Pub Date : 2024-11-02DOI: 10.1016/j.apenergy.2024.124791
Yudan Cheng , Xueyang Geng , Wenjia Tian
This study provides a comprehensive examination of the influence of land misallocation on carbon emissions in urban China, focusing on the relationship between land misallocation, industrial structure, and environmental outcomes from a macroeconomic perspective. Using a cross-regional panel database, the paper calculates the land misallocation index and carbon emissions of construction land, revealing distinct spatial-temporal patterns across regions. To establish a causal relationship, the study employs a two-way fixed-effects model and a two-stage least squares (2SLS) approach, using the 2007 industrial land marketization reform as an instrumental variable. The findings demonstrate that a 1 % increase in the land misallocation index leads to an average increase in carbon emissions of 0.502 %, highlighting the substantial environmental impact of over-allocated industrial land. Through a mediation effect model, the study shows that approximately 16.28 % of the total impact on regional carbon emissions is mediated by changes in industrial structure due to land misallocation. Further analysis reveals that regions with higher levels of land misallocation are more severely affected, and quantile regression results identify a non-linear, inverted U-shaped relationship between land misallocation and carbon emissions across different emission levels. These findings have significant implications for land management policies, industrial development strategies, and environmental governance in China and potentially other developing economies, providing valuable insights for policymakers aiming to balance economic growth with environmental sustainability.
本研究全面考察了中国城市土地错配对碳排放的影响，重点从宏观经济角度分析了土地错配、产业结构和环境结果之间的关系。本文利用跨地区面板数据库，计算了土地错配指数和建设用地碳排放量，揭示了不同地区之间不同的时空模式。为建立因果关系，研究采用了双向固定效应模型和两阶段最小二乘法（2SLS），并将 2007 年工业用地市场化改革作为工具变量。研究结果表明，土地错配指数每增加 1%，碳排放量平均增加 0.502%，凸显了工业用地过度配置对环境的巨大影响。通过中介效应模型，研究表明，在对地区碳排放的总影响中，约有 16.28% 是由土地错配导致的产业结构变化所中介的。进一步的分析表明，土地错配程度越高的地区受到的影响越严重，量子回归结果表明，在不同的排放水平上，土地错配与碳排放之间存在非线性的倒 U 型关系。这些发现对中国以及其他潜在发展中经济体的土地管理政策、工业发展战略和环境治理具有重要意义，为旨在平衡经济增长与环境可持续性的决策者提供了宝贵的见解。
{"title":"Achieving low-carbon production: Impacts of land misallocation and industrial structure in urban China","authors":"Yudan Cheng , Xueyang Geng , Wenjia Tian","doi":"10.1016/j.apenergy.2024.124791","DOIUrl":"10.1016/j.apenergy.2024.124791","url":null,"abstract":"<div><div>This study provides a comprehensive examination of the influence of land misallocation on carbon emissions in urban China, focusing on the relationship between land misallocation, industrial structure, and environmental outcomes from a macroeconomic perspective. Using a cross-regional panel database, the paper calculates the land misallocation index and carbon emissions of construction land, revealing distinct spatial-temporal patterns across regions. To establish a causal relationship, the study employs a two-way fixed-effects model and a two-stage least squares (2SLS) approach, using the 2007 industrial land marketization reform as an instrumental variable. The findings demonstrate that a 1 % increase in the land misallocation index leads to an average increase in carbon emissions of 0.502 %, highlighting the substantial environmental impact of over-allocated industrial land. Through a mediation effect model, the study shows that approximately 16.28 % of the total impact on regional carbon emissions is mediated by changes in industrial structure due to land misallocation. Further analysis reveals that regions with higher levels of land misallocation are more severely affected, and quantile regression results identify a non-linear, inverted U-shaped relationship between land misallocation and carbon emissions across different emission levels. These findings have significant implications for land management policies, industrial development strategies, and environmental governance in China and potentially other developing economies, providing valuable insights for policymakers aiming to balance economic growth with environmental sustainability.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124791"},"PeriodicalIF":10.1,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572652","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 : 2024-11-01DOI: 10.1016/j.apenergy.2024.124775
Arne Lilienkamp , Nils Namockel
Adopting electric vehicles (EVs) and implementing variable electricity tariffs increase peak demand and the risk of congestion in distribution grids. To avert critical grid situations and sidestep expensive grid expansions, Distribution System Operators (DSOs) must have intervention rights, allowing them to curtail charging processes. Various curtailment strategies are possible, varying in spatio-temporal differentiation and possible discrimination. However, evaluating different strategies is complex due to the interplay of economic factors, technical requirements, and regulatory constraints — a complexity not fully addressed in the current literature. Our study introduces a sophisticated model to optimize electric vehicle charging strategies to address this gap. This model considers different tariff schemes (Fixed, Time-of-Use, and Real-Time) and incorporates DSO interventions (basic, variable, and smart) within its optimization framework. Based on the model, we analyze the flexibility demand and total electricity costs from the users’ perspective. Applying our model to a synthetic distribution grid, we find that flexible tariffs offer consumers only marginal economic benefits and increase the risk of grid congestion due to herding behavior. All curtailment strategies effectively alleviate congestion, with variable curtailment featuring spatio-temporal differentiation, approaching optimality regarding flexibility demand. Notably, applying curtailment from the users’ perspective does not lower cost savings significantly.
