77 research outputs found

    Management of Distributed Energy Storage Systems for Provisioning of Power Network Services

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    Because of environmentally friendly reasons and advanced technological development, a significant number of renewable energy sources (RESs) have been integrated into existing power networks. The increase in penetration and the uneven allocation of the RESs and load demands can lead to power quality issues and system instability in the power networks. Moreover, high penetration of the RESs can also cause low inertia due to a lack of rotational machines, leading to frequency instability. Consequently, the resilience, stability, and power quality of the power networks become exacerbated. This thesis proposes and develops new strategies for energy storage (ES) systems distributed in power networks for compensating for unbalanced active powers and supply-demand mismatches and improving power quality while taking the constraints of the ES into consideration. The thesis is mainly divided into two parts. In the first part, unbalanced active powers and supply-demand mismatch, caused by uneven allocation and distribution of rooftop PV units and load demands, are compensated by employing the distributed ES systems using novel frameworks based on distributed control systems and deep reinforcement learning approaches. There have been limited studies using distributed battery ES systems to mitigate the unbalanced active powers in three-phase four-wire and grounded power networks. Distributed control strategies are proposed to compensate for the unbalanced conditions. To group households in the same phase into the same cluster, algorithms based on feature states and labelled phase data are applied. Within each cluster, distributed dynamic active power balancing strategies are developed to control phase active powers to be close to the reference average phase power. Thus, phase active powers become balanced. To alleviate the supply-demand mismatch caused by high PV generation, a distributed active power control system is developed. The strategy consists of supply-demand mismatch and battery SoC balancing. Control parameters are designed by considering Hurwitz matrices and Lyapunov theory. The distributed ES systems can minimise the total mismatch of power generation and consumption so that reverse power flowing back to the main is decreased. Thus, voltage rise and voltage fluctuation are reduced. Furthermore, as a model-free approach, new frameworks based on Markov decision processes and Markov games are developed to compensate for unbalanced active powers. The frameworks require only proper design of states, action and reward functions, training, and testing with real data of PV generations and load demands. Dynamic models and control parameter designs are no longer required. The developed frameworks are then solved using the DDPG and MADDPG algorithms. In the second part, the distributed ES systems are employed to improve frequency, inertia, voltage, and active power allocation in both islanded AC and DC microgrids by novel decentralized control strategies. In an islanded DC datacentre microgrid, a novel decentralized control of heterogeneous ES systems is proposed. High- and low frequency components of datacentre loads are shared by ultracapacitors and batteries using virtual capacitive and virtual resistance droop controllers, respectively. A decentralized SoC balancing control is proposed to balance battery SoCs to a common value. The stability model ensures the ES devices operate within predefined limits. In an isolated AC microgrid, decentralized frequency control of distributed battery ES systems is proposed. The strategy includes adaptive frequency droop control based on current battery SoCs, virtual inertia control to improve frequency nadir and frequency restoration control to restore system frequency to its nominal value without being dependent on communication infrastructure. A small-signal model of the proposed strategy is developed for calculating control parameters. The proposed strategies in this thesis are verified using MATLAB/Simulink with Reinforcement Learning and Deep Learning Toolboxes and RTDS Technologies' real-time digital simulator with accurate power networks, switching levels of power electronic converters, and a nonlinear battery model

    Advanced control of renewable energy microgrids with hybrid energy storage system

