Heating and cooling account for a substantial share of final energy use and greenhouse gas emissions in Europe. District heating systems play a central role in decarbonising heat supply by enabling the integration of centralised, low-carbon heat sources. However, as fossil fuels and waste incineration are phased out and biomass availability becomes increasingly constrained, district heating systems face growing challenges related to cost, resource availability, and long-term resilience. In this context, industrial and urban excess heat and cold could support a low-carbon, flexible heat supply. Despite significant documented technical potential, excess heat remains poorly integrated into district heating systems due to spatial constraints, temperature mismatches, operational variability, and fragmented decision-making among industrial actors, network operators, and policymakers.

Energy system optimisation models are widely used to support long-term energy planning and policy analysis. However, when applied to excess heat recovery, existing modelling approaches struggle to capture several critical dimensions for decision-making, including spatial feasibility, heat quality, operational behaviour, and uncertainty. At the same time, empirical evidence on how excess heat performs within real district heating systems under different technical and market conditions remains limited. This thesis addresses these gaps by combining real-world case studies with the development of methodological models to support strategic planning for excess-heat recovery in district-heating systems.

The overall aim of this thesis is to develop and apply modelling approaches that enable a comprehensive and robust assessment of the integration of excess heat into district heating systems. The work is structured around three research questions, each addressing a distinct but interconnected aspect of the problem.

The first research question examines how well existing energy system optimisation models meet the analytical needs of decision-makers involved in excess heat recovery planning. Through a structured review of modelling tools and an assessment of stakeholder requirements, the thesis shows that while current models provide robust representations of technology costs, energy balances, and long-term investment dynamics, they fall short in representing spatial variation, heat quality, and operational constraints. These limitations are particularly problematic for excess heat recovery, where feasibility and value depend strongly on distance to demand, temperature levels, and temporal stability of supply. The analysis further highlights that limited flexibility and transparency in many models reduce their usefulness for stakeholder engagement. This research question establishes the need for modelling approaches that go beyond single-model optimisation and motivates the development of a multi-model framework.

The second research question investigates how a multi-model framework can improve the analysis of excess heat integration into district heating systems. To address this question, the thesis develops a modular multi-model framework that links exergy analysis, spatial least-cost network optimisation, long-term techno-economic optimisation, and high-resolution operational validation. The framework is implemented using iterative soft linking between models, ensuring that spatial feasibility, heat quality, and operational constraints are consistently reflected in long-term investment planning. The framework is applied to both a new district heating system and a large existing system. The results show that spatial proximity and source temperature strongly influence early investment decisions, while electricity prices and competition with existing technologies shape excess heat uptake in mature systems. Operational validation reveals differences between long-term investment pathways and short-term utilisation patterns, highlighting the importance of thermal storage and flexible operation in aligning planning and operation.

The third research question explores how district heating systems can be planned and adapted to remain resilient amid long-term uncertainty, systemic risks, and external shocks. To address this question, the thesis develops a stochastic–clustering–resilience framework that combines uncertainty sampling with long-term optimisation and post-processing analysis. This approach enables the identification of representative investment pathways and the evaluation of their performance across a wide range of future conditions. The results show that systems with diversified, flexible technology portfolios that combine excess heat recovery with electrification options such as heat pumps, electric boilers, and thermal storage perform best in terms of cost, emissions, and robustness. In contrast, systems that rely heavily on combustion-based technologies are more sensitive to fuel price volatility, policy changes, and supply disruptions.

Across all research questions and case studies, the modelling results demonstrate that excess heat can contribute significantly to cost-effective, low-carbon district heating systems, but only when spatial, thermal, operational, and uncertainty-related factors are jointly considered. Excess heat delivers the greatest system value when evaluated as part of a flexible and diversified technology portfolio rather than as a stand-alone resource.

