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As we are moving towards a future carbon-neutralsociety, development of residential microgrids attracts much attentionaround the world with its efficient utilization of renewableenergy. A residential microgrid is a small power system fora house, which consists of a solar photovoltaic (PV) source,a battery storage, residential loads, and an interface to thegrid. In this paper, a hybrid AC-DC microgrid is proposed,studied and simulated in Matlab/Simulink. A coordinated controlstrategy is developed so that the PV converter is controlledto maximize its power generation, the battery converter iscontrolled to stabilize the system with the battery state of chargeconstraints, and an interlinking converter is controlled to decidethe connection/disconnection and the power flow with the grid.The simulation results show the effectiveness of the proposedsolution under various operating conditions. / I det här pappret föreslås, studeras ochsimuleras ett hybrid-anpassat lokalt självförsörjande elnät iSimulink och Matlab. Solpaneler utgör den distribueradeförnyelsebara energikällan i nätet. Panelerna styrs med enMPPT-algoritm för att maximera kraftgenereringen. Batterietsladdningstillstånd används i det designade batterilagringssystemetför att garantera lång livstid och för att fatta beslut omladdning och urladdning. Kraftöverföring mellan ACoch DCnätverk sker via en dubbelriktad omvandlare. Det konstrueradehybridnätet fungerar självständigt samt vid sammankopplingtill huvudnätet. Ett koordinerat kontrollsystem implementerasför att möjliggöra kommunikationen mellan lokalnätets olikadelar. Resultaten från simuleringstestet visar att det föreslagnanätet uppfyller stabilitetskrav och god funktion under varierandedriftstillstånd. / Kandidatexjobb i elektroteknik 2021, KTH, Stockholm

The Swedish electricity system is transitioning due to the establishment of climate policy goals and trends related to technology and demographics. The transition has resulted in an increased demand for electricity. The increased demand for electricity in combination with lack of forecasts, planning and coordination between actors in the electricity sector has led to the occurrence of grid congestion. Extending the network is time-consuming and requires substantial investments. Instead, an alternative is to utilise the available grid capacity more efficiently by implementing flexibility solutions. Flexibility can be achieved by implementing incentives such as grid tariffs. This solution has recently gained much attention in Sweden, but it is not apparent how grid tariffs should be designed. The purpose of this thesis is to investigate how distribution grid tariffs could be designed to incentivise different actors to contribute to flexibility in a way that results in an efficient use of the electrical grid. A qualitative study was performed, collecting empirical data through semistructured interviews with actors in the Swedish electricity market. The aim is that the results from this thesis will act as a basis for DSOs planning to design grid tariffs with the purpose to utilise the grid more efficiently. The findings present a ToU capacity charge with off-peak periods that are free of charge as the preferable main price signal in the tariff to achieve efficient utilisation of the grid. It is further argued that other structural elements can complement the ToU capacity charge. A small fixed charge could be added in order to contribute to the cost reflectiveness of the grid tariff. A small energy charge could be incorporated in order to provide consumer with incentives to be flexible below the current metered maximum power and strengthen the signal from the ToU capacity charge. A small energy charge can avert difficulties related to providing incentives below the current metered maximum, as it still can provide some incentives to be flexible, or strengthen the signal from the ToU capacity charge. Further, the energy charge can ensure sustainability if customers respond well to a ToU capacity charge and to compensate solar PV customers. Furthermore, recommendations to further enable the grid tariffs potential to provide price signals include shifting the focus of the revenue cap from CapEx to OpEx and exploring the hampering signals of the energy tax as well as contradicting price signals from the wholesale electricity price. / Det svenska elsystemet genomgår en förändring till följd av införandet av klimatmål och trender relaterade till teknik och demografi. Denna förändring har resulterat i ett ökat effektbehov. Ett ökat effektbehov i kombination med bristande prognostisering, planering och samordning mellan aktörer inom elsektorn har lett till uppkomsten av kapacitetsbrist. Att bygga ut elnätet är tar tid och kräver större investeringar. Ett alternativ är att istället utnyttja det befintliga elnätet mer effektivt genom att implementera flexibilitetslösningar. Flexibilitet kan uppnås