Добірка наукової літератури з теми "Community microgrid"

This paper demonstrates a smart energy management scheme for solar photovoltaic-biomass integrated grid-interactive microgrid cluster system. Three interconnected microgrids were chosen as a cluster of microgrids for validation of the proposed community energy management scheme. In this work, a Global System for Mobile (GSM)-based bidirectional communication technique was adopted for real-time coordination among the renewable energy sources and loads. To realize the common phenomenon of local grid outage in rural distribution networks, a practical case study is designed in this work. The optimized scheduling of the energy sources and loadsof different microgrids and the distribution grid were implemented to ensure zero loss of power supply probability (LPSP) for dynamic load profiles. The laboratory-scale prototype of the proposed microgrid clustering was first developed in this work by establishing real-time communication among multiple energy sources and loads through different energymeters located at different places inside the academic campus. The field validation was performed with a microgrid cluster consisting of 45 kWP solar photovoltaic, 50 kVA biogas plant, community loads in a village. The developed smart energy management solution is a generalized one and applicable to satisfy scalable community energy demands as well.

The energy transition to renewable energy in a democratic way is directly connected to the development of energy communities and community microgrids. Los Molinos del Rio Aguas (LMRA), an ecological community in the south of Spain, offers a promising case study for an off-grid community-owned microgrid. In this paper, the interconnection of autonomous solar home systems is proposed with the addition of community assets in order to create an off-grid community microgrid that is financially beneficial for the community. Based on this scenario, a Local Energy Market (LEM) based on Distributed Ledger (DL) technologies is implemented in order to foster the energy exchange and contribute to the social welfare of the community. The results provide a win-win scenario for the community and provides an example of an off-grid community microgrid in combination with a LEM that takes into consideration the social aspect of the community.

This paper presents an energy management strategy (EMS) based on the Stackelberg game theory for the microgrid community. Three agents or layers are considered in the proposed framework. The microgrid cluster (MGC) refers to the agent that coordinates the interactions between the microgrids and the utility grid. The microgrid agent manages the energy scheduling of its own consumers. The third agent represents the consumers inside the microgrids. The game equilibrium point is solved between different layers and each layer will benefit the most. First, an algorithm performs demand response in each microgrid according to load models in smart buildings and determines the load consumption for each consumer. Then, each microgrid determines its selling price to the consumers and the amount of energy required to purchase from the utility grid to achieve the maximum profit. Finally, the balance point will be obtained between microgrids by the microgrid cluster agent. Moreover, the proposed method uses various load types at different times based on real-life models. The result shows that considering these different load models with demand response increased the profit of the user agent by an average of 22%. The demand response is implemented by the time of use (TOU) model and real-time pricing (RTP) in the microgrid.

The project designs a microgrid based on downtown community of El Monte city, California. The system main components include a solar PV system, a battery, a diesel generator, an inverter, a control system, and loads. The microgrid design is simulated using MATLAB Simulink. The results show that the microgrid can supply power to its community adequately and independently without relying on a utility power grid. The microgrid is smart as it can operate autonomously thanks to its automatic control system. For various operational scenarios, the microgrid proves to be resilient where it can supply its load demand successfully using its solar system, battery, and diesel generator. The load voltage is kept at satisfactory values of around 1.0 per unit. The power distribution efficiency is around 99%. The results contribute to development of smart microgrids which, in turn, improve the reliability and resiliency of large power grids, as well as provide energy independence to communities

This paper discusses adding a spatial dimension to the design of community microgrid projects in the interest of expanding the existing discourse related to energy performance optimization measures. A multidimensional vision for designing community microgrids with higher energy performance is considered, leveraging urban form (superstructure) to understand how it impacts the performance of the system’s distributed energy resources and loads (infrastructure). This vision engages the design sector in the technical conversation of developing community microgrids, leading to energy efficient designs of microgrid-connected communities well before their construction. A new generation of computational modeling and simulation tools that address this interaction are required. In order to position the research, this paper presents a survey of existing software packages, belonging to two distinct categories of modeling, simulation, and evaluation of community microgrids: the energy infrastructure modeling and the urban superstructure energy modeling. Results of this software survey identify a lack in software tools and simulation packages that simultaneously address the necessary interaction between the superstructure and infrastructure of community microgrids, given the importance of its study. Conclusions represent how a proposed experimental software prototype may fill an existing gap in current related software packages.

