In this dissertation, an assessment is conducted of the potential benefits of combined heat and power (CHP) based district energy (DE) grids in energy systems of different scale having significant fossil fuel fired electrical generation capacity. Three studies are included in the research. In the first study, the potential benefits of expanding CHP-based DE grids in a large scale energy system are investigated. The impacts of expanding wind power systems are also investigated and a comparison between these technologies is made with respect to fossil fuel utilization and CO2 emissions. A model is constructed and five scenarios are evaluated with the EnergyPLAN software taking the province of Ontario, Canada as the case study. Results show that reductions in fuel utilization and CO2 emissions of up to 8.5% and 32%, respectively, are possible when switching to an energy system comprising widespread CHP-based DE grids. In the second study, a high temporal resolution numerical model (i.e. the SS-VTD model) is developed that is capable of rapidly calculating distribution losses in small scale variable flow DE grids with low error and computational intensity. The SS-VTD model is validated by comparing simulated temperature data with measured temperature data from an existing network. The Saanich DE grid, located near Victoria, Canada, is used as the case study for validation. In the third study, the potential benefits of integrating high penetrations of renewable energy via a power-to-heat plant in a small scale CHP-based DE grid are investigated. The impacts of switching to a CHP-based DE grid equipped with an electric boiler plant versus a conventional wave power system are compared with respect to fossil fuel utilization and CO2 emissions. The SS-VTD model is used to conduct the study. The energy system of the Hot Springs Cove community, located on the west coast of Vancouver Island, Canada is used as the case study in the analysis. Results show that relative to the conventional wave power system, reductions in fuel utilization and CO2 emissions of up to 47% are possible when switching to a CHP-based DE grid. / Graduate

Thermal energy storage (TES), the storage of heat or cooling, is a cost-effective energy storage technology that can greatly enhance the performance of the energy systems with which it interacts. TES acts as a buffer between transient supply and demand of energy. In solar thermal systems, TES enables the power output of the plant to be effectively regulated, despite fluctuating solar irradiance. In district energy systems, TES can be used to shift loads, allowing the system to avoid or take advantage of peak energy prices. The benefit of TES, however, can be significantly enhanced by dynamically optimizing the complete energy system. The ability of TES to shift loads gives the system newfound degrees of freedom which can be exploited to yield optimal performance. In the hybrid solar thermal/fossil fuel system explored in this work, the use of TES enables the system to extract nearly 50% more solar energy when the system is optimized. This requires relaxing some constraints, such as fixed temperature and power control, and dynamically optimizing the over a one-day time horizon. In a district cooling system, TES can help equipment to run more efficiently, by shifting cooling loads, not only between chillers, but temporally, allowing the system to take advantage of the most efficient times for running this equipment. This work also highlights the use of TES in a district energy system, where heat, cooling and electrical power are generated from central locations. Shifting the cooling load frees up electrical generation capacity, which is used to sell power to the grid at peak prices. The combination of optimization, TES, and participation in the electricity market yields a 16% cost savings. The problems encountered in this work require modeling a diverse range of systems including the TES, the solar power plant, boilers, gas and steam turbines, heat recovery equipment, chillers, and pumps. These problems also require novel solution methods that are efficient and effective at obtaining workable solutions. A simultaneous solution method is used for optimizing the solar power plant, while a static/dynamic decoupling method is used for the district energy system. / text

