Pub Date : 2024-02-05DOI: 10.3389/fenef.2024.1337606
Tengfei Wei, Yiyang Wang, Jichang Yang
With the rapid development and increased demand for renewable energy sources, standalone hybrid generation systems have become an essential energy solution. Power optimization control is thus critical to achieving the efficient operation and stability of this system. The distributed ADMM (alternating direction method of multipliers)-based approach has the full potential to deal with the power optimization problem of standalone hybrid generation systems. This study uses an optimization algorithm with a Gaussian penalty function, ADMM-ρ, to alternately optimize the power reference values of wind, light, and battery-containing power generation subsystems. The local controller regulates the output power of the converter according to this reference value. This ensures that the wind and photovoltaic power generation subsystem work in load-tracking or maximum power-tracking modes so that the optimal operation of hybrid power generation meets the balance of supply and demand while prolonging the service life of the batteries. Simulation experiments show that the distributed ADMM algorithm can reliably address the power optimization challenge of hybrid power generation systems.
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Pub Date : 2024-02-05DOI: 10.3389/fenef.2024.1337606
Tengfei Wei, Yiyang Wang, Jichang Yang
With the rapid development and increased demand for renewable energy sources, standalone hybrid generation systems have become an essential energy solution. Power optimization control is thus critical to achieving the efficient operation and stability of this system. The distributed ADMM (alternating direction method of multipliers)-based approach has the full potential to deal with the power optimization problem of standalone hybrid generation systems. This study uses an optimization algorithm with a Gaussian penalty function, ADMM-ρ, to alternately optimize the power reference values of wind, light, and battery-containing power generation subsystems. The local controller regulates the output power of the converter according to this reference value. This ensures that the wind and photovoltaic power generation subsystem work in load-tracking or maximum power-tracking modes so that the optimal operation of hybrid power generation meets the balance of supply and demand while prolonging the service life of the batteries. Simulation experiments show that the distributed ADMM algorithm can reliably address the power optimization challenge of hybrid power generation systems.
{"title":"Distributed ADMM power optimal control for standalone hybrid generation systems","authors":"Tengfei Wei, Yiyang Wang, Jichang Yang","doi":"10.3389/fenef.2024.1337606","DOIUrl":"https://doi.org/10.3389/fenef.2024.1337606","url":null,"abstract":"With the rapid development and increased demand for renewable energy sources, standalone hybrid generation systems have become an essential energy solution. Power optimization control is thus critical to achieving the efficient operation and stability of this system. The distributed ADMM (alternating direction method of multipliers)-based approach has the full potential to deal with the power optimization problem of standalone hybrid generation systems. This study uses an optimization algorithm with a Gaussian penalty function, ADMM-ρ, to alternately optimize the power reference values of wind, light, and battery-containing power generation subsystems. The local controller regulates the output power of the converter according to this reference value. This ensures that the wind and photovoltaic power generation subsystem work in load-tracking or maximum power-tracking modes so that the optimal operation of hybrid power generation meets the balance of supply and demand while prolonging the service life of the batteries. Simulation experiments show that the distributed ADMM algorithm can reliably address the power optimization challenge of hybrid power generation systems.","PeriodicalId":497166,"journal":{"name":"Frontiers in Energy Efficiency","volume":"31 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139864792","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 : 2023-11-14DOI: 10.3389/fenef.2023.1302121
Xingqi Liu, Xuan Liu, Angang Zheng, Hao Chen, Jian Dou
Non-intrusive load monitoring (NILM) is a technique used to monitor energy consumption in buildings without requiring hardware installation on individual appliances. This approach offers a cost-effective and scalable solution to enhance energy efficiency and reduce energy usage. Recent advancements in NILM primarily employ deep-learning algorithms for appliance identification. However, the substantial number of parameters in deep learning models presents challenges in quickly and effectively identifying appliances. An effective technique for appliance identification is analyzing the appliances’ voltage-current (V-I) trajectory signature. This research introduces a novel hashing method that learns compact binary codes to achieve highly efficient appliance V-I trajectory identification. Specifically, this paper uses a profound structure to acquire V-I trajectory image features by acquiring multi-level non-linear transformations. Subsequently, we merge these intermediary traits with high-level visual data from the uppermost layer to carry out the V-I trajectory image retrieval process. These condensed codes are subjected to three distinct standards: minimal loss in quantization, uniformly distributed binary components, and autonomous bits that are not interdependent. As a result, the network easily encodes newly acquired query V-I images for appliance identification by propagating them through the network and quantizing the network’s outputs into binary code representations. Through extensive experiments conducted on the PLAID dataset, we demonstrate the promising performance of our approach compared to state-of-the-art methods.