The contributions of this thesis are twofold. First, it provides insights from multiple real-world district heating case studies, clarifying when and how industrial and urban excess heat can be effectively integrated under varying spatial, technical, and policy conditions. Second, it advances methodological approaches to excess heat modelling by developing a coherent multi-model framework that links industrial-, network-, and system-level perspectives. By integrating spatial, exergy, techno-economic, operational, and uncertainty analyses within a transparent and extensible workflow, the thesis provides improved decision support for planners, district heating operators, and policymakers. It contributes to a deeper understanding of how flexibility and adaptability, rather than single-technology optimisation, underpin resilient and sustainable transitions in district heating systems.

Uppvärmning och kylning står för en betydande andel av den slutliga energianvändningen och utsläppen av växthusgaser i Europa. Fjärrvärmesystem spelar en central roll i utfasningen av fossila bränslen i värmeförsörjningen genom att möjliggöra integration av centraliserade värmekällor med låga koldioxidutsläpp. I takt med att fossila bränslen och avfallsförbränning fasas ut och tillgången på biomassa blir alltmer begränsad, står fjärrvärmesystem inför ökande utmaningar kopplade till kostnader, resurstillgångar och långsiktig resiliens. I detta sammanhang kan industriell och urban överskottsvärme och -kyla bidra till en koldioxidsnål och flexibel värmeförsörjning. Trots en betydande dokumenterad teknisk potential är integrationen av överskottsvärme i fjärrvärmesystem fortfarande begränsad på grund av rumsliga begränsningar, temperaturskillnader, driftmässig variation samt fragmenterat beslutsfattande mellan industriella aktörer, nätoperatörer och beslutsfattare.

Optimeringsmodeller för energisystem används i stor utsträckning för att stödja långsiktig energiplanering och policyanalys. När de tillämpas på återvinning av överskottsvärme har befintliga modelleringsmetoder dock begränsad förmåga att fånga upp flera dimensioner centrala för beslutsfattande, såsom rumslig genomförbarhet, värmekvalitet, driftsbeteende och osäkerhet. Samtidigt är den empiriska kunskapen begränsad gällande hur överskottsvärme fungerar inom verkliga fjärrvärmesystem under olika tekniska och marknadsmässiga förhållanden. Denna avhandling adresserar dessa kunskapsluckor genom att kombinera fallstudier från verkliga system med metodutveckling inom modellering för att stödja strategisk planering av återvinning av överskottsvärme i fjärrvärmesystem.

Det övergripande syftet med denna avhandling är att utveckla och tillämpa modelleringsmetoder som möjliggör en omfattande och robust analys av integrationen av överskottsvärme i fjärrvärmesystem. Arbetet är strukturerat kring tre forskningsfrågor som var och en behandlar en distinkt men sammanlänkad aspekt av problemområdet.

Den första forskningsfrågan undersöker i vilken mån befintliga energisystemmodeller svarar mot de analytiska behov som beslutsfattare har vid planering av återvinning av överskottsvärme. Genom en strukturerad genomgång av modelleringsverktyg och en analys av intressenters behov visar avhandlingen att befintliga modeller ger robusta beskrivningar av teknikkostnader, energibalanser och långsiktiga investeringsdynamiker, men att deras förmåga att representera rumslig variation, värmekvalitet och driftmässiga begränsningar är begränsad. Dessa begränsningar är särskilt problematiska för återvinning av överskottsvärme, där genomförbarhet och värde i hög grad beror på avståndet till efterfrågan, temperaturnivåer och stabiliteten i värmetillförseln över tid. Analysen visar också att begränsad flexibilitet och transparens i många modeller minskar deras användbarhet i dialog med intressenter. Denna forskningsfråga etablerar därmed behovet av modelleringsmetoder som går bortom enskilda optimeringsmodeller och motiverar utvecklingen av ett multimodellramverk.

