District heating is today the most common way of providing a building with heat and hot water in Sweden. It is an environmentally friendly product mostly used with renewable fuel. However, at power peaks most companies use production units that are more expensive and worse for the environment and should therefore be avoided as much as possible. This can be done with a method called load management. When a power peak occurs, the heat supply to buildings connected to the district heating system can be temporarily reduced. The heat energy can later be returned when the heat demand is lower. Thanks to the heat inertia of the buildings, the indoor temperature will not fall within the time frame for the load management. Historical data has been analysed to identify when and why power peaks occur in the district heating network. Power peaks throughout the district heating network have proved difficult to identify. However, for individual consumers clear patterns of power peaks have emerged. These power peaks mainly occur because of large use of hot water but also because of the shifting outdoor temperature. In order to see how the production cost would differ from the actual outcome load management was applied for Gävle's district heating 2018. The load management was calculated manually by identifying the most expensive production unit on an hourly basis. If a cheaper production unit had the potential to deliver higher power the next hour, the production was moved to the cheaper production unit. The process was repeated for each hour during 2018. After carrying out load management for Gävle's district heating network, 1 457 MWh had been shifted to a cheaper production unit. This resulted in a financial saving of 1,0 % of the total production cost. The environmental savings showed a reduction from 6.1 to 5.9 g CO2eq /kWh a total of 197 tonne CO2eq. In the exact same way, a load management was performed for a scenario where Gävle and Sandviken's district heating network were connected. The gain for a load management with Sandviken will be considerably larger, a reduced production cost of 3.6 % is possible. The environmental savings showed a reduction from 8.4 to 7.8 CO2eq /kWh a total of 575 tonne CO2eq. For future efficient load management, buildings should be divided into different classes depending on the building's time constant. User patterns for the entire district heating network have proved difficult to detect. Artificial intelligence can be an option for short-term forecasting of the power output / Fjärrvärme är idag det vanligaste sättet att förse en bostad med värme och tappvarmvatten i Sverige. Fjärrvärmen är ofta en miljövänlig produkt som kan produceras av till exempel biobränsle- och avfallseldade kraftvärmeverk eller spillvärme från industrier. Vid tillfälligt högt effektbehov, effekttoppar, använder sig merparten av bolagen av dyrare produktionsenheter med större miljöpåverkan. Dyrare produktionsenheter bör undvikas i största möjliga mån och i detta syfte används metoden laststyrning. Vid en effekttopp kan värmetillförseln till byggnader sänkas temporärt för att återföras några timmar senare när effektbehovet är lägre. Tack vare värmetrögheten i byggnaderna bör inomhustemperaturen inte sjunka inom tidsramen för laststyrning. Statistik från Gävles fjärrvärmanvändning på timbasis under 2018 har analyserats för att identifiera när och varför effekttoppar sker. Effekttoppar i hela fjärrvärmenätet har visat sig svåra att identifiera. På lokal nivå har däremot tydliga mönster för effekttoppar framkommit. Dessa effekttoppar beror till största del av tappvarmvattenanvändning men även förändringar i utomhustemperaturen. För att se hur produktion och last kunde skiljt sig från det verkliga utfallet tillämpades laststyrning för Gävles fjärrvärmeproduktion 2018. Laststyrningen beräknades manuellt genom att den dyraste produktionsenheten identifierades på timbasis. Om en billigare produktionsenhet hade potential att leverera högre effekt nästkommande timmar försköts produktionen. Därefter upprepades processen för varje timme under 2018. Efter utförd laststyrning för Gävles fjärrvärmenät hade ca 1 457 MWh förskjutits till en billigare produktionsenhet. Det gav en ekonomisk besparing på 1,0 % av Gävles totala produktionskostnad. Den miljömässiga besparingen visade på en sänkning från 6,1 till 5,9 [g CO2ekv /kWh] sammanlagt 197 ton CO2ekv. På samma sätt utfördes en laststyrning för ett scenario där Gävle och Sandvikens fjärrvärmenät sammankopplats. Vinsten för en laststyrning med Sandviken blev betydligt större med en minskad produktionskostnaden på 3,6 %. Den miljömässiga påverkan sjönk från 8,4 till 7,8 g CO2ekv /kWh sammanlagt 575 ton CO2ekv. För en framtida effektiv laststyrning bör byggnader delas in i olika klasser beroende på byggnadens tidskonstant. Användarmönster för hela fjärrvärmenätet har visat sig svårt att identifiera. Artificiell intelligens kan vara ett alternativ i framtiden för att prognostisera effektuttaget

Orientador: Carlos Alberto Canesin / Resumo: Nesta tese é apresentado o desenvolvimento inédito de um equipamento de medição de parâmetros de qualidade de energia elétrica embarcado em um dispositivo FPGA, incorporando funcionalidades que o caraterizam como medidor inteligente. Dessa forma, obteve-se uma plataforma capaz de realizar monitoramento e verificação, em tempo real, do comportamento de sistemas de energia elétrica quando estes operam em condições de desequilíbrio, desbalanços, assimetria nos ângulos de defasagem e presença de componentes harmônicas, impostas pelo comportamento das cargas e/ou pelas tensões de alimentação do sistema. Para isso, foram empregadas as metodologias de cálculos de potência definidas pelo padrão IEEE 1459-2010 e a Teoria da Potência Conservativa. Técnicas de processamento digital de sinais são aplicadas para a descrição dos módulos de sincronismo e janelamento, baseados na norma NBR-IEC-61000-4-30:2010, assim como filtros digitais e deslocadores de fase adaptativos para a extração das componentes fundamentais e componentes fundamentais de sequência positiva. Adicionalmente, são detalhados todos os estágios relacionados com o condicionamento e amostragem dos sinais elétricos, cálculos de potência, cálculo de harmônicos, interface de usuário, acesso aos dados e comando para desconexão/religamento de cargas remotas. Os resultados experimentais obtidos em um sistema trifásico a 4 fios, para diferentes cenários de operação, incluindo a presença de elementos de geração distribuída, evidenci... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: In this thesis, the development of a novel power quality equipment embedded in an FPGA device, incorporating smart-metering features, is presented. Thus, a platform capable of real-time monitoring and verification of power systems operating under sinusoidal, non-sinusoidal, balanced and / or unbalanced conditions, was obtained. For this purpose, power calculation methods defined by both the IEEE 1459-2010 standard and the Conservative Power Theory (CPT) are reviewed and implemented. Based on NBR-IEC-61000-4-30: 2010 standards, digital signal processing techniques for the synchronization and windowing tasks, as well as, adaptive digital filters and adaptive phase shifters for obtaining the extraction of fundamental components as well as the positive-sequence fundamental components, are applied. Likewise, the complete developed stages regarding conditioning and sampling of electrical signals, power calculations, harmonic component calculations, graphical user interface, remote data access, and disconnection/reconnection commands for remote loads, are detailed. The experimental results obtained from a three-phase 4-wire system, under several operations scenarios, including the presence of distributed generation (DG) elements, highlight the advantages of the implemented methodologies, when compared with commercial power quality analyzers, which use traditional definitions of power quantities. / Doutor

The average global temperature is rising due to climate change. This leads to an increase in cooling demand along with higher usage of electricity to operate cooling processes. One way to decrease the electricity usage is to introduce absorption cooling which uses heat instead of electricity as its main source of power. To further increase resource efficiency in urban areas centralized district cooling can substitute independent cooling units. In a district cooling network, a mixture of absorption and compressor cooling units, as well as free cooling, can be included. This enables the ability to coordinate which cooling technology is to be used based on profitability at the current time. By introducing an optimization-based plan, the operation of a district cooling network in a smart energy system can incorporate important factors for the interaction between different sectors, such as electricity and district heating prices. The usage of optimization-based tools to plan the operation of energy systems has previously shown promising results. However, further studies are needed to investigate how they perform in different scenarios. There is also a need to develope more reliable forecasts which motivated this study; a case study on the district cooling network "City" in Linköping.  The study aimed to develope a method for forecasting the cooling demand in a district cooling network, investigating how the coordination of absorption and compressor cooling units, as well as free cooling, can be improved. This has been done from a system perspective that encompasses the district heating and electricity network by developing an optimization-based operational plan. In this study an explorative method has been used to develope a forecasting tool based on an algorithm and a Mixed Integer Linear Programming (MILP) model with appertaining constraints and coefficients which can solve an Unit Commitment problem for a district cooling network. The forecasting tool and MILP model resulted in an optimization-based operational plan that enabled the ability to coordinate the usage between absorption and compressor cooling units as well as free cooling. The method can be divided into five distinct iterative steps; (1) data collection for the parameters that affect the cooling demand, (2) forecasting of the cooling demand based on the identified parameters, (3) pressure simulations of Linköping's district cooling network in the software NetSim, (4) operational optimization via MILP modeling, and (5) evaluation of the optimization-based operational plan from the perspective of operational cost, electricity and heat usage, as well as greenhouse gas emissions. Six different algorithms were developed to forecast the cooling demand. All of the algorithms were based on the retrospective operation the previous day through linear regressions. The algorithm that best followed a historical operational period on the district cooling network City had a margin of error of 14\%. The algorithm was based on the time of the day and either solar irradiation or outside temperature based on the difference between the forecasted outdoor temperature and the measured temperature the previous day. The MILP model that was developed had an objective function that minimized the operational cost which included the cost of electricity and heat usage, distribution, maintenance, and start-up and shut-down costs. The constraints that was constructed in the MILP model to define a district cooling network included balancing the cooling demand, specifications for the operation of cooling units and distribution flows. Furthermore, the coefficients that defined the City network were estimated dynamically. These included power limitations, operational costs, and start-up costs for each cooling unit, as well as distribution costs for each cooling plant.  During this case-study, it was observed that by using optimization-based operational planning produced from a MILP model solving an UC problem, the operational costs, electricity and heat usage can decrease by 27\%, 22\%, and 2\% respectively for this case-study of the City network in Linköping during a seven-month period. In addition, a decrease in greenhouse gases by 16\% was observed when applying the perspective "avoided global emissions". For the calculations an emission factor of 702 $gram \, CO_2-eq/kWh_{el}$ and 130, 72, or 3 $gram \, CO_2-eq/kWh_{heat}$ depending on if waste, bio-oil, or recycled waste wood were used as fuel for the marginal production of district heating. When there was excess heat in the district heating network the emission factor for heat usage was instead assumed to be 0 $gram \, CO_2-eq/kWh_{heat}$. Lastly, this case-study emphasizes the importance of solid operational planning as a foundational pillar in satisfying the increase of future cooling demand in a resource-efficient way for local energy systems in sustainable societies.