{"title":"Integrating EVs into distribution grids — Examining the effects of various DSO intervention strategies on optimized charging","authors":"Arne Lilienkamp , Nils Namockel","doi":"10.1016/j.apenergy.2024.124775","DOIUrl":"10.1016/j.apenergy.2024.124775","url":null,"abstract":"<div><div>Adopting electric vehicles (EVs) and implementing variable electricity tariffs increase peak demand and the risk of congestion in distribution grids. To avert critical grid situations and sidestep expensive grid expansions, Distribution System Operators (DSOs) must have intervention rights, allowing them to curtail charging processes. Various curtailment strategies are possible, varying in spatio-temporal differentiation and possible discrimination. However, evaluating different strategies is complex due to the interplay of economic factors, technical requirements, and regulatory constraints — a complexity not fully addressed in the current literature. Our study introduces a sophisticated model to optimize electric vehicle charging strategies to address this gap. This model considers different tariff schemes (Fixed, Time-of-Use, and Real-Time) and incorporates DSO interventions (basic, variable, and smart) within its optimization framework. Based on the model, we analyze the flexibility demand and total electricity costs from the users’ perspective. Applying our model to a synthetic distribution grid, we find that flexible tariffs offer consumers only marginal economic benefits and increase the risk of grid congestion due to herding behavior. All curtailment strategies effectively alleviate congestion, with variable curtailment featuring spatio-temporal differentiation, approaching optimality regarding flexibility demand. Notably, applying curtailment from the users’ perspective does not lower cost savings significantly.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124775"},"PeriodicalIF":10.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572725","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 : 2024-11-01DOI: 10.1016/j.apenergy.2024.124751
Marianne Biéron , Jérôme Le Dréau , Benjamin Haas
In Europe, the building sector accounts for approximately 35 % of the energy-related emissions. Hybrid systems coordinating heat pumps and gas boilers can avoid greenhouse gas (GHG) emissions from carbonized electricity production by providing demand-side flexibility without any service interruption. This work aimed to develop a control strategy for a fleet of hybrid heat pumps to reduce GHG emissions. The electricity and gas consumption of a fleet of 3000 hybrid heat pumps, heating 100,000 dwellings spread throughout France, was evaluated. A Modelica model of a district archetype was simulated in seven cities representative of the French climatic zones to obtain the national heating demand. The marginal emission factor of the electricity consumption was assessed using a French power system model coupled with marginal emission factors for interconnected power systems, which were assessed through linear regressions. Two types of control strategies (prioritizing the heat pump and fuel switch) are evaluated considering 4 different sizing for the heat pump (120 %, 50 %, 35 %, and 20 %). Between July 2018 and June 2019, a strategy prioritizing the heat pumps would have avoided between 8000 and 26,000 tCO2eq for the power system. A strategy switching between the heat pump and the boiler based on the marginal emission factor of the electricity consumption would have avoided around 38,000 tCO2eq, with a limited influence of the sizing of the heat pump.
