Today, there is a growing number of buildings in a neighborhood and business parks that are utilizing renewable energy generation, to reduce their electric bill and carbon footprint. The most current way of implementing a renewable energy generation is to use solar panels or a windmill to generate power; then use a charge controller connected to a battery bank to store power. Once stored, the user can then access a clean source of power from these batteries instead of the main power grid. This type of power structure is utilizing a single module system in respect of one building. As the industry of renewable power generation continues to increase, we start to see a new way of implementing the infrastructure of the power system. Instead of having just individual buildings generating power, storing power, using power, and selling power there is a fifth step that can be added, sharing power. The idea of multiple buildings connected to each other to share power has been named a microgrid by the power community. With this ability to share power in a microgrid system, a catastrophic event which cause shutdowns of power production can be better managed. This paper then discusses the data from simulations and a built physical model of a resilient microgrid utilizing these principles.

This thesis is concerned with the generation control in small isolated power systems consisting of inverter interfaced generation systems. First the components of an individual distributed generation system (DGS) as well as the corresponding control schemes for active and reactive power flow are discussed and implemented. Then the contribution of multiple DGS to meet the requirement of the loads in both gridconnected and island operations are discussed. Having evaluated the performance of each developed model such as voltage source inverter, PQ and PV controlled as well as reference DGS, the impact of voltage degradation on power load control in isolated systems is analyzed. Finally a new method for generation control in a small power system based on power sharing between multiple DGS with voltage degradation consideration as the last alternative for sustaining the system is proposed and implemented.-11D

Modern power generation aims to utilize renewable energy sources such as solar power and wind to supply customers with power. This approach avoids exhaustion of fossil fuels as well as provides clean energy. Microgrids have become popular over the years, as they contain multiple renewable power sources and battery storage systems to supply power to the entities within the network. These microgrids can share power with the main grid or operate islanded from the grid. During an islanded scenario, self-sustainability is crucial to ensure balance between supply and demand within the microgrid. This can be accomplished by a smart microgrid that can monitor system conditions and respond to power imbalance by shedding loads based on priority. Such a method ensures security of the most important loads in the system and manages energy by automatically disconnecting lower priority loads until system conditions have improved. This thesis introduces a prioritized load shedding algorithm for the microgrid at the University of North Texas Discovery Park and highlight how such an energy management algorithm can add reliability to an islanded microgrid.

Med mikronät åsyftas i denna rapport en sammankoppling av solcellsanläggningar som möjliggör delning av elektrisk energi. Målet med undersökningen var att ta reda på vilka förutsättningar som gör att det är fördelaktigt att bygga mikronät. Detta har gjorts genom att undersöka två tidigare fall där mikronät varit intressant och jämföra slutsatserna från dessa fall med resultaten och slutsatserna från en egen undersökning av Södra Hemlingby där mikronät övervägs. Undersökningen av Södra Hemlingby visar att mikronät i deras fall är lönsamt och att tak som troligtvis inte skulle användas till en enskild solcellsanläggning nu kan komma till användning för solceller. Genom att bygga mikronät skulle mängden inköpt el minska, CO2-utsläpp undvikas och eventuellt skulle en högre nivå av Miljöbyggnad kunna uppnås.  Undersökningen av Södra Hemlingby visar också att ett batteri både kan användas till att reducera effekttoppar och att öka egenanvändningsgraden. Vidare dras slutsatserna att bra förutsättningar för mikronät är vid nybyggnation, när grävarbete kan göras tillsammans med andra grävarbeten, när husen som är tänkta att anslutas står nära varandra, då komponenterna i eventuellt befintligt system är kompatibla med mikronätet och således inte behöver bytas ut, då det finns storanvändare av el i systemet, när elanvändningsprofilerna matchar elproduktionen samt då det finns möjlighet till en ordentlig ökning av egenanvändning. Bäst ekonomi uppnås med en storanvändare som är bra på att ta tillvara på produktionen från solpaneler som har ett högt energiutbyte. / The term microgrid in this report refers to a link-up between solar cell plants which make sharing of electrical energy possible. The aim of this survey was to examinate the pre-requisites that makes building of microgrids meaningful. This has been completed by analyzing two earlier cases where microgrids has been evaluated. The conclusions from these cases have been compared with the results and conclusions from an own made survey of Södra Hemlingby where microgrid is considered. The survey of Södra Hemlingby shows that a microgrid would be a profitable investment and that roofs that probably not would qualify for separate plants now was useful. By building a microgrid the amount of electricity from the power distribution grid would decrease, the carbon dioxide emissions would be avoided, and possibly a higher energy classification for the building would be achieved. The survey of Södra Hemlingby also shows that a battery storage could be used for either power reduction or for increasing the own usage rate. The conclusion about good pre-requisites is drawn to be new housing estate, when ditching could be coordinated with other works, short distances between houses in the system, when the components in a existing system is compatible with a microgrid and dont have to be exchanged, when there is a large consumer of electricity in the system, when the electric consumtion profiles matches the production and when there is room for a large increas in own used electricity. Best economy is reached when large consumer of electricity is utilizing the electricity from panels with a high energy exchange.