This paper presents a community-based CHP microgrid model for optimal operation. The model introduces a microgrid controller and consumption parameters, and that the existing restrictions, the optimization of microgrid operation.bacterial foraging optimization(BFO) algorithm was used to develop microgrid problems. Test results show the effectiveness of the model micro-grid operation.

The reliability of the power grid is a constant problem faced by those who operate, plan and study power systems. An alternative approach to this problem, and others related to the integration of renewable energy sources, is the microgrid. This research seeks to quantify the potential benefits of urban community microgrids, based on the development of planning models with deterministic and stochastic optimization approaches. The models ensure that supply meets demand whilst assuring the minimum cost of investment and operation. To verify their effectiveness, the planning of hundreds of microgrids was set in the city of Santiago de Chile. The most important results highlight the value of community association, such as: a reduction in investment cost of up to 35%, when community microgrids are planned with a desired level of reliability, compared to single residential household microgrids. This reduction is due to the diversity of energy consumption, which can represent around 20%, on average, of cost reduction, and to the Economies of Scale (EoS) present in the aggregation microgrid asset capacity, which can represent close to 15% of the additional reduction in investment costs. The stochastic planning approach also ensures that a community can prepare for different fault scenarios in the power grid. Furthermore, it was found that for approximately 90% of the planned microgrids with reliability requirements, the deterministic solution for the worst three fault scenarios is equivalent to the solution of the stochastic planning problem.

This paper proposes a fuzzy logic-based energy management system (EMS) for microgrids with a combined battery and hydrogen energy storage system (ESS), which ensures the power balance according to the load demand at the time that it takes into account the improvement of the microgrid performance from a technical and economic point of view. As is known, renewable energy-based microgrids are receiving increasing interest in the research community, since they play a key role in the challenge of designing the next energy transition model. The integration of ESSs allows the absorption of the energy surplus in the microgrid to ensure power supply if the renewable resource is insufficient and the microgrid is isolated. If the microgrid can be connected to the main power grid, the freedom degrees increase and this allows, among other things, diminishment of the ESS size. Planning the operation of renewable sources-based microgrids requires both an efficient dispatching management between the available and the demanded energy and a reliable forecasting tool. The developed EMS is based on a fuzzy logic controller (FLC), which presents different advantages regarding other controllers: It is not necessary to know the model of the plant, and the linguistic rules that make up its inference engine are easily interpretable. These rules can incorporate expert knowledge, which simplifies the microgrid management, generally complex. The developed EMS has been subjected to a stress test that has demonstrated its excellent behavior. For that, a residential-type profile in an actual microgrid has been used. The developed fuzzy logic-based EMS, in addition to responding to the required load demand, can meet both technical (to prolong the devices’ lifespan) and economic (seeking the highest profitability and efficiency) established criteria, which can be introduced by the expert depending on the microgrid characteristic and profile demand to accomplish.

This paper introduces a modular testbed to simulate AC/DC microgrids. The testbed is implemented in Matlab Simulink and is based on the energetic macroscopic representation (EMR) formalism. It is designed to be a tool to evaluate energy management strategies in AC/DC microgrids. The microgrid simulation model includes a photovoltaic generator, a fuel cell system, ultracapacitors, and batteries on the DC side. It includes voltage source converters (VSC) to couple the DC side with the AC side of the microgrid, which includes a variable AC load and a synchronous generator. Two case studies illustrate the use of the testbed. The model is implemented in Matlab Simulink and made openly available for the scientific community. Using this model, researchers can develop and evaluate energy management strategies in AC/DC microgrids.