Den andra forskningsfrågan undersöker hur ett multimodellramverk kan stärka analysen av hur överskottsvärme integreras i fjärrvärmesystem. För att besvara denna fråga utvecklar avhandlingen ett modulärt multimodellramverk som kopplar samman exergianalys, rumslig kostnadsoptimering av nät, långsiktig teknoekonomisk optimering samt högupplöst operativ validering. Ramverket implementeras genom iterativ mjuk koppling mellan modeller, vilket gör det möjligt att konsekvent integrera rumslig genomförbarhet, värmekvalitet och driftmässiga begränsningar i långsiktig investeringsplanering. Ramverket tillämpas både på ett nytt fjärrvärmesystem och på ett befintligt system. Resultaten visar att rumslig närhet och källtemperatur starkt påverkar tidiga investeringsbeslut, medan elpriser och konkurrens med befintliga tekniker påverkar upptaget av överskottsvärme i mer mogna system. Operativ validering visar också skillnader mellan långsiktiga investeringsbanor och kortsiktiga utnyttjandemönster, vilket understryker betydelsen av termisk lagring och flexibel drift för att anpassa planering och drift.

Den tredje forskningsfrågan undersöker hur fjärrvärmesystem kan planeras och anpassas för att upprätthålla sin resiliens under långsiktig osäkerhet, systemrisker och externa störningar. För att besvara denna fråga utvecklar avhandlingen ett ramverk som kombinerar stokastisk analys, klustring och resiliensanalys genom att integrera osäkerhetssampling, långsiktig optimering och efterföljande resultatanalys. Detta tillvägagångssätt gör det möjligt att identifiera representativa investeringsbanor och utvärdera deras prestanda under ett brett spektrum av framtida förutsättningar. Resultaten visar att system baserade på diversifierade och flexibla teknikportföljer, där återvinning av överskottsvärme kombineras med elektrifieringsalternativ såsom värmepumpar, elpannor och termisk lagring, presterar bäst när det gäller kostnader, utsläpp och robusthet. System som i hög grad är beroende av förbränningsbaserade tekniker är däremot mer känsliga för volatilitet i bränslepriser, policyförändringar och störningar i energitillförseln.

Sammanfattningsvis visar avhandlingens resultat att överskottsvärme kan bidra väsentligt till kostnadseffektiva och koldioxidsnåla fjärrvärmesystem, men endast om rumsliga, termiska, driftrelaterade och osäkerhetsrelaterade faktorer beaktas samlat. Överskottsvärme skapar störst systemvärde när den betraktas som en del av en flexibel och diversifierad teknikportfölj snarare än som en fristående resurs.

Avhandlingens bidrag är tvådelat. För det första ger den empiriska insikter från flera verkliga fjärrvärmesystem och belyser därigenom när och hur industriell och urban överskottsvärme kan integreras effektivt under olika rumsliga, tekniska och policyrelaterade förutsättningar. För det andra utvecklar avhandlingen metodologiska angreppssätt för modellering av överskottsvärme genom ett sammanhängande multimodellramverk som kopplar samman industriella, nätbaserade och systemövergripande perspektiv. Genom att integrera rumsliga analyser, exergianalys, teknoekonomisk modellering, operativ analys och osäkerhetsanalys i ett transparent och utbyggbart arbetsflöde stärker avhandlingen beslutsstöd för planerare, fjärrvärmeoperatörer och beslutsfattare. Den bidrar därmed till en djupare förståelse för hur flexibilitet och anpassningsförmåga, snarare än optimering av enskilda tekniker, utgör grunden för resilienta och hållbara omställningar av fjärrvärmesystem.

