Abstract

This study evaluates the thermal systems of Swedish houses through a holistic energy system resilience framework, incorporating engineering, economic, and social dimensions. The major limitation identified is the lack of a proper framework to measure resilience. To address this, the study proposes a synthesized framework for measuring resilience, considering dimensions, abilities, properties, and key performance indicators (KPIs). Using a selection of indicators, the framework is applied to a case study to demonstrate its usability. The assessment focuses on measuring the thermal resilience of houses, influenced by the integration of heat pumps and wood stoves. By analysing the properties and KPIs specific to the system, the study aims to measure the resilience abilities of the system. This comprehensive approach supports the idea that Swedish houses can withstand and recover from disruptions, contributing to a sustainable and resilient energy future.

Abstract

Modelica is a powerful language for modeling thermal systems. However, the heat pump models available in open source Modelica libraries often lack sufficient accuracy for CO₂ heat pump systems. Unlike conventional heat pumps that use condensers, CO₂ heat pumps employ gas coolers, introducing significant thermodynamic differences not well captured in standard libraries. While commercial libraries offer more accurate CO₂ heat pump models, they are often costly, computationally intensive, and require substantial development effort—especially when the research focus is on the overall heating system rather than the detailed behavior of the heat pump itself. This study presents a deep learning approach to develop a CO₂ heat pump model based on real system data. The trained model was integrated into a Modelica-based thermal system simulation, enabling a hybrid modeling framework. A case study using a school building located in Oslo demonstrated the effectiveness of the approach. The hybrid deep learning-based heat pump model, when combined with the Modelica system model, improved overall simulation accuracy compared to a traditional Modelica-only model. Furthermore, the proposed framework is flexible and can be applied to other industrial thermal systems, offering a scalable solution for data-driven thermal system modeling.

Abstract

The integration of electric vehicles (EVs) into the power infrastructure can be a viable solution to enhance resilience during power outages. This paper proposes a framework to evaluate the techno-economic feasibility of using EV mobility to support household electricity needs during short-term outages under real-world operational limitations. For instance, EVs get charged in functioning power grid and delivers electricity to areas with outages. A rule-based control strategy is developed for energy delivery operation for EVs in order to maximize energy supply as part of a framework. The study assesses performance across key reliability and
economic indicators. Simulation results across various scenarios show that personal EVs with sufficient battery capacity can effectively meet household demand in short-term outage scenarios. On the other hand, rented EVs and prolonged outages reduce system efficiency and economic viability. The study can offer valuable insights to stakeholders and policymakers for planning EV-based resilience solutions for future energy systems.

Abstract

Indoor vertical farming (IVF) offers promising solutions for urban food security but still faces challenges in resource efficiency and economic viability. This study develops a preliminary LCA-TEA framework to evaluate two scenarios for lettuce production in a Swedish urban environment: (1) conventional vertical farming with municipal water and mineral/synthetic fertilizer, and (2) an integrated IVF system coupling wastewater nutrient recovery with Direct Air Capture (DAC)1 for COâ‚‚ fertilization.
The conventional IVF shows considerable environmental impacts resulting from high energy consumption of LED lighting, water use, and synthetic fertilizer production. Regardless of Sweden’s low-carbon electricity grid, the high energy intensity remains the main challenge to achieve economic viability. The integrated IVF system aims to transform the conventional linear model into a circular one, where municipal wastewater undergoes advanced treatment to recover N and P, while a modular DAC unit captures atmospheric CO₂ that is delivered to crops.
The literature review indicates that such an integrated approach could substantially reduce freshwater consumption, eliminate synthetic fertilizer requirements, and enable potential carbon-negative production through atmospheric COâ‚‚ removal. Economic benefits may arise from avoided input costs and potential revenue including water treatment services and eventually carbon credits. Sensitivity analysis can further explore critical parameters such as electricity prices, nutrient recovery efficiency, and COâ‚‚ recovery efficiency.
In addition, we link the framework to energy resilience, referring to the ability to sustain production during periods of electricity price volatility and interruptions. This is achieved by considering demand flexibility, on-site storage and backup systems, and a substituted COâ‚‚ supply via DAC.
Overall, the work demonstrates that there are promising conditions for developing integrated IVF systems that represent the water-energy-food-carbon nexus which could enhance sustainability and resilience in urban environment and better align with Sweden’s 2045 climate policy goals.

Abstract

This article presents a literature review on the most relevant quality parameters for hosting capacity in the Nordic context. A distribution grid from Norway is presented in detail to be established as a test bench for further studies. The grid covers different voltage levels, from 47 to 0.4 kV.
A hosting capacity analysis is performed on the proposed grid. The solar PV hosting capacity of the proposed grid has been estimated for a PV penetration of about 160% when voltage limits are considered. It was determined that the transformer and cable ratings are the main concerns in determining the hosting capacity, rather than the voltage deviations. This is in line with the findings of the literature review. We argue that this is the case for most grids in the Nordic.