genom att införa incitament i form av elnätstariffer. Denna lösning har nyligen fått mycket uppmärksamhet i Sverige, men det är inte klart inte hur dessa elnätstariffer ska utformas. Syftet med detta arbete är att undersöka hur distributionsnätets tariffer kan utformas för att stimulera olika aktörer att bidra med flexibilitet på ett sätt som resulterar i en effektiv användning av det befintliga elnätet. En kvalitativ studie genomfördes där empiriska data samlades in genom semistrukturerade intervjuer med aktörer på den svenska elmarknaden. Syftet är att resultaten från detta arbete ska fungera som ett underlag för nätägare som planerar att utforma elnätstariffer med syftet att utnyttja nätet mer effektivt. Resultaten visar att en ToU-effektavgift med gratis off-peak perioder bör vara den huvudsakliga prissignalen i en elnätstariff som ämnar att utnyttja det befintliga nätet mer effektivt. Det visar även att andra strukturella element kan komplettera ToU-effektavgiften. En mindre fast avgift kan adderas i syfte att göra elnätstariffen mer kostnadsriktig. En mindre energiavgift kan införas för att ge kunder incitament att vara flexibla även under den nuvarande uppmätta maximala effekten och stärka signalen från ToU-effektavgiften. Vidare kan energiavgiften säkerställa tillräckliga intäkter för nätägaren om kunderna svarar bra på en ToU-effektavgift och för att kompensera kunder med solceller. Ytterligare rekommendationer för att möjliggöra prissignaler genom elnätstariffer inkluderar att skifta fokus på intäktsramen från CapEx till OpEx och utforska de hämmande prissignalerna från energiskatten och de motstridiga prissignalerna från elhandelspriset.

<p>Advances in network technologies and computing resources have led to the deployment of large scale computational systems, such as those following Grid or Cloud architectures. The scheduling problem is a significant issue in these distributed computing environments, where a scheduling algorithm should consider multiple objectives and performance metrics. Moreover, heterogeneity is increasing at both the application and resource levels. The heterogeneity in these systems can have a huge impact on performance in terms of metrics such as average completion time. However, traditional Grid and Cloud scheduling algorithms neglect heterogeneity in their scheduling decisions. This PhD dissertation studies the scheduling challenges in Computational Grid, Data Grid, and Cloud computing systems, and introduces new scheduling algorithms for each of these systems.</p> <p>The main issue in Grid scheduling is the wide distribution of resources. As a result, gathering full state information can add huge overhead to the scheduler. This thesis introduces a Computational Grid scheduling algorithm which simultaneously addresses minimizing completion times (by considering system heterogeneity), while requiring zero dynamic state information. Simulation results show the promising performance of this algorithm, and its robustness with respect to errors in parameter estimates.</p> <p>In the case of Data Grid schedulers, an efficient scheduling decision should select a combination of resources for a task that simultaneously mitigates the computation and the communication costs. Therefore, these schedulers need to consider a large search space to find an appropriate combination. This thesis introduces a new Data Grid scheduling algorithm, which dynamically makes replication and scheduling decisions. The proposed algorithm reduces the search space, decreases the required state information, and improves the performance by considering the system heterogeneity. Simulation results illustrate the promising performance of the introduced algorithm.</p> <p>Cloud computing can be considered as a next generation of Grid computing. One of the main challenges in Cloud systems is the enormous expansion of data in different applications. The MapReduce programming model and Hadoop framework were designed as a solution for executing large scale data-intensive applications. A large number of (heterogeneous) users, using the same Hadoop cluster, can result in tensions between the various performance metrics by which such systems are measured. This research introduces and implements a Hadoop scheduling system, which uses system information such as estimated job arrival rates and mean job execution times to make scheduling decisions. The proposed scheduling system, named COSHH (Classification and Optimization based Scheduler for Heterogeneous Hadoop systems), considers heterogeneity at both the application and cluster levels. The main objective of COSHH is to improve the average completion time of jobs. However, as it is concerned with other key Hadoop performance metrics, it also achieves competitive performance under minimum share satisfaction, fairness and locality metrics, with respect to other well-known Hadoop schedulers. The proposed scheduler can be efficiently applied in heterogeneous clusters, in contrast to most Hadoop schedulers, which assume homogeneous clusters.