A subset S⊆V in a graph G=(V,E) is a [j,k]-set if, for every vertex vεV\-S, j≤|N(v)\∩S|≤k for non-negative integers j and k, that is, every vertex vεV\-S is adjacent to at least j but not more than k vertices in S. In this paper, we focus on small j and k, and relate the concept of [j,k]-sets to a host of other concepts in domination theory, including perfect domination, efficient domination, nearly perfect sets, 2-packings, and k-dependent sets. We also determine bounds on the cardinality of minimum [1, 2]-sets, and investigate extremal graphs achieving these bounds. This study has implications for restrained domination as well. Using a result for [1, 3]-sets, we show that, for any grid graph G, the restrained domination number is equal to the domination number of G.

A subset S⊆V in a graph G=(V,E) is a [j,k]-set if, for every vertex vεV\-S, j≤|N(v)\∩S|≤k for non-negative integers j and k, that is, every vertex vεV\-S is adjacent to at least j but not more than k vertices in S. In this paper, we focus on small j and k, and relate the concept of [j,k]-sets to a host of other concepts in domination theory, including perfect domination, efficient domination, nearly perfect sets, 2-packings, and k-dependent sets. We also determine bounds on the cardinality of minimum [1, 2]-sets, and investigate extremal graphs achieving these bounds. This study has implications for restrained domination as well. Using a result for [1, 3]-sets, we show that, for any grid graph G, the restrained domination number is equal to the domination number of G.

Distributed Generation (DG) is one of the technologies approved by the South African government for the country's generation expansion to meet future load demand and to support economic growth. DGs change the conventional power flow (generation, transmission to distribution) by injecting real and reactive power at distribution voltage levels. The change in the conventional power flow creates complexity in the power system grid planning due to the conversion of the power system from a passive network to an active network. Introduction of bi-directional power flow on the power system can, among other benefits reduce local power demand which opens opportunities for capital investment deferrals on the transmission and distribution sectors. Consequently, DG impact on the transmission and distribution grid planning has been studied by other researchers. However, previous studies evaluated DG integration on a regulated market and assumed a certain level of generation availability during network peaking period. None of the studies have yet evaluated the benefits on an unregulated market using real measured data. Furthermore, SA distribution network expansion is also being planned without incorporating DGs on the network because of unreliability of wind and solar energy and the network operator's inability to influence the size, location and penetration level of DGs. This planning approach forces the network operator to do more to ensure high network strength. This approach can also result in network overdesign and unnecessary capital expenditure due to the potential benefits that can be deduced from DGs. This dissertation therefore aims to investigate whether incorporating future DG integration in distribution network planning can alleviate financial ramifications of grid code compliance requirements. The data used in the simulations was obtained from the distribution network operator and comprises of both real and reactive power values with a sampling time of 60 minutes for a period of a year. Simulations were conducted for both low and high load conditions to cover the extreme ends of the network and the parameters that were assessed are thermal rating, voltage regulation and network grid losses. Results showed that thermal constraints that are expected on the network when DGs are not considered are not evident when DGs are considered. Results further revealed that there are undervoltage improvements on the network when DGs are considered, and this reduces the capital expenditure that would have otherwise been incurred without DGs to result in a grid code compliant network. Furthermore, there is evidence of reduction in losses under high load conditions and increase in losses under low load conditions in the simulation results. Reduction in losses is caused by supplementary generation from wind and solar plants while increase in losses is due to excessive generation from wind plants which necessitate transportation over long distances to the nearest load centres. In addition to location, size and penetration levels as described in the literature, technology selection for a particular load type is also of utmost important to maximise the DG benefits on the network.

