Smart EnergyPub Date : 2025-05-01DOI: 10.1016/j.segy.2025.100182
Rade Ciric , Eivind Lundemoen Håkedal , Oddvin Tesaker Pedersen , Knut Ola Dørum
{"title":"Reliability and electrical safety of grid-connected household PV systems: Data-driven risk analysis and insights","authors":"Rade Ciric , Eivind Lundemoen Håkedal , Oddvin Tesaker Pedersen , Knut Ola Dørum","doi":"10.1016/j.segy.2025.100182","DOIUrl":"10.1016/j.segy.2025.100182","url":null,"abstract":"<div><div>Home photovoltaic generators (PVGs) offer many benefits, including reduced energy costs and environmental sustainability. Ensuring electrical safety in PVGs is crucial to prevent hazards such as electric shock, fires, and system malfunctions. As PVG components age, the likelihood of electrical issues increases. This research assesses the reliability of key components and evaluates the risk of electric shock in household PVGs using fault tree analysis. Due to limited data on failure rate of small-scale PVGs, component reliability was analysed based on survey feedback from 85 Norwegian PVG owners. To gain deeper insights into home PVG vulnerabilities, a Simulink model was applied to simulate various faults, including failures in PV modules, inter-string connections, MOSFETs, and both the DC and AC sides of the inverter. The findings indicate that inverters are the most failure-prone components in household PVGs while the residual current devices (RCDs), as critical protection units, also lose reliability over time. These findings underscore the critical importance of implementing a comprehensive suite of protective measures in PVG systems to ensure both safety and reliability, as well as importance of proactive condition monitoring, particularly for the inverter, battery charger, RCD, and insulation resistance.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"18 ","pages":"Article 100182"},"PeriodicalIF":5.4,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144090337","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}
Smart EnergyPub Date : 2025-05-01DOI: 10.1016/j.segy.2025.100183
Lander Mentens , Herbert Peremans , Johan Springael , Philippe Nimmegeers
{"title":"Flexibility in short-term electricity markets for renewable integration and uncertainty mitigation: A comprehensive review","authors":"Lander Mentens , Herbert Peremans , Johan Springael , Philippe Nimmegeers","doi":"10.1016/j.segy.2025.100183","DOIUrl":"10.1016/j.segy.2025.100183","url":null,"abstract":"<div><div>Globally, the share of renewable energy sources in the electricity mix is increasing. However, higher levels of renewable energy sources and especially those with an intermittent nature introduce uncertainty in delivering reliable and secure electricity. Hence, flexibility becomes more important to counteract imbalances between generation and consumption. This review paper contributes to the nuanced ways in which flexibility can be strategically employed to navigate and mitigate uncertainties amid evolving market dynamics and increasing share of renewable sources in the energy mix. It investigates the impact of renewable energy sources on short-term electricity markets, with a specific focus on day-ahead, intraday, and balancing markets in the Central Western Europe region. It explores the design characteristics and parameters of these markets, emphasizing how these markets deal with the uncertainty arising from the limited predictability of renewable resources. In this context, flexibility becomes a crucial element in reducing this uncertainty. The primary objective is to fully understand and analyze the intricate interplay between the sequential short-term markets and the imperative for flexibility. First, the current short-term markets are discussed. Next, the paper examines how flexibility in its three dimensions (i.e., time, space, and demand-response) can strategically function to not only address but also proactively alleviate uncertainties within these markets. Advancements in market coupling, forecasting accuracy, and increased liquidity have significantly enhanced the efficiency of these markets, particularly in accommodating the growing presence of renewable energy sources.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"18 ","pages":"Article 100183"},"PeriodicalIF":5.4,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205147","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}
Smart EnergyPub Date : 2025-05-01DOI: 10.1016/j.segy.2025.100184
Magnus Askeland, Sigurd Bjarghov, Rubi Rana, Andrei Morch, Henning Taxt
{"title":"Smart flexibility in energy communities: Scenario-based analysis of distribution grid implications and economic impacts","authors":"Magnus Askeland, Sigurd Bjarghov, Rubi Rana, Andrei Morch, Henning Taxt","doi":"10.1016/j.segy.2025.100184","DOIUrl":"10.1016/j.segy.2025.100184","url":null,"abstract":"<div><div>The transition of the power system towards increased renewable energy generation necessitates enhanced flexibility at all system levels, especially within distribution grids. This study investigates the integration of Energy Communities (ECs) as a potential strategy to manage consumer-level flexibility within the context of Norwegian distribution grids. An equilibrium model is developed to analyse both implicit and explicit flexibility activation mechanisms to investigate potential strategies for distribution grid operators (DSOs) and assess the interactions between different stakeholders. The scenarios are evaluated based on their impact on