Dynamic Analysis of a Microgrid Powered With an Inverter and Machine-Based Distributed Resources

The proliferation of renewable distributed energy resources, particularly photovoltaic (PV) power systems, and the increasing need for a reliable power supply has led to the concept of microgrids, a mini-grid that consists of locally connected power generation units and needs, able to operate connected or disconnected from the utility grid, using controlled and coordinated methods to provide for the users of the microgrid the best possible conditions for their needs. The main technical issues facing microgrids include some of the following, seamless transition from stand-alone to utility grid connected operation, how to preserve frequency and voltage stability, and provide the lowest cost power among numerous power resources. Technologies that will be used in the future smart grid will be built, tested, and fielded in modern microgrids with many national laboratories, utility companies, and universities using microgrids of all different types for research and development. This dissertation describes the design, fabrication, and testing of a microgrid facility which comprises adjustable resistive and inductive loads, a diesel-powered generator (DG), an advanced inverter PV system, a battery energy storage system (BESS), monitoring, protection, and control devices. The microgrid facility was built with the foresight that it would be used for conducting tests and experiments related to microgrid technical challenges, thus ease of access and expandability were built in which allows it to be used for both research and education purposes. Numerous experimental tests conducted include the following: (a) the dynamic response of a DG to load changes, (b) an advanced PV inverters autonomous functions, (c) advanced inverter islanding test, (d) load sharing among the DG and PV system, (e) PV and battery storage systems load sharing, (d) dynamic performance of an advanced PV inverter and a DG during unintentional islanding under different power export/import conditions, and (e) BESS iv response to utility outage under different PV operating conditions. Attempts to improve reliability and power quality are made by expanding the PV inverter ride-through times during frequency and voltage abnormalities. An economic analysis in terms of Net Present Value (NPV) is conducted on a residential application where a BESS is paired with a PV system to shift solar energy in favor Time-of-Use (ToU) pricing and to provide ancillary grid services

Real-time Corrective Control in Active Distribution Networks

The continuous growth of renewable energy injected into Medium-Voltage (MV) distribution systems is expected to create new operational problem such as over- and under-voltages and/or thermal overloads of equipment. Therefore, the need for real-time corrective control will go increasing, since reinforcing the network to deal with these temporary situations is seldom an economically viable option for the Distribution System Operator (DSO). This requires monitoring the system through an appropriate measurement and communication infrastructure and taking control actions if the system is going to exceed its prescribed operational limits. In this thesis, number of methods and algorithms have been devised, developed and tested which can allow DSOs to enhance the real-time monitoring and control of their grids, taking into account various practical challenges. The main components taking part in these corrective actions are Dispersed Generation Units and the transformer Load Tap Changer in the main sub-station. A centralized control architecture is chosen mainly for its capability of coordinating multiple control actions. Furthermore, the scheme is extended to a two-level structure in order to combine a fast but partial correction by the local controllers, followed by the smooth, coordinated control of the centralized one. Another extension deals with enabling the controller to contribute to LV network voltage corrections by adjusting voltages on the MV side of the MV/LV transformers where a voltage problem has been detected. Finally, the time frame of the centralized controller is extended with preventive security restoration. The latter uses near-future production/consumption predictions to determine if the active distribution network is going to operate within prescribed limits and, if not, to determine appropriate preventive decisions that can be used, for instance, as reference for the real-time corrective controller.GREDO

Inter-Microgrid Operation: Power Sharing, Frequency Restoration, Seamless Reconnection and Stability Analysis

