Showing papers by "Chen-Ching Liu published in 2021"

Intrusion Detection for Cybersecurity of Smart Meters

Abstract: The integration of Information and Communications Technology (ICT) enables real-time communication for smart meters to participate in power system operations. However, Advanced Metering Infrastructures (AMI) are vulnerable to cyber attacks. Both utilities and power consumers may become victims of cyber intrusions. In this paper, a two-stage cyber intrusion protection system is proposed. At the first stage of intrusion detection, a Support Vector Machine (SVM) is used as a detection algorithm to discover suspicious behaviors inside a smart meter. At the second stage, the Temporal Failure Propagation Graph (TFPG) technique is used to generate attack routes for identifying attack events. Finally, the proposed pattern recognition algorithm is used to calculate the similarity between a detected abnormal event and pre-defined cyber attacks. A higher similarity value implies a higher chance that a smart meter is under attack. An AMI security test platform has been developed to: (1) Collect training/testing data for SVM, (2) Simulate and analyze cyber attack events, and (3) Validate the proposed cyber attack protection system. The test platform consists of Network-Simulator 3 (NS-3) software to simulate an AMI network environment and single board computers (SBCs) to emulate the IEEE 802.15.4 communication between a grid router and a smart meter.

Decentralized Transactive Energy for Flexible Resources in Distribution Systems

Abstract: The increasing penetration of proactive agents in electric power distribution systems calls for mechanisms to coordinate their trading activities. The commonly employed centralized and distributed methods for supply-demand coordination are not only limited by hardware requirements but also restrictive for active participation of the market agents. This paper proposes a novel decentralized transactive coordination framework that allows participants to bid and clear transactions via a bilateral interaction process. The framework is based on 1) power consumption flexibility individually reported by demand agents using model-predictive control, 2) bilateral supply-side bidding individually determined by the supply agents using a Markowitz Portfolio Optimization model, and 3) individual simultaneous clearing of transactions by demand agents based on second-price sealed-bid auctions. The suppliers bid in the market to achieve desired returns while minimizing their risks. The demand agents harness their demand flexibility by competitively clearing the supplier bids. Unlike traditional approaches, the proposed framework does not require master nodes to orchestrate transactions and, therefore, facilitates massive participation of market agents. Simulation cases demonstrate that the proposed framework successfully performs the market function for bilateral transactions among thousands of proactive agents.

Resilience-Motivated Distribution System Restoration Considering Electricity-Water-Gas Interdependency

Abstract: A major outage in the electricity distribution system may affect the operation of water and natural gas supply systems, leading to an interruption of multiple services to critical customers. Therefore, enhancing resilience of critical infrastructures requires joint efforts of multiple sectors. In this paper, a distribution system service restoration method considering the electricity-water-gas interdependency is proposed. The objective is to provide electricity, water, and natural gas supplies to critical customers in the desired ratio according to their needs after an extreme event. The operational constraints of electricity, water, and natural gas networks are considered. The characteristics of electricity-driven coupling components, including water pumps and gas compressors, are also modeled. Relaxation techniques are applied to nonconvex constraints posed by physical laws of those networks. Consequently, the restoration problem is formulated as a mixed-integer second-order cone program, which can readily be solved by the off-the-shelf solvers. The proposed method is validated by numerical simulations on electricity-water-gas integrated systems, developed based on benchmark models of the subsystems. The results indicate that considering the interdependency refines the allocation of limited generation resources and demonstrate the exactness of the proposed convex relaxation.

Distribution System Resilience Under Asynchronous Information Using Deep Reinforcement Learning

Abstract: Resilience of a distribution system can be enhanced by efficient restoration of critical load following a major outage. Existing models include optimization approaches that consider available information without incorporating the inherent asynchrony of data arrival during execution of the restoration plan. Failure to consider the asynchronous nature of information arrival can lead to underutilization of critical resources. Moreover, analytical models become computationally inefficient for large scale systems. On the other hand, artificial intelligence (AI)-based tools have demonstrated efficient results for power system applications. In this paper, it is proposed a Reinforcement Learning (RL) model that learns how to efficiently restore a distribution system after a major outage. The proposed approach is based on a Monte Carlo Tree Search to expedite the training process. The proposed model strategy provides a robust decision-making tool for asynchronous and partial information scenarios. The results, validated with the IEEE 13-bus test feeder and IEEE 8500-node distribution test feeder, demonstrate the effectiveness and scalability of the proposed method.

Privacy-Preserving Hierarchical State Estimation in Untrustworthy Cloud Environments

Abstract: Hierarchical state estimation (HSE) is often deployed to evaluate the states of an interconnected power system from telemetered measurements. By HSE, each low-level control center (LCC) takes charge of the estimation of its internal states, whereas a trusted high-level control center (HCC) assumes the coordination of boundary states. However, a trusted HCC may not always exist in practice; a cloud server can take the role of an HCC in case no such facility is available. Since it is prohibited to release sensitive power grid data to untrustworthy cloud environments, considerations need to be given to avoid breaches of LCCs’ privacy when outsourcing the coordination tasks to the cloud server. To this end, this article proposes a privacy-preserving HSE framework, which rearranges the regular HSE procedure to integrate a degree-2 variant of the Thresholded Paillier Cryptosystem (D2TPC). Attributed to D2TPC, computations by the cloud-based HCC can be conducted entirely in the ciphertext space. Even if the HCC and some LCCs conspire together to share the information they have, the privacy of non-conspiring LCCs is still assured. Experiments on various scales of test systems demonstrate a high level of accuracy, efficiency, and scalability of the proposed framework.

