Pub Date : 2024-10-01DOI: 10.1016/j.ecmx.2024.100738
Abdelkrim Benmehel , Salaheddine Chabab , Arthur Lucas Do Nascimento Rocha , Michael Chepy , Tarik Kousksou
Nowadays, water electrolysis is widely recognized as a crucial step in the transition towards a hydrogen-based economy. Several technologies are available for water electrolysis, and polymer electrolyte membrane (PEM) water electrolyzer offers numerous benefits such as high efficiency, quick response to fluctuations in renewable energy sources, capability to function under high pressure, modular design, ability to handle high current density, and production of high-purity hydrogen with minimal water usage. Numerous modeling methods have been developed in the research literature to describe the operation and performance of PEM electroyzers. Each model has its own advantages and limitations, and is only valid under certain assumptions and running conditions. This article aims to provide an in-depth review of the main factors affecting the performance of PEM technology, as well as provides a comprehensive analysis of PEM system modeling, covering different thermodynamic, electrochemical, energy, momentum, and mass models, and finishing with the physical modeling challenges for PEM technology.
{"title":"PEM water electrolyzer modeling: Issues and reflections","authors":"Abdelkrim Benmehel , Salaheddine Chabab , Arthur Lucas Do Nascimento Rocha , Michael Chepy , Tarik Kousksou","doi":"10.1016/j.ecmx.2024.100738","DOIUrl":"10.1016/j.ecmx.2024.100738","url":null,"abstract":"<div><div>Nowadays, water electrolysis is widely recognized as a crucial step in the transition towards a hydrogen-based economy. Several technologies are available for water electrolysis, and polymer electrolyte membrane (PEM) water electrolyzer offers numerous benefits such as high efficiency, quick response to fluctuations in renewable energy sources, capability to function under high pressure, modular design, ability to handle high current density, and production of high-purity hydrogen with minimal water usage. Numerous modeling methods have been developed in the research literature to describe the operation and performance of PEM electroyzers. Each model has its own advantages and limitations, and is only valid under certain assumptions and running conditions. This article aims to provide an in-depth review of the main factors affecting the performance of PEM technology, as well as provides a comprehensive analysis of PEM system modeling, covering different thermodynamic, electrochemical, energy, momentum, and mass models, and finishing with the physical modeling challenges for PEM technology.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100738"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.ecmx.2024.100752
Mohammad E. Kashan , Alan S. Fung , Amir Hossein Eisapour , John Swift
This study aims to design a highly efficient and applicable air-based photovoltaic-thermal (PVT) collector that maximizes both electrical and thermal energy efficiencies. An innovative industrialization-ready configuration of the air-based PVT system is proposed, utilizing an industrialized heat exchanger (GRIPMetal or GM) as the absorber plate for the PVT air channel. The heat exchanger consists of spikes and cavities to enhance the heat transfer coefficient in the air channel. The proposed heat exchanger plate minimally affects the dimensions and weight of the PVT collector. A numerical model, validated against experimental results, is used to ensure the accuracy of the simulation. The study is followed by a parametric study that investigates the geometric effects of the heat exchanger and air channel, as well as the airflow rate, on the overall performance of the PVT system. It is observed that the utilization of GM plates significantly reduces the average PV panel temperature (with a maximum of 28 ℃ reduction) and enhances the convective heat transfer coefficient in the air channel, the electrical and thermal efficiencies by approximately 164%, 16.1%, and 50%, respectively, when compared to a flat plate PVT collector. The results demonstrate that the proposed PVT collector effectively compensates for the pressure drops and excess fan power consumption at low Reynolds numbers due to the GM heat exchanger, resulting in higher overall system efficiency. The optimal configuration for the proposed PVT system is achieved by employing a low airflow rate, a narrow air channel, and GM spikes of the largest size available.
