A review of microgrid development in the United States – A decade of progress on policies, demonstrations, controls, and software tools

Microgrids have become increasingly popular in the United States. Supported by favorable federal and local policies, microgrid projects can provide greater energy stability and resilience within a project site or community. This paper reviews major federal, state, and utility-level policies driving microgrid development in the United States. Representative U.S. demonstration projects are selected and their technical characteristics and non-technical features are introduced. The paper discusses trends in the technology development of microgrid systems as well as microgrid control methods and interactions within the electricity market. Software tools for microgrid design, planning, and performance analysis are illustrated with each tool's core capability. Finally, the paper summarizes the successes and lessons learned during the recent expansion of the U.S. microgrid industry that may serve as a reference for other countries developing their own microgrid industries

Wide-Area Time-Synchronized Closed-Loop Control of Power Systems And Decentralized Active Distribution Networks

The rapidly expanding power system grid infrastructure and the need to reduce the occurrence of major blackouts and prevention or hardening of systems against cyber-attacks, have led to increased interest in the improved resilience of the electrical grid. Distributed and decentralized control have been widely applied to computer science research. However, for power system applications, the real-time application of decentralized and distributed control algorithms introduce several challenges. In this dissertation, new algorithms and methods for decentralized control, protection and energy management of Wide Area Monitoring, Protection and Control (WAMPAC) and the Active Distribution Network (ADN) are developed to improve the resiliency of the power system. To evaluate the findings of this dissertation, a laboratory-scale integrated Wide WAMPAC and ADN control platform was designed and implemented. The developed platform consists of phasor measurement units (PMU), intelligent electronic devices (IED) and programmable logic controllers (PLC). On top of the designed hardware control platform, a multi-agent cyber-physical interoperability viii framework was developed for real-time verification of the developed decentralized and distributed algorithms using local wireless and Internet-based cloud communication. A novel real-time multiagent system interoperability testbed was developed to enable utility independent private microgrids standardized interoperability framework and define behavioral models for expandability and plug-and-play operation. The state-of-theart power system multiagent framework is improved by providing specific attributes and a deliberative behavior modeling capability. The proposed multi-agent framework is validated in a laboratory based testbed involving developed intelligent electronic device prototypes and actual microgrid setups. Experimental results are demonstrated for both decentralized and distributed control approaches. A new adaptive real-time protection and remedial action scheme (RAS) method using agent-based distributed communication was developed for autonomous hybrid AC/DC microgrids to increase resiliency and continuous operability after fault conditions. Unlike the conventional consecutive time delay-based overcurrent protection schemes, the developed technique defines a selectivity mechanism considering the RAS of the microgrid after fault instant based on feeder characteristics and the location of the IEDs. The experimental results showed a significant improvement in terms of resiliency of microgrids through protection using agent-based distributed communication

Using Renewable-Based Microgrid Capabilities for Power System Restoration

Power system restoration (PSR) is a very important procedure to ensure the consumer supply. In this paper, a decentralized multi-agent system (MAS) for dealing with the microgrid restoration procedure is proposed. In this proposed method, each agent is associated to a consumer or microsource (MS) and these will communicate between each other in order to reach a common decision. The agents solve a 0/1 knapsack problem to determine the best load connection sequence during the microgrid restoration procedure. The proposed MAS is tested in two different case studies: a total blackout and a partial blackout, in which the emergency demand response programs are considered. It is developed in the Matlab/Simulink environment and is validated by performing the corresponding dynamic simulations.Power system restoration (PSR) is a very important procedure to ensure the consumer supply. In this paper, a decentralized multi-agent system (MAS) for dealing with the microgrid restoration procedure is proposed. In this proposed method, each agent is associated to a consumer or microsource (MS) and these will communicate between each other in order to reach a common decision. The agents solve a 0/1 knapsack problem to determine the best load connection sequence during the microgrid restoration procedure. The proposed MAS is tested in two different case studies: a total blackout and a partial blackout, in which the emergency demand response programs are considered. It is developed in the Matlab/Simulink environment and is validated by performing the corresponding dynamic simulations

Development of an Energy Management System Control Algorithm for a Remote Community Microgrid System

Rural communities are often unable to access electrical energy as they are located 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 dependent on connection to a national power grid