{"title":"Similarity preserving hashing for appliance identification based on V-I trajectory","authors":"Xingqi Liu, Xuan Liu, Angang Zheng, Hao Chen, Jian Dou","doi":"10.3389/fenef.2023.1302121","DOIUrl":"https://doi.org/10.3389/fenef.2023.1302121","url":null,"abstract":"Non-intrusive load monitoring (NILM) is a technique used to monitor energy consumption in buildings without requiring hardware installation on individual appliances. This approach offers a cost-effective and scalable solution to enhance energy efficiency and reduce energy usage. Recent advancements in NILM primarily employ deep-learning algorithms for appliance identification. However, the substantial number of parameters in deep learning models presents challenges in quickly and effectively identifying appliances. An effective technique for appliance identification is analyzing the appliances’ voltage-current (V-I) trajectory signature. This research introduces a novel hashing method that learns compact binary codes to achieve highly efficient appliance V-I trajectory identification. Specifically, this paper uses a profound structure to acquire V-I trajectory image features by acquiring multi-level non-linear transformations. Subsequently, we merge these intermediary traits with high-level visual data from the uppermost layer to carry out the V-I trajectory image retrieval process. These condensed codes are subjected to three distinct standards: minimal loss in quantization, uniformly distributed binary components, and autonomous bits that are not interdependent. As a result, the network easily encodes newly acquired query V-I images for appliance identification by propagating them through the network and quantizing the network’s outputs into binary code representations. Through extensive experiments conducted on the PLAID dataset, we demonstrate the promising performance of our approach compared to state-of-the-art methods.","PeriodicalId":497166,"journal":{"name":"Frontiers in Energy Efficiency","volume":"56 46","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134902110","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 : 2023-10-23DOI: 10.3389/fenef.2023.1250795
Ana Margarida Barreto, Nuno Correia de Brito, Anna Carolina Boechat, Luís Oliveira Martins, Fernando Martins
Introduction: Almost 50% of the European Union’s final energy consumption is used for heating and cooling, 80% of which in buildings. The European Commission recently issued the “Efficiency Energy First Principle,” a formal recommendation to EU countries prioritizing energy efficiency measures over other energy-related investments. Decarbonizing the aging housing stock represents a significant challenge to Southern Europe and the remaining Member States. This exploratory research aims to understand why Portuguese people fail to increase their energy efficiency; it then proposes potential interventions. Several studies have looked into the effect of technology-based and behavior-based strategies (individual, socioeconomic and demographic, as well as contextual factors) regarding residential energy consumption. Few, however, have brought all these factors together in one project as in this case. Methods: We used the integrative COM-B model to investigate three core influences of behavior, namely, capability, opportunity, and motivation in a qualitative analysis of a sample of citizens of one specific Lisbon, Portugal community. The Behavior Change Wheel model was then used to propose interventions that might promote energy-responsible behavior. Results: Our finding suggests that investments in structural strategies, and, above all, in behavioral strategies are needed to achieve efficient residential electricity consumption. Specifically, we found a lack of capability (i.e., people’s physical skills and strength, knowledge, and regulation skills) represented the greatest barrier to energy consumption efficiency. A lack of motivation (involving habits and self-conscious intentions or beliefs) was the least decisive factor in the adoption of efficient energy consumption behaviors. Discussion: We therefore recommend the following interventions: 1) training and enablement addressing residents’ physical capability (primarily the replacement of high consumption equipment); 2) training, restriction, environmental restructuring, and enablement would increase residents’ physical opportunity (arising from poor home insulation and citizens’ lack of financial resources to invest in energy solutions); and 3) education, training, and enablement to change psychological capability (regarding insufficient or confusing energy use information).