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    Renewable energy will play an important role in the transition to a new energetic model which, along with other developments of the digital age, will probably bring about the Third Industrial Revolution. However, the change to this new energetic model is subject to overcoming technological barriers, namely the sporadic nature of renewable sources. Which in turn affects both, power quality and economic competitiveness. The imbalance of active and reactive power that renewable energies introduce in the grid causes variation in the voltage supply, grid frequency, harmonics, as well as producing other power quality issues. Energy storage systems appear to be a key factor in compensating generation and demand. The lack of controllability and the penalty for deviations in the regulation market hinder the economic competitiveness of renewable energy. Energy storage systems will be the technological solution enabling controllability in renewable energies, allowing their introduction in the spot energy market. Redesigning the grid into smaller, more manageable units based on microgrids appears as a solution to the outlined problems. In these microgrids, stored energy compensates both the intermittent nature of renewable generation and the randomness of the consumer's behaviour. Traditionally, energy storage has been developed by large hydropower-regulation plants, however, these kinds of plants are subject to natural emplacements and their implementation is subject to environmental impact grades. The high energy density of hydrogen as an energy carrier will play an important role in this new energetic paradigm. However, robust performance and the transient response are the main barriers for its technological implantation and, usually, hydrogen-based systems have a useful life that is sometimes too limited to buffer the associated cost. Batteries and supercapacitors have a better transient response, however, their low energy density does not provide enough autonomy to the system. The design of a hybrid energy storage system, having advanced control systems in charge of taking advantage of each storage system and avoiding the causes of degradation and/or limitations of them, emerges as a technological solution to the problems commented. The high number of constraints and variables to be optimized increases the complexity of the associated control problem, making it necessary to deploy advanced control algorithms. In this thesis, the development of optimal controllers for renewable energy microgrids with hybrid energy storage systems is explored using Model Predictive Control (MPC). The control system is introduction on different time scales resulting in an optimal control solution for the economic dispatch and the power quality of the microgrid. Meanwhile, degradation issues of energy storage systems are analyzed and minimized, improving the longevity of the whole energy storage system

    Integration of Energy Storage into a Future Energy System with a High Penetration of Distributed Photovoltaic Generation

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    Energy storage units (ESU) are increasingly used in electrical distribution systems because they can perform many functions compared with traditional equipment. These include peak shaving, voltage regulation, frequency regulation, provision of spinning reserve, and aiding integration of renewable generation by mitigating the effects of intermittency. As is the case with other equipment on electric distribution systems, it is necessary to follow appropriate methodologies in order to ensure that ESU are installed in a cost-effective manner and their benefits are realized. However, the necessary methodologies for integration of ESU have not kept pace with developments in both ESU and distribution systems. This work develops methodologies to integrate ESU into distribution systems by selecting the necessary storage technologies, energy capacities, power ratings, converter topologies, control strategies, and design lifetimes of ESU. In doing so, the impact of new technologies and issues such as volt-VAR optimization (VVO), intermittency of photovoltaic (PV) inverters, and the smart PV inverter proposed by EPRI are considered. The salient contributions of this dissertation follow. A unified methodology is developed for storage technology selection, storage capacity selection, and scheduling of an ESU used for energy arbitrage. The methodology is applied to make technology recommendations and to reveal that there exists a cost-optimal design lifetime for such an ESU. A methodology is developed for capacity selection of an ESU providing both energy arbitrage and ancillary services under a stochastic pricing structure. The ESU designed is evaluated using ridge regression for price forecasting; Ridge regression applied to overcome numerical stability and overfitting issues associated with the large number of highly correlated predictors. Heuristics are developed to speed convergence of simulated annealing for placement of distributed ESU. Scaling and clustering methods are also applied to reduce computation time for placement of ESU (or any other shunt-connected device) on a distribution system. A probabilistic model for cloud-induced photovoltaic (PV) intermittency of a single PV installation is developed and applied to the design of ESU