The energy demand for cooling in India is projected to double between 2017 and 2027, driven by rapid urbanisation, rising temperatures, and increased access to appliances. As of 2017, approximately 42 % of this demand was met by inefficient, refrigerant-based air conditioners (approximately 42 million units), which contributed significantly to greenhouse gas emissions. In light of India's climate commitments and the Kigali Amendment, which targets the reduction of hydrofluorocarbons, District Cooling (DC) emerges as a more sustainable and scalable alternative. Although air coolers and fans remain widespread, they often fail to meet the standards for maintaining thermal comfort and indoor air quality set by ASHRAE. The centralised nature of DC enhances energy efficiency, supports integration with renewable sources, and enables equitable access to cooling services. Yet, most existing approaches for assessing cooling demand and district cooling viability rely on detailed building-level data, which are often unavailable in developing countries like India. This study presents a top-down, GIS-based approach to evaluate the spatial and economic potential for district cooling deployment in India, incorporating climate zones, population density, and national energy balances. To our knowledge, this is the first national-scale assessment that spatially quantifies DC potential by integrating cooling degree days with high-resolution (250m × 250m) population grids and energy demand indicators. The method is designed to be replicable in other data-constrained contexts, making it relevant for developing countries facing similar challenges. A sensitivity analysis assesses economic feasibility based on cooling demand density thresholds and regional climatic conditions. Results show a total estimated cooling demand of 3780 TWh for 2017, with approximately 75.9 % located in grid zones exceeding 1000 MWh/year, deemed economically viable for DC expansion. States such as Uttar Pradesh (881.3 TWh/year), Bihar (404.6 TWh/year), and Maharashtra (308.3 TWh/year) are identified as high-priority regions. Local cooling hotspots show demand densities reaching up to 529 GWh/year per 250m × 250m grid. These findings highlight both the urgency and opportunity to scale district cooling systems across India and offer a practical planning framework for sustainable cooling in rapidly urbanising, high-temperature regions globally.

In pursuit of the 2050 decarbonisation goals outlined in the Paris Agreement, the European Union aims to integrate renewable energy sources into electricity generation. However, the intermittent nature of solar and wind energy presents challenges for grid stability and reliability. Hydrogen (H2), particularly "green H2" produced through renewable electrolysis, has emerged as a promising energy carrier to complement variable renewable energy. This study investigates the technical and economic feasibility of utilising excess heat generated during Proton Exchange Membrane (PEM) electrolysis, a by-product typically underutilised, to improve the overall efficiency and cost-effectiveness of green hydrogen production. Using Aspen Plus, the study models five heat recovery scenarios: electricity generation via an ammonia Organic Rankine Cycle (ORC), direct heat supply to a District Heating (DH) network, steam generation using hydrogen and electric boilers, and a combined DH and steam generation configuration. The base case assumes no heat recovery and relies solely on cooling towers for heat rejection. Among the alternatives, the DH scenario proved to be the most economically viable, achieving a Net Present Value (NPV) of <euro>9.5 million, an Internal Rate of Return (IRR) of 0.23, and a Payback Period (PB) of 7 years, at a hydrogen price of <euro>9.5/kg. In contrast, the ORC scenario yielded a negative NPV and a payback period exceeding 30 years, indicating limited viability under current conditions. The results highlight the importance of integrating low-grade heat recovery into green hydrogen systems. Redirecting PEM excess heat to existing DH infrastructure offers the most immediate economic and technical benefits, contributing to more efficient, circular, and financially attractive hydrogen production systems.

Heating and cooling activities account for nearly half of the European Union's total energy use, yet only 23 % of this demand is met by renewable sources. As reliance on fossil fuels declines and waste suitable for incineration diminishes, alternative renewable and excess heat (EH) sources become essential. In Sweden, approximately 4.7 TWh of industrial EH is recovered annually, contributing 12 % of available EH and 9 % of the district heating (DH) supply. Despite projections that EH utilisation will rise from 22 TWh in 2015 to 33 TWh by 2050, lowtemperature levels and economic viability challenges have limited Urban Excess Heat (UEH) integration into DH systems. This study develops a spatial-techno-economic optimisation framework to support long-term UEH integration in DH networks. The framework, composed of three open-source tools for spatial network optimisation, long-term planning, and short-term operational optimisation, was applied to the City of Stockholm's DH system, where over 80 % of buildings are DH-connected. Results indicate that UEH sources within a 5-km radius of primary DH pipelines have the highest feasibility for integration. Economic analyses revealed that investment sensitivity is highest with fluctuations in electricity prices, emphasising the cost implications of energy markets on UEH feasibility. Scenarios with varying grid temperatures demonstrated that lower temperatures improve UEH uptake but require adaptive network designs for efficiency. Iterative linking of long-term and highresolution operational models highlighted differences between cost-optimal plans and operational realities, suggesting refinement needs. This framework offers robust pre-feasibility insights for stakeholders, enhancing strategic planning for sustainable urban heating across municipal and regional levels.

