On the Control of Microgrids Against Cyber-Attacks: A Review of Methods and Applications

Nowadays, the use of renewable generations, energy storage systems (ESSs) and microgrids (MGs) has been developed due to better controllability of distributed energy resources (DERs) as well as their cost-effective and emission-aware operation. The development of MGs as well as the use of hierarchical control has led to data transmission in the communication platform. As a result, the expansion of communication infrastructure has made MGs as cyber-physical systems (CPSs) vulnerable to cyber-attacks (CAs). Accordingly, prevention, detection and isolation of CAs during proper control of MGs is essential. In this paper, a comprehensive review on the control strategies of microgrids against CAs and its defense mechanisms has been done. The general structure of the paper is as follows: firstly, MGs operational conditions, i.e., the secure or insecure mode of the physical and cyber layers are investigated and the appropriate control to return to a safer mode are presented. Then, the common MGs communication system is described which is generally used for multi-agent systems (MASs). Also, classification of CAs in MGs has been reviewed. Afterwards, a comprehensive survey of available researches in the field of prevention, detection and isolation of CA and MG control against CA are summarized. Finally, future trends in this context are clarified

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

Resilience-oriented control and communication framework for cyber-physical microgrids

Climate change drives the energy supply transition from traditional fossil fuel-based power generation to renewable energy resources. This transition has been widely recognised as one of the most significant developing pathways promoting the decarbonisation process toward a zero-carbon and sustainable society. Rapidly developing renewables gradually dominate energy systems and promote the current energy supply system towards decentralisation and digitisation. The manifestation of decentralisation is at massive dispatchable energy resources, while the digitisation features strong cohesion and coherence between electrical power technologies and information and communication technologies (ICT). Massive dispatchable physical devices and cyber components are interdependent and coupled tightly as a cyber-physical energy supply system, while this cyber-physical energy supply system currently faces an increase of extreme weather (e.g., earthquake, flooding) and cyber-contingencies (e.g., cyberattacks) in the frequency, intensity, and duration. Hence, one major challenge is to find an appropriate cyber-physical solution to accommodate increasing renewables while enhancing power supply resilience. The main focus of this thesis is to blend centralised and decentralised frameworks to propose a collaboratively centralised-and-decentralised resilient control framework for energy systems i.e., networked microgrids (MGs) that can operate optimally in the normal condition while can mitigate simultaneous cyber-physical contingencies in the extreme condition. To achieve this, we investigate the concept of "cyber-physical resilience" including four phases, namely prevention/upgrade, resistance, adaption/mitigation, and recovery. Throughout these stages, we tackle different cyber-physical challenges under the concept of microgrid ranging from a centralised-to-decentralised transitional control framework coping with cyber-physical out of service, a cyber-resilient distributed control methodology for networked MGs, a UAV assisted post-contingency cyber-physical service restoration, to a fast-convergent distributed dynamic state estimation algorithm for a class of interconnected systems.Open Acces

Modeling and Controlling a Hybrid Multi-Agent based Microgrid in Presence of Different Physical and Cyber Components

This dissertation starts with modeling of two different and important parts of the distribution power systems, i.e. distribution line and photovoltaic (PV) systems. Firstly, it studies different approximation methods and develops a new approach for simplification of Carson\u27s equations to model distribution lines for unbalanced power flow and short circuit analysis. The results of applying the proposed method on a three-phase unbalanced distribution system are compared with different existing methods as well as actual impedance values obtained from numerical integration method. Then steady state modeling and optimal placing of multiple PV system are investigated in order to reduce the total loss in the system. The results show the effectiveness of the proposed method in minimizing the total loss in a distribution power system.;The dissertation starts the discussion about microgrid modeling and control by implementing a novel frequency control approach in a microgrid. This study has been carried out step by step by modeling different part of the power system and proposing different algorithms. Firstly, the application of Renewable Energy Sources (RES) accompanied with Energy Storage Systems (ESS) in a hybrid system is studied in the presence of Distributed Generation (DG) resources in Load Frequency Control (LFC) problem of microgrid power system with significant penetration of wind speed disturbances. The next step is to investigate the effect of PHEVs in modelling and controlling the microgid. Therefore, system with different penetrations of PHEVs and different stochastic behaviors of PHEVs is modeled. Different kinds of control approaches, including PI control as conventional method and proposed optimal LQR and dynamic programming methods, have been utilized and the results have been compared with each other. Then, Multi Agent System (MAS) is utilized as a control solution which contributes the cyber aspects of microgrid system. The modeled microgrid along with dynamic models of different components is implemented in a centralized multi-agent based structure. The robustness of the proposed controller has been tested against different frequency changes including cyber attack implications with different timing and severity. New attack detection through learning method is also proposed and tested. The results show improvement in frequency response of the microgrid system using the proposed control method and defense strategy against cyber attacks.;Finally, a new multi-agent based control method along with an advanced secondary voltage and frequency control using Particle Swarm Optimization (PSO) and Adaptive Dynamic Programming (ADP) is proposed and tested in the modeled microgrid considering nonlinear heterogeneous dynamic models of DGs. The results are shown and compared with conventional control approaches and different multi-agent structures. It is observed that the results are improved by using the new multi-agent structure and secondary control method.;In summary, contributions of this dissertation center in three main topics. Firstly, new accurate methods for modeling the distribution line impedance and PV system is developed. Then advanced control and defense strategy method for frequency regulation against cyber intrusions and load changes in a microgrid is proposed. Finally, a new hierarchical multi-agent based control algorithm is designed for secondary voltage and frequency control of the microgrid. (Abstract shortened by ProQuest.)