</p> <p>A Hadoop system can be described based on three factors: cluster, workload, and user. Each factor is either heterogeneous or homogeneous, which reflects the heterogeneity level of the Hadoop system. This PhD research studies the effect of heterogeneity in each of these factors on the performance of Hadoop schedulers. Three schedulers which consider different levels of Hadoop heterogeneity are used for the analysis: FIFO, Fair sharing, and COSHH. Performance issues are introduced for Hadoop schedulers, and experiments are provided to evaluate these issues. The reported results suggest guidelines for selecting an appropriate scheduler for different Hadoop systems. The focus of these guidelines is on systems which do not have significant fluctuations in the number of resources or jobs.</p> <p>There is a considerable challenge in Hadoop to schedule tasks and resources in a scalable manner. Moreover, the potential heterogeneous nature of deployed Hadoop systems tends to increase this challenge. This thesis analyzes the performance of widely used Hadoop schedulers including FIFO and Fair sharing and compares them with the COSHH scheduler. Based on the discussed insights, a hybrid solution is introduced, which selects appropriate scheduling algorithms for scalable and heterogeneous Hadoop systems with respect to the number of incoming jobs and available resources. The proposed hybrid scheduler considers the guidelines provided for heterogeneous Hadoop systems in the case that the number of jobs and resources change considerably.</p> <p>To improve the performance of high priority users, Hadoop guarantees minimum numbers of resource shares for these users at each point in time. This research compares different scheduling algorithms based on minimum share consideration and under different heterogeneous and homogeneous environments. For this evaluation, a real Hadoop system is developed and evaluated using Facebook workloads. Based on the experiments performed, a reliable scheduling algorithm is suggested which can work efficiently in different environments.</p> / Doctor of Philosophy (PhD)

<p>Solar energy is a clean and abundant renewable energy source which is currently used in many types of photovoltaic (PV) designs. In practical PV systems, solar panels are used to harvest solar energy and convert it into a usable form of electricity. Due to the intermittent nature of solar energy input however, battery storage, in combination with solar panels, must be used to provide an uninterrupted source of power.</p> <p>The process of assigning solar panel and battery configurations for a PV system is referred to as energy resource provisioning. Unfortunately, energy provisioning costs are still relatively high, and this is one of the main obstacles that inhibits the adoption of solar power for many applications. These costs however, can be substantially reduced through cost-efficient resource provisioning methods. The focus of this thesis is on the development of efficient algorithms and energy management methods that will reduce energy provisioning costs in solar powered systems.</p> <p>First, we consider resource provisioning in solar powered wireless mesh networks. In practical solar powered systems, there are usually restrictions in the way that the mesh nodes can be positioned, and this results in a time-varying and node-dependent attenuation of the available solar energy. Unfortunately, conventional resource provisioning methods cannot take this into account and therefore the deployed system may be unnecessarily expensive. In this part of the thesis, the resource provisioning problem is considered from this point of view. We first review conventional resource provisioning mechanisms and give an example which shows the value of introducing positional solar insolation awareness. A Position Aware Provisioning (PAP) algorithm is then introduced that takes known positional variations into consideration when performing the energy provisioning. Simulation results show that reductions in total network provisioning cost can be obtained using the proposed methodology compared to conventional algorithms.</p> <p>In the second part of the thesis, we consider communication infrastructure that is operated from the power grid with a solar powered addition. Resource provisioning and energy management algorithms are introduced to minimize the capital expenditure (CAPEX) and operating expenditure (OPEX) costs. We first derive lower bounds on the costs using a linear programming (LP) formulation where solar components are sized using solar insolation and projected loading data. A variety of different node configurations are considered. Three energy scheduling algorithms are then introduced to optimize online OPEX costs, namely, Grid Purchase Last (GPL), Solar Load Optimization (SLO) and Solar Load Simulation (SLS) algorithms. Simulation results show the extent to which a solar powered add-on can reduce total cost.