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Conventionally, to support varying power demand, the utility company must prepare to supply more electricity than actually needed, which causes inefficiency and waste. With the increasing penetration of renewable energy which is intermittent and stochastic, how to balance the power generation and demand becomes even more challenging. Demand response, which reschedules part of the elastic load in users' side, is a promising technology to increase power generation efficiency and reduce costs. However, how to coordinate all the distributed heterogeneous elastic loads efficiently is a major challenge and sparks numerous research efforts. In this thesis, we investigate different methods to provide demand response and improve power grid efficiency. First, we consider how to schedule the charging process of all the Plugged-in Hybrid Electrical Vehicles (PHEVs) so that demand peaks caused by PHEV charging are flattened. Existing solutions are either centralized which may not be scalable, or decentralized based on real-time pricing (RTP) which may not be applicable immediately for many markets. Our proposed PHEV charging approach does not need complicated, centralized control and can be executed online in a distributed manner. In addition, we extend our approach and apply it to the distribution grid to solve the bus congestion and voltage drop problems by controlling the access probability of PHEVs. One of the advantages of our algorithm is that it does not need accurate predictions on base load and future users' behaviors. Furthermore, it is deployable even when the grid size is large. Different from PHEVs, whose future arrivals are hard to predict, there is another category of elastic load, such as Heating Ventilation and Air-Conditioning (HVAC) systems, whose future status can be predicted based on the current status and control actions. How to minimize the power generation cost using this kind of elastic load is also an interesting topic to the power companies. Existing work usually used HVAC to do the load following or load shaping based on given control signals or objectives. However, optimal external control signals may not always be available. Without such control signals, how to make a tradeoff between the fluctuation of non-renewable power generation and the limited demand response potential of the elastic load, and to guarantee user comfort level, is still an open problem. To solve this problem, we first model the temperature evolution process of a room and propose an approach to estimate the key parameters of the model. Then, based on the model predictive control, a centralized and a distributed algorithm are proposed to minimize the fluctuation and maximize the user comfort level. In addition, we propose a dynamic water level adjustment algorithm to make the demand response always available in two directions. Extensive simulations based on practical data sets show that the proposed algorithms can effectively reduce the load fluctuation. Both randomized PHEV charging and HVAC control algorithms discussed above belong to direct or centralized load shaping, which has been heavily investigated. However, it is usually not clear how the users are compensated by providing load shaping services. In the last part of this thesis, we investigate indirect load shaping in a distributed manner. On one hand, we aim to reduce the users' energy cost by investigating how to fully utilize the battery pack and the water tank for the Combined Heat and Power (CHP) systems. We first formulate the queueing models for the CHP systems, and then propose an algorithm based on the Lyapunov optimization technique which does not need any statistical information about the system dynamics. The optimal control actions can be obtained by solving a non-convex optimization problem. We then discuss when it can be converted into a convex optimization problem. On the other hand, based on the users' reaction model, we propose an algorithm, with a time complexity of O(log n), to determine the RTP for the power company to effectively coordinate all the CHP systems and provide distributed load shaping services. / Graduate

Dirigé par la société Fonroche Géothermie, un consortium de dix partenaires participe au projet FONGEOSEC qui s’inscrit dans le cadre des Investissements d’Avenir de l’ADEME. Ce projet a pour but de concevoir et de réaliser un démonstrateur innovant de centrale géothermique haute enthalpie. L’énergie, ainsi récupérée en profondeur, servira à la cogénération d’électricité et de chaleur. L’une des étapes du projet correspond à l’objectif de cette thèse : développer une méthodologie pour la conception optimale des activités de surface de la centrale géothermique. Il s’agit donc de formuler le problème d’optimisation, de proposer une stratégie de résolution robuste et enfin, de mettre en oeuvre cette stratégie grâce à un outil logiciel.Dans l’outil ainsi développé, la répartition entre la production d’électricité et de chaleur s’effectue en parallèle. Le fluide géothermal est séparé en deux courants, l’un alimentant un Cycle Organique de Rankine (ORC : Organic Rankine Cycle) pour la production d’électricité, et l’autre étant relié à un Réseau de Chaleur Urbain (RCU) pour la distribution de la chaleur. Chaque constituant de l’ORC est dimensionné et la topologie du RCU est déterminée. Cet outil permet alors de déterminer simultanément :quelle est la meilleure répartition entre production d’électricité et de chaleur,quelles sont les meilleures