Abstract

Sweden has a low carbon emissions electricity production. However, peak electricity consumption challenges climate change mitigation and grid resilience. Energy communities could function as a framework to organize peak electricity power reduction. This paper addresses the dynamics of adding electricity demands and then capping the combined peak. This paper explores the number of apartments required to coordinate and how group size affects the electricity demand reduction across the population. A household electricity demand dataset of 558 apartments was applied to explore these questions in the Swedish context. The results show that at least 62 apartments are required to be grouped to make an effective reduction of the total peak. This paper demonstrates that efforts to reduce peak electrical power consumption in residential areas should be coordinated with several households to be effective.

Abstract

The urgency of meeting 2030 climate goals has encouraged housing companies in Sweden, as one of the energy and carbon intensive sectors, to seek effective methods for analyzing and taking action on building retrofits. A key challenge in this process is the need for reliable and efficient tools to estimate the impact of energy conservation measures (ECMs), which are essential for informed renovation planning. Although various tools exist, many rely on simplified models, and there is a lack of expertise in their use. Dynamic simulation tools suffer from limited adaptability to large scale applications. These challenges have made it difficult for housing companies to implement ECMs effectively. This study benchmarks a simple template-based model used by Svenska Bostäder (SvB), __publicly owned rental buildings in Stockholm, Sweden__ against a detailed dynamic simulation called massive area Urban Building Energy Simulation (MUBES) by comparing their Thermal Energy Demand Intensity (TEDI) savings and simulation performance from applying three classical ECMs, namely triple-glazed window insulation, façade insulation, and heat recovery (HR). The results demonstrate that, although the static tool enables very fast estimations, it systematically overestimates energy savings across all ECMs, whereas the calibrated and validated dynamic simulations provide more consistent and moderate estimates of retrofit impacts. The calibration of MUBES was conducted manually and then validated against another dynamic simulation tool called City Energy Analyst (CEA).

Abstract

Healthcare facilities are among the most energy-intensive buildings, with water heating systems accounting for a significant portion of total energy consumption. Conventional electric storage tank water heaters operate inefficiently, leading to excessive energy use, frequent switching, and high peak-period demand. This study proposes an optimized energy management strategy integrating waste heat recovery and a solar-assisted heat pump to enhance system efficiency and reduce peak electricity consumption. A case study was conducted in a high-capacity healthcare facility, where baseline and optimally controlled scenarios were analyzed for both summer and winter conditions. The results indicate that the optimized control strategy successfully shifted heating loads to off-peak periods, minimized reliance on electric resistive heating, and maintained stable water temperature profiles across all tariff periods. The integration of waste heat recovery and solar-assisted heat pump significantly improved operational efficiency, demonstrating the potential for intelligent energy management solutions in large-scale healthcare water heating applications. Future work should explore real-time adaptive control mechanisms and experimental validation through pilot implementations to further enhance system adaptability and performance.

Abstract

With the rapid development of the electric vehicle (EV) industry, the large-scale retirement of batteries has introduced multiple environmental risks and challenges to industrial sustainability. Smart circular business models (SCBMs) utilizing 10R circular strategies (i.e., Refuse, Rethink, Reduce, Reuse, Repair, Refurbish, Remanufacture, Repurpose, Recycle, and Recover) present a promising solution. However, the success of implementing such strategies, policies and regulations is considered the core support factor.
This study combines a review of regulatory frameworks with semi-structured interviews in the Swedish EV battery ecosystem to explore the key challenges in implementing the 10R strategies under the Battery regulation. Finally, it identified four interrelated pillars that shaped battery circularity: (1) policies and regulations, (2) digital technologies, (3) business models and economics, and (4) organizational and behavioral management. These pillars illustrate how various dimensions intersect to influence the implementation of 10R strategies for EV batteries.
This study contributes to both theory and practice by offering a conceptual policy pathway for translating the 10R strategies to actionable strategies. It provides guidance for Europe policymakers and industry actors to build a digitally empowered, regulations-supported, and standardized circular battery ecosystem.

Abstract

The growing share of renewables in the power system has increased the risk of supply and demand imbalances, leading to more frequent grid frequency deviations. To manage this, flexible resources are needed to help close this gap. Batteries have already proven to be a mature technology for energy arbitrage and are financially rewarded for providing reserves that support grid balancing. At the same time, the rising penetration of renewables into the power system has reinforced the link between heat and electricity sectors. Combined Heat and Power (CHP) sits at the intersection of these two systems and plays a key role in supporting this interaction. However, these two technologies operate differently, and their joint potential remains underexplored. This paper presents a mixed-integer linear optimization (MILP) model that maximizes revenue from multi-market participation under current market rules. Two case studies of different system configurations are compared. The results highlight the significance of high-value frequency markets and complementary roles of CHP and batteries in market participation.