Umeå University's logo

Energy community (EC) is a citizen-driven energy initiative that contributes to the clean energy transition within local communities. EC could also contribute positively towards energy security, which is currently a topic of high interest in Europe. Sweden has limited experiences with ECs as compared to many other European countries. This paper, using Multi-Level Perspective (MLP) framework, discuss the challenges and opportunities for establishing ECs in the north of Sweden. The analysis highlights that limited national regulation specific to ECs, and complex concession and taxation rules are barriers to EC implementation. EC development is further constrained in northern Sweden due to relatively lower electricity price, long heating seasons and low solar irradiation affecting economic viability of solar PVs. The landscape development which resulted in new and amended EU directives could facilitate ECs in Sweden. The study concludes that although ECs could provide flexibility and contribute to climate and energy security goals, their wider adoption in high latitude regions requires clearer regulation, targeted financial incentives, adapted business and viable governance models, and stronger institutional support.

Enhancing energy efficiency in the building sector is vital for climate change mitigation. Phase change materials (PCM), known for their high latent heat storage capacity during phase transitions, offer promising potential in regulating indoor temperatures and reducing dependence on HVAC systems. This study presents a preliminary experimental investigation into the thermal performance of wallboards enhanced with PCM under subarctic conditions in Umeå, Sweden. Four types of wallboards were tested: a conventional gypsum board, a commercial PCM board (cPCM), and two lab-fabricated boards with 60% and 82% microencapsulated PCM by mass (mPCM60 and mPCM82). Thermal properties of the PCM were characterized using Differential Scanning Calorimetry (DSC), confirming high latent heat capacity and thermal stability. In a field setup, surface temperatures were monitored to assess thermal buffering capacity. Results show lower temperature fluctuations in the mPCM82 and mPCM60 wallboards, indicating enhanced thermal performance of the envelope compared to the gypsum board. However, the thermal performance of cPCM was even worse than gypsum, which could be attributed to the observed material settlement. These findings suggest the potential of PCM-enhanced wallboards to improve indoor thermal comfort and energy performance, while also emphasizing the importance of material selection and design in practical applications.

Reducing energy use within the building sector is vital to create sustainable cities and mitigate global warming. Urban building energy modelling (UBEM) is useful to evaluate energy demand and renovation potential in districts. In this paper, an archetypes-based calibration approach for UBEM is introduced to evaluate the effect of various timescales for energy data and detail of building-related data on the energy performance of multi-residential buildings. A case district in northern Sweden was used to identify the impact of various refurbishment strategies at district-scale.

The applicability of the archetypes-based calibration approach was validated by comparing the district model performance with high-resolution energy data. Calibrating the archetypes-based model with monthly resolution data showed a similar outcome as using higher-resolution data. Further, a district model with less archetypes can reduce modelling time and complexity, while performing similarly as a model consisting of more archetypes with higher detail. The results suggest that simplifications to UBEM can be used without compromising the performance accuracy and might facilitate district modelling in situations with data limitations.

The findings in this study contribute to the knowledge on UBEM of existing districts and energy efficiency measures’ impact on district-level energy performance.

Introduction: A predominant portion of current Positive Energy District (PED) projects focuses on technical advancements, often neglecting non-technical aspects, which can hinder a just energy transition. This raises the question: How can PEDs be assessed to ensure a just, inclusive, and context-sensitive energy transition beyond technical solutions?

Methods: This study develops a cohesive approach that embeds the multiscale, multisectoral, multi-component, and multi-actor nature of PED development. A multi-criteria PED Matrix was created and refined using Natural Language Processing (NLP) and expert feedback to evaluate and benchmark PEDs across eight dimensions: social, governance, technical, process, environmental, legal, financial, and managerial.

Results: Five European pilot cases (in Austria, Sweden, and Türkiye) were assessed using the matrix, revealing context-specific strengths and capacity-building needs and enabling cross-case learning and comparison.

Discussion and conclusion: The PED Matrix supports self-assessment and co-design processes, helping local stakeholders identify weaknesses, required competencies, and lessons from other PED-related cases, promoting inclusive and context-sensitive energy transitions.

Open data in the renewable energy sector could contribute to a greener future and reduce carbon emissions. This study investigates existing open datasets in the solar thermal domain, challenges in publishing and using open data and its potential impact. The results support the common belief that open data is useful, offering considerable benefits for data re-users and the solar thermal community. While substantial open data in the solar thermal domain already exists, some datasets like plant statistics and cost data are hard to utilize due to licensing, accessibility, and quality issues. The study shows that data owners benefit less from publishing data compared to data re-users and service providers. While data sharing seems appealing to data owners, several barriers discourage data sharing. Suggestions to promote the use and publications of open data in solar thermal domain are discussed.