{"title":"Development of a GHG-based control strategy for a fleet of hybrid heat pumps to decarbonize space heating and domestic hot water","authors":"Marianne Biéron , Jérôme Le Dréau , Benjamin Haas","doi":"10.1016/j.apenergy.2024.124751","DOIUrl":"10.1016/j.apenergy.2024.124751","url":null,"abstract":"<div><div>In Europe, the building sector accounts for approximately 35 % of the energy-related emissions. Hybrid systems coordinating heat pumps and gas boilers can avoid greenhouse gas (GHG) emissions from carbonized electricity production by providing demand-side flexibility without any service interruption. This work aimed to develop a control strategy for a fleet of hybrid heat pumps to reduce GHG emissions. The electricity and gas consumption of a fleet of 3000 hybrid heat pumps, heating 100,000 dwellings spread throughout France, was evaluated. A Modelica model of a district archetype was simulated in seven cities representative of the French climatic zones to obtain the national heating demand. The marginal emission factor of the electricity consumption was assessed using a French power system model coupled with marginal emission factors for interconnected power systems, which were assessed through linear regressions. Two types of control strategies (prioritizing the heat pump and fuel switch) are evaluated considering 4 different sizing for the heat pump (120 %, 50 %, 35 %, and 20 %). Between July 2018 and June 2019, a strategy prioritizing the heat pumps would have avoided between 8000 and 26,000 t<sub>CO2eq</sub> for the power system. A strategy switching between the heat pump and the boiler based on the marginal emission factor of the electricity consumption would have avoided around 38,000 t<sub>CO2eq</sub>, with a limited influence of the sizing of the heat pump.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124751"},"PeriodicalIF":10.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572727","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 : 2024-11-01DOI: 10.1016/j.apenergy.2024.124801
Michael Gleason, Anthony Lopez, Marie Rivers
Visual impacts of wind turbines have been a persistent concern for wind energy development in the United States (US) for decades and remain a major source of project delays and cancellations. Assessments of visual impacts are frequently performed at a local scale for individual projects, but a comprehensive understanding of broader geographic patterns in visual impacts across the US is lacking. This paper presents a visual impact assessment of the existing land-based wind turbine fleet of the contiguous United States (CONUS). The assessment combines geographic information systems and 3D simulation methods to account for key factors driving the visual magnitude of impacts from the installed turbines. The results indicate that, despite the deployment of approximately 70,000 turbines and over 144 gigawatts of land-based wind in the CONUS, the visual impacts are very small when measured as a proportion of land area, population, and sensitive visual resources. Nonetheless, visual impacts are not evenly distributed: people experience a concentrated share in a small number of natural settings, primarily including plains, prairies, and deserts. Finally, we find that although increased density of wind development consistently leads to visual impacts across a greater proportion of land, it does not always lead to impacts to a greater share of the population. These findings suggest that visual impacts from wind energy are generally well-mitigated across the CONUS to date but also highlight the need for a deeper understanding of landscape sensitivity and individual perceptions of wind turbines in the most heavily impacted natural settings.
{"title":"Mapping and characterizing the visual impacts of the existing US wind turbine fleet","authors":"Michael Gleason, Anthony Lopez, Marie Rivers","doi":"10.1016/j.apenergy.2024.124801","DOIUrl":"10.1016/j.apenergy.2024.124801","url":null,"abstract":"<div><div>Visual impacts of wind turbines have been a persistent concern for wind energy development in the United States (US) for decades and remain a major source of project delays and cancellations. Assessments of visual impacts are frequently performed at a local scale for individual projects, but a comprehensive understanding of broader geographic patterns in visual impacts across the US is lacking. This paper presents a visual impact assessment of the existing land-based wind turbine fleet of the contiguous United States (CONUS). The assessment combines geographic information systems and 3D simulation methods to account for key factors driving the visual magnitude of impacts from the installed turbines. The results indicate that, despite the deployment of approximately 70,000 turbines and over 144 gigawatts of land-based wind in the CONUS, the visual impacts are very small when measured as a proportion of land area, population, and sensitive visual resources. Nonetheless, visual impacts are not evenly distributed: people experience a concentrated share in a small number of natural settings, primarily including plains, prairies, and deserts. Finally, we find that although increased density of wind development consistently leads to visual impacts across a greater proportion of land, it does not always lead to impacts to a greater share of the population. These findings suggest that visual impacts from wind energy are generally well-mitigated across the CONUS to date but also highlight the need for a deeper understanding of landscape sensitivity and individual perceptions of wind turbines in the most heavily impacted natural settings.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124801"},"PeriodicalIF":10.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572723","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 : 2024-11-01DOI: 10.1016/j.apenergy.2024.124701