The electric power grid forms the foundation for several other critical infrastructures of national importance such as public health, transportation and telecommunication systems, to thrive. The current power grid runs on the century-old technology and faces serious challenges of the 21st century - Ever-increasing demand and the need to provide a sustainable way to meet the growing demand, increased requirement of resilience against man-made and natural disasters, ability to defend against cyber attacks, increasing demand for reliable power, requirement to integrate with alternate energy generation and storage technologies. Several countries, including the United States, have realized the immediate need to modernize the grid and to pursue the goal of a smart grid. Majority of recent grid modernization efforts are directed towards the distribution systems to be able to meet these new challenges. One of the key enablers of a fully functional Smart Grid are microgrids â subsystems of the grid, utilizing small generation capacities at the distribution system level to increase the overall reliability and power quality of the local grid. It is one of the key directions recommended by national electric delivery technologies roadmap in United States as well as policy makers for electricity delivery in many countries. Microgrids have witnessed serious research activity in the past few years, especially in areas such as multi-agent system (MAS) architectures for microgrid control and auction algorithms for microgrid electricity transaction. However, most of the prior research on electricity transaction in microgrids fails to recognize and represent the true nature of the microgrid electricity market. In this research, a comprehensive microgrid electricity market has been designed, taking into account several unique characteristics of this new market place. This thesis establishes an economic rationale to the vision of wide-scale deployment of microgrids serving residential communities in near future and develops a comprehensive understanding of microgrid electricity market. A novel concept of Community Microgrids is introduced and the market and business models for electricity transaction are proposed and validated based on economic forecasts of key drivers of distributed generation. The most important contribution of this research deals with establishing a need for a trustworthy model framework for microgrid market and introducing the concept of reputation score to market participants. A framework of day-ahead energy market (DAEM) for electricity transaction, incorporating an approach of using the reputation score to incentivize the sellers in the market to be trustworthy, has been designed and implemented in MATLAB with a graphical user interface (GUI). Current implementation demonstrates a market place with two sellers and nine buyers and is easily scalable to support multiple market participants. The proposed microgrid electricity market may spur the deployment of residential microgrids, incorporating distributed generation, thereby making significant contribution to increase the overall reliability and power quality of the local grid.
Master of Science

thesis submitted in partial fulfilment of the requirements for the degree: Master of Technology: Electrical Engineering in the Faculty of Electrical Engineering at the Cape Peninsula University of Technology
Rural communities are often unable to access electrical energy due to their distant location away from the national grid. Renewable energy sources (RESs) make it possible to provide electrical energy to these isolated areas. Sustainable generation is possible at a local level and is not dependant on connection to a national power grid. Microgrids are small scale, stand-alone electricity networks that harness energy at its geographical location, from natural resources. These small scale power grids are either connected to a national grid or operate separately by obtaining their power from an RES. Microgrids are becoming increasingly popular because they can provide electricity, independently of the national grid. The size of microgrid systems are dependent on the amount of energy that needs to be drawn and the amount of energy that has to be stored. Mechanical and electrical system component sizes become bigger due to increased operational energy requirements. Increases in component sizes are required on growing power networks when higher current levels are drawn. Energy management of microgrids must thus be introduced to prevent overloading the power grid network and to extend the operational life of the storage batteries. Energy management systems consist of different components which are seen as operational units. Operational units are responsible for measurement, communication, decision–making and power supply switching control, to manipulate the power output to meet the energy demands. Due to the increasing popularity of DC home appliances, it is important to explore the possibility of keeping these microgrids on a DC voltage basis. Electrical generation equipment such as photovoltaic panels can be used to generate DC at designed voltage levels. The energy management system connects the user loads and generation units together to form the microgrid. The aim of this study was to carry out the design of an agent–based energy management system for rural and under-developed communities. It investigates how the control of the output of the energy management system can be carried out to service the loads. The simulations were done using the following software packages: Simulink, Matlab, and SimPowerSystems. PV sources, energy management system (EMS) and user load parameters are varied in the simulation software to observe how the control algorithm executes load shedding. A stokvel-type charge share concept is dealt with where the state-of-charge (SOC) of batteries and user consumption will determine how grid loads are managed. Load shedding within the grid is executed by monitoring energy flow and calculating how much energy is allowed to be used by each consumer. The energy management system is programmed to always provide the largest amount of energy to the consumer with the lowest energy consumption for each day. The batteries store surplus electrical energy during the day. Load shedding starts at 18:00 each day. Users will be disconnected from the grid whenever their allotted energy capacity were depleted.