<p dir="ltr">The horizon for inclusion of data-driven algorithms in cyber-physical systems is rapidly expanding due to evermore availability of high-performance computing tools and the inception of novel mathematical models in the fields of deep learning and reinforcement learning. In this regard, energy systems are a suitable candidate for data-driven algorithms utilization due to rapid expansion of smart measuring tools and infrastructure. Accordingly, I decided to explore the capabilities of deep reinforcement learning in control, security, and restoration of smart energy systems to tackle well-known problems such as ensuring stability, adversarial attack avoidance, and the black start restoration. To achieve this goal, I employed various reinforcement learning techniques in different capacities to develop transfer learning modules based on a rule-based approach for online control of the power system, utilized reinforcement learning for procedural noise generation in adversarial attacks against contingency detection in a power system and exploited multiple reinforcement learning algorithms to fully restore an energy system in an optimal manner. Per the results of these endeavors, I managed to develop a rule-based transfer learning logic to control the power system under various disturbance types and intensities. Furthermore, I developed an optimal adversarial attack module using a reinforcement-learning-based procedural noise generation to avoid detection by conventional deep-learning-based detection. Finally for the system restoration, the proposed intelligent restoration module managed to provide sustainable results for the black start restoration in energy system.</p>

由於環保意識抬頭及商界和社會之間日益惡化的情況下，企業正在努力尋找新的商業模式來重塑資本主義。麥可·波特主張創造共享價值，試圖找尋新一波創新的商業模式來重塑資本主義。共享價值模式能夠為企業和社會創造財富，因此為越來越多的企業紛紛加入創造共享價值的行列。 本論文主要使用個案分析法和次級資料分析法進行研究。研究係透過了解利害相關人對於智慧電網的態度，以及解析智慧電網產業價值鏈來分辨共享價值之所在。透過對於智慧電網相關的研究，以及共享價值的學術文獻來建立研究架構。同時也蒐集了IBM公司以及智慧電網相關產業的動態訊息支持研究分析。其目的是要找出IBM公司的商業模式是否符共享價值模型之定義。研究彙整了智慧電網的利害相關人的意見，並且進行IBM所提供智慧電網方案與共享價值的關聯性分析。然後建議IBM對於創造共享價值可能的發展方向與模式。 研究結果發現IBM提供的智慧電網方案與創造共享價值其實是有關聯性的。然而，大部分的價值是透過與產業鏈結合而間接被創造出來的。在智慧電網方面，IBM並無法獨立創造出共享價值。因而提出了在面對利害關係人時，需要清楚辨認誰是最主要的影響者。透過連鎖效應的方式使得智慧電網能夠更符合創造共享價值。 另外，由於智慧電網應用技術的複雜性使得本研究的力度受到限制。 / Due to the rise of environmental awareness and the worsening situations between the business community and society, corporations are trying to find a way to reinvent capitalism. Michael E. Porter advocates that Creating Shared Value might be the answer for how business will able to reinvent capitalism and unleash the next wave of business and innovation. More and more corporations have jumped on the CSV bandwagon to create wealth for both the business and the society. Case analysis and secondary data analysis techniques are employed in this paper as the research method, through analyzing the stakeholders that are in the smart grid landscape. Academic literature, research papers, publications and information from relevant websites are used to support the analysis. The purpose is to find out whether IBM Company’s business model is in accordance with the shared value model by analyzing the opinions of stakeholders of smart grid and the proposes values of IBM’s smart grid solutions. The results are that most of the solutions that IBM has for smart grid are somehow relevant to the concept of CSV. However, most of the values proposed are rather indirect　as they are often created through collaborating with other players in the value chain. IBM alone would not be able to create a shared value model of its own. Therefore, suggestion has been made to emphasize on the importance of clearly identifying who has the biggest influence among stakeholders. Through chain effect between the stakeholders to enhance Smart Grid to become a more distinct shared value model. Also, due to the complexity of technologies involved in smart grid, the research has many limitations.

