The European Energy system is currently transitioning towards a reduced use of fossil fuels and increasing use of renewable energy. Hydrogen as energy carrier for renewable electricity has a potential to play a significant role in this transition. It can be stored and transported in its gaseous or liquid state, and utilized in industries that require highprocess heat, which makes them difficult to decarbonize. Further, hydrogen storage canbe employed to store over‐produced renewable electricity in large scale and for long periods of time. This research aims to develop a methodology to conduct a layout and dispatch optimization for utilizing locally produced hydrogen. The objective is to find the least cost supply pathway for a defined demand. In this case study, hydrogen is produced by water electrolysis supplied by the local electricity grid and renewable electricity, such as solar PV, onshore and offshore wind turbines. The scope is limited to gaseous hydrogen thereby the distribution is also limited to pipelines or road trucks. The optimized supplychain comprises four main stages: I) electricity generation and storage; II) hydrogen production; III) hydrogen compression and storage; IV) hydrogen transportation to the end consumer. It results in the system's optimum hourly dispatch schedule and a proposed least‐cost layout. The developed methodology is finally applied to an industrial case study in Sweden, for which scenarios with varying boundary conditions are tested. The least cost supply chain for the case study resulted in a system solely supplied with electricity purchased from the grid, a PEM electrolyzer, a hydrogen storage in a Lined Rock Cavern, and hydrogen transport via pipeline. The lowest Levelized Cost of Hydrogen from electricity purchase until delivery is 5.17 EUR/kgH2. The study concludes that there is no one optimum solution for all and the constraints of the optimization problem need to be evaluated case by case.The study further highlights that intermittency and peaks of both electricity availability and hydrogen demand can lead to an increase in system cost owing to the oversizing and storage needs. / Det europeiska energisystemet är för närvarande i en övergångsprocess mot en minskande användning av fossila bränslen och en ökande användning av förnybar energi. Vätgas som energibärare för förnybar el har potential att spela en viktig roll i denna övergång. Vätgas kan lagras och transporteras i gasform eller flytande form, och användas i industrier som kräver hög processvärme vars koldioxidutsläpp därför är svåra att minska. Vidare kan vätgaslagring användas för att lagra överproducerad förnybar el istor skala och under långa perioder. Denna forskning syftar till att utveckla en metod för layout och distributions optimering för utnyttjandet av lokalt producerad vätgas. Målet är att hitta den minst kostsamma försörjningsvägen för en definierad efterfrågan. I den här fallstudien produceras vätgas genom vattenelektrolys som försörjs av det lokala elnätet och förnybar el, t.ex. solceller, vindkraftverk på land och till havs. Omfattningen är begränsad till gasformig vätgas och därmed är distributionen också begränsad till rörledningar eller lastbilar. Den optimerade försörjningskedjan består av fyra huvudsteg: I) elproduktion och lagring, II) vätgasproduktion, III) komprimering och lagring av vätgas, IV) transport av vätgas till slutkonsumenten. Metodens output är systemets optimala timplan och ett förslag till layout med den lägsta kostnaden.  Den utvecklade metoden tillämpas slutligen i en industriell fallstudie i Sverige, för vilken scenarier med varierande randvillkor testas. Den minst kostsamma försörjningskedjan för fallstudien resulterade i ett system som enbart försörjs med el som köps från nätet, en PEM‐elektrolyser, ett magasin för vätgaslagring i ett fodrat bergrum och vätgastransport via en rörledning. Den lägsta Levelized Cost för vätgas från el inköp till leverans är 5,17EUR/ kgH2. I studien dras slutsatsen att det inte finns någon optimal lösning i allmänhet och att begränsningarna i optimeringsproblemet måste utvärderas från fall till fall. Studien belyser vidare att ostadighet och toppar i både eltillgången och efterfrågan på vätgas kan leda till en ökning av systemkostnaderna på grund av överdimensionering och lagringsbehov.