</p> <p>Finally, we consider solar powered systems where part of their energy demands are deferrable, up to some maximum tolerable delay. The objective is to exploit the flexibility of deferrable energy demands in a way that decreases the total provisioning cost. A mixed integer linear optimization program is derived which gives a lower bound on the provisioning cost. A Delay Aware Provisioning (DAP) algorithm is then proposed to determine practical cost-efficient energy provisioning. The performance of DAP is compared to the provisioning bound and the conventional Stand-alone Node Provisioning (SNP) algorithm. Results are presented which show the significant provisioning cost savings that can be obtained.</p> / Doctor of Philosophy (PhD)

The unimodality of a function seems a simple concept. But in the Euclidean space R^m, m=3,4,..., it is not easy to define. We have an easy tool to find the minimum point of a unimodal function. The goal of this project is to formalize and support distinctive strategies that typically guarantee convergence. Support is given both by analytic arguments and simulation study. Application is envisioned in low-dimensional but non-trivial problems. The convergence of the proposed iterated grid search algorithm is presented along with the results of particular application studies. It has been recognized that the derivative methods, such as the Newton-type method, are not entirely satisfactory, so a variety of other tools are being considered as alternatives. Many other tools have been rejected because of apparent manipulative difficulties. But in our current research, we focus on the simple algorithm and the guaranteed convergence for unimodal function to avoid the possible chaotic behavior of the function. Furthermore, in case the loss function to be optimized is not unimodal, we suggest a weaker condition: almost (noisy) unimodality, under which the iterated grid search finds an estimated optimum point. / Ph. D.

[pt] A crescente demanda energética verificada ao redor do mundo e a conscientização pública acerca dos efeitos deletérios do excesso de gases estufa na atmosfera vem colaborando para a articulação de compromissos de grande alcance em nome da adaptação das matrizes energéticas a formas ambiental e economicamente sustentáveis. A adesão à energias renováveis (como solar e eólica) e a descentralização da matriz energética por meio de tecnologias de geração distribuída (visando a melhoria da eficiência do uso da energia) são alguns dos movimentos mais relevantes realizados para fazer frente a essas demandas. Neste ínterim, o presente trabalho é dedicado à simulação numérica mediante o conceito 4E (Energy, Exergy, Environmental and Economic) de um sistema híbrido CHP (Combined Heat and Power) on-grid para atendimento de pequenas demandas residenciais ou industriais, tendo gás natural e energia solar como vetores energéticos preferenciais. O sistema inclui um reformador de gás natural para produção de gás de síntese rico em hidrogênio, uma célula a combustível com membrana de troca de prótons (PEM), painéis fotovoltaicos, baterias conectadas à rede elétrica por um inversor bidirecional, trocadores de calor e componentes auxiliares como compressores e boilers. Os componentes do sistema foram modelados separadamente com base em equações de conservação e seus modelos devidamente validados. Uma análise energética e exergética do reformador de gás natural foi conduzida mediante a metodologia de planejamento de experimentos a fim de avaliar a necessidade de considerar uma formulação complexa do combustível em vez de um substituto (metano puro). Posteriormente, estes modelos foram inseridos como módulos de uma rotina mais ampla destinada a simular o desempenho econômico do sistema integrado num intervalo de tempo de até 20 anos. Tal rotina, implementada no MATLAB, permite a flexibilização de critérios operacionais importantes como número de consumidores, configuração do sistema híbrido (armazenamento e participação de painéis fotovoltaicos), diferentes tipos de tarifa (convencional ou branca) e o possível uso de rejeito térmico para cogeração, enriquecendo o escopo de resultados obtidos. Paybacks entre 7 e 20 anos de operação do sistema foram alcançados para diferentes combinações dos parâmetros examinados considerando-se a adesão no ano de 2020, onde consumidores residenciais obtiveram resultados predominantemente melhores do que os industriais em virtude da demanda menos exigente dos primeiros. Foram também previstas reduções de até 50% no custo cumulativo total para consumidores residenciais referente a adesão ao sistema proposto por 20 anos, levando-se em conta a queda prevista nos custos de aquisição dos componentes para as próximas décadas. A avaliação do sistema em termos ambientais foi feita através da quantidade equivalente de CO2 por unidade de energia. Concluiu-se que a