Qianggang Wang , Yiyao Zhou , Bingxin Fan , Jianquan Liao , Tao Huang , Xuefei Zhang , Yao Zou , Niancheng Zhou
To facilitate the seamless integration of renewable energy, bipolar DC distribution networks (Bi-DCDNs) have been widely adopted in various applications, including the Shenzhen Future Building, the Boeing 787 aircraft, and DC LED lighting systems in Singapore. Bi-DCDNs incorporate diverse flexible devices to improve both economic efficiency and security. However, a comprehensive coordination framework considering the regulatory heterogeneity among these flexible devices remains absent. Hence, this paper proposes a hierarchical coordination framework for flexible devices in Bi-DCDNs. More specifically, the upper-level model considers the operational differences of the DC transformer (DCT) in various modes to determine the optimal switching scheme for reducing losses; In the lower-level model, the control parameters of the DCT, energy storage systems (ESSs), and DC electrical springs (DCESs) are coordinated to enhance voltage quality. Furthermore, to accurately capture the steady-state behavior of flexible devices, the hierarchical framework incorporates the Newton-Raphson power flow method. This method formulates a steady-state model for multiple flexible devices and demonstrates the impact of different control modes of DCT on power flow. Subsequently, a genetic algorithm is used to solve the proposed model, ensuring that suboptimal decisions made at the upper level are rectified at the lower level, and vice versa. The numerical results indicate that the proposed framework achieves the optimal operation for both reduced losses and enhanced voltage quality in Bi-DCDNs. Furthermore, it exhibits advantageous applications for Bi-DCDNs with additional DCTs for remote residential communities.
{"title":"Hierarchical optimal operation for bipolar DC distribution networks with remote residential communities","authors":"Qianggang Wang , Yiyao Zhou , Bingxin Fan , Jianquan Liao , Tao Huang , Xuefei Zhang , Yao Zou , Niancheng Zhou","doi":"10.1016/j.apenergy.2024.124701","DOIUrl":"10.1016/j.apenergy.2024.124701","url":null,"abstract":"<div><div>To facilitate the seamless integration of renewable energy, bipolar DC distribution networks (Bi-DCDNs) have been widely adopted in various applications, including the Shenzhen Future Building, the Boeing 787 aircraft, and DC LED lighting systems in Singapore. Bi-DCDNs incorporate diverse flexible devices to improve both economic efficiency and security. However, a comprehensive coordination framework considering the regulatory heterogeneity among these flexible devices remains absent. Hence, this paper proposes a hierarchical coordination framework for flexible devices in Bi-DCDNs. More specifically, the upper-level model considers the operational differences of the DC transformer (DCT) in various modes to determine the optimal switching scheme for reducing losses; In the lower-level model, the control parameters of the DCT, energy storage systems (ESSs), and DC electrical springs (DCESs) are coordinated to enhance voltage quality. Furthermore, to accurately capture the steady-state behavior of flexible devices, the hierarchical framework incorporates the Newton-Raphson power flow method. This method formulates a steady-state model for multiple flexible devices and demonstrates the impact of different control modes of DCT on power flow. Subsequently, a genetic algorithm is used to solve the proposed model, ensuring that suboptimal decisions made at the upper level are rectified at the lower level, and vice versa. The numerical results indicate that the proposed framework achieves the optimal operation for both reduced losses and enhanced voltage quality in Bi-DCDNs. Furthermore, it exhibits advantageous applications for Bi-DCDNs with additional DCTs for remote residential communities.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124701"},"PeriodicalIF":10.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572726","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}
Rapid fluctuations in solar irradiation lead to significant variability in PV power output. Traditional ramp rate control methods use battery energy storage systems to smooth power outputs and provide a more consistent supply to the grid. However, these methods require high initial costs and substantial maintenance. In this study, we propose a novel method for controlling PV power output ramp rates using cooling technology, which is essential to stabilize grid operations and ancillary services. The proposed method adjusts power generation efficiency in real-time by controlling PV panel temperature, leveraging their thermoelectric properties. The effectiveness of our method was validated by simulation based on real-world data, which showed reductions in mean and maximum ramp rates of 43.5% and 76.2%, respectively, compared to traditional battery storage solutions. Notably, these improvements were achieved with a cooling unit having a coefficient of performance of less than 10 and a minimal battery capacity of 20 kWh, highlighting the efficiency of the method and its potential to significantly lower system costs and environmental impacts compared to traditional control strategies.