The problem of fleet design and fleet modelling; for decades problems regarding determining fleet sizes and optimized routing problems have formed the groundwork into the fleet design and fleet optimization for a wide range of business sectors. In most of these problems only single entities or fixed design resources are optimized for a certain route and delivery objective based on minimizing operational costs. In the naval industry, there has been a growing need for numerical methods that are able to predict what kind of fleets, in terms of size and capabilities, would be suited to achieve certain operational needs. Further than that, for shipbuilders and designers, what kind of design requirements the individual vessel platforms in such a fleet must contain constitutes the bridge in translating operational needs to ship design and system integration requirements. Especially in an era where technology advances more quickly than it takes to design a naval vessel, creating tools that are able to predict something about future fleet resilience could become an effective asset for future naval fleet development. For this, studies that contribute to developing methods that can evaluate the combined effect of individual vessel platforms from a fleet perspective are still fairly limited. The overall goal of this study was to determine how the development and application of fleet modelling tools can contribute to designing naval fleets that are more robust against future threats and missions. The objective was to extend and build on a fleet modelling method based on Systems Engineering, that is able to generate fleet compositions and produce basic individual platform design requirements for early-stage design phases of naval fleets through scripted naval scenario's. The aim was to construct a functional numerical simulation model through Mixed Integer Linear programming and extend the abilities of the method to be able to include 'future' technologies, with UXV's receiving the main focus. The overall potential and results that the numerical model produces are interesting, through an optimization process it is able to build a fleet from a wide range of platform choices and deliver basic platform design requirements. Actual combat performance of the fleets that are generated, is debatable and needs to be further investigated and tested/verified through different means. The conclusion from the study is that to design future resilient fleets, more research and development is needed in the area of naval fleet modelling and simulation since the functionality of tools available can not overcome the amount of uncertainty that the future brings. Besides that, the method under review does make it able to generate interesting fleet combinations that could spark new ideas on how we could regard the future potential of uprising technology and their combined capabilities with naval vessel platforms. / Problemet med flottdesign och flottmodellering; i årtionden har problem med att bestämma flottans storlek och optimerade routingproblem bildat grunden för flottans design och flottans optimering för ett brett spektrum av affärssektorer. I de flesta av dessa problem är mätvärden för enkel design eller fasta fartyg optimerade för en viss rutt och antal hamnar baserat på minimering av driftskostnader. Inom marinindustrin har det funnits ett växande behov av numeriska metoder som kan förutsäga vilken typ av flotta, när det gäller storlek och kapacitet, som skulle vara lämplig för att möta vissa operativa behov. För varvsbyggare och konstruktörer fungerar dessutom att tillskriva designkrav till enskilda fartygsplattformar i en sådan flotta som bron som översätter operativa behov till krav på fartygsdesign och systemintegration. Särskilt i en tid där tekniken går snabbare än vad som krävs för att utforma ett marinfartyg kan skapandet av verktyg som kan förutsäga motståndskraften hos en framtida flotta vara en effektiv tillgång för framtida marinutveckling. För detta är studier som bidrar till att utveckla metoder som kan utvärdera den kombinerade effekten av enskilda fartygsplattformar ur ett flottperspektiv fortfarande ganska begränsade. Det övergripande målet för denna studie var att avgöra hur utvecklingen och tillämpningen av verktyg för modellering av flottor kan bidra till att utforma marinflottor som är mer robusta mot framtida hot och uppdrag. Målet var att utöka och bygga på en flottmodelleringsmetod baserad på Systems Engineering, som kan generera flottanheter och producera grundläggande individuella plattformskrav för designfasen i de tidiga stadierna av marina flottar genom scenarier för manusskrivning. Syftet var att konstruera en funktionell numerisk simuleringsmodell genom Mixed Integer Linear Programmering och utöka metodens förmåga för att kunna inkludera 'framtida' teknologier, med UXV: er som huvudfokus. Den övergripande potentialen och resultaten som den numeriska modellen ger är intressanta, genom en optimeringsprocess kan den bygga en flotta från ett brett spektrum av plattformsval och leverera grundläggande krav på plattformsdesign. Den faktiska stridsprestandan för de genererade flottorna kan inte bedömas och måste undersökas vidare och testas / verifieras med olika metoder. Studien drar slutsatsen att utformning av framtida motståndskraftiga flottor kräver mer forskning och utveckling inom marinmodellering och simulering, eftersom funktionaliteten hos nuvarande tillgängliga verktyg inte kan övervinna osäkerheten i framtiden. Förutom det gör metoden under granskning det möjligt att generera intressanta flottkombinationer som kan utlösa nya idéer om hur vi kan betrakta den framtida potentialen för upprorsteknologi och deras kombinerade kapacitet med sjöfartygsplattformar.

