decarbonization and renewable energy targets. However, determining optimal EVCS locations requires integrating diverse criteria, including spatial suitability, technical feasibility, environmental impact, socio-economic considerations, and grid connectivity. This study presents a systematic literature review (SLR) of 43 peer-reviewed articles published between 2010 and 2024, applying the PRISMA methodology to examine the use of geographic information systems (GIS) and multi-criteria decision-making (MCDM) approaches in PV-based EVCS site selection. The analysis is structured around five key themes: analytical frameworks, dominant MCDM methods, artificial intelligence (AI) integration, spatial data utilization, and methodological challenges. Results indicate that AHP and TOPSIS are the most widely applied MCDM techniques, enabling structured evaluation of multiple criteria, while GIS is extensively used for spatial visualization, overlay analysis, and suitability mapping. Emerging studies demonstrate the incorporation of AI and machine learning (ML) methods such as Improved whale optimization algorithm (IWOA), particle swarm optimization (PSO), and random forest to enhance site prediction accuracy, adaptability, and planning under uncertainty. Despite methodological progress, gaps remain in the consistent integration of social sustainability dimensions, dynamic real-time data, and empirical model validation. This review contributes by synthesizing current trends, identifying research limitations, and proposing a hybrid GIS–MCDM–AI framework to support future decision-making processes. The insights generated offer practical implications for infrastructure planners and policymakers aiming to scale up context-sensitive, intelligent, and sustainable EVCS deployment worldwide.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"13 ","pages":"Article 100230"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926472","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}
This study addresses two topical issues: carbon-free power production, on the one hand, and secure and reliable energy supply on the other hand. Undeniably, to integrate increasing shares of renewables into sustainable and competitive electricity systems, “capacity mechanisms”, i.e., a range of solutions aimed at ensuring adequate power capacity, are needed. Clean, dispatchable power generation is one such solution. Specifically, gas turbines fed by green fuels such as hydrogen can be scheduled to provide power when the contribution from solar and wind sources is not enough to meet the demand or in challenging situations, even for a few hours per year. With the idea of retrofitting existing gas turbine (GT) plants to hydrogen combustion, a thermodynamic model was developed by means of Thermoflex® software in a dual context: peaking, with a small, simple-cycle (SC) GT or “load-following”, with a large size combined cycle (CC) with 1 × 1 configuration. In both cases, ad hoc control strategies were implemented to increase thermal efficiency (η) at partial load. Simulations were run on an hourly basis to meet the prescribed load profiles at representative locations, for two typical hot and cold days: computations were carried out assuming 100% hydrogen as fuel, for comparison against conventional natural gas (NG), given the same GT output requirement and environmental condition. This study's novelty stems from these constraints.
The results show that replacing NG with hydrogen combines obvious decarbonization with increases in net power (Pn) and net efficiency (ηn), the magnitude of which depends on the off-design control strategy, which in turn is a function of the GT operating environment. Overall, the largest increase in ηn was quantified at about 0.6 percentage points (pp). Furthermore, the combustor shifted towards leaner conditions so that the maximum cycle temperature does not exceed that with the conventional fuel.