Integrating District Heating (DH) with the Electric Power Sector (EPS) offers a key strategy for addressing climate challenges by improving resource efficiency and enabling low-carbon transitions. Through Flexible Sector Coupling (FSC) mechanisms, DH systems can mitigate greenhouse gas emissions and enhance system flexibility by absorbing intermittent renewable electricity surpluses. This study evaluates the potential of FSC enabled through Thermal Energy Storage (TES) in DH applications, using the energy system of Oskarshamn, Sweden, as a case study. A soft-linked modelling framework is developed by combining a long-term investment optimisation model based on the Open-Source energy Modelling System (OSeMOSYS) with a high-resolution hourly dispatch model. These models are iteratively linked to align strategic investment decisions with operational feasibility. The analysis evaluates scenarios based on variations in electricity prices, TES capital costs, and the availability of self-consumption via heat pumps and excess heat. Key performance indicators, including Levelised Cost Of Energy (LCOE) and CO<inf>2</inf> emissions, are used to compare outcomes. Results show that the feasibility of FSC is strongly influenced by electricity price trends and TES investment costs. High electricity prices favour cogeneration of electricity and heat, while lower prices lead to increased investment in TES and heat pumps, prioritising heat production. Scenarios with low electricity prices achieve lower LCOEs (37.5–42.7 €/MWh) compared to those with high prices (46.6 €/MWh). The approach demonstrates that soft linking the capacity expansion model and dispatch models strengthens energy system planning by integrating long-term and short-term perspectives. Overall, the study highlights the potential of FSC with TES for cost-effective and resilient DH planning under different future energy conditions. Future work could explore the wider deployment of FSC by assessing its integration with electricity market services, expanding to multi-city or regional DH networks, and evaluating enabling policies, business models, and digital control strategies for large-scale implementation.

At a time when European countries try to cope with escalating energy prices while decarbonizing their economies, waste heat recovery and reuse arises as part of the solution for sustainable energy transitions. The lack of appropriate assessment tools has been pointed out as one of the main barriers to the wider deployment of waste heat recovery projects and as a reason why its potential remains largely untapped. The EMB3Rs platform emerges as an online, open-source, comprehensive and novel tool that provides an integrated assessment of different types of waste heat recovery solutions, (e.g. internal or external) and comprises several analysis dimensions (e.g. physical, geographical, technical, market, and business models). It has been developed together with stakeholders, and tested in a number of representative contexts, covering both industrial and heat network applications. This has demonstrated the enormous potential of the tool in dealing with complex simulations, while delivering accurate results within a significantly lower time-frame than traditional analysis. The EMB3Rs tool removes important barriers such as analysis costs, time and complexity for the user, and aims at supporting a wider investment in waste heat recovery and reuse by providing an integrated estimation of the costs and benefits of such projects. This paper describes the tool and illustrates how it can be applied to help unlock the potential of waste heat recovery across European countries.

Goa is the smallest state in India, covering 3700 km2 Its unique location makes it an ideal focal point for state-specific analyses representing a small-scale version of India’s diverse energy landscape. There is a lack of local power capacity, and the state primarily relies on centrally allocated power stations dominated by 572 MW of coal, constituting 73 % of the total allocated capacity. Despite advancements in electrification, fossil fuels remain the primary energy source in sectors like cooking, industry, and transportation, with around 36 PJ or 72 % of the total energy supplied. This study presents targeted strategies for achieving 100 % renewable energy deployment by conducting a sectoral analysis and emphasizing temporal resolution. Leveraging open-source models like OSeMOSYS-pulp enhances transparency and accessibility in energy planning. At the same time, stakeholder engagement ensures alignment with local priorities. The findings highlight opportunities for Goa to transition to renewable energy sources, including green electricity generation and imports, alongside policy measures such as Renewable Purchase Obligations (RPOs) and long-term Power Purchase Agreements (PPAs) incentivizing hybrid systems with battery storage. The study also emphasizes the importance of transitioning traditional cooking technologies to cleaner options like biogas and electric cooking for universal clean cooking, thus reducing energy consumption from 6.4 PJ to 2.4 PJ by 2050. Moreover, it proposes electrifying various passenger transport modes, reducing emissions, and lowering final energy consumption from around 20 PJ to 10 PJ by 2050. The study demonstrates the impact of increasing temporal resolution on energy planning by better capturing demand variability and load patterns. This results in a decreased solar installation of around 1.6 GW by 2050. Finally, this study provides insights for sustainable energy transition tailored to local contexts like Goa and similar regions with limited renewable potential.