{"title":"Enhancing grid stability in PV systems: A novel ramp rate control method utilizing PV cooling technology","authors":"Koki Iwabuchi , Daichi Watari , Dafang Zhao , Ittetsu Taniguchi , Francky Catthoor , Takao Onoye","doi":"10.1016/j.apenergy.2024.124737","DOIUrl":"10.1016/j.apenergy.2024.124737","url":null,"abstract":"<div><div>Rapid fluctuations in solar irradiation lead to significant variability in PV power output. Traditional ramp rate control methods use battery energy storage systems to smooth power outputs and provide a more consistent supply to the grid. However, these methods require high initial costs and substantial maintenance. In this study, we propose a novel method for controlling PV power output ramp rates using cooling technology, which is essential to stabilize grid operations and ancillary services. The proposed method adjusts power generation efficiency in real-time by controlling PV panel temperature, leveraging their thermoelectric properties. The effectiveness of our method was validated by simulation based on real-world data, which showed reductions in mean and maximum ramp rates of 43.5% and 76.2%, respectively, compared to traditional battery storage solutions. Notably, these improvements were achieved with a cooling unit having a coefficient of performance of less than 10 and a minimal battery capacity of 20 kWh, highlighting the efficiency of the method and its potential to significantly lower system costs and environmental impacts compared to traditional control strategies.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124737"},"PeriodicalIF":10.1,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572724","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 : 2024-10-31DOI: 10.1016/j.apenergy.2024.124724
Fallon Colberts , Sara Bouguerra , Arnaud Wieclawski , Marta Casasola Paesa , Wim Brand , Sven Mullenders , Hareim Ahmed , Richard de Jong , Tatjana Vavilkin , Wim van de Wall , Christian Mass-Protzen , Jeroen Bergman , Jörgen Boumans , Michaël Daenen , Zeger Vroon
Photovoltaic noise barriers (PVNB) offer dual functionality in reducing traffic noise and generating renewable electricity. In this research, the potential of ZigZag PVNBs has been investigated. The ZigZag Solar product, developed by Wallvision, has proven to offer multiple advantages in energy yield and aesthetics for building façade applications. For noise barrier applications, the ZigZag structure could offer interesting features in safety and noise cancellation (obtained by filling the ZigZag construction with Rockwool material) on top of the advantages in aesthetics and energy yield. A ZigZag PVNB has been designed and constructed at the Brightlands Chemelot Campus in Geleen, after which the electrical performance has been automatically monitored under Dutch climate conditions. The measurements have been compared to simulated data, which allowed optimization of the model. As Rockwool material is used in the ZigZag construction, the thermal model had to be optimized to reduce significant differences in measured and simulated VMPP data. Temperature measurements by a novel Fiber Bragg technology revealed that temperature differences between measured cell temperature and input temperature for the simulations are between 10 and 20 °C. After optimizing the thermal model, the power output of the ZigZag PVNB could be predicted more accurately, resulting in a yearly potential energy yield up to 1066 kWh/kWp. Measured data over the period June 2023 till April 2024 showed an energy yield up to 873 kWh/kWp. A deviation of 18 % between measured yearly energy yield can be related to system losses such as cabling and inverters. Life Cycle Assessment (LCA) of several configurations of a global system, including concrete infrastructure, solar panels, ZigZag cassettes, cabling and converters shows a Global Warming Potential (GWP) score varying from 190 to 290 CO2 eq/kWh, according to the models developed in this study, indicating its interest compared to the Dutch and German electricity mixes. In addition, the energy required to produce and install the ZigZag PVNB system at various lengths has a predicted payback time of 6–10 years (maximum 30 % of the total expected lifetime). The balance of system, in specific the DC/DC converters followed and battery system) followed by the concrete element on which the ZigZag PVNB was mounted are the largest contributors to the carbon footprint of the ZigZag PVNB demonstrator. The carbon footprint could potentially be reduced by using cleaner battery technologies or energy storage systems.