{"title":"Hydrogen impact on gas turbine operating flexibility in simple and combined cycle mode","authors":"Matteo Cappellini, Chiara Castagna, Silvia Ravelli","doi":"10.1016/j.cles.2025.100229","DOIUrl":"10.1016/j.cles.2025.100229","url":null,"abstract":"<div><div>This study addresses two topical issues: carbon-free power production, on the one hand, and secure and reliable energy supply on the other hand. Undeniably, to integrate increasing shares of renewables into sustainable and competitive electricity systems, “capacity mechanisms”, i.e., a range of solutions aimed at ensuring adequate power capacity, are needed. Clean, dispatchable power generation is one such solution. Specifically, gas turbines fed by green fuels such as hydrogen can be scheduled to provide power when the contribution from solar and wind sources is not enough to meet the demand or in challenging situations, even for a few hours per year. With the idea of retrofitting existing gas turbine (GT) plants to hydrogen combustion, a thermodynamic model was developed by means of Thermoflex® software in a dual context: peaking, with a small, simple-cycle (SC) GT or “load-following”, with a large size combined cycle (CC) with 1 × 1 configuration. In both cases, <em>ad hoc</em> control strategies were implemented to increase thermal efficiency (<em>η</em>) at partial load. Simulations were run on an hourly basis to meet the prescribed load profiles at representative locations, for two typical hot and cold days: computations were carried out assuming 100% hydrogen as fuel, for comparison against conventional natural gas (NG), given the same GT output requirement and environmental condition. This study's novelty stems from these constraints.</div><div>The results show that replacing NG with hydrogen combines obvious decarbonization with increases in net power (P<sub>n</sub>) and net efficiency (η<sub>n</sub>), the magnitude of which depends on the off-design control strategy, which in turn is a function of the GT operating environment. Overall, the largest increase in η<sub>n</sub> was quantified at about 0.6 percentage points (pp). Furthermore, the combustor shifted towards leaner conditions so that the maximum cycle temperature does not exceed that with the conventional fuel.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"13 ","pages":"Article 100229"},"PeriodicalIF":0.0,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926485","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}
Pub Date : 2025-12-03DOI: 10.1016/j.cles.2025.100228
Jaroslav Pavelka
Hydrogen logistics remain a bottleneck for sustainable mobility, particularly in off-grid applications where compressed hydrogen and batteries face limits in energy density and infrastructure. This study proposes the first modular ammonia-to-hydrogen propulsion unit engineered for UAVs and ground vehicles. The compact system integrates catalytic cracking of liquid NH₃ at 650–750 °C (Ru/SiO₂ for UAVs, Ni/Al₂O₃ for vehicles), hydrogen purification via Pd/Ag or ceramic membranes, and power conversion through either PEM fuel cells or hydrogen-adapted internal combustion engines. A cartridge-based modular design enables easy replacement of catalysts and membranes, direct adaptation to platform needs, and scalable performance. Modeling indicates that a 200 kg UAV can achieve ranges up to 150 km with 1.2–1.5 kg NH₃ per 100 km. The novelty lies not in the individual processes, but in their first integration into a deployable system architecture optimized for mobility. Coupled with nuclear-sourced ammonia production, this approach outlines a fossil-free pathway that combines high energy density with improved logistics and lifecycle sustainability.
{"title":"Modular ammonia-based hydrogen propulsion for drones and ground vehicles","authors":"Jaroslav Pavelka","doi":"10.1016/j.cles.2025.100228","DOIUrl":"10.1016/j.cles.2025.100228","url":null,"abstract":"<div><div>Hydrogen logistics remain a bottleneck for sustainable mobility, particularly in off-grid applications where compressed hydrogen and batteries face limits in energy density and infrastructure. This study proposes the first modular ammonia-to-hydrogen propulsion unit engineered for UAVs and ground vehicles. The compact system integrates catalytic cracking of liquid NH₃ at 650–750 °C (Ru/SiO₂ for UAVs, Ni/Al₂O₃ for vehicles), hydrogen purification via Pd/Ag or ceramic membranes, and power conversion through either PEM fuel cells or hydrogen-adapted internal combustion engines. A cartridge-based modular design enables easy replacement of catalysts and membranes, direct adaptation to platform needs, and scalable performance. Modeling indicates that a 200 kg UAV can achieve ranges up to 150 km with 1.2–1.5 kg NH₃ per 100 km. The novelty lies not in the individual processes, but in their first integration into a deployable system architecture optimized for mobility. Coupled with nuclear-sourced ammonia production, this approach outlines a fossil-free pathway that combines high energy density with improved logistics and lifecycle sustainability.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"13 ","pages":"Article 100228"},"PeriodicalIF":0.0,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738219","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}
Pub Date : 2025-12-03DOI: 10.1016/j.cles.2025.100226
Richard Arthur , Albert Kotawoke Awopone , Samuel Gyapong
