Pub Date : 2025-02-01Epub Date: 2025-01-20DOI: 10.1016/j.segy.2025.100174
Upeksha Caldera , Andreas Mühlbauer , Mai ElSayed , Arman Aghahosseini , Christian Breyer
About 95% of Egypt is desert and 5% of the land is inhabited by more than 95% of the population. Aim of this research is to show how Egypt can make use of its plentiful renewable resources, available land area, and access to the sea, to establish cost-effective afforestation irrigated with renewable energy-based seawater desalination for land degradation mitigation. This carbon dioxide removal opportunity offers to sequester up to 0.37 GtCO2 annually at an average CO2 sequestration cost of 155 €/tCO2 by mid-century. By 2100, a total of 34 GtCO2 is estimated to be sequestered in an area of 132,500 km2. The CO2 sequestration costs decrease from 420 €/tCO2 in 2030, at the start of the project, to about 80 €/tCO2 by 2100. Regions with cooler climate and closer to the coastline, such as the North Western region of Egypt, offer the least cost CO2 sequestration with values as low as 40–50 €/tCO2 by 2070. The low cost of renewable electricity, especially solar photovoltaics, and the increasing sequestration rate of trees as they mature drive down costs. This research highlights how Egypt can use afforestation with renewable energy-based desalination to sequester CO2 while combatting land degradation and yielding economic benefits.
{"title":"Costs and benefits of afforestation with renewable electricity-based desalination: Case study for Egypt","authors":"Upeksha Caldera , Andreas Mühlbauer , Mai ElSayed , Arman Aghahosseini , Christian Breyer","doi":"10.1016/j.segy.2025.100174","DOIUrl":"10.1016/j.segy.2025.100174","url":null,"abstract":"<div><div>About 95% of Egypt is desert and 5% of the land is inhabited by more than 95% of the population. Aim of this research is to show how Egypt can make use of its plentiful renewable resources, available land area, and access to the sea, to establish cost-effective afforestation irrigated with renewable energy-based seawater desalination for land degradation mitigation. This carbon dioxide removal opportunity offers to sequester up to 0.37 GtCO<sub>2</sub> annually at an average CO<sub>2</sub> sequestration cost of 155 €/tCO<sub>2</sub> by mid-century. By 2100, a total of 34 GtCO<sub>2</sub> is estimated to be sequestered in an area of 132,500 km<sup>2</sup>. The CO<sub>2</sub> sequestration costs decrease from 420 €/tCO<sub>2</sub> in 2030, at the start of the project, to about 80 €/tCO<sub>2</sub> by 2100. Regions with cooler climate and closer to the coastline, such as the North Western region of Egypt, offer the least cost CO<sub>2</sub> sequestration with values as low as 40–50 €/tCO<sub>2</sub> by 2070. The low cost of renewable electricity, especially solar photovoltaics, and the increasing sequestration rate of trees as they mature drive down costs. This research highlights how Egypt can use afforestation with renewable energy-based desalination to sequester CO<sub>2</sub> while combatting land degradation and yielding economic benefits.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"17 ","pages":"Article 100174"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154610","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 : 2025-02-01Epub Date: 2024-11-29DOI: 10.1016/j.segy.2024.100170
Maximilian Roth, Stephan Harmuth, Stephan Rinderknecht
Decentralized energy systems like microgrids can be a favourable alternative to the centralized organisation of the current energy supply system. An important problem regarding microgrids is the optimisation of their operational strategy, although most works assume time-independent behaviour of microgrid components in optimisation models. Therefore, the goal of this study is the integration of the dynamic behaviour of a Gas Stirling engine combined heat and power plant and an auxiliary gas boiler in the operational planning problem of a hybrid microgrid. A dynamic optimisation model is developed and compared to a static and approximated model based on the results of three different test scenarios. The simulation results show that the integration of dynamic component characteristics has a significant impact on the operational strategy. The resulting setpoints for the control of the components are able to consider the transient behaviour of these components and therefore their real behaviour is more accurately represented within the optimisation problem. However, the integration of the dynamic modelling approaches leads to more difficult optimisation problems which require more computational effort. The approximation to a convex quadratic problem represents a good compromise between computation time and setpoint accuracy.