This thesis undertakes a thorough exploration of business models for energy communities, specifically tailored to the unique requirements of the Swedish energy sector. Its objective is to identify and evaluate global business models for energy communities, focusing on their applicability within Sweden's regulatory, market, and socio-cultural contexts. Utilizing the Business Model Canvas as an analytical framework, the study initially identifies twelve distinct business model archetypes, ranging from community-based energy generation to models grounded in circular economy principles. Subsequently, it assesses their viability within Sweden's innovative and sustainability-focused energy landscape. The research is based on a qualitative methodology, incorporating a systematic literature review and comparative analysis to understand the complex dynamics of energy communities. By examining the structure of the Swedish energy system, the study pinpoints key factors influencing the success of energy- community models in Sweden, including regulatory frameworks, technological infrastructure, economic and financial viability, community engagement, and environmental sustainability. The findings emphasize six business models that closely align with Swedish values and objectives, highlighting the significance of community involvement, sustainability, and innovation in transforming Sweden's energy sector. These models include community-based energy generation, residential energy self-consumption, shared community energy generation, electric mobility cooperatives, collective financial initiatives, and circular economy-based approaches. In conclusion, the thesis proposes an Integrated Sustainable Energy Community Model (ISECM) as a comprehensive futuristic energy community model to guide Sweden's transition towards a more decentralized, participative, and sustainable energy future. This model integrates sustainable energy production, smart urban mobility, resource recovery, and digital integration. Further recommending strategic initiatives for implementation such as developing community platforms, forging strategic partnerships, and establishing environmental and social metrics. The research contributes to both academic and practical discussions on sustainable energy transitions, offering a strategic framework for leveraging community-based models to achieve Sweden's environmental and energy goals. It calls for active engagement from government, industry, academia, and communities to unlock the potential of innovative business models in advancing Sweden's energy sustainability agenda. / Denna avhandling genomför en omfattande utforskning av affärsmodeller för energigemenskaper, särskilt anpassade till de unika kraven i den svenska energisektorn. Syftet är att identifiera och utvärdera globala affärsmodeller för energigemenskaper med fokus på deras tillämplighet inom Sveriges regelverk, marknadsdynamik och sociokulturella sammanhang. Med hjälp av Business Model Canvas som analytiskt ramverk kartlägger studien tolv distinkta affärsmodellsarketyper, från gemenskapsbaserad energiproduktion till modeller baserade på cirkulär ekonomi, och bedömer deras livskraft i Sveriges innovativa och hållbarhetsinriktade energilandskap. Forskningen är grundad i en kvalitativ metodik, inkluderande en systematisk litteraturgenomgång och jämförande analys för att förstå de mångfacetterade dynamikerna inom energigemenskaper. Genom att utforska strukturen i det svenska energisystemet identifierar studien nyckelfaktorer som påverkar framgången för modeller av energigemenskaper i Sverige, inklusive regelverk, teknologisk infrastruktur, ekonomisk och finansiell livskraft, gemenskapsengagemang och miljömässig hållbarhet. Resultaten belyser sex affärsmodeller som ligger i linje med svenska värderingar och mål, och betonar vikten av gemenskapsinvolvering, hållbarhet och innovation i omvandlingen av Sveriges energisektor. Dessa modeller inkluderar gemenskapsbaserad energiproduktion, självkonsumtion av energi i bostäder, delad gemenskapsenergiproduktion, kooperativ för elektrisk mobilitet, kollektiva finansiella initiativoch modeller baserade på cirkulär ekonomi. Som avslutning föreslår avhandlingen en Integrerad Hållbar Energi Gemenskaps Modell (ISEGM) som ett holistiskt framtida energigemenskap för att vägleda Sveriges övergång mot en mer decentraliserad, deltagande och hållbar energiframtid. Denna modell inkluderar hållbar energiproduktion, smart stadsrörlighet, återvinning av resurser och digital integration. Som vidare rekommenderar strategiska initiativ för implementering, såsom utveckling av gemenskapsplattformar, skapande av strategiska partnerskap och etablering av miljö- och sociala mätvärden. Forskningen bidrar till akademiska och praktiska diskussioner om hållbara energiövergångar, och erbjuder ett strategiskt ramverk för att utnyttja gemenskapsbaserade modeller för att uppnå Sveriges miljö- och energimål. Den uppmanar till aktivt engagemang från regeringen, industrin, akademin och gemenskaper för att förverkliga potentialen i innovativa affärsmodeller för att främja Sveriges hållbarhetsagenda inom energi.