{"title":"Why don’t we consume energy more efficiently? a Lisbon Parish council case study","authors":"Ana Margarida Barreto, Nuno Correia de Brito, Anna Carolina Boechat, Luís Oliveira Martins, Fernando Martins","doi":"10.3389/fenef.2023.1250795","DOIUrl":"https://doi.org/10.3389/fenef.2023.1250795","url":null,"abstract":"Introduction: Almost 50% of the European Union’s final energy consumption is used for heating and cooling, 80% of which in buildings. The European Commission recently issued the “Efficiency Energy First Principle,” a formal recommendation to EU countries prioritizing energy efficiency measures over other energy-related investments. Decarbonizing the aging housing stock represents a significant challenge to Southern Europe and the remaining Member States. This exploratory research aims to understand why Portuguese people fail to increase their energy efficiency; it then proposes potential interventions. Several studies have looked into the effect of technology-based and behavior-based strategies (individual, socioeconomic and demographic, as well as contextual factors) regarding residential energy consumption. Few, however, have brought all these factors together in one project as in this case. Methods: We used the integrative COM-B model to investigate three core influences of behavior, namely, capability, opportunity, and motivation in a qualitative analysis of a sample of citizens of one specific Lisbon, Portugal community. The Behavior Change Wheel model was then used to propose interventions that might promote energy-responsible behavior. Results: Our finding suggests that investments in structural strategies, and, above all, in behavioral strategies are needed to achieve efficient residential electricity consumption. Specifically, we found a lack of capability (i.e., people’s physical skills and strength, knowledge, and regulation skills) represented the greatest barrier to energy consumption efficiency. A lack of motivation (involving habits and self-conscious intentions or beliefs) was the least decisive factor in the adoption of efficient energy consumption behaviors. Discussion: We therefore recommend the following interventions: 1) training and enablement addressing residents’ physical capability (primarily the replacement of high consumption equipment); 2) training, restriction, environmental restructuring, and enablement would increase residents’ physical opportunity (arising from poor home insulation and citizens’ lack of financial resources to invest in energy solutions); and 3) education, training, and enablement to change psychological capability (regarding insufficient or confusing energy use information).","PeriodicalId":497166,"journal":{"name":"Frontiers in Energy Efficiency","volume":"5 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135405606","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 : 2023-09-18DOI: 10.3389/fenef.2023.1244106
Asifa Iqbal, Humaira Nazir, Muhammad Ashar Awan
With the rising global temperatures, developing countries are one of the most adversely affected countries by climate change. Furthermore, changes in lifestyle and unsustainable ways of development have resulted in a shift away from passive strategies in the construction industry, which contribute to excessive energy consumption. This demands immediate action to use passive strategies and one of the most widely used passive strategies is shading devices, which can significantly lower the indoor temperature and give the structure the most efficient energy performance. Shading devices were a dominant identity of traditional architecture in Pakistan; however, it has been evident during the past decade the use of such devices has become obsolete due to modernized solutions. This study aims to examine the performance and effectiveness of shading devices in terms of heat gain and daylight levels in residential areas. A comparative case study methodology has been used. The fixed overhanging shading devices of six residential units in Mansehra City, Khyber Pakhtunkhwa province, Pakistan, have been used. Sun angles are calculated through the SketchUp tool Curic Sun to analyze and determine the performance of overhanging in both summers and winters. This article reveals south shading devices as an essential part of houses built before 2,000 in Mansehra City. Though, houses built after 2,000 do not consider using south shading devices to maximize energy use. This study emphasizes considering the type, design, and use of shading devices according to the building’s orientation to improve building performance and energy efficiency.
{"title":"Design of external shading devices in Mansehra, Pakistan and their role in climate change","authors":"Asifa Iqbal, Humaira Nazir, Muhammad Ashar Awan","doi":"10.3389/fenef.2023.1244106","DOIUrl":"https://doi.org/10.3389/fenef.2023.1244106","url":null,"abstract":"With the rising global temperatures, developing countries are one of the most adversely affected countries by climate change. Furthermore, changes in lifestyle and unsustainable ways of development have resulted in a shift away from passive strategies in the construction industry, which contribute to excessive energy consumption. This demands immediate action to use passive strategies and one of the most widely used passive strategies is shading devices, which can significantly lower the indoor temperature and give the structure the most efficient energy performance. Shading devices were a dominant identity of traditional architecture in Pakistan; however, it has been evident during the past decade the use of such devices has become obsolete due to modernized solutions. This study aims to examine the performance and effectiveness of shading devices in terms of heat gain and daylight levels in residential areas. A comparative case study methodology has been used. The fixed overhanging shading devices of six residential units in Mansehra City, Khyber Pakhtunkhwa province, Pakistan, have been used. Sun angles are calculated through the SketchUp tool Curic Sun to analyze and determine the performance of overhanging in both summers and winters. This article reveals south shading devices as an essential part of houses built before 2,000 in Mansehra City. Though, houses built after 2,000 do not consider using south shading devices to maximize energy use. This study emphasizes considering the type, design, and use of shading devices according to the building’s orientation to improve building performance and energy efficiency.","PeriodicalId":497166,"journal":{"name":"Frontiers in Energy Efficiency","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135202590","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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