The creation of an efficient, sustainable, and resilient energy system is of paramount importance in the European agenda. To reach this goal, the integration of the existing structures, and the proposal of new design paradigms are key factors. The contribution of the thesis goes along this line, by proposing two solutions to foster the electricity market integration. At system-wide level, a novel market clearing approach is proposed, to deal with some of the main issues of the European electricity market. At local level, a novel community microgrid market model is developed, where people can pool their resources, trade in a local electricity market, and provide ancillary services. The European market clearing problem is characterized by a set of heterogeneous orders and rules that force the implementation of heuristic and iterative solving methods. In particular, curtailable block orders and the uniform purchase price pose serious difficulties. A block order spans over multiple hours, and can be either fully accepted or fully rejected. The uniform purchase price prescribes that all consumers pay a common price in all the zones, while producers receive zonal prices, which can differ from one zone to another. The uniform purchase price scheme leads to a non-linear optimization problem involving both primal and dual variables, whereas block orders introduce multi-temporal constraints and binary variables into the problem. The market clearing problem in the presence of both the uniform purchase price and block orders is still an open issue in the European context. To deal with this integration problem, a novel, non-iterative, and heuristic-free approach is proposed, which results in a mixed-integer linear program, built starting from a non-linear integer bilevel program. At local level, the increasing share of renewable energy sources, and the availability of storage systems in distribution grids, pave the way to new market designs that favor the local usage of energy. Community microgrids fit in this context. A community microgrid is a collection of entities that pool their resources to achieve an efficient use of their assets. To foster the integration of entities at local level, a novel market model for community microgrid is proposed. By using the community, participants can match their demand and supply through an internal local market with a significant reduction of the exchanges with the grid. As a consequence, each participant can benefit from a reduction of its energy costs, a drop of the energy peak, and can effectively provide ancillary services to the grid. The proposed community model ensures that no entity is penalized by participating in the community. This requirement is termed Pareto superior condition. The proposed approach is structured as a bilevel model, which is then recast as a single mathematical program by using primal and dual relations. Numerical results and sensitivity analyses are reported to show the effectiveness of the two proposed approaches.

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.

Remote communities, characterized by no connection to the main power grid, traditionally get their power from diesel generators. Long geographical distances and lack of suitable roads make the fuel transportation difficult and costly, increasing the final cost of electricity. A microgrid using renewable energy as the main source can serve as a viable solution for this problem with considerable economical and environmental benefits. The focus of this research is to develop a microgrid for a remote community in northern Ontario (Canada) that combines wind, as a renewable source of energy, and a hydrogen-based energy storage system, with the goal of meeting the demand, while minimizing the cost of energy and adverse effect on the environment. The existing diesel generators remain in the system, but their use is minimized. The microgrid system studied in this research uses a wind turbine to generate electricity, an electrolyser to absorb the excess power from the wind source, a hydrogen tank to store the hydrogen generated by the electrolyser, a fuel cell to supply the demand when the wind resource is not adequate, and a diesel generator as a backup power. Two scenarios for unit-sizing are defined and their pros. and cons. are discussed. The economic evaluation of scenarios is performed and a cost function for the system is defined. The optimization problem thus formulated is solved by solvers in GAMS. The inputs are wind profile of the area, load profile of the community, existing sources of energy in the area, operating voltage of the grid, and sale price of electricity in the area. The outputs are the size of the fuel cell and electrolyser units that should be used in the microgrid, the capital and running costs of each system, the payback period of the system, and cost of generated electricity. Following this, the best option for the microgrid structure and component sizes for the target community is determined. Finally, a MATLAB-based dynamic simulation platform for the system under study with similar load/wind profile and sizing obtained in optimization problem is developed and the dynamic behaviour of microgrid at different cases is studied.