This study assessed the impact of electric vehicle (EV) charging on low voltage (LV) distribution systems at different penetration levels. The existing electric power distribution system of Takoradi, the Western Regional capital city of Ghana was modelled using the power analysis software Electrical Transient and Analysis Program 2019. Load flow analysis was then performed on the low voltage distribution system to further assess the total amount of EVs the distribution system can handle. EV charging impacts on the current LV distribution system was assessed under three different scenarios; current state, minimum and maximum uptakes penetration levels of EVs. Two different EV charger models were employed to represent home charging (HC)-7.4 kW level-2 and fast charging (FC)-50 kW level-3. Voltage variations and transformer loading at twelve substations were meticulously noted in all simulations. The load flow simulation did not show any significant impact on the distribution system at the current state and minimum uptake penetration levels. However, at a maximum penetration level of 1.88 % for HC and 1.11 % for FC, under voltage conditions were observed at most buses with the condition deteriorating to the highest penetration level of 11.63 % and 6.87 % for HC and FC respectively where the system tend to fail. Domestic loads significantly increased along with the increment of EV penetration levels over the years which contributed to total instability of Takoradi Distribution System (TDS). The study revealed that, the impact of EV charging on low voltage networks vary by factors such as vehicle density, power demand and network architecture. In effect, EV charging types, significantly impact load and voltage variables, contributing to network instability in TDS. To address these challenges, integrating renewable energy sources like solar and wind with EV charging infrastructure is recommended to promote grid stability and sustainable energy practices. The findings of this study will assist policy-makers take the appropriate actions needed to manage EV loads.
{"title":"Assessment of the impact of electric vehicle charging on low voltage distribution system in Takoradi","authors":"Richard Arthur , Albert Kotawoke Awopone , Samuel Gyapong","doi":"10.1016/j.cles.2025.100226","DOIUrl":"10.1016/j.cles.2025.100226","url":null,"abstract":"<div><div>This study assessed the impact of electric vehicle (EV) charging on low voltage (LV) distribution systems at different penetration levels. The existing electric power distribution system of Takoradi, the Western Regional capital city of Ghana was modelled using the power analysis software <span><span>Electrical Transient and Analysis Program 2019</span></span>. Load flow analysis was then performed on the low voltage distribution system to further assess the total amount of EVs the distribution system can handle. EV charging impacts on the current LV distribution system was assessed under three different scenarios; current state, minimum and maximum uptakes penetration levels of EVs. Two different EV charger models were employed to represent home charging (HC)-7.4 kW level-2 and fast charging (FC)-50 kW level-3. Voltage variations and transformer loading at twelve substations were meticulously noted in all simulations. The load flow simulation did not show any significant impact on the distribution system at the current state and minimum uptake penetration levels. However, at a maximum penetration level of 1.88 % for HC and 1.11 % for FC, under voltage conditions were observed at most buses with the condition deteriorating to the highest penetration level of 11.63 % and 6.87 % for HC and FC respectively where the system tend to fail. Domestic loads significantly increased along with the increment of EV penetration levels over the years which contributed to total instability of Takoradi Distribution System (TDS). The study revealed that, the impact of EV charging on low voltage networks vary by factors such as vehicle density, power demand and network architecture. In effect, EV charging types, significantly impact load and voltage variables, contributing to network instability in TDS. To address these challenges, integrating renewable energy sources like solar and wind with EV charging infrastructure is recommended to promote grid stability and sustainable energy practices. The findings of this study will assist policy-makers take the appropriate actions needed to manage EV loads.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"13 ","pages":"Article 100226"},"PeriodicalIF":0.0,"publicationDate":"2025-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145926484","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}
Pub Date : 2025-12-02DOI: 10.1016/j.cles.2025.100227
Mercedes Rodríguez, José A. Camacho
This study explores sectoral differences in renewable energy adoption among Small and Medium-Sized Enterprises (SMEs) in the European Union, with a particular focus on the understudied service sector, which has received considerably less attention than industrial and manufacturing activities. Drawing on data from the Flash Eurobarometer 498 on SMEs, Resource Efficiency, and Green Markets, the analysis examines how internal resources, especially financial capacity, and external support—such as public funding and advisory services—shapes renewable energy decisions. The findings reveal that industrial (48.7 %) and manufacturing (48.1 %) SMEs are significantly more likely to plan renewable energy adoption in the near future compared to service-sector SMEs (41.1 %). Internal financial resources emerge as a key driver across all sectors, while the effectiveness of external support varies. In particular, public funding is notably underutilized in the service sector, despite its strategic potential. These sectoral disparities reflect deeper differences in energy consumption patterns, investment priorities, and the perceived returns from renewable energy. The study highlights the need for tailored, sector-specific policy interventions to remove adoption barriers in the service sector and improve the alignment of financial and advisory mechanisms. By identifying the distinct challenges and enablers across sectors, this research contributes to the design of more effective renewable energy policies for SMEs, supporting a more inclusive and sustainable energy transition in line with broader Sustainable Development Goals.