configuração completa, mesmo auxiliada por cogeração, supera a média de emissões da matriz energética brasileira (devido à alta participação das fontes renováveis nessa matriz), permanecendo, ainda assim, como uma opção melhor do que a combustão pura do gás natural, especialmente no que diz respeito ao atendimento de demanda térmica. / [en] The growing energy demand verified around the world and public awareness about the harmful effects of greenhouse gases excess in the atmosphere have been contributing to the articulation of far-reaching commitments in the name of adapt energy matrices to environmentally and economically sustainable ways. The adherence to renewable energy (such as solar and eolic) and descentralization of energy matrix through distributed generation technologies (aiming at the improvment of efficiency of energy use) are some of the more relevant movements done in order to deal with these demands. In the meantime, the present work is dedicated to numerical simulation using the 4E (Energy, Exergy, Environmental and Economic) concept of an on-grid hybrid CHP system to meet small residential or industrial demands, using natural gas and solar energy as preferred energy vectors. The system includes a natural gas reformer for the production of hydrogen-rich synthesis gas, a proton exchange membrane fuel cell (PEM), photovoltaic panels, batteries connected to the grid by a bidirectional inverter, heat exchanger and auxiliary componentes, such as compressors and boilers. The system components were modeled separately based on conservation equations and their models duly validated. An energy and exergy analysis of the natural gas reformer was conducted using design of experiment methodology in order to assess the necessity to consider a complex formulation of the fuel instead of a surrogate (pure methane). Subsequently, these models were inserted as modules of a broader routine designed to simulate the economic performance of the integrated system in a time interval of up to 20 years. This routine implemented in MATLAB allows for the flexibility of important operational criteria such as the number of consumers, configuration of the hybrid system (storage and participation of solar energy), different types of tariff (conventional or white) and the posible use of reject heat for cogeneration, enriching the scope of the results obtained. Paybacks between 7 and 20 years of system operation were achieved for different combinations of the examined parameters considering adherence in the year 2020, where residential consumers have predominantly obtained better results than industrial ones due to the less intense demand of the first ones. Reductions of up to 50% in the total cumulative cost related to adherence to the proposed system for 20 years for residential users were also foreseen, taking into account the expected drop in component acquisition costs over the next few decades. The evaluation of the system in environmental terms was assessed through equivalent amount of CO2 by energy unit. It was concluded that the complete configuration, even supported by cogeneration, exceeds the average of the brazilian energy matrix emissions (due to the high share of renewable sources in this matrix), nevertheless remaining as a better option than pure combustion of natural gas, specially for meeting thermal demand.

<p>The ongoing and rapidly accelerating integration of inverter-based resources (IBRs), such as solar panels, into power distribution systems has heightened the importance of computational tools that can be used to study the dynamics of such systems. IBRs use power electronics to interface the energy sources to the grid, thereby introducing faster dynamics than their electromechanical counterparts, which could lead to instabilities in distribution systems and microgrids. Hence, there is a need for conducting simulations of distribution systems containing large numbers of single- and three-phase inverters, which could be operating under either grid-following or grid-forming modes.</p> <p>A key objective of this thesis is to derive detailed, high-fidelity models of inverters and their controls in the context of unbalanced distribution networks. In addition, a diesel synchronous generator model is derived, for the sake of completeness. The main contribution of this work is that these models are developed for use in a novel simulation toolbox called Dynamic Simulation Tool using a Sparse Tableau Approach in Python, DynaSTPy (pronounced dynasty). This thesis outlines how the components can be modeled in the sparse tableau framework as electrical networks with topology described using a node-branch incidence matrix. In addition, the thesis explains how controller dynamics and constraints can be handled within this framework. These models are tailored to seamlessly integrate into the DynaSTPy toolbox. The proposed approach can be readily extended to model other such components in the future.</p>