{"title":"Performance study and LCA of a ZigZag PV noise barrier: Towards mass-customization of IIPV applications","authors":"Fallon Colberts , Sara Bouguerra , Arnaud Wieclawski , Marta Casasola Paesa , Wim Brand , Sven Mullenders , Hareim Ahmed , Richard de Jong , Tatjana Vavilkin , Wim van de Wall , Christian Mass-Protzen , Jeroen Bergman , Jörgen Boumans , Michaël Daenen , Zeger Vroon","doi":"10.1016/j.apenergy.2024.124724","DOIUrl":"10.1016/j.apenergy.2024.124724","url":null,"abstract":"<div><div>Photovoltaic noise barriers (PVNB) offer dual functionality in reducing traffic noise and generating renewable electricity. In this research, the potential of ZigZag PVNBs has been investigated. The ZigZag Solar product, developed by Wallvision, has proven to offer multiple advantages in energy yield and aesthetics for building façade applications. For noise barrier applications, the ZigZag structure could offer interesting features in safety and noise cancellation (obtained by filling the ZigZag construction with Rockwool material) on top of the advantages in aesthetics and energy yield. A ZigZag PVNB has been designed and constructed at the Brightlands Chemelot Campus in Geleen, after which the electrical performance has been automatically monitored under Dutch climate conditions. The measurements have been compared to simulated data, which allowed optimization of the model. As Rockwool material is used in the ZigZag construction, the thermal model had to be optimized to reduce significant differences in measured and simulated <em>V</em><sub>MPP</sub> data. Temperature measurements by a novel Fiber Bragg technology revealed that temperature differences between measured cell temperature and input temperature for the simulations are between 10 and 20 °C. After optimizing the thermal model, the power output of the ZigZag PVNB could be predicted more accurately, resulting in a yearly potential energy yield up to 1066 kWh/kWp. Measured data over the period June 2023 till April 2024 showed an energy yield up to 873 kWh/kWp. A deviation of 18 % between measured yearly energy yield can be related to system losses such as cabling and inverters. Life Cycle Assessment (LCA) of several configurations of a global system, including concrete infrastructure, solar panels, ZigZag cassettes, cabling and converters shows a Global Warming Potential (GWP) score varying from 190 to 290 CO<sub>2</sub> eq/kWh, according to the models developed in this study, indicating its interest compared to the Dutch and German electricity mixes. In addition, the energy required to produce and install the ZigZag PVNB system at various lengths has a predicted payback time of 6–10 years (maximum 30 % of the total expected lifetime). The balance of system, in specific the DC/DC converters followed and battery system) followed by the concrete element on which the ZigZag PVNB was mounted are the largest contributors to the carbon footprint of the ZigZag PVNB demonstrator. The carbon footprint could potentially be reduced by using cleaner battery technologies or energy storage systems.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124724"},"PeriodicalIF":10.1,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142561451","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 : 2024-10-31DOI: 10.1016/j.apenergy.2024.124749
Xuan Liu, Dujuan Yang, Alex Donkers, Bauke de Vries
The imperative of sustainable urban development demands reductions in energy consumption and carbon emissions. Solar energy emerges as a pivotal player in facilitating the vision of energy transition, serving as a significant renewable energy source for the urban sector. To advance the goals of energy transition and carbon neutrality, it is critical to comprehend the photovoltaic (PV) generation planning at the neighbourhood level, as it offers opportunities that do not exist at either the household level or city level. However, there is a lack of studies that focus on the integration of PV energy generation prediction at the neighbourhood level due to the complexity arising from the abundance of data from disparate disciplines. Supporting the estimation process for electric energy generation is important for neighbourhood level grid-resolving energy planning and management. Semantic web technologies present a promising approach to address the challenge. Through this method, we have developed the Neighbourhood Photovoltaic Generation Ontology (NPO), designed to integrate heterogeneous data to facilitate electric energy estimation processes. This approach streamlines PV energy generation estimation and enriches the data structure by improving the interoperability of data across various formats. A case study in the Netherlands validated the methodology using monthly PV energy generation data, demonstrating that our semantic-based framework significantly enhances the estimation process. The findings demonstrate the potential of semantic web technologies for neighbourhood-level energy planning and management, offering a scalable model that can be adapted to other urban settings. Moreover, the research contributes to the body of knowledge by illustrating how linked data can be strategically support energy transition goals and carbon neutrality initiatives at the neighbourhood level.