Tese de mestrado integrado, Engenharia da Energia e do Ambiente, Universidade de Lisboa, Faculdade de Ciências, 2018
In the European Union, the current energy paradigm promotes the deployment and integration of renewables, particularly of the distributed kind, as a way to increase the share of clean energy in the global energy mix. Investments made in this sense have simultaneously been allowing and leading towards the integration of energy produced at the local level on the distribution grid. Recent price drops in small and micro scale energy generation systems have allowed residential consumers to invest in small scale units for self-production. Due to its low maintenance requirements and modularity, photovoltaic panels are the preferred choice when it comes to small energy generation. However, as solar energy alone cannot match all daily consumption needs, only by investments in energy storage units one can further decrease the dependency on the main grid. In this dissertation a second option is suggested – energy exchange between local prosumers in a smart microgrid. The hypothesis was studied through the simulation, in AIMMS software, of an energy system intended to reproduce a typical urban neighborhood, composed by six prosumers of different activity sectors and, hence, having different daily load profiles. Considering that at least some of those will have an energy surplus during a part of the day, the idea of a local energy market for trading such surplus is introduced. For the management of this virtual energy market, two models were proposed: a centralized management model, which is intended to simulate a microgrid controlled by a single entity holding access to all data regarding production and demand of the microgrid participants, and a decentralized management model, simulating a scenario where prosumers individually manage their energy trades. Both models were optimized with mixed integer linear programming for cost minimization and simulated for four day-types, with hourly time intervals: winter week- and weekend-days and summer week- and weekend-days. A base scenario with no energy exchange between the prosumers, only with the main grid, serves as a reference for comparison. The results were quantified in terms of self-consumed power and financial balance analyses. Finally, a contextualization for the Portuguese legislation regarding self-consumption was made, in order to determine if this case-study and corresponding results could be adequate for the national legal situation. The results show that very similar outcomes of self-consumption are obtained for both management approaches, with a maximum daily divergence of 2,3%. Considering the overall average for the daily self-consumption values obtained, the difference between the two models is below 1%. When comparing with the base scenario it was verified that, on average, an overall 10% increase in self-consumption is obtained for the micro-grid as a whole. Regarding the financial outcomes, the application of a local energy market for energy exchange between microgrid prosumers resulted in an energy surplus valorization of 135%, on average for the day types simulated, compared to the value stipulated by the Portuguese legislation for self-consumption units. As a logical consequence of this result, an average of 21,6% increase in overall revenues for the prosumers was verified, compared with the revenues in the base scenario. The highest increases on the revenues are verified in the winter week-day scenario, in particular for the office. On average, the individual costs’ reduction is 1,2%, mostly due to savings during the summer. An overall economic analysis on the expected electricity bill of each prosumer and for the microgrid as a whole, revealed that the local energy market can cause a bill reduction of 3,3% for the winter week, and 5,3% for the summer. It can be concluded that, when considering the whole microgrid, the overall economic benefits in terms of economic savings are not so relevant as the results obtained in terms of self-consumed energy, for this particular case-study, although a more profound economic evaluation would be interesting to fully acknowledge the impacts of the observed financial benefits on the overall implied investment. When analyzing the results under the Portuguese legal framework it was concluded that 3 of the production units were oversized in terms of resulting connection power.
No atual contexto de descarbonização da rede energética e da sua transição para um modelo de funcionamento mais distribuído e flexível, tem sido dado uma ênfase crescente ao papel que as micro redes poderão desempenhar na integração de fontes de energia descentralizadas e de pequena escala nas redes nacionais. Por outro lado, o paradigma atual é de desruralização e crescimento e densificação das cidades, criando necessidade de fomentar a produção de energia próxima do consumo em ambiente urbano, mesmo com todas as limitações associadas, e.g. de espaço. Uma das formas de aproveitamento descentralizado de energia mais utilizadas na atualidade é a conversão de energia solar em energia elétrica através de painéis solares fotovoltaicos. A nível global tem-se assistido a uma grande adesão a esta tecnologia, que pode ser explicada pelas políticas económicas de incentivo à sua utilização e constantes desenvolvimentos na tecnologia que levaram a uma queda no seu preço de mercado, tornando-a competitiva mesmo sem subsídios. Isto levou a que utilizadores e investidores de pequena escala apostassem em unidades para autoconsumo ou pequena produção, com ou sem ligação à rede elétrica nacional. As pequenas unidades urbanas de produção de energia solar fotovoltaica têm vindo portanto a ganhar destaque, embora a sua curva de produção coincida com a da radiação solar disponível a cada instante, tornando indispensável o recurso a sistemas de armazenamento de energia, como baterias, ou a esquemas de venda de energia à rede em horas de produção excessiva, eventualmente beneficiando de tarifas subsidiadas, e à compra em horas de défice. Uma terceira alternativa é exposta nesta dissertação – a da troca de energia entre consumidores-produtores (para os quais foi criada a designação de ‘prosumers’) de uma micro-rede. Neste trabalho analisa-se um caso em que dado conjunto de prosumers com painéis fotovoltaicos instalados no espaço disponível da cobertura dos respetivos edifícios consumem em primeira instância a energia que produzem, sendo o excesso disponibilizado num mercado local de energia para venda aos restantes prosumers. Para demonstrar os hipotéticos benefícios desta alternativa, dois cenários com modos diferentes de gestão de micro-redes, com troca de energia, foram comparados com um cenário base, sem troca de