{"title":"Utilizing novel industrialized heat exchanger plate in air-based photovoltaic/thermal collectors to enhance thermal and electrical efficiency","authors":"Mohammad E. Kashan , Alan S. Fung , Amir Hossein Eisapour , John Swift","doi":"10.1016/j.ecmx.2024.100752","DOIUrl":"10.1016/j.ecmx.2024.100752","url":null,"abstract":"<div><div>This study aims to design a highly efficient and applicable air-based photovoltaic-thermal (PVT) collector that maximizes both electrical and thermal energy efficiencies. An innovative industrialization-ready configuration of the air-based PVT system is proposed, utilizing an industrialized heat exchanger (GRIPMetal or GM) as the absorber plate for the PVT air channel. The heat exchanger consists of spikes and cavities to enhance the heat transfer coefficient in the air channel. The proposed heat exchanger plate minimally affects the dimensions and weight of the PVT collector. A numerical model, validated against experimental results, is used to ensure the accuracy of the simulation. The study is followed by a parametric study that investigates the geometric effects of the heat exchanger and air channel, as well as the airflow rate, on the overall performance of the PVT system. It is observed that the utilization of GM plates significantly reduces the average PV panel temperature (with a maximum of 28 ℃ reduction) and enhances the convective heat transfer coefficient in the air channel, the electrical and thermal efficiencies by approximately 164%, 16.1%, and 50%, respectively, when compared to a flat plate PVT collector. The results demonstrate that the proposed PVT collector effectively compensates for the pressure drops and excess fan power consumption at low Reynolds numbers due to the GM heat exchanger, resulting in higher overall system efficiency. The optimal configuration for the proposed PVT system is achieved by employing a low airflow rate, a narrow air channel, and GM spikes of the largest size available.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100752"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With high energy demand and large available area, agricultural farms offer significant potential for renewable energy investments, like photovoltaic systems and electrical energy storages. However, the profitability of such investments depends strongly on self-consumption, so accurate planning requires computation-intensive simulation and optimization considering local consumption. This study presents a novel methodology for the optimal dimensioning and configuration of photovoltaic systems and electrical energy storages using efficient techniques from continuous non-linear optimization. Combining physical and economic models with measured consumption data, an investment’s net present value over 20 years is maximized. Using gradient-based solver WORHP, the simulation, optimal control, and optimal dimensioning of the local energy system are calculated simultaneously, allowing for efficient computation over an entire year of hourly data to capture both daily and seasonal variations.
The approach is demonstrated with simple use cases, including an exemplary day of a dairy farm’s consumption, for which optimal systems with and without storage achieve 77% and 43% of autarky, respectively. Saturation effects of optimal plant size can be observed when sizes are large enough for optimal self-consumption but not expanded further for grid export. With energy storage, this saturation is reached at higher values. Optimizing photovoltaic plants with different orientations to match the specific consumption patterns characteristic of the dairy farm achieves similar autarky as a single plant while reducing investment costs by more than 20%. While thorough validation and comparison against heuristic methods predominantly used in the field is part of ongoing research, the presented use cases demonstrate the flexibility and efficiency of the proposed method and highlight its promise as a planning tool in the agricultural domain and beyond.
{"title":"Optimal dimensioning of renewable energy generation and storage systems","authors":"Annika Hackenberg , Lars Kappertz , Satish Rapol , Viacheslav Solovievskyi , Christof Büskens","doi":"10.1016/j.ecmx.2024.100773","DOIUrl":"10.1016/j.ecmx.2024.100773","url":null,"abstract":"<div><div>With high energy demand and large available area, agricultural farms offer significant potential for renewable energy investments, like photovoltaic systems and electrical energy storages. However, the profitability of such investments depends strongly on self-consumption, so accurate planning requires computation-intensive simulation and optimization considering local consumption. This study presents a novel methodology for the optimal dimensioning and configuration of photovoltaic systems and electrical energy storages using efficient techniques from continuous non-linear optimization. Combining physical and economic models with measured consumption data, an investment’s net present value over 20 years is maximized. Using gradient-based solver WORHP, the simulation, optimal control, and optimal dimensioning of the local energy system are calculated simultaneously, allowing for efficient computation over an entire year of hourly data to capture both daily and seasonal variations.</div><div>The approach is demonstrated with simple use cases, including an exemplary day of a dairy farm’s consumption, for which optimal systems with and without storage achieve 77% and 43% of autarky, respectively. Saturation effects of optimal plant size can be observed when sizes are large enough for optimal self-consumption but not expanded further for grid export. With energy storage, this saturation is reached at higher values. Optimizing photovoltaic plants with different orientations to match the specific consumption patterns characteristic of the dairy farm achieves similar autarky as a single plant while reducing investment costs by more than 20%. While thorough validation and comparison against heuristic methods predominantly used in the field is part of ongoing research, the presented use cases demonstrate the flexibility and efficiency of the proposed method and highlight its promise as a planning tool in the agricultural domain and beyond.