Electrification in the rural areas sometimes become very challenging due to area accessibility and economic concern. Standalone Microgrids (MGs) play a very crucial role in these kinds of a rural area where a large power grid is not available. The intermittent nature of distributed energy sources and the load uncertainties can create a power mismatch and can lead to frequency and voltage drop in rural isolated community MG. In order to avoid this, various intelligent load shedding techniques, installation of micro storage systems and coupling of neighbouring MGs can be adopted. Among these, the coupling of neighbouring MGs is the most feasible in the rural area where large grid power is not available. The interconnection of neighbouring MGs has raised concerns about the safety of operation, protection of critical infrastructure, the efficiency of power-sharing and most importantly, stable mode of operation. Many advanced control techniques have been proposed to enhance the load sharing and stability of the microgrid. Droop control is the most commonly used control technique for parallel operation of converters in order to share the load among the MGs. But most of them are in the presence of large grid power, where system voltage and frequency are controlled by the stiff grid. In a rural area, where grid power is not available, the frequency and voltage control become a fundamental issue to be addressed. Moreover, for accurate load sharing a high value of droop gain should be chosen as the R/X ratio of the rural network is very high, which makes the system unstable. Therefore, the choice of droop gains is often a trade-off between power-sharing and stability. In the context, the main focus of this PhD thesis is the fundamental investigations into control techniques of inverter-based standalone neighbouring microgrids for available power sharing. It aims to develop new and improved control techniques to enhance performance and power-sharing reliability of remote standalone Microgrids. In this thesis, a power management-based droop control is proposed for accurate power sharing according to the power availability in a particular MG. Inverters can have different power setpoints during the grid-connected mode, but in the standalone mode, they all need their power setpoints to be adjusted according to their power ratings. On the basis of this, a power management-based droop control strategy is developed to achieve the power-sharing among the neighbouring microgrids. The proposed method helps the MG inverters to share the power according to its ratings and availability, which does not restrict the inverters for equal power-sharing. The paralleled inverters in coupled MGs need to work in both interconnected mode and standalone mode and should be able to transfer between modes seamlessly. An enhanced droop control is proposed to maintain the frequency and voltage of the MGs to their nominal value, which also helps the neighbouring MGs for seamless (de)coupling. This thesis also presents a mathematical model of the interconnected neighbouring microgrid for stability and robustness analysis. Finally, a laboratory prototype model of two MGs is developed to test the effectiveness of the proposed control strategies

Towards intelligent operation of future power system: bayesian deep learning based uncertainty modelling technique

The increasing penetration level of renewable energy resources (RES) in the power system brings fundamental changes of the system operating paradigms. In the future, the intermittent nature of RES and the corresponding smart grid technologies will lead to a much more volatile power system with higher level uncertainties. At the same time, as a result of the larger scale installation of advanced sensor devices in power system, power system engineers for the first time have the opportunity to gain insights from the influx of massive data sets in order to improve the system performance in various aspects. To this end, it is imperative to explore big data methodologies with the aim of exploring the uncertainty space within such complex data sets and thus supporting real-time decision-making in future power system. In this thesis, Bayesian Deep learning is investigated with the aim of exploring data-driven methodologies to deal with uncertainties which is in the following three aspects. (1) The first part of this thesis proposes a novel probabilistic day-ahead net load forecasting method to capture both epistemic uncertainty and aleatoric uncertainty using Bayesian deep long short-term memory network. The proposed methodological framework employs clustering in sub-profiles and considers residential rooftop PV outputs as input features to enhance the performance of aggregated net load forecasting. Numerical experiments have been carried out based on fine-grained smart meter data from the Australian grid with separately recorded measurements of rooftop PV generation and loads. The results demonstrate the superior performance of the proposed scheme compared with a series of state-of-the-art methods and indicate the importance and effectiveness of sub-profile clustering and high PV visibility. (2) The second part of this thesis studies a novel Conditional Bayesian Deep Auto-Encoder (CBDAC) based security assessment framework to compute a confidence metric of the prediction. This informs not only the operator to judge whether the prediction can be trusted, but it also allows for judging whether the model needs updating. A case study based on IEEE 68-bus system demonstrates that CBDAC outperforms the state-of-the-art machine learning-based DSA methods and the models that need updating under different topologies can be effectively identified. Furthermore, the case study verifies that effective updating of the models is possible even with very limited data. (3) The last part of this thesis proposes a novel Bayesian Deep Reinforcement Learning-based resilient control approach for multi-energy micro-grid. In particular, the proposed approach replaces deterministic network in traditional Reinforcement Learning with Bayesian probabilistic network in order to obtain an approximation of the value function distribution, which effectively solves Q-value overestimation issue. The proposed model is able to provide both energy management during normal operating conditions and resilient control during extreme events in a multi-energy micro-grid system. Comparing with naive DDPG method and optimisation method, the effectiveness and importance of employing Bayesian Reinforcement Learning approach is investigated and illustrated across different operating scenarios. Case studies have shown that by using the Monte Carlo posterior mean of the Bayesian value function distribution instead of a deterministic estimation, the proposed BDDPG method achieves a near-optimum policy in a more stable process, which verifies the robustness and the practicability of the proposed approach.Open Acces