{"title":"Building sustainable urban energy systems: The role of linked data in photovoltaic generation estimation at neighbourhood level","authors":"Xuan Liu, Dujuan Yang, Alex Donkers, Bauke de Vries","doi":"10.1016/j.apenergy.2024.124749","DOIUrl":"10.1016/j.apenergy.2024.124749","url":null,"abstract":"<div><div>The imperative of sustainable urban development demands reductions in energy consumption and carbon emissions. Solar energy emerges as a pivotal player in facilitating the vision of energy transition, serving as a significant renewable energy source for the urban sector. To advance the goals of energy transition and carbon neutrality, it is critical to comprehend the photovoltaic (PV) generation planning at the neighbourhood level, as it offers opportunities that do not exist at either the household level or city level. However, there is a lack of studies that focus on the integration of PV energy generation prediction at the neighbourhood level due to the complexity arising from the abundance of data from disparate disciplines. Supporting the estimation process for electric energy generation is important for neighbourhood level grid-resolving energy planning and management. Semantic web technologies present a promising approach to address the challenge. Through this method, we have developed the Neighbourhood Photovoltaic Generation Ontology (NPO), designed to integrate heterogeneous data to facilitate electric energy estimation processes. This approach streamlines PV energy generation estimation and enriches the data structure by improving the interoperability of data across various formats. A case study in the Netherlands validated the methodology using monthly PV energy generation data, demonstrating that our semantic-based framework significantly enhances the estimation process. The findings demonstrate the potential of semantic web technologies for neighbourhood-level energy planning and management, offering a scalable model that can be adapted to other urban settings. Moreover, the research contributes to the body of knowledge by illustrating how linked data can be strategically support energy transition goals and carbon neutrality initiatives at the neighbourhood level.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124749"},"PeriodicalIF":10.1,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142561450","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 : 2024-10-31DOI: 10.1016/j.apenergy.2024.124731
Dat-Nguyen Vo , Meng Qi , Chang-Ha Lee , Xunyuan Yin
The Power-to-methanol (PtMe) process faces significant challenges, including high production costs, low energy efficiency, and a lack of systematic and applicable integrated design and superstructure optimization methods. This study proposes advanced integration and machine learning (ML)-based superstructure optimization approaches that aim to enhance the performance of the PtMe process. Alkaline water electrolyzer (AWE), polymer electrolyte membrane electrolyzer (PEM), and solid oxide electrolyzer (SOE) are chosen for investigation due to their high technology readiness levels. The validated mathematical models for these electrolyzers are integrated with other units to form 3 conventional and 12 advanced designs. The conventional designs comprise electrolyzer-based H and CO-to-methanol sections. In contrast, the advanced designs integrate these sections with four waste-utility reutilization strategies, including heat (H), heat and steam (HS), heat and power (HP), and heat, steam, and power (HSP) generations. A techno-economic analysis demonstrates the pivotal role of electrolyzers in the PtMe process. Two deep neural networks (DNN) models are developed to represent the superstructure design of the PtMe process. With marginal training and test errors (0.28% and 1.03%), the one-hot vector-DNN (OHV-DNN) model is selected to formulate four optimization problems, identifying the PtMe-SOE-HSP and PtMe-AWE-HSP designs as optimal solutions for minimizing energy consumption and production cost considering carbon tax. The PtMe-AWE and PtMe-SOE designs are the best candidates among the conventional designs. Compared to the optimal conventional designs, the optimal advanced designs improve the techno-economic-environmental performance by 1.8–29.7%. Additionally, compared to the PtMe-AWE-HSP design, the PtMe-SOE-HSP design achieves a 4.3% reduction in net CO reduction and a 10.2% reduction in energy consumption. Then, an economic analysis reveals the PtMe-SOE-HSP design as the superior design under scenarios of reduced electrolyzer CAPEX and increased electrolyzer lifetime. These findings are valuable for improving the techno-economic-environmental performance of the PtMe process. Moreover, the proposed integration strategies and ML-based superstructure optimization approach hold the promise for enhancing other power-to-liquid processes.