Load-shedding techniques for microgrids: A comprehensive review

Abstract: The increasing interest in integrating renewable energies source has raised concerns about control operations. The presence of new energy sources, distributed storage, power electronic devices and communication links make a power system’s control and monitoring more complex and adaptive than ever before. Recently, the use of agent-based distributed control has seen to have a significant impact on the grid and microgrid controls. The load-shedding technique is among the features used to balance the power consumption in the power system upon less power production. Towards achieving these, different mechanisms, algorithms, challenges, and approaches have been developed and hence need to be reviewed and integrated from the system solution perspective. This research focuses on the review of the state-of-the-art load-shedding techniques, whereby the focus is on control algorithms, simulation platforms and integrations, and control devices for DC microgrid. The research also investigates open issues and challenges that need further investigations. The analyses reported in the paper upholds the importance of the distributed multi-agent system, MAS, in implementing distinct control operations including load-shedding. The effectiveness of the control operations using MAS rely on low-latency and secure communication links in which IoT has been branded as a promising technology for implementing distributed MAS.</p

Resilience-driven planning and operation of networked microgrids featuring decentralisation and flexibility

High-impact and low-probability extreme events including both man-made events and natural weather events can cause severe damage to power systems. These events are typically rare but featured in long duration and large scale. Many research efforts have been conducted on the resilience enhancement of modern power systems. In recent years, microgrids (MGs) with distributed energy resources (DERs) including both conventional generation resources and renewable energy sources provide a viable solution for the resilience enhancement of such multi-energy systems during extreme events. More specifically, several islanded MGs after extreme events can be connected with each other as a cluster, which has the advantage of significantly reducing load shedding through energy sharing among them. On the other hand, mobile power sources (MPSs) such as mobile energy storage systems (MESSs), electric vehicles (EVs), and mobile emergency generators (MEGs) have been gradually deployed in current energy systems for resilience enhancement due to their significant advantages on mobility and flexibility. Given such a context, a literature review on resilience-driven planning and operation problems featuring MGs is presented in detail, while research limitations are summarised briefly. Then, this thesis investigates how to develop appropriate planning and operation models for the resilience enhancement of networked MGs via different types of DERs (e.g., MGs, ESSs, EVs, MESSs, etc.). This research is conducted in the following application scenarios: 1. This thesis proposes novel operation strategies for hybrid AC/DC MGs and networked MGs towards resilience enhancement. Three modelling approaches including centralised control, hierarchical control, and distributed control have been applied to formulate the proposed operation problems. A detailed non-linear AC OPF algorithm is employed to model each MG capturing all the network and technical constraints relating to stability properties (e.g., voltage limits, active and reactive power flow limits, and power losses), while uncertainties associated with renewable energy sources and load profiles are incorporated into the proposed models via stochastic programming. Impacts of limited generation resources, load distinction intro critical and non-critical, and severe contingencies (e.g., multiple line outages) are appropriately captured to mimic a realistic scenario. 2. This thesis introduces MPSs (e.g., EVs and MESSs) into the suggested networked MGs against the severe contingencies caused by extreme events. Specifically, time-coupled routing and scheduling characteristics of MPSs inside each MG are modelled to reduce load shedding when large damage is caused to each MG during extreme events. Both transportation networks and power networks are considered in the proposed models, while transporting time of MPSs between different transportation nodes is also appropriately captured. 3. This thesis focuses on developing realistic planning models for the optimal sizing problem of networked MGs capturing a trade-off between resilience and cost, while both internal uncertainties and external contingencies are considered in the suggested three-level planning model. Additionally, a resilience-driven planning model is developed to solve the coupled optimal sizing and pre-positioning problem of MESSs in the context of decentralised networked MGs. Internal uncertainties are captured in the model via stochastic programming, while external contingencies are included through the three-level structure. 4. This thesis investigates the application of artificial intelligence techniques to power system operations. Specifically, a model-free multi-agent reinforcement learning (MARL) approach is proposed for the coordinated routing and scheduling problem of multiple MESSs towards resilience enhancement. The parameterized double deep Q-network method (P-DDQN) is employed to capture a hybrid policy including both discrete and continuous actions. A coupled power-transportation network featuring a linearised AC OPF algorithm is realised as the environment, while uncertainties associated with renewable energy sources, load profiles, line outages, and traffic volumes are incorporated into the proposed data-driven approach through the learning procedure.Open Acces