    Control and Stability of Residential Microgrid with Grid-Forming Prosumers

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    The rise of the prosumers (producers-consumers), residential customers equipped with behind-the-meter distributed energy resources (DER), such as battery storage and rooftop solar PV, offers an opportunity to use prosumer-owned DER innovatively. The thesis rests on the premise that prosumers equipped with grid-forming inverters can not only provide inertia to improve the frequency performance of the bulk grid but also support islanded operation of residential microgrids (low-voltage distribution feeder operated in an islanded mode), which can improve distribution grids’ resilience and reliability without purposely designing low-voltage (LV) distribution feeders as microgrids. Today, grid-following control is predominantly used to control prosumer DER, by which the prosumers behave as controlled current sources. These grid-following prosumers deliver active and reactive power by staying synchronized with the existing grid. However, they cannot operate if disconnected from the main grid due to the lack of voltage reference. This gives rise to the increasing interest in the use of grid-forming power converters, by which the prosumers behave as voltage sources. Grid-forming converters regulate their output voltage according to the reference of their own and exhibit load sharing with other prosumers even in islanded operation. Making use of grid-forming prosumers opens up opportunities to improve distribution grids’ resilience and enhance the genuine inertia of highly renewable-penetrated power systems. Firstly, electricity networks in many regional communities are prone to frequent power outages. Instead of purposely designing the community as a microgrid with dedicated grid-forming equipment, the LV feeder can be turned into a residential microgrid with multiple paralleled grid-forming prosumers. In this case, the LV feeder can operate in both grid-connected and islanded modes. Secondly, gridforming prosumers in the residential microgrid behave as voltage sources that respond naturally to the varying loads in the system. This is much like synchronous machines extracting kinetic energy from rotating masses. “Genuine” system inertia is thus enhanced, which is fundamentally different from the “emulated” inertia by fast frequency response (FFR) from grid-following converters. Against this backdrop, this thesis mainly focuses on two aspects. The first is the small-signal stability of such residential microgrids. In particular, the impact of the increasing number of grid-forming prosumers is studied based on the linearised model. The impact of the various dynamic response of primary sources is also investigated. The second is the control of the grid-forming prosumers aiming to provide sufficient inertia for the system. The control is focused on both the inverters and the DC-stage converters. Specifically, the thesis proposes an advanced controller for the DC-stage converters based on active disturbance rejection control (ADRC), which observes and rejects the “total disturbance” of the system, thereby enhancing the inertial response provided by prosumer DER. In addition, to make better use of the energy from prosumer-owned DER, an adaptive droop controller based on a piecewise power function is proposed, which ensures that residential ESS provide little power in the steady state while supplying sufficient power to cater for the demand variation during the transient state. Proposed strategies are verified by time-domain simulations

    Evolution of microgrids with converter-interfaced generations: Challenges and opportunities

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    © 2019 Elsevier Ltd Although microgrids facilitate the increased penetration of distributed generations (DGs) and improve the security of power supplies, they have some issues that need to be better understood and addressed before realising the full potential of microgrids. This paper presents a comprehensive list of challenges and opportunities supported by a literature review on the evolution of converter-based microgrids. The discussion in this paper presented with a view to establishing microgrids as distinct from the existing distribution systems. This is accomplished by, firstly, describing the challenges and benefits of using DG units in a distribution network and then those of microgrid ones. Also, the definitions, classifications and characteristics of microgrids are summarised to provide a sound basis for novice researchers to undertake ongoing research on microgrids

    Electric Power Conversion and Micro-Grids

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    This edited volume is a collection of reviewed and relevant research chapters offering a comprehensive overview of recent achievements in the field of micro-grids and electric power conversion. The book comprises single chapters authored by various researchers and is edited by a group of experts in such research areas. All chapters are complete in themselves but united under a common research study topic. This publication aims at providing a thorough overview of the latest research efforts by international authors on electric power conversion, micro-grids, and their up-to-the-minute technological advances and opens new possible research paths for further novel developments

    Modeling and Integration of Demand Response and Demand Side Resources for Smart Grid Application in Distribution Systems