A sudden extreme change in the weather can result in significant impact onthe life system in the present-day scenario. A well-planned prediction for damage during extreme weather conditions can have minimal impact on the grid components and efficient response and recovery models. With technology advancements and innovation in smart grid technologies we can now have accesses to uninterrupted power supply with smart utilization of energy and reduce CO2 emissions. Artificial Intelligence plays a vital role insolving present day power issues. Large amounts of data and rapid usage of computational power has accelerated to use machine learning models topredict and forecast the energy demand. Hence this study aims to determine how machine learning will improve the microgrid operation at Tezpur University. The main application areas studied in this thesis are identified as demand and load forecasting, simulating Photovoltaic (PV)production in a Microgrid and power outages. This thesis is aimed to develop and compare different ML algorithms to test validate and predict the PV production, energy demand and power outages.

In this research, an attempt is made to evaluate alternative model-predictive microgrid control approaches and to understand the trade-offs that emerge between model complexity and the ability to achieve real-time optimized system performance. Three alternative controllers are considered and their computational and optimization performance compared. In the first, nonlinearities of the generators are included within the optimization. Subsequently, an approach is considered wherein alternative (non-traditional) states and inputs of generators are used which enables one to leverage linear models with the model predictive control (MPC). Nonlinearities are represented outside the control in maps between MPC inputs and the physical inputs. Third, a recently proposed linearized trajectory (LTMPC) is considered. Finally, the performance of the controllers is examined utilizing alternative models of the synchronous machine that have been proposed for power system analysis.

With increasing shares of variable renewable energy sources in the power mix, the need for energy storage solutions is projected to increase as well. Storage can in such combined systems help mitigate the issues with relying on intermittent sources by time-shifting the supply and smoothing out frequency fluctuations, to name some examples. This thesis has focused on Azelio ABs flagship product, the TES.POD, which is a long-duration thermal energy storage technology. When integrated with, for example, solar PV power, the TES.POD can store excess energy and dispatch it during times of low supply or when during the evening/night. The aim of the thesis has been the development of a day-ahead dispatch optimization tool for systems that include multiple TES.PODs, combined into a Cluster, and solar PV. The model was to be built using the Python programming language and based on Mixed-Integer-Linear-Programming (MILP) methods. The PV+storage system was then allowed to be connected to supplementary power sources such as a larger electric grid, or diesel generators in off-grid locations. The purpose of the optimization model is to find the most economic way to operate the individual TES.PODs while also keeping track of other system components, using a cost-based objective function (minimize costs). A focus has been on using high time resolution (small time step) in order to investigate the impact that the TES.PODs dynamic constraints has on operation. Another strength compared to pre-existing models was the ability to operate individual units indifferent to each other, as opposed to having them all operated in unison. Final results from benchmarking tests and two case studies indicated that using the optimization tool with smaller time steps had an effect on key indicators, and could lead to improved economy in the system. It was observed in both cases that the cost of electricity was reduced by running the optimization tool with time steps of either two or three minutes when compared with using an hourly resolution. Furthermore, several usage parameters for the TES.PODs, notably the total amount of operated hours and energy output per cycle, saw improvements which could lead to reduced cost of operation and maintenance. While not the main intent, testing different Cluster sizes and amount of installed PV capacity with the model, it could also be used in strategic decisions for system sizing. However, due to rapidly growing computational times in systems with large TES.POD clusters and using smaller time steps, the possibility of adding more complexity to the model in future work must be done with caution. To combat this issue, either improvements to the model formulation could be attempted, or by using more powerful hardware or optimizer (imported software algorithm that handles solving the model).