This project was done at Mälardalens University at the school of Innovation, Design & Engineering. The project is a thesis of 15hp for the program in innovation and product design, the project began in spring 2018 and was completed in the summer 2020, its focus on design and construction with regards to, among other things, the environment. The work covers a project development process where a self-sufficient accommodation inside of a shipping container is designed and constructed with a goal to end in an overall construction. The project is not for a company but comes from an individual idea where the result is presented in the form of a report and a entailed CAD-assembly of the accommodations different parts. The content and construction of the accommodation is produced with the first phases of the project development processes, information is collected, concepts are created, and solutions are designed. These phases are iterated so that the result generates a as solid base as possible. Through the work process, the environment and cost are of great importance. The result of the project was an accommodation, which for a week is self-sufficient in electricity and water usage for one person. The resulting accommodation includes; bathroom with shower and toilet, kitchen with sink and gas-hob, electricity and water central where electricity and water is stored and processed, and bed, table and storage. All these functions are located on a floor area of 9,3 m2. The accommodation is constructed in CAD, where its different systems have been developed and designed at a basic level for easy further work at a detail level. The accommodation is not fully designed/constructed but provides an overall plan on how this type of accommodation can be created and its approximate cost, 95´000:-. The solutions and costs may differ in the realization of the accommodation as certain delimitations were made so that this work could be carried out. The project har several development directions where the focus can be within; detail development, selfsufficient living, or temporary conventional accommodation. / Detta examensarbete gjordes på Mälardalens Högskola på akademin för Innovation, Design Teknik. Arbetet är ett examensarbete på 15hp för programmet i innovation och produktdesign, arbetet påbörjades våren 2018 och slutfördes sommaren 2020, det är inriktat på design och konstruktion med avseende på bland annat miljö. Arbetet består av en produktutvecklingsprocess där ett självförsörjande boende inuti en container designas och konstrueras med avseende att sluta i en övergriplig konstruktion. Arbetet sker inte mot ett företag utan kommer från en individuell idé där resultatet presenteras i form av en rapport och en medförande CAD-sammanställning som utgör boendets olika delar. Boendets innehåll och konstruktion har tagitsfram med hjälp av produktutvecklingsprocessens första faser, insamlad information leder till koncept som leder till lösningar. Dessa faser itereras för att resultatet ska generera en så ordentlig bas som möjligt. Genom arbetets gång har miljö och kostnad stor vikt. Resultatet blev ett boende vilket under en veckas period är självförsörjande av el och vatten för en person. Boendet inkluderar; badrum med dusch och toalett, kök med diskho och gasolplatta, el-och vatten-central där el och vatten förvaras och processas, och säng, bord och förvaring. Alla dessa funktioner ligger på en golvyta av 9,3 m2.Boendet är konstruerat i CAD där dess olika delsystem tagits fram och designats på grundnivå för enkelt vidarearbete av detaljnivå. Boendet är inte designat/konstruerat till fullo utan ger en övergriplig plan om hur ett boende av denna typ kan skapas och dess ungefärliga kostnad, 95 ́000:-. Boendets lösningaroch kostnader kan skilja sig vid förverkligandet av boendet då vissa avgränsningar gjordes för att detta arbete skulle kunna genomföras. Arbetet har flera potentiella utvecklingsriktningar där fokus kan ligga inom; detaljutveckling, självförsörjning, eller portabelt temporärt konventionell boende.

Energy consumption by buildings, due to various factors such as temperature regulation, lighting, poses a threat to our environment and energy resources. In the United States, statistics reveal that commercial and residential buildings combined contribute about 40 percent of the overall energy consumption, and this figure is expected to increase. In order to manage the growing demand for energy, there is a need for energy system optimization, which would require a realistic, high-resolution energy-demand model. In this work, we investigate and model the energy consumption of buildings by taking into account physical, structural, economic, and social factors that influence energy use. We propose a novel activity based modeling framework that generates an energy demand profile on a regular basis for a given nominal day.  We use this information to generate a building-level energy demand profile at highly dis-aggregated level. We then investigate the different possible uses of generated demand profiles in different What-if scenarios like urban-area planning, demand-side management, demand sensitive pricing, etc. We also provide a novel way to resolve correlational and consistency problems in the generation of individual-level and building-level "shared" activities which occur due to individuals\' interactions. / Master of Science

京都大学 / 新制・課程博士 / 博士(工学) / 甲第23158号 / 工博第4802号 / 新制||工||1751(附属図書館) / 京都大学大学院工学研究科電気工学専攻 / (主査)教授 引原 隆士, 教授 大村 善治, 特定講師 木村 真之 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