TOWARDS OPTIMAL OPERATION AND CONTROL OF EMERGING ELECTRIC DISTRIBUTION NETWORKS

The growing integration of power-electronics converters enabled components causes low inertia in the evolving electric distribution networks, which also suffer from uncertainties due to renewable energy sources, electric demands, and anomalies caused by physical or cyber attacks, etc. These issues are addressed in this dissertation. First, a virtual synchronous generator (VSG) solution is provided for solar photovoltaics (PVs) to address the issues of low inertia and system uncertainties. Furthermore, for a campus AC microgrid, coordinated control of the PV-VSG and a combined heat and power (CHP) unit is proposed and validated. Second, for islanded AC microgrids composed of SGs and PVs, an improved three-layer predictive hierarchical power management framework is presented to provide economic operation and cyber-physical security while reducing uncertainties. This scheme providessuperior frequency regulation capability and maintains low system operating costs. Third, a decentralized strategy for coordinating adaptive controls of PVs and battery energy storage systems (BESSs) in islanded DC nanogrids is presented. Finally, for transient stability evaluation (TSE) of emerging electric distribution networks dominated by EV supercharging stations, a data-driven region of attraction (ROA) estimation approach is presented. The proposed data-driven method is more computationally efficient than traditional model-based methods, and it also allows for real-time ROA estimation for emerging electric distribution networks with complex dynamics

Self-organizing Coordination of Multi-Agent Microgrid Networks

abstract: This work introduces self-organizing techniques to reduce the complexity and burden of coordinating distributed energy resources (DERs) and microgrids that are rapidly increasing in scale globally. Technical and financial evaluations completed for power customers and for utilities identify how disruptions are occurring in conventional energy business models. Analyses completed for Chicago, Seattle, and Phoenix demonstrate site-specific and generalizable findings. Results indicate that net metering had a significant effect on the optimal amount of solar photovoltaics (PV) for households to install and how utilities could recover lost revenue through increasing energy rates or monthly fees. System-wide ramp rate requirements also increased as solar PV penetration increased. These issues are resolved using a generalizable, scalable transactive energy framework for microgrids to enable coordination and automation of DERs and microgrids to ensure cost effective use of energy for all stakeholders. This technique is demonstrated on a 3-node and 9-node network of microgrid nodes with various amounts of load, solar, and storage. Results found that enabling trading could achieve cost savings for all individual nodes and for the network up to 5.4%. Trading behaviors are expressed using an exponential valuation curve that quantifies the reputation of trading partners using historical interactions between nodes for compatibility, familiarity, and acceptance of trades. The same 9-node network configuration is used with varying levels of connectivity, resulting in up to 71% cost savings for individual nodes and up to 13% cost savings for the network as a whole. The effect of a trading fee is also explored to understand how electricity utilities may gain revenue from electricity traded directly between customers. If a utility imposed a trading fee to recoup lost revenue then trading is financially infeasible for agents, but could be feasible if only trying to recoup cost of distribution charges. These scientific findings conclude with a brief discussion of physical deployment opportunities.Dissertation/ThesisDoctoral Dissertation Systems Engineering 201