{"title":"Integration of dynamic CHPP and gas boiler behaviour into the convex planning problem for the optimised operation of multimodal microgrids","authors":"Maximilian Roth, Stephan Harmuth, Stephan Rinderknecht","doi":"10.1016/j.segy.2024.100170","DOIUrl":"10.1016/j.segy.2024.100170","url":null,"abstract":"<div><div>Decentralized energy systems like microgrids can be a favourable alternative to the centralized organisation of the current energy supply system. An important problem regarding microgrids is the optimisation of their operational strategy, although most works assume time-independent behaviour of microgrid components in optimisation models. Therefore, the goal of this study is the integration of the dynamic behaviour of a Gas Stirling engine combined heat and power plant and an auxiliary gas boiler in the operational planning problem of a hybrid microgrid. A dynamic optimisation model is developed and compared to a static and approximated model based on the results of three different test scenarios. The simulation results show that the integration of dynamic component characteristics has a significant impact on the operational strategy. The resulting setpoints for the control of the components are able to consider the transient behaviour of these components and therefore their real behaviour is more accurately represented within the optimisation problem. However, the integration of the dynamic modelling approaches leads to more difficult optimisation problems which require more computational effort. The approximation to a convex quadratic problem represents a good compromise between computation time and setpoint accuracy.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"17 ","pages":"Article 100170"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143155048","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 : 2024-11-01Epub Date: 2024-11-20DOI: 10.1016/j.segy.2024.100167
Vladimir Z. Gjorgievski, Natasa Markovska, Brian Vad Mathiesen, Neven Duić
As a significant challenge to sustainable development, climate changes require prompt and coordinated action based on a holistic approach for decarbonizing the energy system. In this framework, accounting for the sectoral interdependencies of the energy system, and their interactions with water and environmental systems is essential. The 18th SDEWES Conference in Dubrovnik, held in September 2023, served as a platform that offers experts the opportunity to exchange ideas on state-of-the-art research on the topic. This special issue of Smart Energy highlights peer-reviewed papers from the conference, covering diverse topics such as the energy-water nexus, innovative funding models for district heating, planning of thermal energy storage, and machine learning-based monitoring for HVAC appliances. These contributions highlight the importance of pursuing an integrated analysis of energy systems and provide valuable insights relevant to spearheading the energy transition.
{"title":"Fostering sustainable development of energy, water and environment through a smart energy framework","authors":"Vladimir Z. Gjorgievski, Natasa Markovska, Brian Vad Mathiesen, Neven Duić","doi":"10.1016/j.segy.2024.100167","DOIUrl":"10.1016/j.segy.2024.100167","url":null,"abstract":"<div><div>As a significant challenge to sustainable development, climate changes require prompt and coordinated action based on a holistic approach for decarbonizing the energy system. In this framework, accounting for the sectoral interdependencies of the energy system, and their interactions with water and environmental systems is essential. The 18th SDEWES Conference in Dubrovnik, held in September 2023, served as a platform that offers experts the opportunity to exchange ideas on state-of-the-art research on the topic. This special issue of Smart Energy highlights peer-reviewed papers from the conference, covering diverse topics such as the energy-water nexus, innovative funding models for district heating, planning of thermal energy storage, and machine learning-based monitoring for HVAC appliances. These contributions highlight the importance of pursuing an integrated analysis of energy systems and provide valuable insights relevant to spearheading the energy transition.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"16 ","pages":"Article 100167"},"PeriodicalIF":5.4,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143167927","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 : 2024-11-01Epub Date: 2024-10-09DOI: 10.1016/j.segy.2024.100160
Albert Hiesl, Jasmine Ramsebner, Reinhard Haas