The New AC/DC Hybrid Microgrid Paradigm: Analysis and Operational Control

AC/DC hybrid microgrids (HMGs) represent a promising architecture that allows the hosting of innovative dc energy resources, such as renewables, and modern dc loads, such as electric vehicles, thereby reducing the number of conversion stages and offering other technical and cost benefits. Such advantages have prompted power distribution planners to begin investigating the possibility of hybridizing existing ac grids and designing new ac/dc hybrid clusters, referred to as microgrids, as a step toward an envisioned smart grid that incorporates multiple ac/dc microgrids characterized by "plug-and-play" features. Despite their potential, when either islanded or interfaced with the main grid, HMGs create challenges with respect to system operation and control, such as difficulties related to precise power sharing, voltage stability during a contingency, the control and management of power transfer through the interlinking converters (ICs), and the coordination of local distributed energy resources (DERs) with the hosting main grid. An understanding of HMGs and their operational philosophy during islanding will assuredly pave the way toward the realization of a future smart grid that includes a plug-and-play feature and will alleviate any operational challenges. However, the planning and operation of such islanded and hybrid systems are reliant on a powerful and efficient power flow analysis tool. To this end, this thesis introduces a novel unified, generic, flexible power flow algorithm for islanded/isolated HMGs. The developed algorithm is generic in the sense that it includes consideration of the unique characteristics of islanded HMGs: a variety of possible topologies, droop controllability of the DERs and bidirectionality of the power flow in the ICs. The new power flow formulation is flexible and permits the easy incorporation of any changes in the DER operating modes and the IC control schemes. The developed algorithm was validated against a detailed time-domain model and applied for the analysis of a variety of operational and control aspects in islanded HMGs, including the problem of imprecise power sharing and droop control of the ICs. The proposed load flow program can form the basis of and provide direction for further studies of islanded HMGs. This thesis also presents a deeper look at the problem of inaccurate active and reactive power sharing in islanded droop-based HMGs and proposes a unified and universal power sharing scheme that can simultaneously ensure precise power sharing in both ac and dc subgrids. Test results demonstrate the capability of the developed scheme with respect to achieving exact power sharing not only among DERs in proportion to their ratings but also among ICs that interface adjacent ac and dc microgrids. The developed unified power sharing scheme would assist system planners with the effective design of droop characteristics for DERs and ICs, which would result in enhancements such as the avoidance of converter overloading and the achievement of precise load sharing. Another operational aspect that was thoroughly investigated for this thesis is the possibility of voltage instability/collapse in islanded HMGs during contingencies. This research unveiled the possibility of voltage instability in HMGs that include constant power loads and a mix of synchronous-based and converter-based generating units. As indicated by the voltage stability analysis presented here, despite the fact that healthy microgrids have far-reaching loadability boundaries, the voltage at some ac/dc load buses can unexpectedly collapse during abnormal conditions. The analysis also revealed that fine tuning the droop characteristics of DERs and ICs can enlarge the voltage stability margin and safeguard the entire microgrid against collapse during contingencies, all without the sacrifice of a single load. A final component of this thesis is the proposal of a two-stage stochastic centralized dispatch scheme for ac/dc hybrid distribution systems. The developed dispatch scheme coordinates the operation of a variety of DERs, such as distributed generators and energy storage systems. It also ensures the coordinated charging of electric vehicles and models the degradation of their batteries that occurs due to the vehicle-to-grid action. The energy coordination problem has been formulated as a two-stage day-ahead resource scheduling problem: the intermittent supply; the variable demand, which includes electric vehicles; and the fluctuating real-time energy price are all modelled as random variables. The first stage produces day-ahead dispatch decisions for the dispatchable DG units. For a set of possible scenarios over the next 24 h, the second stage determines appropriate corrective decisions with respect to the import/export schedule, storage charging/discharging cycles, and electric vehicle charging/discharging patterns. The simulation results demonstrate the effectiveness of the developed scheme for optimally coordinating the various components of future ac/dc hybrid smart grids. Despite its substantial merits and value as a host for ac and dc technologies, a smart grid with HMGs creates previously unexperienced operational challenges for system planners and operators. The work completed for this thesis could help pave the way for the realization of ac/dc hybrid smart grids in years to come

