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Game theory has its applications in various domains, but has only recently been applied to study open problems in smart microgrids. A simple microgrid system with a small wind farm, a storage facility and an aggregate load entity is studied here using a non-cooperative game-theoretic framework. The framework developed is used to study the behavior of rational market participants (players), namely wind power producer and energy storage. The framework is implemented to find the existence of any Nash equilibria and see if cooperation is a natural outcome of the game. If cooperation is not self-enforcing then usefulness of the framework to find the conditions for cooperation is presented. It must be noted that cooperation is not automatically guaranteed as the payoff of the energy storage operator is dependent on the strategy employed by the wind power producer. Similarly, the payoff for the wind power producer is highly intertwined with the strategy employed by the energy storage operator. Historical weather and market data is used to calculate expected payoffs for each possible combination of strategies. The results are presented in the form of payoff matrices and the best response algorithm and/or elimination of dominated strategies is used to find the Nash equilibrium. Sensitivity of the Nash equilibrium to various storage parameters like storage size, charging/discharging limits, charging/discharging efficiency, and other market parameters like energy imbalance penalties, efficiency of up/down regulation, and electricity market prices is studied and necessary conditions for cooperation are presented. / Master of Science

In this dissertation, applications of thermodynamics at the macroscopic and quantum levels of description are developed. Within the macroscopic level, an upper-level Sustainability Assessment Framework (SAF) is proposed for evaluating the sustainable and resilient synthesis/design and operation of sets of small renewable and non-renewable energy production technologies coupled to power production transmission and distribution networks via microgrids. The upper-level SAF is developed in accord with the four pillars of sustainability, i.e., economic, environmental, technical and social. A superstructure of energy producers with a fixed transmission network initially available is synthesized based on the day with the highest energy demand of the year, resulting in an optimum synthesis, design, and off-design network configuration. The optimization is developed in a quasi-stationary manner with an hourly basis, including partial-load behavior for the producers. Since sustainability indices are typically not expressed in the same units, multicriteria decision making methods are employed to obtain a composite sustainability index. Within the quantum level of description, steepest-entropy-ascent quantum thermodynamics (SEA-QT) is used to model the phenomenon of decoherence. The two smallest microscopic composite systems encountered in Nature are studied. The first of these is composed of two two-level-type particles, while the second one is composed of a two-level-type particle and an electromagnetic field. Starting from a non-equilibrium state of the composite and for each of the two different composite systems, the time evolution of the state of the composite as well as that of the reduced and locally-perceived states of the constituents are traced along their relaxation towards stable equilibrium at constant system energy. The modeling shows how the initial entanglement and coherence between constituents are reduced during the relaxation towards a state of stable equilibrium. When the constituents are non-interacting, the initial coherence is lost once stable equilibrium is reached. When they are interacting, the coherence in the final stable equilibrium state is only that due to the interaction. For the atom-photon field composite system, decoherence is compared with data obtained experimentally by the CQED group at Paris. The SEA-QT method applied in this dissertation provides an alternative and comprehensive explanation to that obtained with the "open system" approach of Quantum Thermodynamics (QT) and its associated quantum master equations of the Kossakowski-Lindblad-Gorini-Sudarshan type. / Ph. D.