A crucial challenge introduced by the decentralized installations of photovoltaic (PV) systems in the residential sector, is the mismatch between PV electricity generation and the load curve for energy consumption. To overcome this incompatibility between production and consumption, energy storage and demand response are seen as effective solutions. Smart meters and the installation of intelligent smart appliances in homes have paved the way for efficient energy consumption monitoring and active household load control in the residential sector.  The aim of the thesis work is to develop a dynamic energy management algorithm tailored to optimize the energy consumption pattern of controllable household assets to maximize PV selfconsumption. A rolling horizon algorithm based dynamic model was designed using mixedinteger linear programming (MILP) and later compared with the baseline model to understand the real-time operational benefits of the rolling horizon approach.  Analyzing device scheduling patterns based on the feed-in-tariff showed considerable differences in the scheduling approach for both optimization models. A comparative analysis was conducted to understand the system benefits offered by both optimization models under different feed-in-tariff structures. Higher self-consumption rates were achieved through annual scheduling approach, but it does not reflect the real-time operation of the systems in the household. A rolling horizon optimization reflects the real-time operation of the energy system and has a lower self-consumption rate due to a limited optimization horizon. The method indicates the significant potential of self-consumption specially in lieu of decreasing feed-in tariffs. / En viktig utmaning som de decentraliserade installationerna av solcellssystem i bostadssektorn innebär är att elproduktionen från solcellerna inte stämmer överens med belastningskurvan för energiförbrukningen. För att komma till rätta med denna oförenlighet mellan produktion och konsumtion ses energilagring och efterfrågeflexibilitet som effektiva lösningar. Smarta mätare och installation av intelligenta smarta apparater i hemmen har banat väg för effektiv övervakning av energiförbrukningen och aktiv styrning av hushållens belastning i bostadssektorn.  Syftet med avhandlingen är att utveckla en dynamisk energihanteringsalgoritm som är skräddarsydd för att optimera energiförbrukningsmönstret för kontrollerbara hushållstillgångar för att maximera självförbrukningen av solceller. En dynamisk modell baserad på en algoritm med rullande horisont utformades med hjälp av blandad linjär programmering (MILP) och jämfördes senare med basmodellen för att förstå de operativa realtidsfördelarna med metoden med rullande horisont. Analysen av schemaläggningsmönster för enheter baserat på inmatningstariffen visade att det fanns betydande skillnader i schemaläggningsmetoden för båda optimeringsmodellerna. En jämförande analys genomfördes för att förstå de systemfördelar som erbjuds av de båda optimeringsmodellerna under olika strukturer för inmatningstariffer. Högre självförbrukningsnivåer uppnåddes genom den årliga schemaläggningsmetoden, men den återspeglar inte realtidsdriften av systemen i hushållet. En optimering med rullande horisont återspeglar energisystemets drift i realtid och har en lägre självförbrukningsgrad på grund av en begränsad optimeringshorisont. Metoden visar på den betydande potentialen för självförbrukning speciellt i stället för minskande inmatningstariffer.