Operating strategies to preserve the adequacy of power systems circuit breakers

The objective of the proposed research is to quantify the limits of overstressed and aging circuit breakers in terms of probability of failure and to provide guidelines to determine network reconfigurations, generator commitment, and economic dispatch strategies that account for these limits. The proposed temporary power system operating strategies address circuit breaker adequacy issues and allow overstressed breakers to be operated longer and more reliably until they are replaced with adequate equipment. The expansion of electric networks with new power sources (nuclear plants, distributed generation) results in increased short-circuit or fault currents levels. As fault currents increase, they will eventually exceed circuit breaker ratings. Circuit breakers exposed to fault currents in excess of their ratings are said to be overstressed, underrated, or inadequate. Insufficient ratings expose overstressed breakers to increased failure probabilities. Extensive common-mode outages caused by circuit breaker failures reduce the reliability of power systems. To durably avoid outages and system unreliability, overstressed breakers must eventually be replaced. Large-scale replacements of overstressed breakers cannot be completed in a short time because of budgetary limits, capital improvement schedules, and manufacturer-imposed constraints. Meanwhile, to preserve the ability of old and overstressed breakers to safely interrupt faults, short-circuit currents must be kept within the limits imposed by the ratings and the age of these breakers by using the substation reconfiguration and generator commitment strategies described in this study. The immediate benefit of the above-mentioned operating strategies is a reduction of the failure probability of overstressed breakers obtained by avoiding the interruption of currents in excess of breaker ratings. Other benefits include (i) increased network reliability, (ii) restored operating margins with respect to existing equipment, and (iii) prioritized equipment upgrades that enhance the long-term planning of power systems.Ph.D.Committee Chair: Meliopoulos, A. P. Sakis; Committee Member: Divan, Deepakraj M.; Committee Member: Harley, Ronald G.; Committee Member: Johnson, Ellis L.; Committee Member: Taylor, David G

Power quality improvement in low voltage distribution network utilizing improved unified power quality conditioner.

Doctoral Degree. University of KwaZulu-Natal, Durban.The upgrade of the power system, network, and as it attained some complexity level, the voltage related problems and power loss has become frequently pronounced. The power quality challenges load at extreme end of the feeder like voltage sag and swell, and power loss at load centre due to peak load as not received adequate attention. Therefore, this research proposes a Power Angle Control PAC approach for enhancing voltage profile and mitigating voltage sag, voltage swell, and reduced power loss in low voltage radial distribution system (RDS). The amelioration of voltage sag, voltage swell, weak voltage profile, and power loss with a capable power electronics-based power controller device known as Improve Unified Power Quality Conditioner I-UPQC was conceived. Also, the same controller was optimally implemented using hybrid of genetic algorithm and improved particle swarm optimization GA-IPSO in RDS to mitigate the voltage issues, and power loss experienced at peak loading. A new control design-model of Power Angle Control (PAC) of the UPQC has been designed and established using direct, quadrature, and zero components dq0 and proportional integral (PI) controller method. The simulation was implemented in MATLAB/Simulink environment. The results obtained at steady-state condition and when the new I-UPQC was connected show that series inverter can participate actively in ameliorating in the process of mitigating sag and swell by maintaining a PAC of 25% improvement. It was observed that power loss reduced from 1.7% to 1.5% and the feeder is within the standard limit of ±5%. Furthermore, the interconnection of I-UPQC with photovoltaic solar power through the DC link shows a better voltage profile while the load voltage within the allowable range of ±5% all through the disturbance and power loss reduction is 1.3%. Lastly, results obtained by optimal allocation of I-UPQC in RDS using analytical and GA-IPSO show that reactive power injection improved the voltage related issues from 0.952 to 0.9989 p.u., and power loss was further reduced to 1.2% from 3.4%. Also, the minimum bus voltage profile, voltage sag, and power loss are within statutory limits of ±5 % and less than 2 %, respectively. The major contributions of this research are the reduction of sag impact and power loss on the sensitive load in RDS feeder.Publications on page iii

