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

Enhancing Cyber-Resiliency of DER-based SmartGrid: A Survey

The rapid development of information and communications technology has enabled the use of digital-controlled and software-driven distributed energy resources (DERs) to improve the flexibility and efficiency of power supply, and support grid operations. However, this evolution also exposes geographically-dispersed DERs to cyber threats, including hardware and software vulnerabilities, communication issues, and personnel errors, etc. Therefore, enhancing the cyber-resiliency of DER-based smart grid - the ability to survive successful cyber intrusions - is becoming increasingly vital and has garnered significant attention from both industry and academia. In this survey, we aim to provide a systematical and comprehensive review regarding the cyber-resiliency enhancement (CRE) of DER-based smart grid. Firstly, an integrated threat modeling method is tailored for the hierarchical DER-based smart grid with special emphasis on vulnerability identification and impact analysis. Then, the defense-in-depth strategies encompassing prevention, detection, mitigation, and recovery are comprehensively surveyed, systematically classified, and rigorously compared. A CRE framework is subsequently proposed to incorporate the five key resiliency enablers. Finally, challenges and future directions are discussed in details. The overall aim of this survey is to demonstrate the development trend of CRE methods and motivate further efforts to improve the cyber-resiliency of DER-based smart grid.Comment: Submitted to IEEE Transactions on Smart Grid for Publication Consideratio

Co-design of Security Aware Power System Distribution Architecture as Cyber Physical System

The modern smart grid would involve deep integration between measurement nodes, communication systems, artificial intelligence, power electronics and distributed resources. On one hand, this type of integration can dramatically improve the grid performance and efficiency, but on the other, it can also introduce new types of vulnerabilities to the grid. To obtain the best performance, while minimizing the risk of vulnerabilities, the physical power system must be designed as a security aware system. In this dissertation, an interoperability and communication framework for microgrid control and Cyber Physical system enhancements is designed and implemented taking into account cyber and physical security aspects. The proposed data-centric interoperability layer provides a common data bus and a resilient control network for seamless integration of distributed energy resources. In addition, a synchronized measurement network and advanced metering infrastructure were developed to provide real-time monitoring for active distribution networks. A hybrid hardware/software testbed environment was developed to represent the smart grid as a cyber-physical system through hardware and software in the loop simulation methods. In addition it provides a flexible interface for remote integration and experimentation of attack scenarios. The work in this dissertation utilizes communication technologies to enhance the performance of the DC microgrids and distribution networks by extending the application of the GPS synchronization to the DC Networks. GPS synchronization allows the operation of distributed DC-DC converters as an interleaved converters system. Along with the GPS synchronization, carrier extraction synchronization technique was developed to improve the system’s security and reliability in the case of GPS signal spoofing or jamming. To improve the integration of the microgrid with the utility system, new synchronization and islanding detection algorithms were developed. The developed algorithms overcome the problem of SCADA and PMU based islanding detection methods such as communication failure and frequency stability. In addition, a real-time energy management system with online optimization was developed to manage the energy resources within the microgrid. The security and privacy were also addressed in both the cyber and physical levels. For the physical design, two techniques were developed to address the physical privacy issues by changing the current and electromagnetic signature. For the cyber level, a security mechanism for IEC 61850 GOOSE messages was developed to address the security shortcomings in the standard

Design and Implementation of a True Decentralized Autonomous Control Architecture for Microgrids

Microgrids can serve as an integral part of the future power distribution systems. Most microgrids are currently managed by centralized controllers. There are two major concerns associated with the centralized controllers. One is that the single controller can become performance and reliability bottleneck for the entire system and its failure can bring the entire system down. The second concern is the communication delays that can degrade the system performance. As a solution, a true decentralized control architecture for microgrids is developed and presented. Distributing the control functions to local agents decreases the possibility of network congestion, and leads to the mitigation of long distance transmission of critical commands. Decentralization will also enhance the reliability of the system since the single point of failure is eliminated. In the proposed architecture, primary and secondary microgrid controls layers are combined into one physical layer. Tertiary control is performed by the controller located at the grid point of connection. Each decentralized controller is responsible of multicasting its status and local measurements, creating a general awareness of the microgrid status among all decentralized controllers. The proof-of concept implementation provides a practical evidence of the successful mitigation of the drawback of control command transmission over the network. A Failure Management Unit comprises failure detection mechanisms and a recovery algorithm is proposed and applied to a microgrid case study. Coordination between controllers during the recovery period requires low-bandwidth communications, which has no significant overhead on the communication infrastructure. The proof-of-concept of the true decentralization of microgrid control architecture is implemented using Hardware-in-the-Loop platform. The test results show a robust detection and recovery outcome during a system failure. System test results show the robustness of the proposed architecture for microgrid energy management and control scenarios

Secure Control and Operation of Energy Cyber-Physical Systems Through Intelligent Agents