The rising cost of military aircraft has driven the DoD to increase the utilization of commercial off-the-shelf (COTS) components in new acquisitions. Despite several demonstrated advantages of COTS-based systems, challenges relating to obsolescence arise when attempting to design and sustain such systems using traditional acquisition processes. This research addresses these challenges through the creation of an Agile Systems Engineering framework that is specifically aimed at COTS-based systems. This framework, known as the Cyber-physical Acquisition Strategy for COTS-based Agility-Driven Engineering (CASCADE), amends the traditional systems engineering process through the addition of an "identification phase" during which requirements are balanced against the capabilities of commercially-available components. The CASCADE framework motivates the creation of a new Mixed Integer Linear Programming (MILP) formulation which enables the creation of optimum obsolescence mitigation plans. Using this CASCADE MILP formulation, two sets of experiments are carried out: First, verification experiments demonstrate that the CASCADE MILP conforms to expected trends and agrees with existing results. Next, the CASCADE MILP is applied to a representative set of COTS-based systems in order to determine the appropriate level of obsolescence forecast accuracy, and to uncover new system-level cost-vs-reliability trends associated with COTS component modification.

Dans un contexte de développement durable, la question énergétique constitue un des problèmes majeurs des décennies à venir. Bien que la solution pour faire face à la raréfaction de certaines ressources, l'augmentation globale de la demande l'augmentation des émissions de CO2, réside dans le développement des énergies renouvelables, il est clair que ces nouvelles technologies ne seront matures que dans plusieurs décennies. A court terme, les énergies fossiles demeureront la source principale d'énergie primaire. Il est donc essentiel de promouvoir de nouvelles méthodologies permettant une utilisation plus rationnelle de l'énergie. Dans le secteur industriel, le développement de centrales de production d'utilités sur le site industriel (en général des centrales de cogénération) contribue grandement à l'amélioration de l'efficacité énergétique des procédés. Traditionnellement, la gestion de ce type de système repose sur une approche séquentielle : ordonnancement de l'atelier de production, calcul des besoins énergétiques et planification de la centrale de cogénération. Toutefois, dans ce type d'approche, l'accent est mis avant tout sur l'atelier de production, la centrale de cogénération étant considérée comme une unité esclave. Pour améliorer le processus de décision, cette thèse développe une approche intégrée pour l'ordonnancement simultanée et cohérent des ateliers de production et des centrales de production d'utilités. La méthodologie proposée repose sur une formulation MILP à temps discret. Par ailleurs, une extension du formalisme RTN a été développée : les ERTN ("Extended Resource Task Network"). Celui-ci permet d'une part, de décrire de manière systématique les recettes et d'autre part, permet une modélisation explicite et générique des différents types de systèmes dont notamment les centrales d'utilités. Les résultats montrent que l'approche intégrée permet d'obtenir une réduction notable du coût énergétique grâce une meilleure coordination des activités de production et de fabrication d'utilités. En effet, les tâches de production sont ordonnancées de manière à consommer sur les mêmes périodes les utilités générées simultanément par la centrale de cogénération, conduisant ainsi à une réduction significative du rapport quantité de biens fabriqués / quantité de carburant consommé et des émissions de gaz à effet de serre. / The issue of energy has emerged as one of the greatest challenges facing the mankind. The search is on for finding alternative sources of energy that will replace fossil fuels as the primary source of energy. However, for the foreseeable future, fossil fuels will remain the main source of energy. Therefore, it is of paramount importance to devise methodologies for more rational use of energy in all walks of human life. In the industrial perspective, the deployment of site utility system (generally CHP plants) provides a great potential source for energy savings. However, the management of such type of industrial units is traditionally carried out using sequential three step approach: scheduling of the production plant, estimation of the utility needs of production plant and finally scheduling of the site utility system. In this kind of approach, all the focus is placed on the production plant and the utility system is treated as its subsidiary. To improve the decision-making process, this thesis proposes an integrated approach which addresses this imbalance by carrying out simultaneous and coherent scheduling of batch production plant and site utility system. The proposed methodology relies on discrete time modeling and uses Mixed Integer Linear Programming (MILP). Moreover, to permit an efficient and generic formulation of various kinds of industrial problems, a new scheduling framework called Extended Resource Task Network (ERTN) has been developed. The ERTN framework (an extension of existing RTN framework) allows for accurate representation and scheduling of any type of production plant and any type of site utility system. The results show that the integrated approach leads to better synchronization between production plant and site utility system. Thereby, the integrated approach leads to significant reduction in energy costs and decrease in harmful gas emissions.