ReSCon '12, Research Student Conference: Book of Abstracts

The fifth SED Research Student Conference (ReSCon2012) was hosted over three days, 18-20 June 2012, in the Hamilton Centre at Brunel University. The conference consisted of 130 oral and 70 poster presentations, based on the high quality and diverse research being conducted within the School of Engineering and Design by postgraduate research students. The conference is held annually, and ReSCon plays a key role in contributing to research and innovations within the School

Optimized charging control method for plug-in electric vehicles in LV distribution networks

207 p.Title: Optimized charging control method for plug-in electric vehicles in low voltage distributionnetworksKeywords: plug-in electric vehicles, smart charging, V2G, distribution networks, smart grids, multiobjectiveoptimization, demand side management, voltage unbalances, DIgSILENT PowerFactory[EN] This thesis proposes a new methodology to integrate plug-in electric vehicles in low voltagedistribution networks. Charging a significant number of plug-in electric vehicles will lead to severalimpacts in low voltage distribution networks such as increase of energy losses, overloads of linesand distribution transformers, voltage drops and unbalances, etc. These impacts will dependlargely on the charging control method used. Furthermore, there can be a conflict of interestsbetween electric vehicle users and electric utilities. In this context, this thesis proposes a newmethodology to efficiently integrate plug-in electric vehicles and, at the same time, it reducescharging costs for electric vehicle users. This new methodology is based on a multi-objectiveoptimization which objective functions are minimizing load variance and charging costs. Inaddition, an improvement has been proposed to coordinate the charging of multiple PEVs in orderto reduce voltage drops and unbalances. Furthermore, the proposed solution has beenimplemented in a decentralized architecture which provides several advantages. Aspects such asusers¿ privacy, reliability and scalability are improved compared to centralized controlarchitectures. A real distribution network located in Borup (Denmark) has been used as model totest the effectiveness of the proposed methodology. Simulation results show that the newmethodology improves load factor, limits energy losses, reduces charging costs and limits voltagedrops and unbalances. Considering all these aspects, the proposed methodology improves theintegration of plug-in electric vehicles in low voltage distribution networks.[SP] La presente tesis doctoral propone una nueva metodología para integrar los vehículoseléctricos enchufables en las redes de baja tensión. La carga de un número significativo devehículos eléctricos producirá varios impactos en las redes de baja tensión como son el aumentode pérdidas, la sobrecarga de líneas y transformadores, caídas de tensión, desequilibrios detensión, etc. Estos impactos dependerán en gran medida del método de control de carga utilizado.Además, puede existir un conflicto de intereses entre los usuarios de vehículos eléctricos y lascompañías distribuidores de electricidad. En este contexto, la presente tesis propone una nuevametodología para integrar eficientemente los vehículos eléctricos enchufables y, al mismo tiempo,reducir los costes de carga. Esta metodología está basada en una optimización multiobjetivo cuyasfunciones objetivo son la minimización de la varianza de la carga y de los costes de carga.Asimismo, se introduce una mejora para coordinar la carga de los vehículos eléctricos enchufablescon el objeto de reducir los desequilibrios y las caídas de tensión. Igualmente, la soluciónpropuesta ha sido implementada en una arquitectura descentralizada que proporciona una seriede mejoras adicionales. Aspectos como la privacidad de los usuarios, la fiabilidad y la modularidadson mejorados respecto a soluciones con arquitecturas centralizadas. Un modelo de una red dedistribución real, localizada en el municipio de Borup (Dinamarca), ha sido utilizado paracomprobar la eficacia de la metodología propuesta. Los resultados obtenidos en las simulacionesdemuestran que la nueva metodología mejora el factor de carga, limita las pérdidas de energía,reduce los costes de carga y limita los desequilibrios y caídas de tensión. Teniendo en cuenta todosestos aspectos, la metodología propuesta mejora la integración de los vehículos eléctricosenchufables en las redes de distribución de baja tensión