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100773"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Plug-in hybrid electric vehicles (PHEVs) can operate in both charge-depleting (CD) and charge-sustaining (CS) modes offering flexibility to users and potentially playing a critical role in the transition path towards the transport decarbonisation. This study assesses the impact of vehicle and battery ageing on PHEV emissions, energy and fuel consumption, through two approaches: detailed laboratory testing of a representative gasoline PHEV and fleet-wide real-world data analysis. After 47,000 km and two years of driving the aged vehicle exhibited higher CO, NOx, and THC emissions, and lower particle number (PN) emissions due to improved filter efficiency. Laboratory tests revealed a 7 % increase in CD CO2 emissions, a 2.2 % reduction in all electric range, and a 4.8 % decline in battery capacity, indicating battery degradation. Meanwhile, CS CO2 emissions and energy consumption decreased by 2.1 % and 2.8 %, respectively, possibly due to reduced drivetrain friction losses. A fleet-wide analysis of over 1,900 similar PHEVs registered in the European market uncovered a significant gap, up to 3.5 times, between official and real-world CO2 emissions, complicating efforts to assess long-term ageing effects. Annual distance driven correlated with increased real-world CO2 emissions and a decrease in electric drive share (EDS), indicating insufficient battery charging during longer trips. Over two years, PHEVs driven primarily in electric mode showed 5 % higher CO2 emissions, pointing to the possible impact of battery ageing, while those driven mainly in conventional mode saw emissions decrease by 2 %. These findings provide novel insights into how PHEV performance evolves with age, offering critical data for researchers and engineers to better address emissions and battery durability standards as vehicles age.
{"title":"Influence of vehicle and battery ageing and driving modes on emissions and efficiency in Plug-in hybrid vehicles","authors":"Jelica Pavlovic, Alessandro Tansini, Jaime Suarez, Georgios Fontaras","doi":"10.1016/j.ecmx.2024.100776","DOIUrl":"10.1016/j.ecmx.2024.100776","url":null,"abstract":"<div><div>Plug-in hybrid electric vehicles (PHEVs) can operate in both charge-depleting (CD) and charge-sustaining (CS) modes offering flexibility to users and potentially playing a critical role in the transition path towards the transport decarbonisation. This study assesses the impact of vehicle and battery ageing on PHEV emissions, energy and fuel consumption, through two approaches: detailed laboratory testing of a representative gasoline PHEV and fleet-wide real-world data analysis. After 47,000 km and two years of driving the aged vehicle exhibited higher CO, NOx, and THC emissions, and lower particle number (PN) emissions due to improved filter efficiency. Laboratory tests revealed a 7 % increase in CD CO<sub>2</sub> emissions, a 2.2 % reduction in all electric range, and a 4.8 % decline in battery capacity, indicating battery degradation. Meanwhile, CS CO<sub>2</sub> emissions and energy consumption decreased by 2.1 % and 2.8 %, respectively, possibly due to reduced drivetrain friction losses. A fleet-wide analysis of over 1,900 similar PHEVs registered in the European market uncovered a significant gap, up to 3.5 times, between official and real-world CO<sub>2</sub> emissions, complicating efforts to assess long-term ageing effects. Annual distance driven correlated with increased real-world CO<sub>2</sub> emissions and a decrease in electric drive share (EDS), indicating insufficient battery charging during longer trips. Over two years, PHEVs driven primarily in electric mode showed 5 % higher CO<sub>2</sub> emissions, pointing to the possible impact of battery ageing, while those driven mainly in conventional mode saw emissions decrease by 2 %. These findings provide novel insights into how PHEV performance evolves with age, offering critical data for researchers and engineers to better address emissions and battery durability standards as vehicles age.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100776"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.ecmx.2024.100739
Odi Fawwaz Alrebei , Mohammad Alherbawi , Zeineb Thiehmed , Rim Ismail , Mohamed Nasery , Abdulkarem I. Amhamed , Tareq Al-Ansari
Investing in Sustainable Aviation Fuel (SAF) is crucial for reducing the aviation industry’s carbon footprint and mitigating climate change. As global air travel demand increases, SAF offers a viable solution to significantly lower greenhouse gas emissions and enhance energy security, ensuring a more sustainable future for aviation. Additionally, converting biomass, particularly waste materials, into SAF adds value by turning potential environmental liabilities into valuable energy resources, promoting a circular economy and reducing overall waste. This study evaluates the aircraft performance of a novel sustainable aviation fuel (SAF) derived from multiple feedstocks in a hybrid biorefinery. SAF performance is compared to two conventional jet fuels, specifically a blend of 30% kerosene and 70% gasoline and JET-A1. The results demonstrated that the optimal SAF outperformed conventional fuels in terms of both thrust and range. Specifically, SAF exhibited a 17% increase in thrust and a 10% increase in range compared to conventional Jet A1 fuel. This novel fuel did not only mitigate CO2 emissions and achieve a cost reduction of 0.13 to 8.08%, but also exhibited superior aircraft performance. In addition, this fuel also meets the criteria of a “drop-in fuel” as it does not necessitate significant alterations to the currently existing CFM56-7B turbofan engine. This is due to its similar key thermodynamic indicators, such as heat capacities and combustion temperature, which are comparable to those of conventional jet fuels. In addition, this paper identifies the sensitivity of the CFM56–7B turbofan engine fuelled by the novel fuel.