Islands all over the world face common challenges connected to energy costs and greenhouse gas emissions. Thus, islands have been identified as perfect sites for implementing and testing innovative solutions to boost the green energy transition towards a sustainable and clean energy system. The supply of clean water is a major issue that affects small islands, and desalination, particularly Reverse Osmosis, represents a valid solution to this challenge. In this research, an energy system model is used to analyse long-term water and energy supply strategies of the tourist island of Favignana, Italy. The model is built with the Open Source long-term energy modelling tool OSeMOSYS at an hourly resolution. It considers both the potential synergies offered by Reverse Osmosis Desalination and the use of water storage to store the excess electricity when needed. The indirect emissions for the maritime transportation of goods and fuels (i.e., water and diesel) to the island are also accounted for. Different energy policies are compared to understand how a carbon tax, a limit on emissions and no policy would impact the long-term energy strategy of the island. The results show that a carbon tax that covers also the maritime transportation sector would lead to the lowest overall cumulative emissions. They additionally reveal that the contribution of emissions for maritime transportation of goods and fuels is relevant and cannot be neglected if a full decarbonisation has to be achieved. On the technological side, investment in a desalination plant is the most viable option in all cases. Finally, for the first time, OSeMOSYS is applied with hourly resolution and the results are compared with those obtained with lower time resolution showing that inaccuracies are found both for overall values and for the dispatching strategies.

With increasing heating and cooling demands, decarbonisation of the heating and cooling sectors is key to achieving a carbon-neutral energy system. Using industrial excess heat in heating systems helps offset emissions by reducing the use of fossil fuels. While several studies have analysed the temperature of heat availability, the cost of extending or constructing the heating network and techno-economic feasibility, it is important to consider all aspects together to achieve a comprehensive design of industrial excess heat recovery. This study proposes a method to link an energy system optimisation tool with a spatial analysis tool and an exergy analysis tool to achieve a comprehensive design. An iterative soft link is implemented between the energy system model and the spatial analysis tool for high spatial and temporal resolution. The developed method is applied to a case study of an industrial park in Greece. Scenarios are developed to assess the robustness of the developed method and the system profitability of excess heat recovery. The scenarios indicated that the profitability of excess heat depends heavily on the price of natural gas with the share of excess heat increasing from 10% to 45% with a 20% increase in natural gas prices in cases where heat pumps are needed for temperature boosting. In cases where heat pumps are not needed, excess heat indicates higher system profitability with a share of around 40% and reduces the emissions by around 50 times. The method provides robust results in considered scenarios with convergence within four iterations.

Recovery and use of industrial excess heat and cold are expected to play a huge role in the decarbonisation of heating and cooling systems in Europe. From the perspective of the industry, it could also promote a coupling between the sectors and help offset emissions, leading to a sustainable industry. However, there exists a gap in knowledge regarding the planning of infrastructure for utilization of excess heat, specifically for industries. This study aims at reviewing energy system optimisation tools that can be used by industrial stakeholders to plan energy investments for recovery and utilization of excess heat and cold. Through a study of existing energy systems models, seven tools are found suitable for analysing industrial excess heat and cold recovery. A detailed review of these tools is conducted and they are compared. The capability of the models to represent and analyse industrial excess heat and cold recovery options are critically discussed. The main requirements of such an analysis are used to establish criteria for comparison. The results of the comparison are used as a knowledge base to form a simple decision support tool to help industrial stakeholders choose the most suitable energy system model. The results from the review, comparison and decision support tool indicate that none of the models is capable of fulfilling all needs in every case. They also highlight that the choice of the tool depends especially on the required temporal and spatial resolution and its interoperability.