energia. Os cenários foram montados para o mesmo sistema energético, constituído por seis prosumers (dois prédios residenciais, um restaurante, uma escola, um pequeno escritório, e um banco). Os dois diferentes modelos de gestão são: (1) gestão centralizada , que pretende simular um cenário em que existe uma unidade central gestora que tem total conhecimento e acesso aos perfis de produção e consumo dos participantes da micro-rede durante o dia todo, e com essa informação gere os recursos; (2) gestão descentralizada, que simula uma situação em que cada prosumer gere a energia que compra no mercado energético consoante o preço desta em comparação com a da rede nacional. Os dois modelos incluem uma otimização matemática do balanço entre custos e receitas, com vista à minimização da conta da energia para os prosumers da micro rede em estudo. Para fins de simulação, os consumidores foram considerados clientes da EDP, e divididos em escalões de potência contratada, de maneira a definir os preços a pagar pela energia da rede nacional. Os dados de consumo dos consumidores residenciais (dois prédios com vários apartamentos) e do banco foram cedidos pela Intelligent Sensing Anywhere, referentes a consumidores de Lisboa, com formatação de intervalos de quinze em quinze minutos. Os restantes perfis foram retirados de uma base de dados de perfis padrão criada pelo Departamento de Energia dos Estados Unidos da América, com intervalos de tempo horários. Assim dos perfis anuais foram escolhidas semanas representativas da época de Verão e Inverno para cada consumidor, e destas foram selecionados dois dias representativos, um dia de semana e um dia de fim-de-semana. Referentemente à produção fotovoltaica, foram feitos dimensionamentos dos sistemas fotovoltaicos com base na média do consumo diário para os dias considerados, permitindo, de acordo com as áreas consideradas como sendo utilizáveis para o efeito, determinar o número de painéis a instalar e a capacidade instalada para cada um. De acordo com os resultados das simulações foi possível verificar as diferenças entre os modelos de gestão do mercado local e o cenário base sem troca de energia, em termos de autoconsumo, individual e coletivo, e balanço financeiro, bem como uma análise detalhada aos custos e receitas obtidos por cada um. A análise das simulações permitiu verificar que as diferenças obtidas entre os modelos centralizado e descentralizado são pouco significativas– uma análise comparativa dos valores de autoconsumo do sistema para os dois casos demonstra uma diferença máxima de 2,3 %, no dia de semana de Inverno, sendo que para o dia de verão de fim-de-semana a diferença era inexistente. Para os restantes dias, o nível de autoconsumo no sistema estudado foi superior sob gestão centralizada. Assumindo uma relação entre o aumento da diferença entre o autoconsumo para cada modelo e a quantidade de energia disponível no mercado local (no Inverno há menos produção pelos painéis fotovoltaicos e os consumos são superiores nos dias de semana), procurou-se demonstrar que estas diferenças podem ser explicadas como uma resposta aos preços praticados. Por outras palavras, no modelo descentralizado havendo menos energia disponível para venda no mercado local da micro-rede, a tendência será para os preços subirem, o que eu comparação com o preço de comprar à rede nacional pode tornar o mercado local uma fonte de energia menos atrativa. Já para o modelo centralizado, onde uma entidade gestora tem informação plena, terá presumivelmente capacidade para atribuir preços mais baixos à energia no mercado local, mesmo quando há pouca energia disponível, de maneira a aumentar o rendimento do sistema no seu todo. Comparativamente ao cenário base, verificou-se que em termos diários se atingiram aumentos em média de 10% na quantidade de energia autoconsumida pela totalidade do sistema. Uma análise às trocas de energia entre prosumers da micro-rede permitiu determinar que o restaurante é o que mais beneficia do mercado local de energia em termos de quantidade comprada, seguido pelos edifícios residenciais. Em média as poupanças nos custos rondaram os 1,2% para cada, e o aumento das receitas foi em média 21,6%. Uma análise financeira revelou que a aplicação de um mercado local de energia resultou numa valorização média de 135% do excedente de energia, em comparação com o valor a este atribuído em linha com a legislação portuguesa referente. Já para a micro rede como unidade, os balanços financeiros estimados para uma semana inteira de cada estação revelaram que a conta da eletricidade poderia ser reduzida em 3,3% no Inverno e 5,3% no Verão. Embora estes valores não sejam muito elevados, permitem apoiar a ideia defendida nesta dissertação, e quantificar os seus benefícios, na medida em que a implementação de um modelo de troca de energia, quer centralizada quer descentralizada, permite benefícios económicos para os prosumers envolvidos e um maior grau de autoconsumo da energia produzida na micro-rede. Considerou-se importante frisar que para a atual legislação em vigor em Portugal para o que diz respeito a autoconsumo, esta seria uma maneira de conseguir valorizar o excedente de energia produzida. De maneira geral um mercado local como o sugerido beneficiaria tanto consumidores como produtores, dando opção aos primeiros de comprar energia mais barata do que a vendida na rede nacional, e aos produtores uma opção viável de venda do excedente. Uma análise crítica aos valores considerados de potência instalada e máximas potências injetadas na rede em comparação com os limites estipulados pelo Decreto-Lei 2014 referente a unidades de autoconsumo permitiu concluir que: 1) no que toca à potência instalada, os valores considerados constituem sobredimensionamentos em 3 casos; 2) relativamente à potência injetada na rede nacional, esta excedeu o limite estipulado apenas nos casos de sobredimensionamento. Com isto se conclui que os benefícios obtidos, em termos de autoconsumo e redução nos custos da eletricidade, poderão ter interesse no contexto nacional, uma vez que para alguns dos participantes da micro rede, não se verificando sobredimensionamento ou excedente de energia injetada na rede, foi possível beneficiar de melhorias no autoconsumo e redução dos custos. A ter em consideração há que várias simplificações foram feitas neste estudo, tal como a atribuição de uma eficiência de 100% para o sistema de transmissão da micro-rede, ou a assunção de que não existem perdas no inversor e cablagem dos sistemas fotovoltaicos. É também de referir que a utilização de intervalos de tempo com dimensão de uma hora implica maiores erros que numa simulação de escala mais fina, uma vez que não retrata com tão grande aproximação uma situação real de produção e consumo de energia.