peak load reduction, cost efficiency, and grid usage. Results from a Norwegian case study show that EC flexibility activation can reduce total system costs by 1.8% while lowering peak grid capacity needs by 13.1%. These reductions contribute to mitigating distribution grid congestion and deferring costly infrastructure reinforcements. Although derived from a specific geographical context, the findings offer valuable insights applicable to other regions with similar grid conditions and regulatory frameworks. The study concludes that combining active DSO strategies with local coordination in ECs enhances the cost-efficiency of flexibility activation, though careful consideration of pricing structures is necessary to realise the potential while preventing unintended consequences. Our scenario-based framework illustrates the potential of smart flexibility activation mechanisms to optimise grid operations, reduce peak loads, and enhance cost-efficiency. Key challenges and prerequisites to overcome them are also highlighted. By integrating advanced flexibility mechanisms and leveraging local market coordination, this study underscores the role of energy communities in accelerating the transition to decentralised smart energy systems.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"18 ","pages":"Article 100184"},"PeriodicalIF":5.4,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144241040","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}
Smart EnergyPub Date : 2025-04-11DOI: 10.1016/j.segy.2025.100180
Federico Battini , Andrea Menapace , Giulia Stradiotti , Ariele Zanfei , Francesco F. Nicolosi , Daniele Dalla Torre , Massimiliano Renzi , Giovanni Pernigotto , Francesco Ravazzolo , Maurizio Righetti , Andrea Gasparella , Jakob Zinck Thellufsen , Henrik Lund
{"title":"Urban Smart Energy Systems from a Climate Change Perspective: Technical, Economic and Environmental Optimization Analysis","authors":"Federico Battini , Andrea Menapace , Giulia Stradiotti , Ariele Zanfei , Francesco F. Nicolosi , Daniele Dalla Torre , Massimiliano Renzi , Giovanni Pernigotto , Francesco Ravazzolo , Maurizio Righetti , Andrea Gasparella , Jakob Zinck Thellufsen , Henrik Lund","doi":"10.1016/j.segy.2025.100180","DOIUrl":"10.1016/j.segy.2025.100180","url":null,"abstract":"<div><div>In response to the growing need for sustainable urban development, energy systems modelling must provide long-term carbon-neutral solutions at the city scale while balancing competing criteria. This work introduces a multi-objective optimization approach addressing technical, economic, and environmental criteria for urban smart energy systems designed to achieve 100% renewable energy integration. The analysis incorporates climate change impacts on both energy demand and production. Two optimization strategies are evaluated using Bozen-Bolzano, Italy, as a case study. Specifically, the energy systems were modelled using EnergyPLAN, integrated with Python for automation. Grid search and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) were adopted as optimization methods to compare the advantages and limitations of two different approaches. The results show that both methods produce similar solutions on the Pareto front, with the grid search slightly outperforming due to the consideration of extreme input ranges. However, NSGA-II generated a significantly larger number of Pareto solutions, demonstrating its effectiveness in exploring the solution space more comprehensively. This study underscores the importance of incorporating climate change into multi-objective optimization for robust decision-making in the design of smart urban energy systems for sustainable development.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"18 ","pages":"Article 100180"},"PeriodicalIF":5.4,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143843774","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}
Smart EnergyPub Date : 2025-02-28DOI: 10.1016/j.segy.2025.100178
Milky Ali Gelchu , Jimmy Ehnberg , Dereje Shiferaw , Erik O. Ahlgren
{"title":"Exploring the advantages of a multi-year-adaptive approach on cost-optimal long-term mini-grid design under different demand evolution scenarios","authors":"Milky Ali Gelchu , Jimmy Ehnberg , Dereje Shiferaw , Erik O. Ahlgren","doi":"10.1016/j.segy.2025.100178","DOIUrl":"10.1016/j.segy.2025.100178","url":null,"abstract":"<div><div>Mini-grids are essential for rural electrification in sub-Saharan Africa, but due to uncertainty about future demand evolution in non-electrified communities, cost-optimal long-term sizing and design is particularly difficult. Standard, non-adaptive design approaches single-year and multi-year, are highly susceptible to demand evolution uncertainties. Despite potentially great advantages there is a lack of studies investigating adaptive design approaches. Thus, this study, using particle swarm optimization, explores the advantages of a multi-year-adaptive approach on cost-optimal long-term solar PV mini-grid component sizing under three demand evolution scenarios, considering the impacts of load flexibility, varying discount rates, and potential future mini-grid component cost reductions. The results show that the multi-year-adaptive approach helps to manage demand evolution challenges. It leads to significant cost-savings, up to three-quarters, in higher demand evolution scenarios, compared to multi-year and single-year approaches. These cost-savings increase with load flexibility (up to 4 % with 10 % flexibility), higher discount rates (up to 9.4 % with rates from 7 % to 20 %), and component cost reductions (up to 3.6 % per 1 % reduction). The study demonstrates how an adaptive approach can be utilized to optimize mini-grid component sizing and enhance cost efficiency.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"18 ","pages":"Article 100178"},"PeriodicalIF":5.4,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143548729","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}