dimensions pour les composants de l’ORC,et quelle est la meilleure topologie du RCU.Concernant l’ORC, l’outil permettra de savoir si l’utilisation d’un éventuel récupérateur de chaleur interne (IHE : Internal Heat Exchanger) est avantageuse ou non. Du point de vue du RCU, tous les consommateurs (sous-stations) envisagés ne sont pas obligatoires. L’outil permettra de choisir quels consommateurs relier au réseau et dans quelle disposition. L’utilisation de variables discrètes est alors nécessaire et le problème d’optimisation ainsi résolu est un problème de type MINLP (Mixed Integer Non Linear Programming).Une méthodologie de résolution permettant l’obtention d’une solution de « confiance » (probablement, mais non certainement, l’optimum global) est proposée. Cette stratégie de résolution est testée pour différents cas d’étude proches des conditions du projet FONGEOSEC. La stabilité et la robustesse de cette stratégie sont alors mises en avant. Une analyse économique et une analyse énergétique sont réalisées. La résolution multi-objectif est alors effectuée dans le but de fournir le meilleur compromis entre bénéfices annuels nets et destruction d’exergie. Pour finir, la diversité des résultats montre qu’il n’est pas satisfaisant de dissocier les études des deux systèmes (ORC et RCU) et démontre l’intérêt de l’outil développé. / A consortium of ten partners, led by “FONROCHE Géothermie”, works on the FONGEOSEC project, an “Investissement d’Avenir” organized by the French Agency for Environment and Energy (ADEME). The aim of this project is to design and create an innovative demonstrator of a high-energy geothermal power plant. The geothermal energy will be used to produce electricity and heat. Among other tasks, this project aims to develop a support tool for the optimal design of the structure for the surface activities in the geothermal plant.Within the developed tool, the repartition between electricity and heat production is in parallel. The geothermal fluid is split in two streams, one is used for an Organic Rankine Cycle (ORC) for electricity production, and the other is connected to a District Heating Network (DHN) for the heat distribution. This tool enables to determine simultaneously:which is the best repartition between electricity and heat,which is the best sizing for ORC components,which is the best configuration for the DHN.About the ORC, the tool will enable to decide if the use of an Internal Heat Exchanger (IHE) is interesting or not. For the DHN point of view, all the consumers envisaged are not mandatory. The tool will enable to choose which consumers it is better to connect to the network and in which disposition. The use of discrete variables is necessary and the optimization problem to be solved is a MINLP (Mixed Integer Non Linear Programming) problem.A solution strategy is implemented in order to obtain a confident solution with a determinist algorithm. This strategy is tested for different study cases close to FONGEOSEC conditions. Stability and Robustness of this strategy are then highlighted. An economic and an exergetic analysis are carried out. In order to find a good compromise between the two objectives, a multi-objective solution is performed. Finally, the diversity of results obtained shows it is not suitable to dissociate ORC and DHN studies and shows the interest of the developed tool.

Organic Rankine cycles can be integrated with district heating systems and in applications of biogas digestion. Evaluating the performance of the installations by Againity AB in Ronneby and Norrköping, Sweden, is a unique opportunity which can support the establishment of ORC technology in the waste heat recovery market, unveiling its feasibilities and limitations. Operational data gathered from October 2017 until April 2018, provides this thesis with information about the ORC-systems. A method using Coolprop and Matlab has been used to detect steady-state series in the Ronneby installation using moving standard deviation and inclination criteria. By screening the data and selecting these series, analytical equations can be used to determine the performance of the installations and map the linear relationship between variables like pressure and generator power. The largest impact on the system in Ronneby is developed in the condenser. Large coolant volume flow creates large heat sink capacity and higher generator efficiency and power. However, with increasing generator power the condenser pressure decrease. Lower condenser pressure results in a decreased evaporation pressure, which could be maintained if the pump was able to run at higher frequencies. The Plant in Norrköping needs further studies and a review of its sensors. The code in Matlab is a resource to Againity and Linköpings university for future work in performance evaluation. It can be used to detect errors in energy balance, local readings, and picture the machines' performance graphically.