碩士
國立中正大學
電機工程研究所
105
Domestic energy consumption is mainly divided into industrial power, agricultural power, commercial power and residential power, etc. Economic development, climatic factors and population size are common factors which influence the energy consumption and bring on gradual increase of energy consumption. In the economy, the development of heavy industry is required to consume so much energy that the energy consumption increases as well. People's daily life is also closely related to energy consumption. For the general residential users, the gradual increase in load demand will lead to power outage crisis. Therefore, the above problems can be reduced after the community-based micro-grid which is composed of renewable energy generation, storage and control system incorporated into the system. Furthermore, the community-based micro-grid not only can monitor the load demand and power supply but also it can save customers money and utilize energy more efficiently at the same time. To save the cost of testing on physical system, we could verify the feasibility of the proposed method through the system simulations. This thesis analyzes the cases based on actual community-based micro-grid system with construction of renewable energy sources, storage system and controller models and proposes some controlling strategies. Moreover, real-time simulation techniques are used to resolve limitations of off-line simulations and simulation analysis is implemented in condition of grid mode and island mode and limiting power, etc. In the thesis, load forecasting is also executed to extend the functions of simulation system. With the implementation of system simulations, the results show that it not only brings economic benefit for customers but also validate the efficiency of the proposed methods and controlling strategies.