<div><div>Due to the great cost decrease of photovoltaics as well as battery storage, especially in the segment of decentralised home storage, the number of grid-connected battery-supported photovoltaic systems being installed in recent years is steadily increasing. However, the scientific community has intensively discussed that lithium-based battery storage systems cannot yet be operated economically in most cases. This paper addresses the level to which the cost of lithium battery storage needs to decrease in order to be economically viable. For this purpose, the economic viability of battery storage systems in single-family buildings, multi-apartment buildings and across-buildings is analysed on the basis of a linear optimisation model and the method of the internal rate of return. The utilisation of the storage system is optimised for different battery and photovoltaic capacities on the basis of generation and consumption. The internal rate of return method is used to compare the savings resulting from the reduced consumption from the electricity grid with the investment costs and the operation and maintenance costs. In order to be able to estimate the influence of the most important parameters a sensitivity analysis is also carried out. The analysis concludes that, depending on the combination of capacities of photovoltaics, battery storage and in relation to the load profile, the battery storage costs would have to drop by at least 85% in order to generate a certain predefined return over a depreciation period of 25 years. Furthermore, the more different load profiles can be covered directly with photovoltaic electricity, e.g. in a multi-apartment building or across buildings, the less electricity needs to be stored and this reduces the benefit and the utilisation of the battery storage and therefore the specific investment costs must further decrease. Another conclusion that emerges from the sensitivity analysis is that the electricity price and the spread between the electricity price and the feed-in tariff have the greatest influence on the investment costs and profitability. Due to limited space for photovoltaics and simultaneously high consumption, self-consumption is already quite high with cross-building utilisation and can no longer be increased to the necessary extent by the battery storage system, which is why the investment costs must also be lower. The novelty of this paper lies in particular in the fact that it deals with the target costs of battery storage systems in various scenarios for certain rates of return. The analyses in this paper are intended to provide a deeper understanding of the framework conditions for the economic operation of a battery storage system in the aforementioned scenarios. However, this paper does not take into account alternative sources of income other than savings on grid consumption. The possibility of time-variable (grid) tariffs, for example, is also not considered in detail in this paper and
{"title":"Economic viability of decentralised battery storage systems for single-family buildings up to cross-building utilisation","authors":"Albert Hiesl, Jasmine Ramsebner, Reinhard Haas","doi":"10.1016/j.segy.2024.100160","DOIUrl":"10.1016/j.segy.2024.100160","url":null,"abstract":"<div><div>Due to the great cost decrease of photovoltaics as well as battery storage, especially in the segment of decentralised home storage, the number of grid-connected battery-supported photovoltaic systems being installed in recent years is steadily increasing. However, the scientific community has intensively discussed that lithium-based battery storage systems cannot yet be operated economically in most cases. This paper addresses the level to which the cost of lithium battery storage needs to decrease in order to be economically viable. For this purpose, the economic viability of battery storage systems in single-family buildings, multi-apartment buildings and across-buildings is analysed on the basis of a linear optimisation model and the method of the internal rate of return. The utilisation of the storage system is optimised for different battery and photovoltaic capacities on the basis of generation and consumption. The internal rate of return method is used to compare the savings resulting from the reduced consumption from the electricity grid with the investment costs and the operation and maintenance costs. In order to be able to estimate the influence of the most important parameters a sensitivity analysis is also carried out. The analysis concludes that, depending on the combination of capacities of photovoltaics, battery storage and in relation to the load profile, the battery storage costs would have to drop by at least 85% in order to generate a certain predefined return over a depreciation period of 25 years. Furthermore, the more different load profiles can be covered directly with photovoltaic electricity, e.g. in a multi-apartment building or across buildings, the less electricity needs to be stored and this reduces the benefit and the utilisation of the battery storage and therefore the specific investment costs must further decrease. Another conclusion that emerges from the sensitivity analysis is that the electricity price and the spread between the electricity price and the feed-in tariff have the greatest influence on the investment costs and profitability. Due to limited space for photovoltaics and simultaneously high consumption, self-consumption is already quite high with cross-building utilisation and can no longer be increased to the necessary extent by the battery storage system, which is why the investment costs must also be lower. The novelty of this paper lies in particular in the fact that it deals with the target costs of battery storage systems in various scenarios for certain rates of return. The analyses in this paper are intended to provide a deeper understanding of the framework conditions for the economic operation of a battery storage system in the aforementioned scenarios. However, this paper does not take into account alternative sources of income other than savings on grid consumption. The possibility of time-variable (grid) tariffs, for example, is also not considered in detail in this paper and ","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"16 ","pages":"Article 100160"},"PeriodicalIF":5.4,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421645","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 : 2024-11-01Epub Date: 2024-09-23DOI: 10.1016/j.segy.2024.100157