投资可持续航空燃料（SAF）对于减少航空业的碳足迹和减缓气候变化至关重要。随着全球航空旅行需求的增加，可持续航空燃料为大幅降低温室气体排放和提高能源安全提供了可行的解决方案，从而确保航空业拥有更加可持续的未来。此外，将生物质（尤其是废料）转化为 SAF 还能将潜在的环境责任转化为宝贵的能源资源，促进循环经济并减少整体浪费，从而实现增值。本研究评估了一种新型可持续航空燃料（SAF）在混合生物炼制过程中从多种原料中提取的飞机性能。将 SAF 的性能与两种传统喷气燃料（特别是 30% 煤油和 70% 汽油的混合燃料）和 JET-A1 进行了比较。结果表明，最佳 SAF 在推力和航程方面都优于传统燃料。具体来说，与传统的 Jet A1 燃料相比，SAF 的推力增加了 17%，航程增加了 10%。这种新型燃料不仅减少了二氧化碳排放，降低了 0.13% 至 8.08% 的成本，还表现出卓越的飞机性能。此外，这种燃料还符合 "即插即用燃料 "的标准，因为它无需对现有的 CFM56-7B 涡扇发动机进行重大改动。这是因为其关键热力学指标（如热容量和燃烧温度）与传统喷气燃料相似。此外，本文还确定了使用新型燃料的 CFM56-7B 涡扇发动机的敏感性。
{"title":"Aircraft performance of a novel SAF: Lower costs, lower environmental impact, and higher aircraft performance","authors":"Odi Fawwaz Alrebei , Mohammad Alherbawi , Zeineb Thiehmed , Rim Ismail , Mohamed Nasery , Abdulkarem I. Amhamed , Tareq Al-Ansari","doi":"10.1016/j.ecmx.2024.100739","DOIUrl":"10.1016/j.ecmx.2024.100739","url":null,"abstract":"<div><div>Investing in Sustainable Aviation Fuel (SAF) is crucial for reducing the aviation industry’s carbon footprint and mitigating climate change. As global air travel demand increases, SAF offers a viable solution to significantly lower greenhouse gas emissions and enhance energy security, ensuring a more sustainable future for aviation. Additionally, converting biomass, particularly waste materials, into SAF adds value by turning potential environmental liabilities into valuable energy resources, promoting a circular economy and reducing overall waste. This study evaluates the aircraft performance of a novel sustainable aviation fuel (SAF) derived from multiple feedstocks in a hybrid biorefinery. SAF performance is compared to two conventional jet fuels, specifically a blend of 30% kerosene and 70% gasoline and JET-A1. The results demonstrated that the optimal SAF outperformed conventional fuels in terms of both thrust and range. Specifically, SAF exhibited a 17% increase in thrust and a 10% increase in range compared to conventional Jet A1 fuel. This novel fuel did not only mitigate CO<sub>2</sub> emissions and achieve a cost reduction of 0.13 to 8.08%, but also exhibited superior aircraft performance. In addition, this fuel also meets the criteria of a “drop-in fuel” as it does not necessitate significant alterations to the currently existing CFM56-7B turbofan engine. This is due to its similar key thermodynamic indicators, such as heat capacities and combustion temperature, which are comparable to those of conventional jet fuels. In addition, this paper identifies the sensitivity of the CFM56–7B turbofan engine fuelled by the novel fuel.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100739"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.ecmx.2024.100758
A. Hosseinpour
Hybrid electrical vehicles (HEV) should be designed somehow torque is smooth. Because torque ripple not only reduces control precision but also increases elements vibration that causes acoustic noise, mechanical instability and early aging parts. Furthermore, torque per volume should be maximized and heat removal should be accomplished without torque weakening. It is proposed the volume and internal dimensions are determined due to the thermal considerations and maximize torque per volume. The mentioned application is neglected heat removal so volume is constant. Therefore, HEV is manufactured by two objective functions: either minimum fluctuations or maximum average torque. In this paper series hybrid excitation synchronous machine (SHESM) is utilized as HEV. Two-objective optimization problems are solved by MOEA/D, NSGA II, PESA II and SPEA II algorithms based on a two-dimensional (2-D) model. The performance indices of optimal structure are evaluated by 2-D and confirmed by numerical method.