Information and communication technologies are being implemented more than ever in the power industry in order to make smarter power grids, termed as cyber-physical power systems (CPPSs). Along with the privileges of such modern power networks like reducing the total operation cost for end-use customers, they may be negatively affected by cyberattacks, above all false data injection (FDI) attacks as they are easier to be performed. As a case in point, an adversary can detour security systems, penetrate into the cyber layer of a typical CPPS, and manipulate the information, finally leading to security threats. Although prevention and detection mechanisms are significant tools to be utilized by power system operators to improve the reliability of such systems against cyberattacks, they cannot ensure the security of power grids since some FDI attacks might be designed to bypass the detection stage. Hence, a more powerful tool will be required, which is called remedial action scheme (RAS), to be implemented by power system operators to recover the targeted power grid in a timely manner. Toward this end, different RAS frameworks are presented in this dissertation in transmission, distribution, and microgrid levels to highlight the effectiveness of such reaction mechanisms in case of cyber threats targeting modern power systems. In the transmission level, optimal power flow (OPF) integrated with thyristor controlled series capacitor (TCSC) have been utilized to design a RAS to mitigate the negative impacts of FDI attacks, resulting in system congestion or power outages. In the distribution level, system operators take advantage of static VAR compensator (SVC) through solving a customized version of distribution feeder reconfiguration (DFR) problem to mitigate voltage violations in the form of overvoltages and undervolatges, caused by FDI cyberattacks. In light of the fact that some FDI attacks bypass the employed detection methods, it is crucial to prepare in advance for such scenarios. Hence, in this dissertation, a real-world framework is also proposed for mitigating false data injection (FDI) attacks targeting a lab-scale wind/PV microgrid and resulting in power shortage. The proposed RAS is developed as a hardware-in-the-loop (HIL) testbed within the cyber-physical structure of the smart microgrid. Finally, as a prerequisite of the proposed intelligent RAS, which is able to be used on different levels of a CPPS, power system operator is being in attacker’s shoe to scrutinize different scenarios of cyberattacks to make an initial archive set. The design of such mechanisms incorporates long-short-term memory (LSTM) cells into a deep recurrent neural network (DRNN) for the processing of archived data, termed intelligent archive framework (IAF), identifying the proper reaction mechanisms for different FDI cyberattacks. To react to cyberattacks for which similar pre-investigated remedial measures were not saved in the IAF, a power flow analysis is considered to a) examine the interdependency between transmission and distribution sectors and b) generate appropriate RASs in real time.

In the search for environmentally friendly methods to implement renewable energy in the power system residential microgrids have been proposed and proven. The direct current (DC) microgrid topology is a promising implementation of a microgrid system due to the increasing amount of DC-operated loads and production units expected in the near future. In this project, the proposed DC microgrid consists of a solar photovoltaic (PV) power source, a battery, a DC load, and an interlinking bidirectional converter to connect the microgrid to the external three-phase power grid. The PV system is controlled with a Maximum Power Point Tracking (MPPT) algorithm to maximise the power production in all weathers. The DC bus voltage is stabilised by the battery controller and a coordinated control scheme considering the electricity price and battery State of Charge (SOC) is implemented to govern the power exchange with the utility grid. Simulations of the system are shown to validate the functionality of the microgrid and the performance of the controllers in multiple scenarios. The proposed DC microgrid is proven to function in both utility grid-connected mode and in isolation from the utility grid. / I sökandet efter miljövänliga metoder att implementera förnybar energi i kraftsystemet har lokalt självförsörjande elsystem för bostäder föreslagits och visats fungera. Den likströmsbaserade topologin är en lovande implementering av ett sådant lokalt elsystem till följd av den ökande mängden likströmsdrivna laster och produktionsenheter som förväntas komma inom en snar framtid. I detta projekt består det föreslagna likströmsbaserade elsystemet av en solenergikälla, ett batteri, en likströmslast och en sammanlänkande dubbelriktad omvandlare för att ansluta det lokala elsystemet till det externa trefasiga elnätet. Solenergisystemet styrs med en maximal kraftpunktföljande algoritm för att maximera kraftproduktionen i alla väder. Likströmsbussens spänning stabiliseras av batteristyrenheten och ett samordnat styrschema som tar hänsyn till elpriset och batteriets laddningstillstånd implementeras för att styra energiutbytet med elnätet. Simuleringar av systemet presenteras för att validera mikronätets funktionalitet och styrteknikens prestanda i flera olika scenarier. Det föreslagna likströmsbaserade elsystemet visas fungera i både nätanslutet läge och isolerat från elnätet. / Kandidatexjobb i elektroteknik 2022, KTH, Stockholm

En av de största utmaningarna framöver är att säkerställa en jämn övergång från fossila bränslen till förnybar energi utan att kompromissa driftstabilitet. För att genomföra detta behövs det någon form av energilagring för att lagra överskott av förnybar energi, exempelvis solenergi, som sedan kan användas när solenergin inte räcker till för att täcka elbehovet. Syftet med detta projektet är att modellera ett fristående mikronät med vätgaslagring i Simulink. Empiriska data har samlats för samtliga komponenter, som inkluderar en PEM bränslecell, ett NMC622 litiumjonbatteri och en AEM elektrolysör. På så sätt kunde ideala driftparametrar identifieras för komponenterna. Det modellerade systemet klarade elbehovet av en 2 W lampa för en hel vinter-, vår- och sommardag. Genom att använda väderdata för en vårdag kunde systemet dimensioneras för att uppfylla kravet för neutral balans med avseende på vätgasnivån och batteriernas laddningstillstånd. Det krävdes 38 solceller (med en total nominell effekt på 37.95 W), 5 batterier (med en total kapacitet av 175 mAh, 2 bränsleceller (med en vald effekt på 2.34 W inom det ohmiska intervallet) och 2 elektrolysörer (med en maximal effekt på 14.8504 W) för att uppfylla kravet. För att mikronätsystemet ska ha en större ekonomisk potential och en bättre genomförbarhet bör simuleringen förbättras genom att inkludera fler parametrar och använda väderdata som täcker längre perioder.