{"title":"Renewable energy adoption in european small and medium-sized enterprises: A comparative sectoral analysis","authors":"Mercedes Rodríguez, José A. Camacho","doi":"10.1016/j.cles.2025.100227","DOIUrl":"10.1016/j.cles.2025.100227","url":null,"abstract":"<div><div>This study explores sectoral differences in renewable energy adoption among Small and Medium-Sized Enterprises (SMEs) in the European Union, with a particular focus on the understudied service sector, which has received considerably less attention than industrial and manufacturing activities. Drawing on data from the Flash Eurobarometer 498 on SMEs, Resource Efficiency, and Green Markets, the analysis examines how internal resources, especially financial capacity, and external support—such as public funding and advisory services—shapes renewable energy decisions. The findings reveal that industrial (48.7 %) and manufacturing (48.1 %) SMEs are significantly more likely to plan renewable energy adoption in the near future compared to service-sector SMEs (41.1 %). Internal financial resources emerge as a key driver across all sectors, while the effectiveness of external support varies. In particular, public funding is notably underutilized in the service sector, despite its strategic potential. These sectoral disparities reflect deeper differences in energy consumption patterns, investment priorities, and the perceived returns from renewable energy. The study highlights the need for tailored, sector-specific policy interventions to remove adoption barriers in the service sector and improve the alignment of financial and advisory mechanisms. By identifying the distinct challenges and enablers across sectors, this research contributes to the design of more effective renewable energy policies for SMEs, supporting a more inclusive and sustainable energy transition in line with broader Sustainable Development Goals.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"13 ","pages":"Article 100227"},"PeriodicalIF":0.0,"publicationDate":"2025-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685875","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}
Pub Date : 2025-12-01DOI: 10.1016/j.cles.2025.100221
Hasanain A. Abdul Wahhab , Miqdam T. Chaichan
This research involves both experimental and numerical studies that explore how different amounts of iron oxide nanoparticles (Fe₃O₄) in biodiesel blends influence combustion in a single cylinder diesel engine. To simulate the engine dynamics and combustion processes, Diesel Engine Fluent, a specialized numerical tool from ANSYS 19.0 software, was employed. Biodiesel blends were tested with three levels of Fe₃O₄ concentration: 50, 100, and 150 ppm. The samples used in these tests were labelled as D100, D80B20, D80B20N50, D80B20N100, and D80B20N150 (D80 stands for 80 % diesel, B20 for 20 % biodiesel, and N for nanoparticle). Various engine loads, ranging from 20 % to 90 %, were examined at speeds between 1100 and 2200 rpm. The presence of nano additives led to a reduction in emissions, attributed to their catalytic effects and enhanced surface area. The findings indicated that the addition of nanoparticles effectively lowered emissions. At a 90 % load, CO₂ emissions decreased by 3 %, 5 %, and 8 % for the D80B20, D80B20N50, D80B20N100, and D80B20N150 blends, respectively. Additionally, the presence of nano-additives also contributed to a decline in CO emissions from these blends. Furthermore, the combustion of the nanoparticle mixtures produced lower NOx emissions compared to the D80B20 blend.