Shivaraj Chandrakant Patil , Corinna Schulze-Netzer , Magnus Korpås
In response to the rise in waste crisis and the possibility of energy utilization from waste, there has been increasing interest in waste-to-energy (WtE) conversion technologies, which requires intense scientific attention. There are diverse WtE technologies that apply to different waste types and require multidisciplinary decision support. The paper applies a Multi-criteria Decision Analysis (MCDA) tool to compare their economic, technological, socio-cultural, and environmental aspects to help identify the most promising choice. The comparison used in this study concerns four widely used technologies: Incineration (INC), Anaerobic Digestion (AD), Gasification (GAS), and Pyrolysis (PYR), and one emerging WtE conversion technology, Hydro-thermal Carbonization (HTC). The Comparison criteria are divided into four main criteria and fifteen sub-criteria. The Analytical Hierarchy Process (AHP) model was implemented using ’SuperDecisions’ software to make pairwise comparisons of identified criteria and to rank the WtE technology alternatives. Thirty-two international studies were shortlisted to gather data and provide input into the AHP model. The results show that the environmental factors are prioritized with a priority vector of 0.56. Further, the study concludes that the most suitable WtE technology, based on chosen parameters, is AD, followed by HTC, INC, and PYR with the priority vectors of 0.348, 0.201, 0.162, and 0.148, respectively, provided applicability. The emerging technology, HTC, is found to be the second most suitable technology. Further, the results represent the hierarchy structure arranged so that the main components are divided into sub-components with alternatives at the structure’s base, and the ’SuperDecisions’ model based on this hierarchy can be used in the future to find suitable WtE technology for a specific city with the necessary input for identified main and sub-criteria. This research not only provides a structured comparison of WtE technologies but also offers a scalable AHP framework that can be adapted for specific municipal contexts in future studies. By addressing the diverse needs of decision-makers across different regions, our model contributes to a more nuanced understanding of WtE technology selection and lays the groundwork for incorporating local policies and regulations in subsequent research phases.
{"title":"Current and emerging waste-to-energy technologies: A comparative study with multi-criteria decision analysis","authors":"Shivaraj Chandrakant Patil , Corinna Schulze-Netzer , Magnus Korpås","doi":"10.1016/j.segy.2024.100157","DOIUrl":"10.1016/j.segy.2024.100157","url":null,"abstract":"<div><div>In response to the rise in waste crisis and the possibility of energy utilization from waste, there has been increasing interest in waste-to-energy (WtE) conversion technologies, which requires intense scientific attention. There are diverse WtE technologies that apply to different waste types and require multidisciplinary decision support. The paper applies a Multi-criteria Decision Analysis (MCDA) tool to compare their economic, technological, socio-cultural, and environmental aspects to help identify the most promising choice. The comparison used in this study concerns four widely used technologies: Incineration (INC), Anaerobic Digestion (AD), Gasification (GAS), and Pyrolysis (PYR), and one emerging WtE conversion technology, Hydro-thermal Carbonization (HTC). The Comparison criteria are divided into four main criteria and fifteen sub-criteria. The Analytical Hierarchy Process (AHP) model was implemented using ’SuperDecisions’ software to make pairwise comparisons of identified criteria and to rank the WtE technology alternatives. Thirty-two international studies were shortlisted to gather data and provide input into the AHP model. The results show that the environmental factors are prioritized with a priority vector of 0.56. Further, the study concludes that the most suitable WtE technology, based on chosen parameters, is AD, followed by HTC, INC, and PYR with the priority vectors of 0.348, 0.201, 0.162, and 0.148, respectively, provided applicability. The emerging technology, HTC, is found to be the second most suitable technology. Further, the results represent the hierarchy structure arranged so that the main components are divided into sub-components with alternatives at the structure’s base, and the ’SuperDecisions’ model based on this hierarchy can be used in the future to find suitable WtE technology for a specific city with the necessary input for identified main and sub-criteria. This research not only provides a structured comparison of WtE technologies but also offers a scalable AHP framework that can be adapted for specific municipal contexts in future studies. By addressing the diverse needs of decision-makers across different regions, our model contributes to a more nuanced understanding of WtE technology selection and lays the groundwork for incorporating local policies and regulations in subsequent research phases.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"16 ","pages":"Article 100157"},"PeriodicalIF":5.4,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666955224000273/pdfft?md5=d09ea75c7df06468cfc89c10a57bc0bd&pid=1-s2.0-S2666955224000273-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142315407","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 : 2024-11-01Epub Date: 2024-10-05DOI: 10.1016/j.segy.2024.100161