The use of pit thermal energy storages (PTES) enables higher solar fraction in district heating networks by counteracting the mismatch between heat demand and production in solar district heating (SDH) installations. Capital costs linked to land areas with site-specific geological conditions are the deciding factors for PTES constructions. This study investigates non-technical and technical factors for the implementation of PTES in Swedish district heating networks. Having several SDH and PTES installations in operation the country of Denmark is used as a reference. This study, based on literature review, discusses the drivers and challenges for the use of PTES in district heating networks.

Recent advancements in occupancy and indoor environmental monitoring have encouraged the development of innovative solutions. This paper presents a novel approach to room occupancy detection using Wi-Fi probe requests and machine learning techniques. We propose a methodology that splits occupancy detection into two distinct subtasks: personnel presence detection, where the model predicts whether someone is present in the room, and occupancy level detection, which estimates the number of occupants on a six-level scale (ranging from 1 person to up to 25 people) based on probe requests. To achieve this, we evaluated three types of neural networks: CNN (Convolutional Neural Network), LSTM (Long Short-Term Memory), and GRU (Gated Recurrent Unit). Our experimental results show that the GRU model exhibits superior performance in both tasks. For personnel presence detection, the GRU model achieves an accuracy of 91.8%, outperforming the CNN and LSTM models with accuracies of 88.7% and 63.8%, respectively. This demonstrates the effectiveness of GRU in discerning room occupancy. Furthermore, for occupancy level detection, the GRU model achieves an accuracy of 75.1%, surpassing the CNN and LSTM models with accuracies of 47.1% and 52.8%, respectively. This research contributes to the field of occupancy detection by providing a cost-effective solution that utilizes existing Wi-Fi infrastructure and demonstrates the potential of machine learning techniques in accurately classifying room occupancy.

This study investigates primary energy use and CO₂ emission reduction potential resulting from the integration of solar thermal heating in biomass-based district heating systems in high-latitude regions. A newly commissioned solar thermal system based on parabolic trough collectors for an existing district heating network in Häarnösand, Sweden, is used as a case study, and its hourly one-year measured data are used as inputs for the analysis. The changes in operation and fuel use for local district heat production are extended to a regional context, considering the short- and long-term perspectives of the energy system. The results show that during the studied period, the solar water heating system provided 335 MWh of heat to the existing district heating system with a supply/return temperature of approximately 80/45 °C. Consequently, 339–382 MWh of biomass fuel consumption could be reducedannually with such an installation, depending on the district heat production technologies being substituted. An annual CO₂ reduction of 65.3–189 tons can be achieved in an overall energy system perspective when the saved biomass substitutes fossil fuels. The reduction of CO₂ emission depends on the fuels being substituted and energy conversion technology.

In 2018, EU launched the programme “Positive energy districts and neighbourhoods for sustainable urban development” with an aim to support the planning, deployment and replication of 100 Positive energy districts (PEDs) by 2025. This is an ambitious target considering the various challenges on implementing PEDs. This paper, based on literature review, provides an overview on the challenges and possibilities on the three main components of PEDs; energy production, energy efficiency and energy flexibility.

This study investigates the influence of a microencapsulated Phase Change Material (mPCM) on building systems in a subarctic climate which is not commonly studied for PCM applications. The mPCM is incorporated into gypsum to make a composite board with a volume fraction of 30 vt%. The fabricated composite board is then used to make a box model. This model along with a reference model built only with gypsum boards are placed inside a climate chamber where temperature is regulated to a summer day of a subarctic country, where large temperature variation exists between day and night. In addition, a Finite Element Method (FEM), is also used for the validation of the experimental data. The thermal-physical properties of the mPCM gypsum board including the specific heat capacity and thermal conductivity are measured. The microscopic features of the composite board are also studied. In addition, the temperature variation and the thermal energy storage of the boards of the two models have been studied. Results indicate that incorporation of mPCM into gypsum will change the thermal properties of the material. PCM can work as an additional insulation layer due to its low thermal conductivity. Further, the temperature fluctuation inside of the model with mPCM is reduced. In addition, the energy stored in the mPCM composite is around 3 times higher than that of gypsum board, making it promising for building energy improvement and load shifting.