混合动力汽车（HEV）在设计时应确保扭矩平稳。因为扭矩波纹不仅会降低控制精度，还会增加元件振动，从而导致噪音、机械不稳定和零件早期老化。此外，应最大限度地提高单位体积的扭矩，并在不削弱扭矩的情况下实现散热。建议根据热量因素确定体积和内部尺寸，并使单位体积扭矩最大化。上述应用忽略了散热，因此体积不变。因此，混合动力车的制造有两个目标函数：最小波动或最大平均扭矩。本文采用串联混合励磁同步机（SHESM）作为 HEV。基于二维（2-D）模型，采用 MOEA/D、NSGA II、PESA II 和 SPEA II 算法解决了双目标优化问题。优化结构的性能指标通过二维模型进行了评估，并通过数值方法进行了确认。
{"title":"Torque ripple reduction and increasing of torque per volume for hybrid electrical vehicle","authors":"A. Hosseinpour","doi":"10.1016/j.ecmx.2024.100758","DOIUrl":"10.1016/j.ecmx.2024.100758","url":null,"abstract":"<div><div>Hybrid electrical vehicles (HEV) should be designed somehow torque is smooth. Because torque ripple not only reduces control precision but also increases elements vibration that causes acoustic noise, mechanical instability and early aging parts. Furthermore, torque per volume should be maximized and heat removal should be accomplished without torque weakening. It is proposed the volume and internal dimensions are determined due to the thermal considerations and maximize torque per volume. The mentioned application is neglected heat removal so volume is constant. Therefore, HEV is manufactured by two objective functions: either minimum fluctuations or maximum average torque. In this paper series hybrid excitation synchronous machine (SHESM) is utilized as HEV. Two-objective optimization problems are solved by MOEA/D, NSGA II, PESA II and SPEA II algorithms based on a two-dimensional (2-D) model. The performance indices of optimal structure are evaluated by 2-D and confirmed by numerical method.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100758"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.ecmx.2024.100765
Shun Nakayama , Wanglin Yan , Amane Fujita
High-performance buildings (HPBs) are designed to minimize environmental impacts during operation, but ensuring continuous efficiency improvements remains a challenge. Existing energy audit methodologies have been developed with limited support of precise operational data. However, the advent of Building Energy Management Systems (BEMS) and the establishment of de facto industry standards for building service and space usage have enabled energy audits to be conducted at an unprecedented level of detail. Taking advantage of these developments, this study proposes an original integrated approach for HPB by combining a standard energy audit framework with BEMS data. The novel method conducts: (1) detailed energy and water consumption profiling across multiple timescales; (2) benchmarking using data envelopment analysis against other HPBs; (3) building diagnostics to identify further carbon reduction opportunities; and (4) marginal abatement cost analysis to explore economically feasible improvement measures for owners. When specifically applied to an HPB in Tokyo, the findings reveal substantial room for further improvements. At least 10.1% in energy saving potential exists compared to the building’s design performance. Moreover, implementing selected cost-effective measures could economically achieve an 8.9% reduction in CO2 emissions. This multifaceted study makes three key original contributions. First, it develops a systematic energy audit methodology tailored to BEMS-equipped HPBs, enabling granular, spatiotemporal analysis of resource consumption. Second, it extends this framework beyond energy to holistically encompass water consumption. Third, it provides quantitative evidence that even highly-rated HPBs may still have significant remaining potential for operational environmental impact reductions, which can be identified in detail through the proposed approach. Overall, by harnessing BEMS data and industry standards, this research demonstrates a feasible and cost-effective pathway for HPB owners and operators to continuously optimize resource efficiency. As the urgency of climate action intensifies, this innovative approach offers a crucial toolkit for the building sector to enhance its contribution to global sustainability goals.