Exploitation of waste heat could achieve economic and environmental benefits, while at the same time increase energy efficiency in process sites. Diverse commercialised technologies exist to recover useful energy from waste heat. In addition, there are multiple on-site and offsite end-uses of recovered energy. The challenge is to find the optimal mix of technologies and end-uses of recovered energy taking into account the quantity and quality of waste heat sources, interactions with interconnected systems and constraints on capital investment. Explicit models for waste heat recovery technologies that are easily embedded within appropriate process synthesis frameworks are proposed in this work. A novel screening tool is also proposed to guide selection of technology options. The screening tool considers the deviation of the actual performance from the ideal performance of technologies, where the actual performance takes into account irreversibilities due to finite temperature heat transfer. Results from applying the screening tool show that better temperature matching between heat sources and technologies reduces the energy quality degradation during the conversion process. A ranking criterion is also proposed to evaluate end-uses of recovered energy. Applying the ranking criterion shows the use to which energy recovered from waste heat is put determines the economics and potential to reduce CO2 emissions when waste heat recovery is integrated in process sites. This thesis also proposes a novel methodological framework based on graphical and optimization techniques to integrate waste heat recovery into existing process sites. The graphical techniques are shown to provide useful insights into the features of a good solution and assess the potential in industrial waste heat prior to detailed design. The optimization model allows systematic selection and combination of waste heat source streams, selection of technology options, technology working fluids, and exploitation of interactions with interconnected systems. The optimization problem is formulated as a Mixed Integer Linear Program, solved using the branch-and-bound algorithm. The objective is to maximize the economic potential considering capital investment, maintenance costs and operating costs of the selected waste heat recovery technologies. The methodology is applied to industrial case studies. Results indicate that combining waste heat recovery options yield additional increases in efficiency, reductions in CO2 emissions and costs. The case study also demonstrates that significant benefits from waste heat utilization can be achieved when interactions with interconnected systems are considered simultaneously. The thesis shows that the methodology has potential to identify, screen, select and combine waste heat recovery options for process sites. Results suggest that recovery of waste heat can improve the energy security of process sites and global energy security through the conservation of fuel and reduction in CO2 emissions and costs. The methodological framework can inform integration of waste heat recovery in the process industries and formulation of public policies on industrial waste heat utilization.

La thèse répond à deux problématiques, d'une part la quantification des effacements de consommation d'électricité par technologies gaz dans l'habitat et d'autre part de l'intégration de leurs valorisations dans une perspective de planification des infrastructures. Ces travaux se justifient dans un contexte d'augmentation de la pointe électrique, à l'origine d'une hausse du risque de défaillance du système, et de la baisse des consommations de gaz naturel conduisant à une sous utilisation du réseau de distribution. Pourtant, alors que la demande en gaz naturel croît du fait de l'installation de centrales à cycle combiné sur le réseau de transport, l'interaction des réseaux de distribution gaz/électricité n'est pas exploitée.Ce manuscrit envisage l'intégration des technologies gaz comme moyen de Maîtrise de la Demande en Électricité dans le processus de planification des réseaux. Ainsi les effacements de consommations d'électricité lors des périodes dimensionnantes par des micro-cogénérateurs ou des chaudières hybrides sont des solutions alternatives aux solutions de renforcement de réseaux.Pour quantifier le gisement d'effacement, nous nous intéressons à l'impact marginal des systèmes sur la demande en termes de modification de la quantité d'Énergie Non Distribuée potentielle. Les estimations des impacts de systèmes de chauffage sur la demande sont donc des prérequis à cette approche. Nous modélisons les courbes de charge régionales par une approche Bottom-Up permettant de déterminer les profils de demande marginale de chauffage en fonction des systèmes. La mise en application de cette méthode est à fiabiliser par des études socio-technico-économiques permettant de réduire les incertitudes sur les déterminants des besoins de chauffage. Une calibration en puissance des profils générés a été proposée mais n'a pu être réalisée. En revanche, nous apportons une contribution à l'analyse des courbes de charge agrégées en montrant que le modèle d'estimation actuellement utilisé par le gestionnaire de réseau s'apparente à un modèle simplifié de bâtiment / This PhD thesis addresses two issues: Firstly, the assessment of Demand Side Management (DSM) opportunity of gas and electricity technologies in dwellings, and secondly, the integration of their valuations in infrastructure planning schemes.This work originaites from a context of the growth of electricity peaks (which increased risk of system failure) and the natural gas consumption decrease which leads to an under-utilization of the gas distribution network.This manuscript focuses on the integration of gas technologies as DSM solution to contribute to the planning of electricity grid. Indeed, relieving the electricity consumption during constrained periods by diffusing micro-cogeneration or hybrid boiler, is an actual alternative to network reinforcement solutions. To quantify the load shedding capacity, we are interested in the marginal impact of demand systems on the amount of Energy Not Supplied potential. Estimating systems' impacts on heating demand is a prerequisite to this approach. So we model the regional heating load curves by a Bottom-Up approach to simulate marginal demand profiles depending on heating systems. The implementation of this method requires socio-technico-economic studies to reduce uncertainty of the determinants of heating needs. A load calibration methodology has been proposed but has not been performed. However, we make a contribution to the analysis of aggregated load curves emphasizing that the load model currently used by network operator similar to a simplified building model.