{"title":"Analysing emissions in compression ignition engines powered by diesel blend with bio diesel and nano particles","authors":"Hasanain A. Abdul Wahhab , Miqdam T. Chaichan","doi":"10.1016/j.cles.2025.100221","DOIUrl":"10.1016/j.cles.2025.100221","url":null,"abstract":"<div><div>This research involves both experimental and numerical studies that explore how different amounts of iron oxide nanoparticles (Fe₃O₄) in biodiesel blends influence combustion in a single cylinder diesel engine. To simulate the engine dynamics and combustion processes, Diesel Engine Fluent, a specialized numerical tool from ANSYS 19.0 software, was employed. Biodiesel blends were tested with three levels of Fe₃O₄ concentration: 50, 100, and 150 ppm. The samples used in these tests were labelled as D100, D80B20, D80B20N50, D80B20N100, and D80B20N150 (D80 stands for 80 % diesel, B20 for 20 % biodiesel, and N for nanoparticle). Various engine loads, ranging from 20 % to 90 %, were examined at speeds between 1100 and 2200 rpm. The presence of nano additives led to a reduction in emissions, attributed to their catalytic effects and enhanced surface area. The findings indicated that the addition of nanoparticles effectively lowered emissions. At a 90 % load, CO₂ emissions decreased by 3 %, 5 %, and 8 % for the D80B20, D80B20N50, D80B20N100, and D80B20N150 blends, respectively. Additionally, the presence of nano-additives also contributed to a decline in CO emissions from these blends. Furthermore, the combustion of the nanoparticle mixtures produced lower NOx emissions compared to the D80B20 blend.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100221"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145617413","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}
Pub Date : 2025-12-01DOI: 10.1016/j.cles.2025.100220
Azzeddine Elghomari, Amine Tilioua
This study examines the thermal performance of cement-polystyrene walls, both with and without Phase Change Material (PCM), using a scaled-down thermal cavity with interchangeable sidewalls. The primary objective is to optimize the PCM layer placement within the wall structure by analyzing changes in surface temperature and reductions in heat flux. The results reveal that positioning the PCM layer next to the heat source maximizes latent heat release, thereby improving thermal regulation. Various factors, including the phase transition temperature, heat source temperature, and heat flux density, were taken into account. Experiments conducted at 45 °C, which represents typical summer conditions in the Drâa-Tafilalet Region in south-east Morocco, show that walls enhanced with phase change materials (PCMs) effectively reduce both surface heat flux and temperature. This study underscores the potential of incorporating PCM-enhanced cement-polystyrene walls to enhance thermal performance and energy efficiency in building materials.
{"title":"Optimizing phase change material placement in sustainable building envelopes for enhanced thermal performance","authors":"Azzeddine Elghomari, Amine Tilioua","doi":"10.1016/j.cles.2025.100220","DOIUrl":"10.1016/j.cles.2025.100220","url":null,"abstract":"<div><div>This study examines the thermal performance of cement-polystyrene walls, both with and without Phase Change Material (PCM), using a scaled-down thermal cavity with interchangeable sidewalls. The primary objective is to optimize the PCM layer placement within the wall structure by analyzing changes in surface temperature and reductions in heat flux. The results reveal that positioning the PCM layer next to the heat source maximizes latent heat release, thereby improving thermal regulation. Various factors, including the phase transition temperature, heat source temperature, and heat flux density, were taken into account. Experiments conducted at 45 °C, which represents typical summer conditions in the Drâa-Tafilalet Region in south-east Morocco, show that walls enhanced with phase change materials (PCMs) effectively reduce both surface heat flux and temperature. This study underscores the potential of incorporating PCM-enhanced cement-polystyrene walls to enhance thermal performance and energy efficiency in building materials.</div></div>","PeriodicalId":100252,"journal":{"name":"Cleaner Energy Systems","volume":"12 ","pages":"Article 100220"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145617410","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}
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