{"title":"Developing an energy audit methodology for assessing decarbonization potential in high performance buildings","authors":"Shun Nakayama , Wanglin Yan , Amane Fujita","doi":"10.1016/j.ecmx.2024.100765","DOIUrl":"10.1016/j.ecmx.2024.100765","url":null,"abstract":"<div><div>High-performance buildings (HPBs) are designed to minimize environmental impacts during operation, but ensuring continuous efficiency improvements remains a challenge. Existing energy audit methodologies have been developed with limited support of precise operational data. However, the advent of Building Energy Management Systems (BEMS) and the establishment of de facto industry standards for building service and space usage have enabled energy audits to be conducted at an unprecedented level of detail. Taking advantage of these developments, this study proposes an original integrated approach for HPB by combining a standard energy audit framework with BEMS data. The novel method conducts: (1) detailed energy and water consumption profiling across multiple timescales; (2) benchmarking using data envelopment analysis against other HPBs; (3) building diagnostics to identify further carbon reduction opportunities; and (4) marginal abatement cost analysis to explore economically feasible improvement measures for owners. When specifically applied to an HPB in Tokyo, the findings reveal substantial room for further improvements. At least 10.1% in energy saving potential exists compared to the building’s design performance. Moreover, implementing selected cost-effective measures could economically achieve an 8.9% reduction in CO2 emissions. This multifaceted study makes three key original contributions. First, it develops a systematic energy audit methodology tailored to BEMS-equipped HPBs, enabling granular, spatiotemporal analysis of resource consumption. Second, it extends this framework beyond energy to holistically encompass water consumption. Third, it provides quantitative evidence that even highly-rated HPBs may still have significant remaining potential for operational environmental impact reductions, which can be identified in detail through the proposed approach. Overall, by harnessing BEMS data and industry standards, this research demonstrates a feasible and cost-effective pathway for HPB owners and operators to continuously optimize resource efficiency. As the urgency of climate action intensifies, this innovative approach offers a crucial toolkit for the building sector to enhance its contribution to global sustainability goals.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100765"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142540334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a procedure to build a Time of the Week AutoRegressive eXogenous (TOW-ARX) model, indexed with respect to time and day of the week, to characterize heat consumption in tertiary buildings. Models for building heat load characterization and prediction are crucial to enhance energy efficiency. The proposed model can be used for different purposes, e.g., control of indoor climate, or characterization of the thermal response of the building. A case study is described where the TOW-ARX model is used to characterize the energy consumption of a large retail building in Madrid. In order to discard the risk of model overfitting, cross validation is applied using the k-fold technique. The performance of the TOW-ARX model is compared with a set of different models: a reduced version of the model where similar segments are clustered using the k-means method (R-TOW-ARX), a general ARX model, a linear regression steady-state TOW model (TOW-LR), a version of the latter reduced through clustering (R-TOW-LR), and a general multiple linear regression model (LR). The results reveal that ARX-based models notably outperforms the rest. The TOW-ARX model shows the best metrics, but also outnumbers the number of coefficients of the other models by far. The selection of the most suitable model is not straightforward and should depend on the purpose of such model: the TOW-ARX model would arguably be the best for control purposes due to its low mean absolute error, but the ARX model would be preferable for an efficient characterization of the thermal response of a building due to its reduced number of parameters.