Panna 6 på Högdalenverket i södra Stockholm (P6) med tillhörande ångturbin producerar kraftvärme genom förbränning av utsorterat returbränsle från industri och samhälle. För att minimera underhållskostnader och öka anläggningens tillgänglighet är det viktigt att fel och oönskat processbeteende kan upptäckas i ett tidigt skede. I detta syfte testas här en metod för detektering av avvikande händelser med hjälp av principalkomponentanalys (PCA) på produktionsprocessen för kraftvärme. En PCA-modell med reducerad dimension skapas utifrån processdata från en problemfri driftperiod och används som mall för inkommande data att jämföras med i ett kontrolldigram. Avvikelser ifrån modellen bör vara en indikation på att ett onormalt drifttillstånd har uppkommit och orsaker till avvikelsen analyseras. Som avvikande händelse testas två fall av tubläckage som uppstod i ett av tubpaketen för kylning av rökgaserna under 2014 och 2015. Resultatet visar att processavvikelser ifrån normallägesmodellerna tydligt syns i kontrolldiagrammen vid båda tubläckagen och avvikelserna kan härledas till variabler som är kopplade till tubläckage. Det finns potential för att tillämpa metoden för övervakning av processen, en svårighet ligger i att skapa en modell som representerar processen när den är stabil på grund av att det finns många varierande driftfall som anses stabila, detta kräver vidare arbete. Metoden kan redan användas som analysverktyg exempelvis vid misstanke om tubläckage. / Boiler 6 at the Högdalen facility in southern Stockholm (P6) combined with a a steam turbine produces Combined Heat and Power (CHP) through combustion of treated industry waste. In order to minimise maintenance costs and increase plant availability it is of importance to detect process faults and deviations at an early state. In this study a method for outlier detection using Principal Component Analysis (PCA) is applied on the CHP production process. A PCA model with reduced dimension is created using process data from a problem free period and is used as a template for new operating data to be compared with in a control chart. Deviations from the model should be an indication of the presence of abnormal conditions and the reasons for the deviations are analysed. Two cases of tube failure in 2014 and 2015 are used to study the deviations. The result shows that process deviations from the models can be detected in the control chart in both cases of tube failure and the variables known to be associated with tube failure contributes highly to the deviating behaviour. There is potential for applying this method for process control, a difficulty lies in creating a model that represents the stable process when there are big variances within what is considererd a stable process state. The method can be used for data analysis when suspecting a tube failure.

La micro cogénération désigne la génération simultanée de deux types d’énergie à faible puissance. En énergétique, ce terme désigne en pratique la production simultanée d’électricité et de chaleur : le principe reposant sur la récupération de la chaleur fatale induite par la production électrique. Deux bancs d’essais ont d’abord été réalisés sur deux prototypes de micro cogénérateurs : un moteur Stirling à gaz et un moteur à vapeur à granulés de bois. Une campagne expérimentale a été menée pour caractériser chaque système au niveau énergétique et environnemental. Les résultats expérimentaux ont abouti sur deux modèles numériques dynamiques et semi-physiques de micro cogénérateurs programmés dans l’environnement numérique TRNSYS où une plateforme numérique de simulation a été développée. Celle-ci intègre principalement des modèles de systèmes de stockage d’énergie, des générateurs stochastiques de fichiers de besoins énergétiques et des stratégies innovantes de pilotage des systèmes et des charges selon des critères de précision et de réalisme.Cette plateforme a permis d’évaluer la pertinence énergétique, environnementale et économique de micro cogénérateurs couplés aux bâtiments d’habitation et au réseau électrique selon différentes configurations. / Micro combined heat and power (µCHP) or cogeneration means the simultaneous generation of two energy types. In energetic fields, this term refers usually to the simultaneous production of electricity and heat: the principle being based on the recovering of the fatal heat induced by the electricity production processes.Firstly, two test benches were carried out on two µCHP prototypes: a gas Stirling engine and a wood pellets steam engine. Experimental investigations were conducted to characterize each system at energy and environmental levels. The experimental results led two dynamic and semi physical numerical models of µCHP systems programmed in the numerical tool TRNSYS where a numerical platform has been developed. This platform integrates mainly energy storage systems models, stochastic energy needs file generators and innovative management strategy of systems and energy loads according to precision and realism criteria.This platform allows assessing realistic energy, environmental and economic relevance of µCHP systems coupled with dwelling buildings and the power grid according to different configurations.