Elisabeth Andreae , Marianne Petersen , Iva Ridjan Skov , Frederik Dahl Nielsen , Shi You , Henrik W. Bindner
This study explores the integration of offshore wind energy and hydrogen production into the Faroe Islands’ energy system to support decarbonisation efforts, particularly focusing on the maritime sector. The EnergyPLAN model is used to simulate the impact of incorporating green hydrogen, produced via electrolysis, within a closed energy system. The study evaluates different configurations of hydrogen production and their feasibility focusing on electrolyser technologies and placement options (in-turbine, platform-based, and shoreline). The hydrogen produced is intended for ammonia production, replacing 11% of the fossil fuels used in maritime transport by 2030. Results indicate that integrating hydrogen with offshore wind energy can reduce fossil fuel reliance and carbon dioxide emissions. The in-turbine electrolyser setup offers the cost-effective placement option, while the platform setup is the most expensive. Among the three electrolyser technologies evaluated (alkaline, solid oxide and proton exchange membrane), the alkaline electrolyser results in the lowest overall system cost. The findings provide insights into the potential for renewable energy systems in a small island context and contribute to a broader understanding of green hydrogen’s role in energy transitions.
{"title":"The impact of offshore energy hub and hydrogen integration on the Faroe Island’s energy system","authors":"Elisabeth Andreae , Marianne Petersen , Iva Ridjan Skov , Frederik Dahl Nielsen , Shi You , Henrik W. Bindner","doi":"10.1016/j.segy.2024.100161","DOIUrl":"10.1016/j.segy.2024.100161","url":null,"abstract":"<div><div>This study explores the integration of offshore wind energy and hydrogen production into the Faroe Islands’ energy system to support decarbonisation efforts, particularly focusing on the maritime sector. The EnergyPLAN model is used to simulate the impact of incorporating green hydrogen, produced via electrolysis, within a closed energy system. The study evaluates different configurations of hydrogen production and their feasibility focusing on electrolyser technologies and placement options (in-turbine, platform-based, and shoreline). The hydrogen produced is intended for ammonia production, replacing 11% of the fossil fuels used in maritime transport by 2030. Results indicate that integrating hydrogen with offshore wind energy can reduce fossil fuel reliance and carbon dioxide emissions. The in-turbine electrolyser setup offers the cost-effective placement option, while the platform setup is the most expensive. Among the three electrolyser technologies evaluated (alkaline, solid oxide and proton exchange membrane), the alkaline electrolyser results in the lowest overall system cost. The findings provide insights into the potential for renewable energy systems in a small island context and contribute to a broader understanding of green hydrogen’s role in energy transitions.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"16 ","pages":"Article 100161"},"PeriodicalIF":5.4,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421647","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 : 2024-11-01Epub Date: 2024-09-30DOI: 10.1016/j.segy.2024.100159
Chris Hermans, Jad Al Koussa, Tijs Van Oevelen, Dirk Vanhoudt
The topic of this paper is fault detection for district heating substations, which is an important enabler for the transition towards fourth-generation district heating systems. Classical fault detection approaches are often based on anomaly detection, commonly making the implicit assumption that the errors between the measurements and the predictions made by the baseline model are i.i.d. and following an underlying Gaussian distribution. Our analysis shows that this does not hold up in the field, showing clear seasonality in the error over time. We propose to replace the Gaussian error model by a quantile regression model in order to provide a more nuanced fault threshold, conditioned on time and other input variables. Additionally, we observed that properly training the baseline model comes with its own challenges due to this time dependency, which we propose to resolve by employing an ensemble of models, trained on different periods of time. We demonstrate our method on unlabelled operational data obtained from a Swedish district heating operator to illustrate its use in the field. In addition, we validate it on labelled data from our residential lab setup, testing a variety of common faults.