{"title":"Time of the week AutoRegressive eXogenous (TOW-ARX) model to predict thermal consumption in a large commercial mall","authors":"Iñigo Lopez-Villamor , Olaia Eguiarte , Beñat Arregi , Roberto Garay-Martinez , Antonio Garrido-Marijuan","doi":"10.1016/j.ecmx.2024.100777","DOIUrl":"10.1016/j.ecmx.2024.100777","url":null,"abstract":"<div><div>This paper proposes a procedure to build a Time of the Week AutoRegressive eXogenous (TOW-ARX) model, indexed with respect to time and day of the week, to characterize heat consumption in tertiary buildings. Models for building heat load characterization and prediction are crucial to enhance energy efficiency. The proposed model can be used for different purposes, e.g., control of indoor climate, or characterization of the thermal response of the building. A case study is described where the TOW-ARX model is used to characterize the energy consumption of a large retail building in Madrid. In order to discard the risk of model overfitting, cross validation is applied using the k-fold technique. The performance of the TOW-ARX model is compared with a set of different models: a reduced version of the model where similar segments are clustered using the k-means method (R-TOW-ARX), a general ARX model, a linear regression steady-state TOW model (TOW-LR), a version of the latter reduced through clustering (R-TOW-LR), and a general multiple linear regression model (LR). The results reveal that ARX-based models notably outperforms the rest. The TOW-ARX model shows the best metrics, but also outnumbers the number of coefficients of the other models by far. The selection of the most suitable model is not straightforward and should depend on the purpose of such model: the TOW-ARX model would arguably be the best for control purposes due to its low mean absolute error, but the ARX model would be preferable for an efficient characterization of the thermal response of a building due to its reduced number of parameters.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100777"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142561339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-01DOI: 10.1016/j.ecmx.2024.100775
Yohanis Tangke Tosuli , Cahyadi , Hafif Dafiqurrohman , Rudi Hermawan , Adi Surjosatyo
Sago-based foods have become a staple food in eastern Indonesia. Sago waste, as a by-product, has the potential to be used as a renewable energy fuel. This research aims to use sago dregs waste as an energy source by converting it into renewable energy using Top Lit Updraft (TULD) fixed bed gasification. Al2O3, a potential solid waste derived from coal fly ash, is also being investigated for use in sago dreg pellets.The two various Al2O3 contents in sago dreg pellets that will be examined with 5 % Al2O3 and 10 % Al2O3. Operational parameters employed in the gasification process involving the TULD reactor, such as gasification temperature, air flow rate, air-to-fuel ratio (AFR), and syngas assessment. According to the results, adding Al2O3 as a catalyst to sago dreg pellets can improve syngas production (H2, CO, and CH4). The most significant alteration is that the average hydrogen gas (H2) content has increased, with the greatest being in 5 % Al2O3 with 31.65 %, and 10 % Al2O3 with 29.94 %. Meanwhile, the CO and CH4 gas content was found to be highest at 10 % Al2O3, with each experiencing an increase in average (CO 4.33 % and CH4 26.45 %) as compared to sago dregs pellets without Al2O3. Finally, sago dregs pellets with an Al2O3 catalyst have a high potential as an alternative energy fuel for internal combustion engines with H2/CO of 1.65 and 1.51 respectively, for 5 % Al2O3 and 10 % Al2O3, with low tar content.
{"title":"Gasification of sago dreg waste in a top-lit updraft fixed bed gasifier: Syngas composition and its effect with additional Al2O3 as catalyst","authors":"Yohanis Tangke Tosuli , Cahyadi , Hafif Dafiqurrohman , Rudi Hermawan , Adi Surjosatyo","doi":"10.1016/j.ecmx.2024.100775","DOIUrl":"10.1016/j.ecmx.2024.100775","url":null,"abstract":"<div><div>Sago-based foods have become a staple food in eastern Indonesia. Sago waste, as a by-product, has the potential to be used as a renewable energy fuel. This research aims to use sago dregs waste as an energy source by converting it into renewable energy using Top Lit Updraft (TULD) fixed bed gasification. Al<sub>2</sub>O<sub>3</sub>, a potential solid waste derived from coal fly ash, is also being investigated for use in sago dreg pellets.The two various Al<sub>2</sub>O<sub>3</sub> contents in sago dreg pellets that will be examined with 5 % Al<sub>2</sub>O<sub>3</sub> and 10 % Al<sub>2</sub>O<sub>3</sub>. Operational parameters employed in the gasification process involving the TULD reactor, such as gasification temperature, air flow rate, air-to-fuel ratio (AFR), and syngas assessment. According to the results, adding Al<sub>2</sub>O<sub>3</sub> as a catalyst to sago dreg pellets can improve syngas production (H<sub>2</sub>, CO, and CH<sub>4</sub>). The most significant alteration is that the average hydrogen gas (H<sub>2</sub>) content has increased, with the greatest being in 5 % Al<sub>2</sub>O<sub>3</sub> with 31.65 %, and 10 % Al<sub>2</sub>O<sub>3</sub> with 29.94 %. Meanwhile, the CO and CH<sub>4</sub> gas content was found to be highest at 10 % Al<sub>2</sub>O<sub>3</sub>, with each experiencing an increase in average (CO 4.33 % and CH<sub>4</sub> 26.45 %) as compared to sago dregs pellets without Al<sub>2</sub>O<sub>3</sub>. Finally, sago dregs pellets with an Al<sub>2</sub>O<sub>3</sub> catalyst have a high potential as an alternative energy fuel for internal combustion engines with H<sub>2</sub>/CO of 1.65 and 1.51 respectively, for 5 % Al<sub>2</sub>O<sub>3</sub> and 10 % Al<sub>2</sub>O<sub>3</sub>, with low tar content.