{"title":"Advanced integration strategies and machine learning-based superstructure optimization for Power-to-Methanol","authors":"Dat-Nguyen Vo , Meng Qi , Chang-Ha Lee , Xunyuan Yin","doi":"10.1016/j.apenergy.2024.124731","DOIUrl":"10.1016/j.apenergy.2024.124731","url":null,"abstract":"<div><div>The Power-to-methanol (PtMe) process faces significant challenges, including high production costs, low energy efficiency, and a lack of systematic and applicable integrated design and superstructure optimization methods. This study proposes advanced integration and machine learning (ML)-based superstructure optimization approaches that aim to enhance the performance of the PtMe process. Alkaline water electrolyzer (AWE), polymer electrolyte membrane electrolyzer (PEM), and solid oxide electrolyzer (SOE) are chosen for investigation due to their high technology readiness levels. The validated mathematical models for these electrolyzers are integrated with other units to form 3 conventional and 12 advanced designs. The conventional designs comprise electrolyzer-based H<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> and CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span>-to-methanol sections. In contrast, the advanced designs integrate these sections with four waste-utility reutilization strategies, including heat (H), heat and steam (HS), heat and power (HP), and heat, steam, and power (HSP) generations. A techno-economic analysis demonstrates the pivotal role of electrolyzers in the PtMe process. Two deep neural networks (DNN) models are developed to represent the superstructure design of the PtMe process. With marginal training and test errors (0.28% and 1.03%), the one-hot vector-DNN (OHV-DNN) model is selected to formulate four optimization problems, identifying the PtMe-SOE-HSP and PtMe-AWE-HSP designs as optimal solutions for minimizing energy consumption and production cost considering carbon tax. The PtMe-AWE and PtMe-SOE designs are the best candidates among the conventional designs. Compared to the optimal conventional designs, the optimal advanced designs improve the techno-economic-environmental performance by 1.8–29.7%. Additionally, compared to the PtMe-AWE-HSP design, the PtMe-SOE-HSP design achieves a 4.3% reduction in net CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> reduction and a 10.2% reduction in energy consumption. Then, an economic analysis reveals the PtMe-SOE-HSP design as the superior design under scenarios of reduced electrolyzer CAPEX and increased electrolyzer lifetime. These findings are valuable for improving the techno-economic-environmental performance of the PtMe process. Moreover, the proposed integration strategies and ML-based superstructure optimization approach hold the promise for enhancing other power-to-liquid processes.</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124731"},"PeriodicalIF":10.1,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553144","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 : 2024-10-30DOI: 10.1016/j.apenergy.2024.124754
Xiaoqiang Jiang , Feifei Cao , Hongda Shi , Kai Zhu , Chongwei Zhang
This study analyzes a pendulum-based wave energy converter with multiple degrees of freedom and a rigid hull encapsulation design that enhances robustness and extends lifespan. The kinetic equation of the vertical axis parametric pendulum is proposed alongside the concept of the Prescribed Excitation Model. This model can be applied to evaluate the pendulum's performance in the early design stage at an extremely low cost. A mathematical approximation of this model is derived using the Perturbation Technique. The maximum linear damping obtained from the approximation provides a reference value for the numerical model, reducing the simulation quantity required for optimization. The power assessment of the pendulum through both mathematical approximation and numerical simulation is compared, indicating that the mathematical approximation is reliable for comparing the performance of different pendulums. Finally, a case study reveals that mounting the pendulum upon the mass center of the hull enhances performance. Additionally, the mass of the pendulum and its moment of inertia have less influence on the optimization of the mounting position, suggesting that the optimization process can be divided into two separate parts. The numerical modeling shows that the pendulum under optimal mounting position has the potential to product energy of 6.79 (annually).
{"title":"Optimization of pendulum-based wave energy converter through mathematical approximation","authors":"Xiaoqiang Jiang , Feifei Cao , Hongda Shi , Kai Zhu , Chongwei Zhang","doi":"10.1016/j.apenergy.2024.124754","DOIUrl":"10.1016/j.apenergy.2024.124754","url":null,"abstract":"<div><div>This study analyzes a pendulum-based wave energy converter with multiple degrees of freedom and a rigid hull encapsulation design that enhances robustness and extends lifespan. The kinetic equation of the vertical axis parametric pendulum is proposed alongside the concept of the Prescribed Excitation Model. This model can be applied to evaluate the pendulum's performance in the early design stage at an extremely low cost. A mathematical approximation of this model is derived using the Perturbation Technique. The maximum linear damping obtained from the approximation provides a reference value for the numerical model, reducing the simulation quantity required for optimization. The power assessment of the pendulum through both mathematical approximation and numerical simulation is compared, indicating that the mathematical approximation is reliable for comparing the performance of different pendulums. Finally, a case study reveals that mounting the pendulum upon the mass center of the hull enhances performance. Additionally, the mass of the pendulum and its moment of inertia have less influence on the optimization of the mounting position, suggesting that the optimization process can be divided into two separate parts. The numerical modeling shows that the pendulum under optimal mounting position has the potential to product energy of 6.79 <span><math><mi>MW</mi><mo>∙</mo><mi>h</mi></math></span> (annually).</div></div>","PeriodicalId":246,"journal":{"name":"Applied Energy","volume":"378 ","pages":"Article 124754"},"PeriodicalIF":10.1,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553571","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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