This chapter consists of two sections, ‘Effective Improvement in Generation Efficiency due to Partition Cooperation Management of a Fuel Cell Microgrid’ and ‘Equipment Plan of Compound Interconnection Microgrid Composed from Diesel Power’. In the 1st section, the PEFC microgrid is explored as a distributed power supply with little environmental impact. The proposed system obtains results with high generation efficiency compared with the central system of a fuel cell microgrid. An independent microgrid that compounds and connects a diesel power plant generator and PEFC is proposed in the 2nd section. A complex community model and residential area model were used for analysis.

Microgrids are systems of linked distributed energy (DE) generation sources that provide power for a relatively small number of users. In this work, we show how microgrids can be used to reduce emissions and deliver power with an annual amortized cost that is competitive with grid power. To perform the analysis, average hourly electrical load profiles for residential customers in Washington, DC were obtained from the utility company (Pepco). Hot water and heating fuel consumption is modeled computationally using prototype building characteristics. The energy consumption data is then used with a computer-based model to analyze grid-tied microgrids. The DE sources examined in this work are photovoltaic arrays and combined heat and power (CHP). The cost and CO2 emissions for the microgrid are compared to the case where power is drawn solely from the grid. We show that when DE capacity is optimally utilized, the microgrid is cost competitive, and the cost to reduce emissions is lowered.

Abstract Community microgrids present a compelling new approach for designing and operating the next generation of power grids. The extent to which their benefits can be realized depends on their constituent buildings, energy infrastructure, and the control algorithms that maintain grid balance. Conventional practice has been to treat the former as inflexible, meaning micro-grids are often designed for a preset group to buildings. However, as microgrids evolve to consider multiple stakeholder needs (such as consumers, prosumers and utilities), the ability for them to maximize stakeholder value — in terms of demand flexibility and energy resiliency — relies on an optimal building composition. This work advances the hypothesis that heterogeneous microgrid compositions exhibit distinguishable value propositions for different stakeholders which, if identified and understood, can provide decision support for microgrid design and adoption at scale. By leveraging the US Department of Energy’s ComStock dataset, we conduct an in-depth empirical study which uncovers trends to support the inclusion (and in some cases exclusion) of a variety of building types when composing community microgrids. The pairing of hotels with quick service restaurants, for example, was one of several key findings that illustrate how complimentary building relationships can be leveraged to advance energy self sufficiency and demand flexibility in community microgrids.

The interaction between technology and people is characterized by sociotechnical models. In the context of design, these types of systems are analyzed to increase productivity. The level of productivity is expected to increase as the technology evolves. Still, a lack of focus on adaptive design hinders the success of sociotechnical systems. The problem is evident in the relationship between microgrid technology and the residents of developing communities. An analysis of this type of sociotechnical system is analyzed in this paper. Rural villages in the developing world often lack access to the power grid. However, microgrids can provide electrical power in these locations. Power can be harnessed from renewable resources such as wind, solar, geothermal, and hydropower. Large batteries are used to store energy and buffer the electrical supply with the demand. The system powers security lighting, water pumps, and purification systems. Microgrids also power small machines that sustain agriculture in developing communities. The access to energy uplifts the developing community socially and economically. Still, as the community evolves, energy demand increases and the microgrid is unable to provide sufficient energy. A challenge in microgrid design involves the scalability of the system. Currently, there is no method for adapting the microgrid system to the increases in demand that occur over time. Accordingly, a mathematical framework is needed to support design decisions that could otherwise support adaptability. A demand model to predict the energy use for a composite rural village is presented. The predicted demand requirements are configured using a design optimization simulation model. These configurations are studied, and adaptive design techniques are devised through the process. The outcome of this study identifies a basic design methodology for microgrid design that is cognizant of scalability. Moreover, it identifies key attributes and relationships for the mathematical framework that supports the overarching goal of adaptable design.