Smart EnergyPub Date : 2025-02-13DOI: 10.1016/j.segy.2025.100175
Pascal Friedrich , Thanh Huynh , Stefan Niessen
{"title":"Optimizing district heating operations: Network modeling and its implications on system efficiency and operation","authors":"Pascal Friedrich , Thanh Huynh , Stefan Niessen","doi":"10.1016/j.segy.2025.100175","DOIUrl":"10.1016/j.segy.2025.100175","url":null,"abstract":"<div><div>Efficient utilization of local heat sources in urban areas necessitates integrating various suppliers into District Heating Systems (DHSs), considering the diverse ownership and physical characteristics of these sources. This study addresses the challenges in operational planning and pricing through local heat markets, emphasizing the importance of accurately representing the District Heating Network (DHN) physics for reliable market matching. We explore different DHN modeling approaches for day-ahead operational planning, balancing between numerical efficiency, economic viability, and operational feasibility. Our models, ranging from mixed-integer linear to non-linear, aim to maximize social welfare under steady-state conditions and are tested on small scenarios to highlight potential synergies between Heatpumps (HPs) and Combined Heat and Power Units (CHPs). Assuming regulations enable cost-competitive operations between HPs and CHP units, we anchor our energy price assumptions in 2030 forecasts for Germany. This approach allows us to highlight the techno-economic advantages of leveraging non-linear model flexibility during the transition to sustainable heat supply. The model’s operational schedules are further validated through detailed physical simulations in Modelica, revealing the impact of transient effects on actual performance, particularly the risks associated with thermo-hydraulic oscillations. The study concludes by discussing the required model complexity for effective DHS scheduling.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"18 ","pages":"Article 100175"},"PeriodicalIF":5.4,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143455064","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}
Smart EnergyPub Date : 2025-02-03DOI: 10.1016/j.segy.2025.100177
Vittoria Battaglia , Aseed Ur Rehman , Laura Vanoli
{"title":"Optimizing storage capacity in 100 % renewable electricity supply: A GIS-based approach for Italy","authors":"Vittoria Battaglia , Aseed Ur Rehman , Laura Vanoli","doi":"10.1016/j.segy.2025.100177","DOIUrl":"10.1016/j.segy.2025.100177","url":null,"abstract":"<div><div>The sustainability of energy systems relies on the integration of renewable local sources. This study aimed to optimize Italy's electricity supply by leveraging a hybrid PV-wind energy system, employing advanced optimization techniques. The primary goal was pinpointing the minimum storage capacity necessary for Italy's power grid in a scenario completely reliant on PV and wind energy. To achieve this, the potential of both PV and wind energy was evaluated through a GIS-based analysis, while dynamic simulation was used to estimate power generation across regions. The Mixed-integer linear programming algorithm underwent a three-step process: computing the hourly residual load for diverse PV and wind capacity combinations, determining the hourly storage requirements and ultimately identifying the mix with the least storage capacity. Applying Mixed-integer linear programming to Italy's complete PV and wind energy potential revealed a necessity for 33 TWh of storage capacity. To decrease the required storage capacity, two new scenarios were proposed: the island scenario, in which the total annual electricity production from solar and wind energy is equal to the annual electricity demand, and the peak hour scenario, where generation from PV and wind is matched to the consumption in peak hour electric demand. The economic analysis of the proposed scenarios shows that although hydrogen can be used to store enormous amounts of energy, the inefficiencies in the conversion processes make it less cost-effective compared to other technologies. Pumped-hydro storage is the most cost-effective option for energy storage. The results show that the most economically viable scenario is the island scenario with an optimal mix of 16.9 % PV and 83.1 % wind, requiring a storage capacity of 7.04 TWh and a 3.34 trillion euro investment for pump-hydro storage.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"18 ","pages":"Article 100177"},"PeriodicalIF":5.4,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143290355","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}
Smart EnergyPub Date : 2025-02-01DOI: 10.1016/j.segy.2024.100171
Dominique Grondin , Chao Tang , Andrew Barney , Agnès François , Heracles Polatidis , Michel Benne , Béatrice Morel