Energy forms a vital input and critical infrastructure for the economic development of countries and for improving the quality of life of people. Energy is utilized in society through the operation of large socio-technical systems called energy systems. In a growing world, as the focus shifts to better access and use of modern energy sources, there is a rising demand for energy. However, certain externalities result in this demand not being met adequately, especially in developing countries. This constitutes the energy demand – supply matching problem. Load shedding is a response used by distribution utilities in developing countries, to deal with the energy demand – supply problem in the short term and to secure the grid. This response impacts the activities of consumers and entails economic losses. Given this scenario, demand – supply matching becomes a crucial decision making activity. Traditionally demand – supply matching has been carried out by increasing supply centrally in the long term or reducing demand centrally in the short term. Literature shows that these options have not been very effective in solving the demand-supply problem. Gaps in literature also show that the need of the hour is the design of alternate solutions which are tailored to a nation's specific energy service needs in a sustainable way. Microgrids using renewable and clean energy resources and demand side management can be suitable decentralized alternatives to augment the centralized grid based systems and enable demand – supply matching at a local community level. The central research question posed by this thesis is: “How can we reduce the demand – supply gap existing in a community, due to grid insufficiency, using locally available resources and the grid in an optimal way; and thereby facilitate microgrid implementation?” The overall aim of this dissertation is to solve the energy demand – supply matching problem at the community level. It is known that decisions for the creation of energy systems are influenced by several factors. This study focuses on those factors which policy-makers and stakeholders can influence. It proposes an integrated decision framework for the creation of community microgrids. The study looks at several different dimensions of the existing demand – supply problem in a holistic way. The research objectives of this study are: 1. To develop an integrated decision framework that solves the demand – supply matching problem at a community level. 2. To decompose the consumption patterns of the community into end-uses. solar thermal, solar lighting and solar pumps and a combination of these at different capacities. The options feasible for medium income consumers are solar thermal, solar pumps, municipal waste based systems and a combination of these. The options for high income consumers are municipal waste based CHP systems, solar thermal and solar pumps. Residential consumers living in multi-storied buildings also have the options of CHP, micro wind and solar. For cooking, LPG is the single most effective alternative. 3. To identify the ‗best fitting‘ distributed energy system (microgrid), based on the end-use consumption patterns of the community and locally available clean and renewable energy resources, for matching demand – supply at the community level. 4. To facilitate the implementation of microgrids by * Contextualizing the demand – supply matching problem to consider the local social and political environment or landscape, * Studying the economic impact of load shedding and incorporating it into the demand-supply matching problem, and * Presenting multiple decision scenarios, addressing the needs of different stakeholders, to enable dialogue and participative decision making. A multi-stage Integrated Decision Framework (IDF) is developed to solve the demand - supply matching problem in a sequential manner. The first stage in the IDF towards solving the problem is the identification and estimation of the energy needs / end-uses of consumers in a community. This process is called End-use Demand Decomposition (EUDD) and is accomplished by an empirical estimation of consumer electricity demand based on structural and socio-economic factors. An algorithm/ heuristic is also presented to decompose this demand into its constituent end-uses at the community level for the purpose of identifying suitable and optimal alternatives/ augments to grid based electricity. The second stage in the framework is Best Fit DES. This stage involves identifying the “best-fit‘ distributed energy system (microgrid) for the community that optimally matches the energy demand with available forms of supply and provides a schedule for the operation of these various supply options to maximize stakeholder utility. It provides the decision makers with a methodology for identifying the optimal distributed energy resource (DER) mix, capacity and annual operational schedule that “best fits” the given end-use demand profile of consumers in a community and under the constraints of that community such that it meets the needs of the stakeholders. The optimization technique developed is a Mixed Integer Linear Program and is a modification of the DER-CAM™ (Distributed Energy Resources Customer Adoption Model), which is developed by the Environmental Energy Technologies Division, Lawrence Berkeley National Laboratory using the GAMS platform. The third stage is the Community Microgrid Implementation (CMI) stage. The CMI stage of IDF includes three steps. The first one is to contextualize the energy demand and supply for a specific region and the communities within it. This is done by the Energy Landscape Analysis (ELA). The energy landscape analysis attempts to understand the current scenario and develop a