Intrusion Detection Against MMS-Based Measurement Attacks at Digital Substations

Abstract: Information and Communications Technology (ICT) supports the development of novel control and communication functions for monitoring, operation, and control of power systems. However, the high-level deployment of ICT also increases the risk of cyber intrusions for Supervisory Control And Data Acquisition (SCADA) systems. Attackers can gain access to the protected infrastructures of the grid and launch attacks to manipulate measurements at the substations. The fabricated measurements can mislead the operators in the control center to take undesirable actions. The Intrusion Detection System (IDS) proposed in this paper is deployed in IEC 61850 based substations. The proposed IDS identifies falsified measurements in Manufacturing Messaging Specification (MMS) messages. By cross-checking the consistency of electric circuit relationships at the substation level in a distributed manner, the falsified measurements can be detected and discarded before the malicious packets are sent out of the substations through DNP3 communication. A cyber-physical system testbed is used to validate the performance of the proposed IDS. Using the IEEE 39-bus test system, simulation results demonstrate high accuracy of the proposed substation-based intrusion detection system.

Cyber-Physical System Security of Distribution Systems

Abstract: Threats of cyberattacks targeting the electric power grid have been increasing in recent years. The consequence of cyber incidents on the power grid includes equipment damage, cascading events, large-scale power outages, and disruption of market functions. Government and industry have made a significant effort to strengthen the protection of the power infrastructure against cyber threats by setting standards and guidelines. This survey paper provides the basic concepts of cyber vulnerabilities of distribution systems and cyber-physical system security. Important ICT subjects for distribution systems covered in this paper include Supervisory Control and Data Acquisition (SCADA) and Distributed Energy Resources (DERs), including renewable energy and smart meters. This publication is intended to serve as a module in senior-level undergraduate as well as graduate courses in power engineering. The objective of this paper is to provide fundamental concepts of cyber security for the distribution system as a cyber-physical system. To meet the objective, vulnerabilities of cyber intrusions and mitigation strategies are discussed. The evolution of the ICT for the power grid and cyber security measures are presented, as well as the ICT in the power system environment. An overview of smart grid communication standards and protocols are included, and the detection of cyber intrusions in distribution systems are considered. Finally, simulation cases are provided.

Integrated Outage Management With Feeder Restoration for Distribution Systems With DERs

Abstract: The increasing deployment of distributed energy resources (DERs) and microgrids benefits power grids by improving system resilience. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. In this paper, algorithms are proposed for outage management and feeder restoration for distribution systems with multiple DERs. The Advanced Outage Management (AOM) identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The Advanced Feeder Restoration (AFR) is proposed to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs as well as the feeder configuration. By partitioning the system into islands, critical load will be served with the available generation resources within islands. When the utility systems become available, the optimal path will be determined to reconnect these islands back to substations and restore the remaining load. The proposed method has been validated with modified IEEE 123-Bus and 8500-Node Test Feeders. Simulation results demonstrate the capability of the integrated AOM and AFR to enhance distribution system resilience.

Bilateral Market for Distribution-level Coordination of Flexible Resources using Volttron

Abstract: Increasing penetrations of distributed energy resources (DERs) and responsive loads (RLs) in the electric power distribution systems calls for a mechanism for joint supply-demand coordination. Recently, several transactive/bilateral co-ordination mechanisms have been proposed for the distribution-level coordination of flexible resources. Implementing a transactive market coordination approach requires a secure, reliable, and computationally efficient multi-agent platform. An example of such a platform is VOLTTRON, developed by the Pacific Northwest National Laboratories (PNNL). The VOLTTRON platform allows the market actors to exchange information and execute proper control actions in a decentralized way. This paper aims to provide a proof-of-concept of the transactive market coordination approach via a small-scale demonstration on the VOLTTRON platform. The steps needed to implement the proposed market architecture using virtual machines and VOLTTRON are thoroughly described, and illustrative examples are provided to show the market-clearing process for different scenarios.

Bilateral Market for Distribution-level Coordination of Flexible Resources using Volttron

Abstract: Increasing penetrations of distributed energy resources (DERs) and responsive loads (RLs) in the electric power distribution systems calls for a mechanism for joint supply-demand coordination. Recently, several transactive/bilateral coordination mechanisms have been proposed for the distribution-level coordination of flexible resources. Implementing a transactive market coordination approach requires a secure, reliable, and computationally efficient multi-agent platform. An example of such a platform is VOLTTRON, developed by the Pacific Northwest National Laboratories (PNNL). The VOLTTRON platform allows the market actors to exchange information and execute proper control actions in a decentralized way. This paper aims to provide a proof-of-concept of the transactive market coordination approach via a small-scale demonstration on the VOLTTRON platform. The steps needed to implement the proposed market architecture using virtual machines and VOLTTRON are thoroughly described, and illustrative examples are provided to show the market-clearing process for different scenarios.