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100775"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The rapid increase in biomass and plastic waste poses significant environmental challenges. Co-pyrolysis of biomass with plastic wastes offers a promising avenue for sustainable waste management and renewable energy generation. This study covers several novel aspects: First, it investigates the impacts of feedstock composition and operating conditions in pyrolysis (individual feedstock) and co-pyrolysis (biomass and plastic wastes). The study reveals that synergistic effects, specifically improved yields and optimized temperature, exist in the co-pyrolysis of biomass and plastic wastes compared to individual feedstock. Secondly, a suitable blended machine learning predictive model (with Random Forest, Gradient Boosting Regressor, and XGBoost) and robust optimization framework are developed to address model accuracy, non-linear interactions, and uncertainties in pyrolysis such as temperature, heating rate, and biomass-to-plastic ratio. This study predicts the bio-oil yield quantitatively (amount) and qualitatively (composition) with high accuracy (R2 > 0.97). Thirdly, key factors contributing to yield include plastic content (18 %) and biomass type (13 %) have been identified through Gini feature importance and Shapley Additive Explanation (SHAP) analysis. Furthermore, multi-objective optimization techniques reveal the most optimal bio-oil yield under specific conditions, supported by uncertainty analysis, which confines bio-oil yield to a range of 30–50 %. Finally, it also demonstrates a case study to find the optimal bio-oil yield and quality conditions using co-pyrolysis of local resources, i.e., biomass (wood and bagasse) and plastic wastes. The case study suggests optimal conditions like > 50 °C heating rate, <50 min pyrolysis time, and > 60 % plastic content in a blend of wood and HDPE. This study assists industries and policymakers to assess and understand the viability of co-pyrolysis, optimal design parameters, and process impacts.
{"title":"Optimizing pyrolysis and Co-Pyrolysis of plastic and biomass using Artificial Intelligence","authors":"Manish Sharma Timilsina , Yuvraj Chaudhary , Prikshya Bhattarai , Bibek Uprety , Dilip Khatiwada","doi":"10.1016/j.ecmx.2024.100783","DOIUrl":"10.1016/j.ecmx.2024.100783","url":null,"abstract":"<div><div>The rapid increase in biomass and plastic waste poses significant environmental challenges. Co-pyrolysis of biomass with plastic wastes offers a promising avenue for sustainable waste management and renewable energy generation. This study covers several novel aspects: First, it investigates the impacts of feedstock composition and operating conditions in pyrolysis (individual feedstock) and co-pyrolysis (biomass and plastic wastes). The study reveals that synergistic effects, specifically improved yields and optimized temperature, exist in the co-pyrolysis of biomass and plastic wastes compared to individual feedstock. Secondly, a suitable blended machine learning predictive model (with Random Forest, Gradient Boosting Regressor, and XGBoost) and robust optimization framework are developed to address model accuracy, non-linear interactions, and uncertainties in pyrolysis such as temperature, heating rate, and biomass-to-plastic ratio. This study predicts the bio-oil yield quantitatively (amount) and qualitatively (composition) with high accuracy (R<sup>2</sup> > 0.97). Thirdly, key factors contributing to yield include plastic content (18 %) and biomass type (13 %) have been identified through Gini feature importance and Shapley Additive Explanation (SHAP) analysis. Furthermore, multi-objective optimization techniques reveal the most optimal bio-oil yield under specific conditions, supported by uncertainty analysis, which confines bio-oil yield to a range of 30–50 %. Finally, it also demonstrates a case study to find the optimal bio-oil yield and quality conditions using co-pyrolysis of local resources, i.e., biomass (wood and bagasse) and plastic wastes. The case study suggests optimal conditions like > 50 °C heating rate, <50 min pyrolysis time, and > 60 % plastic content in a blend of wood and HDPE. This study assists industries and policymakers to assess and understand the viability of co-pyrolysis, optimal design parameters, and process impacts.</div></div>","PeriodicalId":37131,"journal":{"name":"Energy Conversion and Management-X","volume":"24 ","pages":"Article 100783"},"PeriodicalIF":7.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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