baseline for the study. It identifies the potential solutions for the demand - supply problem from a stakeholder perspective. The next step provides a rationale for the creation of community level decentralized energy systems and microgrids from a sustainability perspective. This is done by presenting a theoretical model for outage costs (or load shedding), empirically substantiating it and providing a simulation model to demonstrate the viability for distributed energy systems. Outage cost or the cost of non supply is a variable that can be used to determine the need for alternate systems in the absence/ unavailability of the grid. The final step in the CMI stage is to provide a scenario analysis for the implementation of community microgrids. The scenario analysis step in the framework enlightens decision makers about the baselines and thresholds for the solutions obtained in the “best fit‘ analysis. The first two stages of IDF, EUDD and Best Fit DES, address the problem from a bottom-up perspective. The solution obtained from these stages constitutes the optimal solution from a technical perspective. The third stage CMI is a top-down approach to the problem, which assesses the social and policy parameters. This stage provides a set of satisficing solutions/ scenarios to enable a dialogue between stakeholders to facilitate implementation of microgrids. Thus, IDF follows a hybrid approach to problem solving. The proposed IDF is then used to demonstrate the choice of microgrids for residential communities. In particular, the framework is demonstrated for a typical residential community, Vijayanagar, situated in Bangalore and the findings presented. The End-use Demand Decomposition (EUDD) stage provides the decision makers with a methodology for estimating consumer demand given their socio-economic status, fuel choice and appliance profiles. This is done by the means of a statistical analysis. For this a primary survey of 375 residential households belonging to the LT2a category of BESCOM (Bangalore Electricity Supply Company) was conducted in the Bangalore metropolitan area. The results of the current study show that consumer demand is a function of the variables family income, refrigeration, entertainment, water heating, family size, space cooling, gas use, wood use, kerosene use and space heating. The final regression model (with these variables) can effectively predict up to 60% of the variation in the electricity consumption of a household ln(ElecConsumption) = 0.2880.396*ln(Income)+0.2 66*Refri geration+ 0.708*Entertainment+0.334*WaterHeating+0.047*FamSize+ 0243*SpaceCooling.+580*GasUse+0.421*WoodUse–0.159*KeroseneUse+ 0.568*SpaceHeating ln(ElecConsumption) = 0.406*ln(Income)0.168*Ref rigeration+0.139*Entertainment+ 0.213*WaterHeating+0.114*FamSize+0.121*SpacCooling+0.171*GasUse+ 0.115*WoodUse–0.094*KeroseneUse+0.075*SpaceHeating   The next step of EUDD is to break up the demand into its constituent end-uses. The third step involves aggregating the end-uses at the community level. These two steps are to be performed using a heuristic. The Best Fit DES stage of IDF is demonstrated with data from an urban community in Bangalore. This community is located in an area called Vijayanagar in Bangalore city. Vijayanagar is a mainly a residential area with some pockets of mixed use. Since grid availability is the constraining parameter that yields varying energy availability, this constraint is taken as the criteria for evaluation of the model. The Best Fit DES model is run for different values of the grid availability parameter to study the changes in outputs obtained in DER mix, schedules and overall cost of the system and the results are tabulated. Sensitivity analysis is also performed to study the effect of changing load, price options, fuel costs and technology parameters. The results obtained from the BEST Fit DES model for Vijayanagar illustrate that microgrids and DERs can be a suitable alternative for meeting the demand – supply gap locally. The cost of implementing DERs is the optimal solution. The savings obtained from this option however is less than 1% than the base case due to the subsidized price of grid based electricity. The corresponding costs for different hours of grid availability are higher than the base case, but this is offset by the increased efficiency of the overall system and improved reliability that is obtained in the community due to availability of power 24/7 regardless of the availability of grid based power. If the price of grid power is changed to reflect the true price of electricity, it is shown that DERs continue to be the optimal solution. Also the combination of DERs chosen change with the different levels of non-supply from the grid. For the study community, Vijayanagar, Bangalore, the DERs chosen on the basis of resource availability are mainly discrete DERs. The DERs chosen are the LPG based CHP systems which run as base and intermediate generating systems. The capacity of the discrete DERs selected, depend on the end-use load of the community. Biomass based CHP systems are not chosen by the model as this technology has not reached maturity in an urban setup. Wind and hydro based systems are not selected as these resources are not available in Vijayanagar. The CMI stage of IDF demonstrates the top-down approach to the demand-supply matching problem. For the Energy Landscape Analysis (ELA), Bangalore metropolis was chosen in the study for the purpose of demonstration of the IDF framework. Bangalore consumes 25% of the state electricity supply and its per capita consumption at 1560kWh is higher than the state average of 1230kWh and is 250% more than the Indian average of 612kWh. A stakeholder workshop was conducted to ascertain the business value for clean and renewable energy technologies. From the workshop it was established that significant peak power savings could be obtained with even low penetrations of distributed energy technologies in Bangalore. The feasible options chosen by stakeholders for low income consumers are The second step of CMI is finding an economic rationale for the implementation of community microgrids. It is hypothesized that the ‘The cost of non-supply follows an s-shaped curve similar to a growth curve.’ It is moderated by the consumer income, consumer utility, and time duration of the load shedding. A pre and post event primary survey was conducted to analyze the difference in the pattern of consumer behaviour before and after the implementation of a severe load shedding program by BESCOM during 2009-10. Data was collected from 113 households during February 2009 and July 2010. The analysis proves that there is indeed a significant difference in the number of uninterrupted power systems (inverters) possessed by households. This could be attributed mainly to the power situation in Karnataka during the same period. The data also confirms the nature of the cost of non-supply curve. The third step in CMI is scenario analysis. Four categories of scenarios are developed based on potential interventions. These are business-as-usual, demand side, supply side and demand-supply side. About 21 scenarios are identified and their results compared. Comparing the four categories of scenarios, it is shown that business-as-usual scenarios may result in exacerbation of the demand-supply gap. Demand side interventions result in savings in the total costs for the community, but cannot aid communities with load shedding. Supply side interventions increase the reliability of the energy system for a small additional cost and communities have the opportunity to even meet their energy needs independent of the grid. The combination of both demand and supply side interventions are the best solution alternative for communities, as they enable communities to meet their energy needs 24/7 in a reliable manner and also do it at a lower cost. With an interactive microgrid implementation, communities have the added opportunity to sell back power to the grid for a profit. The thesis concludes with a discussion of the potential use of IDF in policy making, the potential barriers to implementation and minimization strategies. It presents policy recommendations based on the framework developed and the results obtained.

<div>Aerospace and shipboard power systems, as well as merging terrestrial microgrids, typically include a large ercentage of regulated power-electronic loads. It is well nown that such systems are prone to so-called negative- mpedance instabilities that may lead to deleterious scillations and/or the complete collapse of bus voltage. umerous small-displacement criteria have been developed o ensure dynamic stability for small load perturbations, and echniques for estimating the regions of asymptotic stability bout specic equilibrium points have previously been established. However, these criteria and analysis techniques o not guarantee system stability following large nd/or rapid changes in net load power. More recent research as focused on establishing criteria that ensure arge-displacement stability for arbitrary time varying loads rovided that the net load power is bounded. These yapunov-based techniques and recent advancements in eachability analysis described in this thesis are applied to xample dc and ac microgrids to not only introduce a large- isplacement stability margin, but to demonstrate that the elected systems can be designed to be large-displacement table with practicable constraints and parameters.</div>

Este trabalho apresenta maneiras de trabalhar com o controle de potência reativa e estabilidade de tensão em microgrids. A estratégia de controle utilizada é o Controle por Tensão Distribuída (Distributed Voltage Control - DVC), ou controle por tensões distribuídas, um laço integral que considera as potências reativas em todas as barras como entradas e as tensões respectivas como sinais de controle. Diferentes estratégias de controle para distribuição de potência foram propostas e analisadas, sempre enfatizando seus aspectos conceituais. O cálculo dos ganhos do controlador, embora fundamental para o sucesso de qualquer estratégia de controle, geralmente não é discutido, e não são dados métodos ou linhas gerais para esta tarefa. Neste trabalho, apresentamos e discutimos diferentes metodologias para o projeto de ganhos de controle em DVC. Além disso, sendo o sistema não-linear, grandes variações de performance podem ser observadas se os mesmos ganhos de controle são usados para todos os pontos de operação, o que motiva a proposta de uma estratégia de programação de ganhos, também apresentada neste trabalho. / This text deals with the control of reactive power distribution and voltage stability in microgrids. The control strategy studied is the Distributed Voltage Control (DVC), an integral loop considering entries as reactive in every bus and the bus voltages as control signals. Different control strategies for power distribution have been proposed and analysed, always emphasising its conceptual aspects; design of the controller’s gains, however fundamental for the success of any control strategy, is usually not discussed, and no methods or guideline are given for this task. In this text we present and discuss different methodologies for tuning the control gains in DVC. Moreover, since power systems are nonlinear, large variations in performance can be observed if the same control gains are used for all operating points, which motivates the proposal of a gain scheduling strategy, also presented in here.