{"title":"Fault detection for district heating substations: Beyond three-sigma approaches","authors":"Chris Hermans, Jad Al Koussa, Tijs Van Oevelen, Dirk Vanhoudt","doi":"10.1016/j.segy.2024.100159","DOIUrl":"10.1016/j.segy.2024.100159","url":null,"abstract":"<div><div>The topic of this paper is fault detection for district heating substations, which is an important enabler for the transition towards fourth-generation district heating systems. Classical fault detection approaches are often based on anomaly detection, commonly making the implicit assumption that the errors between the measurements and the predictions made by the baseline model are i.i.d. and following an underlying Gaussian distribution. Our analysis shows that this does not hold up in the field, showing clear seasonality in the error over time. We propose to replace the Gaussian error model by a quantile regression model in order to provide a more nuanced fault threshold, conditioned on time and other input variables. Additionally, we observed that properly training the baseline model comes with its own challenges due to this time dependency, which we propose to resolve by employing an ensemble of models, trained on different periods of time. We demonstrate our method on unlabelled operational data obtained from a Swedish district heating operator to illustrate its use in the field. In addition, we validate it on labelled data from our residential lab setup, testing a variety of common faults.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"16 ","pages":"Article 100159"},"PeriodicalIF":5.4,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421646","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 : 2024-11-01Epub Date: 2024-08-30DOI: 10.1016/j.segy.2024.100155
Stepan Vesely, Gloria Amaris, Christian A. Klöckner
Survey research on the adoption of smart energy technologies is growing rapidly, generating important knowledge about factors on the consumer side that may help facilitate transition towards sustainable energy systems. However, much of this research uses survey measures to elicit consumer preferences without explicit consideration of whether and how in-survey experience with the technologies affects preference estimates. For this reason, we experimentally test (for the first time) whether brief in-survey product experience, mainly in the form of additional time spent deliberating about relevant products, influences stated consumer preferences for smart energy monitoring and management apps. Findings obtained in our first experiment conducted in the United Kingdom suggest modest effects of in-survey product experience on consumer preferences, where consumer preferences can be both strengthened or weakened depending on the type of in-survey product experience. These findings are, however, not replicated in our second experiment conducted in Spain. The Spanish experiment, nonetheless, suggests that brief in-survey product experience can help participants make more reasoned choices better reflecting their environmental concern and income constraints. Our results point to possible ways how to improve the reliability of stated preference surveys by providing respondents with adequate in-survey experience with unfamiliar products.