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Energy efficiency and renewable energy become more attractive in smart grid. In order to efficiently reduce global energy usage in building energy systems and to improve local environmental sustainability, it is essential to optimize the operation and the performance of combined heat and power (CHP) systems. In addition, intermittent renewable energy and imprecisely predicted customer loads have introduced great challenges in energy-efficient buildings' optimal operation. In the deterministic optimal operation, we study the modeling of components in energy-efficient building systems, including the power grid interface, CHP and boiler units, energy storage devices, and building appliances. The mixed energy resources are applied to collaboratively supply both electric and thermal loads. The results show that CHP can effectively improve overall energy efficiency by coordinating electric and thermal power supplies. Through the coordinated operation of all power sources, the daily operation cost of building energy system for generating energy can be significantly reduced. In order to address the risk from energy consumption forecast errors and renewable energy production volatility, we utilize the approach of stochastic programming and robust optimizations to operate energy-efficient building systems under uncertainty. The multi-stage stochastic programming model is introduced so that the reliable operation of building energy systems would be probabilistically guaranteed with stochastic decisions. The simulation results show that the stochastic operation of building energy systems is a promising strategy to account for the impact of the uncertainty on power dispatch decisions of energy-efficient building systems. In order to provide absolute guarantee for the reliable operation of building energy systems, a robust energy supply to electric and thermal loads is studied by exploring the effectiveness of energy storage on energy supply against the uncertainty. The robustness can be adjusted to control the conservativeness of the proposed robust operation model. For the purpose of achieving adaptability in the robust optimal operation and attaining robustness in the stochastic optimal operation of building energy systems, we also develop an innovative robust stochastic optimization (RSO) model. The proposed RSO model not only overcomes the conservativeness in the robust operation model, but also circumvents the curse of dimensionality in the stochastic operation model.

The increased integration of distributed and renewable energy resources (DERs) has motivated the evolution of new standards in grid interconnection requirements. New standards have the requirement for the DERs to remain connected during the transient grid fault conditions and to offer support to the grid. This requirement is known as the fault ride-through (FRT) capability of the inverter-based DERs and is an increasingly important issue. This dissertation presents the FRT capability of the DERs that employ a voltage control strategy in their control systems. The voltage control strategy is increasingly replacing the current control strategy in the DERs due to the fact that it provides direct voltage support. However, the voltage control technique limits the ability of direct control over the inverter current. This presents a challenge in addressing the FRT capability where the problem is originally formulated in terms of the current control. This dissertation develops a solution for the FRT capability of inverters that use a voltage control strategy. The proposed controller enables the inverter to ride through the grid faults and support the grid by injecting a balanced current with completely controlled real and reactive power components. The proposed controller is flexible and can be used in connection with various voltage control strategies. Stability analysis of the proposed control structure is performed based on a new linear time-invariant model developed in this dissertation. This model significantly facilitates the stability and design of such control loops. Detailed simulation, real-time and experimental results are presented to evaluate the performance of the proposed control strategy in various operating conditions. Desirable transient and steady-state responses of the proposed controller are observed. Furthermore, the newly established German and Danish grid fault ride-through standards are implemented in this research as two application examples and the effectiveness of the dissertation results are illustrated in the context of those two examples.

Filtering or estimation is of great importance to virtually all disciplines of engineering and science that need inference, learning, information fusion, and knowledge discovery of dynamical systems. The filtering problem is to recursively determine the states and/or parameters of a dynamical system from a sequence of noisy measurements made on the system. The theory and practice of optimal estimation of linear Gaussian dynamical systems have been well established and successful, but optimal estimation of nonlinear and non-Gaussian dynamical systems is much more challenging and in general requires solving partial differential equations and intractable high-dimensional integrations. Hence, Gaussian approximation filters are widely used. In this dissertation, three innovative point-based Gaussian approximation filters including sparse Gauss-Hermite quadrature filter, sparse-grid quadrature filter, and the anisotropic sparse-grid quadrature filter are proposed. The relationship between the proposed filters and conventional Gaussian approximation filters is analyzed. In particular, it is proven that the popular unscented Kalman filter and the cubature Kalman filter are subset of the proposed sparse-grid filters. The sparse-grid filters are employed in three aerospace applications including spacecraft attitude estimation, orbit determination, and relative navigation. The results show that the proposed filters can achieve better estimation accuracy than the conventional Gaussian approximation filters, such as the extended Kalman filter, the cubature Kalman filter, the unscented Kalman filter, and is computationally more efficient than the Gauss-Hermite quadrature filter.