Driven by economic, technical and environmental factors, the energy sector is currently undergoing a profound paradigm shift towards a smarter grid setup. Increased intake of Distributed and Renewable Generation (DG) units is one of the Smart Grid (SG) pillars that will lead to numerous advantages among which lower electricity losses, increased reliability and reduced greenhouse gas emissions are the most salient. The increase of DG units’ penetration will cause changes to the characteristics of distribution networks from being passive with unidirectional power flow towards Active Distribution Networks (ADNs) with multi-direction power flow. However, such changes in the current distribution systems structure and design will halt the seamless DG integration due to various technical issues that may arise. Voltage and reactive power control is one of the most significant issues that limit increasing DG penetration into distribution systems. On the other hand, the term microgrid has been created to be the building block of ADNs. A microgrid should be able to operate in two modes of operation, grid-connected or islanded. The successful implementation of the microgrid concept demands a proper definition of the regulations governing its integration in distribution systems. In order to define such regulations, an accurate evaluation of the benefits that microgrids will bring to customers and utilities is needed. Therefore, there is a need for careful consideration of microgrids in the assessment, operation, planning and design aspects of ADNs. Moreover, SG offers new digital technologies to be combined with the existing utility grids to substantially improve the overall efficiency and reliability of the network. Advanced network monitoring, two ways communication acts and intelligent control methods represent the main features of SG. Thus it is required to properly apply these features to facilitate a seamless integration of DG units in ADNs considering microgrids. Motivated by voltage and reactive power control issues in ADNs, the concept of microgrids, and SG technologies, three consequent stages are presented in this thesis. In the first stage, the issues of voltage and reactive power control in traditional distribution systems are addressed and assessed in order to shed the light on the potential conflicts that are expected with high DG penetration. A simple, yet efficient and generic three phase power flow algorithm is developed to facilitate the assessment. The results show that utility voltage and reactive power control devices can no longer use conventional control techniques and there is a necessity for the evolution of voltage and reactive power control from traditional to smart control schemes. Furthermore, a probabilistic approach for assessing the impacts of voltage and reactive power constraints on the probability of successful operation of islanded microgrids and its impacts on the anticipated improvement in the system and customer reliability indices is developed. The assessment approach takes into account: 1) the stochastic nature of DG units and loads variability, 2) the special philosophy of operation for islanded microgrids, 3) the different configurations of microgrids in ADNs, and 4) the microgrids dynamic stability. The results show that voltage and reactive power aspects cannot be excluded from the assessment of islanded microgrids successful operation. The assessment studies described in the first stage should be followed by new voltage and reactive power planning approaches that take into account the characteristics of ADNs and the successful operation of islanded microgrids. Feeders shunt capacitors are the main reactive power sources in distribution networks that are typically planned to be located or reallocated in order to provide voltage support and reduce the energy losses. Thus, in the second stage, the problem of capacitor planning in distribution network has been reformulated to consider microgrids in islanded mode. The genetic algorithm technique (GA) is utilized to solve the new formulation. The simulation results show that the new formulation for the problem of capacitor planning will facilitate a successful implementation of ADNs considering islanded microgrids. In the third stage, the SG technologies are applied to construct a two ways communication-based distributed control that has the capability to provide proper voltage and reactive power control in ADNs. The proposed control scheme is defined according to the concept of multiagent technology, where each voltage and reactive power control device or DG unit is considered as a control agent. An intelligent Belief-Desire-Intention (BDI) model is proposed for the interior structure of each control agent. The Foundation for Intelligent Physical Agents (FIPA) performatives are used as communication acts between the control agents. First, the distributed control scheme is applied for voltage regulation in distribution feeders at which load tap changer (LTC) or step voltage regulators are installed at the begging of the feeder. In this case, the proposed control aims to modify the local estimation of the line drop compensation circuit via communication. Second, the control scheme is modified to take into consideration the case of multiple feeders having a substation LTC and unbalanced load diversity. To verify the effectiveness and robustness of the proposed control structure, a multiagent simulation model is proposed. The simulation results show that distributed control structure has the capability to mitigate the interference between DG units and utility voltage and reactive power control devices.