The operation of the smart grid is expected to be heavily reliant on microprocessor-based control. Thus, there is a strong need for interoperability standards to address the heterogeneous nature of the data in the smart grid. In this research, we analyzed in detail the security threats of the Generic Object Oriented Substation Events (GOOSE) and Sampled Measured Values (SMV) protocol mappings of the IEC 61850 data modeling standard, which is the most widely industry-accepted standard for power system automation and control. We found that there is a strong need for security solutions that are capable of defending the grid against cyber-attacks, minimizing the damage in case a cyber-incident occurs, and restoring services within minimal time. To address these risks, we focused on correlating cyber security algorithms with physical characteristics of the power system by developing intelligent agents that use this knowledge as an important second line of defense in detecting malicious activity. This will complement the cyber security methods, including encryption and authentication. Firstly, we developed a physical-model-checking algorithm, which uses artificial neural networks to identify switching-related attacks on power systems based on load flow characteristics. Secondly, the feasibility of using neural network forecasters to detect spoofed sampled values was investigated. We showed that although such forecasters have high spoofed-data-detection accuracy, they are prone to the accumulation of forecasting error. In this research, we proposed an algorithm to detect the accumulation of the forecasting error based on lightweight statistical indicators. The effectiveness of the proposed algorithms was experimentally verified on the Smart Grid testbed at FIU. The test results showed that the proposed techniques have a minimal detection latency, in the range of microseconds. Also, in this research we developed a network-in-the-loop co-simulation platform that seamlessly integrates the components of the smart grid together, especially since they are governed by different regulations and owned by different entities. Power system simulation software, microcontrollers, and a real communication infrastructure were combined together to provide a cohesive smart grid platform. A data-centric communication scheme was selected to provide an interoperability layer between multi-vendor devices, software packages, and to bridge different protocols together

Multi-Agent Systems Based Advanced Energy Management of Smart Micro-grid

Microgrids play a major role in enabling the widespread adoption of renewable distributed energy resources. However, as the power generated from renewable resources is intermittent in nature, it impacts the dynamics and stability of the microgrid, and hence their integration needs new approaches to coordination and control. The existing systems lack run-time adaptive behavior. To face these constraints, the electric energy system must adapt by integrating Information and Communication Technologies (ICT). Multiagent system (MAS) is emerging as an integrated solution approach to distributed computing, communication, and data integration needs for smart grid application. Distributed and heterogeneous information can be efficiently processed locally, but utilized globally to coordinate distributed knowledge networks, resulting in reduction of information processing time and network bandwidth. Parallel operations, asynchronous communication, and autonomous actions of agents enable MAS to adapt to dynamic changes of the environment, thereby improving the reliability, responsiveness, fault tolerance, and stability of the microgrid. In this chapter, MAS is implemented with Java Agent DEvelopment (JADE) framework for advanced energy management of a microgrid. Also, MAS is linked with Arduino microcontroller for practical verification of agent operations. Three microgrids are interconnected to form a microgrid testbed, and smart grid features such as demand side management and plug and play are implemented, making it into a smart microgrid

Intelligent agent for formal modelling of temporal multi-agent systems

Software systems are becoming complex and dynamic with the passage of time, and to provide better fault tolerance and resource management they need to have the ability of self-adaptation. Multi-agent systems paradigm is an active area of research for modeling real-time systems. In this research, we have proposed a new agent named SA-ARTIS-agent, which is designed to work in hard real-time temporal constraints with the ability of self-adaptation. This agent can be used for the formal modeling of any self-adaptive real-time multi-agent system. Our agent integrates the MAPE-K feedback loop with ARTIS agent for the provision of self-adaptation. For an unambiguous description, we formally specify our SA-ARTIS-agent using Time-Communicating Object-Z (TCOZ) language. The objective of this research is to provide an intelligent agent with self-adaptive abilities for the execution of tasks with temporal constraints. Previous works in this domain have used Z language which is not expressive to model the distributed communication process of agents. The novelty of our work is that we specified the non-terminating behavior of agents using active class concept of TCOZ and expressed the distributed communication among agents. For communication between active entities, channel communication mechanism of TCOZ is utilized. We demonstrate the effectiveness of the proposed agent using a real-time case study of traffic monitoring system

Voltage-based droop control of renewables to avoid on-off oscillations caused by overvoltages

To achieve the environmental goals set by many governments, an increasing amount of renewable energy, often delivered by distributed-generation (DG) units, is injected into the electrical power system. Despite the many advantages of DG, this can lead to voltage problems, especially in times of a high local generation and a low local load. The traditional solution is to invest in more and stronger lines, which could lead to massive investments to cope with the huge rise of DG connection. Another common solution is to include hard curtailment; thus, ON-OFF control of DG units. However, hard curtailment potentially leads to ON-OFF oscillations of DG and a high loss of the available renewable energy as storage is often not economically viable. To cope with these issues, applying a grid-forming control in grid-connected DG units is studied in this paper. The voltage-based droop control that was originally developed for power sharing in islanded microgrids, enables an effective way for soft curtailment without communication. The power changes of the renewable energy sources are delayed to more extreme voltages compared to those of the dispatchable units. This restricts the renewable energy loss and avoids ON-OFF oscillations

A framework for analyzing and testing cyber-physical interactions for smart grid applications

The reliable performance of the smart grid is a function of the configuration and cyber- physical nature of its constituting sub-systems. Therefore, the ability to capture the interactions between its cyber and physical domains is necessary to understand the effect that each one has on the other. As such, the work in this paper presents a co-simulation platform that formalizes the understanding of cyber information flow and the dynamic behavior of physical systems, and captures the interactions between them in smart grid applications. Power system simulation software packages, embedded microcontrollers, and a real communication infrastructure are combined together to provide a cohesive smart grid cyber-physical platform. A data-centric communication scheme, with automatic network discovery, was selected to provide an interoperability layer between multi-vendor devices and software packages, and to bridge different protocols. The effectiveness of the proposed framework was verified in three case studies: (1) hierarchical control of electric vehicles charging in microgrids, (2) International Electrotechnical Committee (IEC) 61850 protocol emulation for protection of active distribution networks, and (3) resiliency enhancement against fake data injection attacks. The results showed that the cosimulation platform provided a high-fidelity design, analysis, and testing environment for cyber information flow and their effect on the physical operation of the smart grid, as they were experimentally verified, down to the packet, over a real communication network