{"title":"Long-term energy scenario ranking with MCDA analysis: The case of Reunion Island","authors":"Dominique Grondin , Chao Tang , Andrew Barney , Agnès François , Heracles Polatidis , Michel Benne , Béatrice Morel","doi":"10.1016/j.segy.2024.100171","DOIUrl":"10.1016/j.segy.2024.100171","url":null,"abstract":"<div><div>Island territories rely heavily on fossil fuel resources, and transitioning to other energy sources is essential for their progress. To accomplish this, it is imperative to utilize local renewable energy sources. In this study, an analysis of energy planning for Reunion Island has been conducted where Multi-Criteria Decision Analysis (MCDA) methodologies have been used to evaluate the sustainability of energy scenarios for 2050. This evaluation is carried out considering criteria encompassing technical, economic, environmental, and social aspects of the scenarios. Further, perspectives of local actors were considered in the evaluation of these criteria. The results indicate that the greenhouse gas emissions and job creation criteria are considered to be of utmost significance, whilst technical criteria were regarded as the least significant by these local stakeholders. PROMETHEE II and TOPSIS MCDA analysis reveal that the Combined scenario, a scenario where all local energy resources are exploited to their maximum, is the preferred electricity generation scenario. The findings are used to formulate policy recommendations for island planners, helping them to adjust the island's current energy strategies. This study also serves as a valuable resource for other non-interconnected islands undergoing an energy transition.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"17 ","pages":"Article 100171"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154611","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}
Smart EnergyPub Date : 2025-02-01DOI: 10.1016/j.segy.2024.100168
Felix Agner , Ulrich Trabert , Anders Rantzer , Janybek Orozaliev
{"title":"A data-based comparison of methods for reducing the peak flow rate in a district heating system","authors":"Felix Agner , Ulrich Trabert , Anders Rantzer , Janybek Orozaliev","doi":"10.1016/j.segy.2024.100168","DOIUrl":"10.1016/j.segy.2024.100168","url":null,"abstract":"<div><div>This work concerns reduction of the peak flow rate of a district heating grid, a key system property which is bounded by pipe dimensions and pumping capacity. The peak flow rate constrains the number of additional consumers that can be connected, and may be a limiting factor in reducing supply temperatures when transitioning to the 4th generation of district heating. We evaluate a full year of operational data from a subset of customer meters in a district heating system in Germany. We consider the peak flow rate reduction that could be achieved with full a posteriori knowledge of this data. Three strategies for reducing the peak flow rate are investigated: A load shifting demand response strategy, an upper limitation in substation return temperatures, and an upper limitation on each substation’s volume flow rate. We show that imposing up to 18 % load flexibility for the customers provides an equal reduction in the peak system flow rate under the load shifting strategy. The limited return temperature strategy is less efficient at curtailing the peak flow rate, but provides an overall reduction of volume flow rates. Finally, the flow rate limitation method can introduce new, higher flow rate peaks, reducing performance.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"17 ","pages":"Article 100168"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154605","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}
Smart EnergyPub Date : 2025-02-01DOI: 10.1016/j.segy.2024.100169
Manuela Linke, Tobias Meßmer, Gabriel Micard, Gunnar Schubert
{"title":"Power grid operation in distribution grids with convolutional neural networks","authors":"Manuela Linke, Tobias Meßmer, Gabriel Micard, Gunnar Schubert","doi":"10.1016/j.segy.2024.100169","DOIUrl":"10.1016/j.segy.2024.100169","url":null,"abstract":"<div><div>The efficient and reliable operation of power grids is of great importance for ensuring a stable and uninterrupted supply of electricity. Traditional grid operation techniques have faced challenges due to the increasing integration of renewable energy sources and fluctuating demand patterns caused by the electrification of the heat and mobility sector. This paper presents a novel application of convolutional neural networks in grid operation, utilising their capabilities to recognise fault patterns and finding solutions. Different input data arrangements were investigated to reflect the relationships between neighbouring nodes as imposed by the grid topology. As disturbances we consider voltage deviations exceeding 3% of the nominal voltage or transformer and line overloads. To counteract, we use tab position changes of the transformer stations as well as remote controllable switches installed in the grid. The algorithms are trained and tested on a virtual grid based on real measurement data. Our models show excellent results with test accuracy of up to 99.06% in detecting disturbances in the grid and suggest a suitable solution without performing time-consuming load flow calculations. The proposed approach holds significant potential to address the challenges associated with modern grid operation, paving the way for more efficient and sustainable energy systems.</div></div>","PeriodicalId":34738,"journal":{"name":"Smart Energy","volume":"17 ","pages":"Article 100169"},"PeriodicalIF":5.4,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154606","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}