The global community is facing great challenges as the energy system is transforming towards more reliable, effective, clean and renewable production. Small-scale and micro networks will play an important role in this changeover. Its advantages over today’s large conventional energy systems are their reliability and stability. In small-scale and micro networks, there is usually a variety of production units such as photovoltaic, wind power and micro-combined heat and power (micro-CHP). In this study, a small-scale network with an application of two different types of biogas fueled micro-CHPs is analyzed. The units are a micro gas engine (MGM) and a micro gas turbine (MGT). The application of micro-CHP is validated using a reference facility connected to a small-scale district heating network. The reference facility is a heat production plant at a horse race track outside Eskilstuna, Sweden consisting of an oil boiler, a pellet boiler and a heat storage tank. The potential in replacing the oil boiler with renewable micro-CHP is investigated. A simulation model is built in the software GAMS, using Mixed Integer Linear Programming (MILP) and the solver CPLEX, and the model is simulated using the heat demand from the horse race track. Results from the model validation shows that it is possible for both the MGM or the MGT together with the pellet boiler and the heat storage tank to fulfill the heat demand of the facility. The horse race track handles 4 000 m3 of horse manure annually, which is transported 124 km to a compost treatment facility. Therefore, a general analysis of biogas production from horse manure is conducted in order to investigate the possibilities for better horse manure treatment on site. A calculation for a biogas reactor with a capacity for the maximum biogas requirement of the micro-CHP is implemented. Horse manure is suggested to be co-digested with food waste, in order to provide a higher biogas exchange. The result of a Life Cycle Cost (LCC) analysis indicates difficulties in justifying an investment of a micro-CHP together with a biogas plant at current prices for heat and electricity. The results show that the payback period for the MGM is 7 years which is 2 years shorter than its lifetime and the MGT payback period is 12 year which also is it lifetime. The MGM shows the largest investment potential since it has an investment cost approximately 860 kSEK lower than for the MGT. The MGM also has a slightly higher electrical efficiency which results in higher revenues from produced electricity. The chosen MGM in this study is slightly smaller than the MGT, resulting in a lower biogas demand and a lower investment cost for a biogas plant. A sensitivity analysis shows great impact of the electricity price on the payback period for both types of micro-CHP. The results show that with an electricity price of 280 SEK/MWh, both the MGM and the MGT repays within their lifetime. But since MGM has a higher net present value at all electric prices, is the MGM considered to be a more economical feasible investment. What the authors think should be highlighted is also the environmental benefits of more efficient treatment of horse manure at the horse race track together with the possibility of local production of fuel resulting in reduced CO2 emissions by 47 tons/year.

Context: Unmanned Aerial Vehicles are being widely being used for various scientific and non-scientific purposes. This increases the need for effective and efficient path planning of Unmanned Aerial Vehicles.Two of the most commonly used methods are the A-star algorithm and Mixed Integer Linear Programming.Objectives: Conduct a simulation experiment to determine the performance of A-star algorithm and Mixed Integer Linear Programming for path planning of Unmanned Aerial Vehicle in a simulated environment.Further, evaluate A-star algorithm and Mixed Integer LinearProgramming based computational time and computational space to find out the efficiency. Finally, perform a comparative analysis of A star algorithm and Mixed Integer Linear Programming and analyse the results.Methods: To achieve the objectives, both the methods are studied extensively, and test scenarios were generated for simulation of Objectives: Conduct a simulation experiment to determine the performance of A-star algorithm and Mixed Integer Linear Programming for path planning of Unmanned Aerial Vehicle in a simulated environment.Further, evaluate A-star algorithm and Mixed Integer LinearProgramming based computational time and computational space to find out the efficiency. Finally, perform a comparative analysis of A star algorithm and Mixed Integer Linear Programming and analyse the results.Methods: To achieve the objectives, both the methods are studied extensively, and test scenarios were generated for simulation of Methods: To achieve the objectives, both the methods are studied extensively, and test scenarios were generated for simulation of these methods. These methods are then implemented on these test scenarios and the computational times for both the scenarios were observed.A hypothesis is proposed to analyse the results. A performance evaluation of these methods is done and they are compared for a better performance in the generated environment. Results: It is observed that the efficiency of A-star algorithm andMILP algorithm when no obstacles are considered is 3.005 and 12.03functions per second and when obstacles are encountered is 1.56 and10.59 functions per seconds. The results are statistically tested using hypothesis testing resulting in the inference that there is a significant difference between the computation time of A-star algorithm andMILP. Performance evaluation is done, using these results and the efficiency of algorithms in the generated environment is obtained.Conclusions: The experimental results are analysed, and the Conclusions: The experimental results are analysed, and the efficiencies of A-star algorithm and Mixed Integer Linear Programming for a particular environment is measured. The performance analysis of the algorithm provides us with a clear view as to which algorithm is better when used in a real-time scenario. It is observed that Mixed IntegerLinear Programming is significantly better than A-star algorithm.