Energy Management of Distributed Generation Systems

The book contains 10 chapters, and it is divided into four sections. The first section includes three chapters, providing an overview of Energy Management of Distributed Systems. It outlines typical concepts, such as Demand-Side Management, Demand Response, Distributed, and Hierarchical Control for Smart Micro-Grids. The second section contains three chapters and presents different control algorithms, software architectures, and simulation tools dedicated to Energy Management Systems. In the third section, the importance and the role of energy storage technology in a Distribution System, describing and comparing different types of energy storage systems, is shown. The fourth section shows how to identify and address potential threats for a Home Energy Management System. Finally, the fifth section discusses about Economical Optimization of Operational Cost for Micro-Grids, pointing out the effect of renewable energy sources, active loads, and energy storage systems on economic operation

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

© 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

Management of Islanded Operation of Microgirds

Distributed generations with continuously growing penetration levels offer potential solutions to energy security and reliability with minimum environmental impacts. Distributed Generations when connected to the area electric power systems provide numerous advantages. However, grid integration of distributed generations presents several technical challenges which has forced the systems planners and operators to account for the repercussions on the distribution feeders which are no longer passive in the presence of distributed generations. Grid integration of distributed generations requires accurate and reliable islanding detection methodology for secure system operation. Two distributed generation islanding detection methodologies are proposed in this dissertation. First, a passive islanding detection technique for grid-connected distributed generations based on parallel decision trees is proposed. The proposed approach relies on capturing the underlying signature of a wide variety of system events on a set of critical system parameters and utilizes multiple optimal decision tress in a parallel network for classification of system events. Second, a hybrid islanding detection method for grid-connected inverter based distributed generations combining decision trees and Sandia frequency shift method is also proposed. The proposed method combines passive and active islanding detection techniques to aggregate their individual advantages and reduce or eliminate their drawbacks. In smart grid paradigm, microgrids are the enabling engine for systematic integration of distributed generations with the utility grid. A systematic approach for controlled islanding of grid-connected microgrids is also proposed in this dissertation. The objective of the proposed approach is to develop an adaptive controlled islanding methodology to be implemented as a preventive control component in emergency control strategy for microgrid operations. An emergency power management strategy for microgrid autonomous operation subsequent to inadvertent islanding events is also proposed in this dissertation. The proposed approach integrates microgrid resources such as energy storage systems, demand response resources, and controllable micro-sources to layout a comprehensive power management strategy for ensuring secure and stable microgrid operation following an unplanned islanding event. In this dissertation, various case studies are presented to validate the proposed methods. The simulation results demonstrate the effectiveness of the proposed methodologies

Optimal and Secure Electricity Market Framework for Market Operation of Multi-Microgrid Systems

Traditional power systems were typically based on bulk energy services by large utility companies. However, microgrids and distributed generations have changed the structure of modern power systems as well as electricity markets. Therefore, restructured electricity markets are needed to address energy transactions in modern power systems. In this dissertation, we developed a hierarchical and decentralized electricity market framework for multi-microgrid systems, which clears energy transactions through three market levels; Day-Ahead-Market (DAM), Hour-Ahead-Market (HAM) and Real-Time-Market (RTM). In this market, energy trades are possible between all participants within the microgrids as well as inter-microgrids transactions. In this approach, we developed a game-theoretic-based double auction mechanism for energy transactions in the DAM, while HAM and RTM are cleared by an optimization algorithm and reverse action mechanism, respectively. For data exchange among market players, we developed a secure data-centric communication approach using the Data Distribution Service. Results demonstrated that this electricity market could significantly reduce the energy price and dependency of the multi-microgrid area on the external grid. Furthermore, we developed and verified a hierarchical blockchain-based energy transaction framework for a multi-microgrid system. This framework has a unique structure, which makes it possible to check the feasibility of energy transactions from the power system point of view by evaluating transmission system constraints. The blockchain ledger summarization, microgrid equivalent model development, and market players’ security and privacy enhancement are new approaches to this framework. The research in this dissertation also addresses some ancillary services in power markets such as an optimal power routing in unbalanced microgrids, where we developed a multi-objective optimization model and verified its ability to minimize the power imbalance factor, active power losses and voltage deviation in an unbalanced microgrid. Moreover, we developed an adaptive real-time congestion management algorithm to mitigate congestions in transmission systems using dynamic thermal ratings of transmission lines. Results indicated that the developed algorithm is cost-effective, fast, and reliable for real-time congestion management cases. Finally, we completed research about the communication framework and security algorithm for IEC 61850 Routable GOOSE messages and developed an advanced protection scheme as its application in modern power systems