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    Today\u27s electric grid is undergoing drastic changes to evolve into a smart grid. Deregulation of the integrated and monopolistic power system into genco, transco and disco has led to tremendous competition among these players. These entities are in the process of developing innovative smart grid strategies that can improve their reliability and profit. In this thesis work, some of the smart grid initiatives by discos have been explored.;This thesis work is driven by two major objectives. The primary objective is to explore Demand Response (DR), develop its comprehensive model and to analyze various effects and implications of DR on distribution networks. The second major objective of the thesis is to integrate the developed demand response model into a microgrid market optimization. A microgrid network is a real world demonstration of smart grid that integrates and coordinates various demand side resources into its operation. For this reason, a microgrid has been chosen in this work so that it offers a broader scope where in addition to DR models, Battery Energy Storage System (BESS) and Distributed Energy Resources (DER) or Distributed Generation (DG) can also be modeled and integrated.;This thesis develops a model for DR by utilizing consumer behavior modeling considering different scenarios and levels of consumer rationality. Consumer behavior modeling has been done by developing extensive demand-price elasticity matrices for different types of consumers. These Price Elasticity Matrices (PEMs) are utilized to calculate the level of demand response for a given consumer. DR thus obtained is applied to a real world distribution network considering a day-ahead real time pricing scenario to study the effects of demand reduction and redistribution on system voltage and losses. Results show considerable boost in system voltage that paves way for further demand curtailment through demand side management techniques like Volt/Var Control (VVC).;Following this, the thesis develops a market optimization model for an islanded microgrid that includes Smart Grid elements namely DR, DERs and BESS. Comprehensive models for DR and BESS have been developed and integrated into the optimization program. Demand Side Bidding (DSB) by DR Aggregators is introduced into the proposed double sided microgrid energy market by utilizing the DR models developed. The optimization program uses Linear Programming (LP) technique to determine the dispatch schedule of DERs, BESS and the level of DR to minimize the operating cost of the microgrid market. A time series simulation of a large microgrid test system is performed to show the feasibility of the proposed market optimization

    Protection of Active Distribution Networks and Their Cyber Physical Infrastructure

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    Today’s Smart Grid constitutes several smaller interconnected microgrids. However, the integration of converter-interfaced distributed generation (DG) in microgrids has raised several issues such as the fact that fault currents in these systems in islanded mode are way less than those in grid connected microgrids. Therefore, microgrid protection schemes require a fast, reliable and robust communication system, with backup, to automatically adjust relay settings for the appropriate current levels according to the microgrid’s operation mode. However, risks of communication link failures, cyber security threats and the high cost involved to avoid them are major challenges for the implementation of an economic adaptive protection scheme. This dissertation proposes an adaptive protection scheme for AC microgrids which is capable of surviving communication failures. The contribution is the use of an energy storage system as the main contributor to fault currents in the microgrid’s islanded mode when the communication link fails to detect the shift to the islanded mode. The design of an autonomous control algorithm for the energy storage’s AC/DC converter capable of operating when the microgrid is in both grid-connected and islanded mode. Utilizing a single mode of operation for the converter will eliminate the reliance on communicated control command signals to shift the controller between different modes. Also, the ability of the overall system to keep stable voltage and frequency levels during extreme cases such as the occurrence of a fault during a peak pulse load period. The results of the proposed protection scheme showed that the energy storage -inverter system is able to contribute enough fault current for a sufficient duration to cause the system protection devices to clear the fault in the event of communication loss. The proposed method was investigated under different fault types and showed excellent results of the proposed protection scheme. In addition, it was demonstrated in a case study that, whenever possible, the temporary disconnection of the pulse load during the fault period will allow the utilization of smaller energy storage device capacity to feed fault currents and thus reduce the overall expenditures. Also, in this dissertation we proposed a hybrid hardware-software co-simulation platform capable of modeling the relation between the cyber and physical parts to provide a protection scheme for the microgrid. The microgrid was simulated on MATLAB/Simulink SimPowerSystems to model the physical system dynamics, whereas all control logic was implemented on embedded microcontrollers communicating over a real network. This work suggested a protection methodology utilizing contemporary communication technologies between multi-agents to protect the microgrid
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