I dagsläget står bostads- och servicesektorn för cirka 40% av den totala slutliga energianvändningen i Sverige [1], vilket motsvarar utsläpp av cirka 6 miljoner ton koldioxidekvivalenter [2]. Cirka 90% av denna energianvändning har sitt ursprung från hushåll och lokalbyggnader [1]. Eftersom Sveriges nationella klimatmål innefattar att utsläppen år 2020 ska minska med 40% jämfört med år 1990  [3] är det aktuellt att minska energianvändningen i byggnader. Det här examensarbetet har som syfte att ta fram åtgärdsförslag som bör realiseras vid renovering av en ändamålslokal med kulturhistoriskt värde. Åtgärdsförslag har därför tagits fram genom en livscykelkostnadsoptimering i OPERA-MILP. Eftersom det var känt att inomhustemperaturen sommartid ofta översteg normalt sett accepterad maxtemperatur (24°C [4]) har även åtgärdsförslag för ett förbättrat inomhusklimat undersökts. Byggnaden i dagsläget, en planerad renovering samt en livscykelkostnadsoptimerad byggnad har modellerats i IDA-ICE för att simulera energiflöden och inomhusklimat.  Modellen av byggnaden i dagsläget resulterade i ett fjärrvärmebehov på cirka 120 000 kWh under ett år, vilket är en avvikelse med 6% mot historisk fjärrvärmedata. Den planerade renoveringen fick ett ökat behov med cirka 5 000 kWh på grund av att källaren kommer att värmas upp. Livscykelkostnadsoptimeringen i OPERA-MILP gav följande åtgärder: byte till energiglas och vindbjälksisolering på 14 cm. Dessa åtgärder minskade fjärrvärmebehovet med cirka 2 000 kWh jämfört med den planerade renoveringen, vilket innebär att behovet fortfarande är större än i dagsläget. Den specifika energianvändningen minskade dock något då den gick från 114 kWh/(m2, år) till 100 kWh/(m2, år), vilket beror på den ökade tempererade arean och de energibesparande åtgärderna. Vid simulering av modellerna sågs att byggnaderna var överhettade sommartid. Därför undersöktes inre solavskärmning, fjärrkyla, ventilationsstyrning och olika ventilationstyper. Fjärrkyla resulterade i ett behagligt inomhusklimat med en driftskostnad på cirka 4 000 sek årligen. Slutligen simulerades en kombination av olika åtgärder vilket resulterade i ett minskat fjärrvärmebehov med cirka 13 000 kWh jämfört med dagsläget och en specifik energianvändning på 88 kWh/(m2, år). Detta gjordes genom att kombinera de livscykelkostnadsoptimerade åtgärderna med tätning, fjärrkyla samt närvarostyrd ventilation. / As of today, the housing and service sector stands for about 40% of the total net energy use in Sweden [1], which equal emissions of about 60 million tons of carbon dioxide equivalents [2]. About 90% of this energy use originates from households and facilities [1]. Since Sweden's national climate goal includes that the emissions year 2020 should be reduced by 40% in comparison with year 1990 [3] it is up-to-date to reduce the energy use in buildings. This master's thesis aims to develop measure proposals that should be implemented during refurbishment of a facility with a cultural-historical value. Measures has therefore been proposed by a life cycle cost optimization in OPERA-MILP. Since it was known that the indoor temperature during summer reaches over the normally accepted maximum temperature (24°C [4]), indoor climate improving measures has also been investigated. The building of today, the planned refurbished building and the life cycle cost optimized building has been modeled in IDA-ICE to simulate the energy flows and indoor climate. The model of the building of today resulted in a district heating requirement of about 120 000 kWh per year, which is a variation of 6% in comparison to historical district heating data. The planned refurbishment got an increased requirement of about 5 000 kWh due to the fact that the basement will be heated. The life cycle cost optimization in OPERA-MILP gave the following measures: change to energy glas and 14 cm insulation in the attic. These measures