{"title":"The effect of brief in-survey product experience on preferences for smart energy technologies","authors":"Stepan Vesely, Gloria Amaris, Christian A. Klöckner","doi":"10.1016/j.segy.2024.100155","DOIUrl":"10.1016/j.segy.2024.100155","url":null,"abstract":"<div><p>Survey research on the adoption of smart energy technologies is growing rapidly, generating important knowledge about factors on the consumer side that may help facilitate transition towards sustainable energy systems. However, much of this research uses survey measures to elicit consumer preferences without explicit consideration of whether and how in-survey experience with the technologies affects preference estimates. For this reason, we experimentally test (for the first time) whether brief in-survey product experience, mainly in the form of additional time spent deliberating about relevant products, influences stated consumer preferences for smart energy monitoring and management apps. Findings obtained in our first experiment conducted in the United Kingdom suggest modest effects of in-survey product experience on consumer preferences, where consumer preferences can be both strengthened or weakened depending on the type of in-survey product experience. These findings are, however, not replicated in our second experiment conducted in Spain. The Spanish experiment, nonetheless, suggests that brief in-survey product experience can help participants make more reasoned choices better reflecting their environmental concern and income constraints. Our results point to possible ways how to improve the reliability of stated preference surveys by providing respondents with adequate in-survey experience with unfamiliar products.</p></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"16 ","pages":"Article 100155"},"PeriodicalIF":5.4,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266695522400025X/pdfft?md5=13e902ec5ea4db2e6cd8085030831554&pid=1-s2.0-S266695522400025X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142242720","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 : 2024-11-01Epub Date: 2024-10-22DOI: 10.1016/j.segy.2024.100164
Valentin Kaisermayer , Daniel Muschick , Martin Horn , Gerald Schweiger , Thomas Schwengler , Michael Mörth , Richard Heimrath , Thomas Mach , Michael Herzlieb , Markus Gölles
Retrofitting buildings with predictive control strategies can reduce their energy demand and improve thermal comfort by considering their thermal inertia and future weather conditions. A key challenge is minimizing additional infrastructure, such as sensors and actuators, while ensuring user comfort at all times. This study focuses on retrofitting with intelligent software, incorporating the users’ feedback directly into the control loop. We propose a predictive control strategy using an optimization-based energy management system (EMS) to control thermal zones in an office building. It uses a physically motivated grey-box model to predict and adjust thermal demand, with individual zones modelled using an RC-approach and parameter estimation handled by an unscented Kalman filter (UKF). This reduces deployment effort as the parameters are learned from historical data. The objective function ensures user comfort, penalizes undesirable behaviour and minimizes heating and cooling costs. An internal comfort model, automatically calibrated with user feedback by another UKF, further improves system performance. The practical case study is an office building at the ”Innovation District Inffeld”. Operation of the system for one year yielded significant results compared to conventional control. Thermal comfort was improved by 12% and thermal energy consumption for heating and cooling was reduced by about 35%.
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Pub Date : 2024-11-01Epub Date: 2024-10-16DOI: 10.1016/j.segy.2024.100163
Dhekra Bousnina , Gilles Guerassimoff
This research work introduces a novel approach to energy management in Smart Energy Systems (SES) using Deep Reinforcement Learning (DRL) to optimize the management of flexible energy systems in SES, including heating, cooling and electricity storage systems along with District Heating and Cooling Systems (DHCS). The proposed approach is applied on Meridia Smart Energy (MSE), a french demonstration project for SES. The proposed DRL framework, based on actor–critic architecture, is first applied on a Modelica digital twin that we developed for the MSE SES, and is benchmarked against a rule-based approach. The DRL agent learnt an effective strategy for managing thermal and electrical storage systems, resulting in optimized energy costs within the SES. Notably, the acquired strategy achieved annual cost reduction of at least 5% compared to the rule-based benchmark strategy. Moreover, the near-real time decision-making capabilities of the trained DRL agent provides a significant advantage over traditional optimization methods that require time-consuming re-computation at each decision point. By training the DRL agent on a digital twin of the real-world MSE project, rather than hypothetical simulation models, this study lays the foundation for a pioneering application of DRL in the real-world MSE SES, showcasing its potential for practical implementation.
这项研究工作介绍了一种新颖的智能能源系统（SES）能源管理方法，利用深度强化学习（DRL）优化智能能源系统中灵活能源系统的管理，包括供热、制冷和电力存储系统以及区域供热和制冷系统（DHCS）。所提出的方法适用于法国的 SES 示范项目 Meridia Smart Energy (MSE)。提议的 DRL 框架基于行为批判架构，首先应用于我们为 MSE SES 开发的 Modelica 数字孪生系统，并以基于规则的方法为基准。DRL 代理学习了管理热能和电力存储系统的有效策略，从而优化了 SES 的能源成本。值得注意的是，与基于规则的基准策略相比，所获得的策略实现了每年至少 5% 的成本降低。此外，与需要在每个决策点进行耗时的重新计算的传统优化方法相比，训练有素的 DRL 代理的近实时决策能力具有显著优势。通过在现实世界 MSE 项目的数字孪生而非假设的仿真模型上训练 DRL 代理，本研究为 DRL 在现实世界 MSE SES 中的开创性应用奠定了基础，展示了其实际应用的潜力。
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