decreased the district heating requirement with about 2 000 kWh in comparison with the planned refurbishment, which means that the requirement is still larger than the requirement of the building of today. However, the specific energy use decreased as it went from 114 kWh/(m2, year) to 100 kWh/(m2, year), due to the increased heated area and the energy saving measures. In simulation of the models it was seen that the buildings were overheated during summer. Therefore blinds, district cooling, ventilation controlling and ventilation types were investigated. District cooling resulted in a pleasant indoor climate with an operation cost of about 4 000 sek yearly. Lastly, a combination of different measures were simulated which resulted in a decreased district heating use of about 13 000 kWh compared to the model of today and a specific energy use of 88 kWh/(m2, year). This was done by combining the optimal life cycle cost measures with sealing, district cooling and presence controlled ventilation.

No description available.

A growing need for clean and sustainable energy is causing a significant shift in the electricity generation paradigm. In the electricity system of the future, integration of renewable energy sources with smart grid technologies can lead to potentially huge economical and environmental benefits ranging from lesser dependency on fossil fuels and improved efficiency to greater reliability and eventually reduced cost of electricity. In this context, microgrids serve as one of the main components of smart grids with high penetration of renewable resources and modern control strategies. This dissertation is concerned with developing optimal control strategies to manage an energy storage unit in a grid-connected microgrid under uncertainty of electricity demand and prices. Two methods are proposed based on the concept of rolling horizon control, where charge/discharge activities of the storage unit are determined by repeatedly solving an optimization problem over a moving control window. The predicted values of the microgrid net electricity demand and electricity prices over the control horizon are assumed uncertain. The first formulation of the control is based on the scenario-based stochastic conditional value at risk (CVaR) optimization, where the cost function includes electricity usage cost, battery operation costs, and grid signal smoothing objectives. Gaussian uncertainty is assumed in both net demand and electricity prices. The second formulation reduces the computations by taking a worst-case CVaR stochastic optimization approach. In this case, the uncertainty in demand is still stochastic but the problem constraints are made robust with respect to price changes in a given range. The optimization problems are initially formulated as mixed integer linear programs (MILP), which are non-convex. Later, reformulations of the optimization problems into convex linear programs are presented, which are easier and faster to solve. Simulation results under different operation scenarios are presented to demonstrate the effectiveness of the proposed methods. Finally, the energy management problem in network of grid-connected microgrids is investigated and a strategy is devised to allocate the resulting net savings/costs of operation of the microgrids to the individual microgrids. In the proposed approach, the energy management problem is formulated in a deterministic co-operative game theoretic framework for a group of connected microgrids as a single entity and the individual savings are distributed based on the Shapley value theory. Simulation results demonstrate that this co-operation leads to higher economical return for individual microgrids compared to the case where each of them is operating independently. Furthermore, this reduces the dependency of the microgrids on the utility grid by exchanging power locally. / Thesis / Master of Applied Science (MASc)