Showing papers by "Chen-Ching Liu published in 2020"

A Two-Layer Distributed Cooperative Control Method for Islanded Networked Microgrid Systems

Abstract: This paper presents a two-layer distributed cooperative control method for networked microgrid (NMG) systems, taking into account the proprietary nature of microgrid (MG) owners. The proposed control architecture consists of an MG-control layer and an NMG-control layer. In the MG layer, the primary and distributed secondary controls realize accurate power sharing among distributed generators (DGs) and the frequency/voltage reference following within each MG. In the NMG layer, the tertiary control enables regulation of the power flowing through the point of common coupling (PCC) of each MG in a decentralized manner. Furthermore, distributed quaternary control restores the system frequency and critical bus voltage to their nominal values and ensures accurate power sharing among MGs. A small-signal dynamic model is developed to evaluate the dynamic performance of NMG systems with the proposed control method. Time-domain simulations and experiments on NMG test systems are performed to validate the effectiveness of the proposed method.

Decentralized Intrusion Prevention (DIP) Against Co-Ordinated Cyberattacks on Distribution Automation Systems

Abstract: Integration of Information and Communications Technology (ICT) into the distribution system makes today’s power grid more remotely monitored and controlled than it has been. The fast increasing connectivity, however, also implies that the distribution grid today, or smart grid, is more vulnerable. Thus, research into intrusion/anomaly detection systems at the distribution level is in critical need. Current research on Intrusion Detection Systems for the power grid has been focused primarily on cyber security at the Supervisory Control And Data Acquisition, and single node levels with little attention on coordinated cyberattacks at multiple nodes. A holistic approach toward system-wide cyber security for distribution systems is yet to be developed. This paper presents a novel approach toward intrusion prevention, using a multi-agent system, at the distribution system level. Simulations of the method have been performed on the IEEE 13-Node Test Feeder, and the results compared to those obtained from existing methods. The results have validated the performance of the proposed method for protection against cyber intrusions at the distribution system level.

Assessing Cyber-Physical Risks of IoT-Based Energy Devices in Grid Operations

Abstract: The growing number of consumer-grade network-enabled Distributed Energy Resources (DER) installations introduces new attack vectors that could impact grid operations through coordinated attacks. This work presents a cyber-physical model and risk assessment methodology for analyzing the emerging nexus between Internet of Things-based energy devices and the bulk transmission grid. The cyber model replicates the device-level interconnectivity and software components interaction found within these architectures to understand the feasibly of coordinated attacks, while the physical model is used to assess the attack's impacts on the grid. The manuscript questions the validity of previous papers' claims regarding IoT-based grid attacks by addressing key limitations in both the power grid and cyber infrastructure models of those works. The resulting methodology is then evaluated using the Western Electricity Coordinating Council (WECC) electrical model coupled with DER's operational statistics from California. The results suggest that current DER penetration rates are not yet significant enough to present serious risk, but continued DER growth may be problematic. Furthermore, the work identifies policies that mitigate these risks through increased device diversity and cybersecurity requirements.

Optimal Capacity and Placement of Microgrids for Resiliency Enhancement of Distribution Networks Under Extreme Weather Events

Abstract: When a fault or a series of faults occur in a distribution network, it is of considerable significance to feeding loads, most importantly critical loads. Although network reconfiguration by switching operations has been usually considered as a relatively low-cost method for load restoration, it alone may not able to restore critical loads under extreme weather events such as hurricanes where multiple faults can happen within the network. Under such severe circumstances, one of the complementary methods for service restoration is benefiting from existing installed microgrids. In this paper, the idea of planning future microgrids -in terms of optimal location and capacity- in combination with switching operations to restore critical loads, for the first time, is considered. To this planning-operation concept end, a graph-theoretic method is developed to find optimal switching operations coupled with a heuristic optimization method developed to determine future microgrids' location and capacity to maximize the resiliency of the network while keeping the associated cost with distributed generations (DGs) in microgrids as low as possible. Simulations results on the modified IEEE 37-node distribution network show the effectiveness of the proposed idea. Moreover, using appropriate reduction techniques, the computational efficacy of the method has also been greatly improved.

Online Voltage Stability Monitoring and Control Using Limited Synchrophasor Measurements

Abstract: As the scale and complexity of an interconnected power grid has increased significantly, power systems can be operated close to the verge of voltage instability. With the application of Phasor Measurement Units (PMUs), dispatchers are able to monitor long term voltage stability in a real time operational environment. This research addresses the critical issues by proposing three different methods. Voltage Stability Assessment Index (VSAI) is a Thevenin Equivalent (TE) based method considering voltage dynamic mechanisms. To extend the model from one load bus to a critical load center, Optimal Power Flow-Loading limit (OPF-LI) is developed to assess the voltage stability margin. To utilize limited available PMU measurements, State Calculator (SC) is included in the algorithm to approximate the dynamic states at the buses where PMU measurements are not available. The online voltage regulating method in terms of On-load Tap Changer (OLTC) control is also investigated. The methods proposed in this research have been validated with the test cases from the WECC 179 bus system.

Moving horizon-based optimal scheduling of EV charging: A power system-cognizant approach

Abstract: The rapid escalation in plug-in electric vehicles (PEVs) and their uncoordinated charging patterns pose several challenges in distribution system operation. Some of the undesirable effects include overloading of transformers, rapid voltage fluctuations, and over/under voltages. While this compromises the consumer power quality, it also puts on extra stress on the local voltage control devices. These challenges demand for a well-coordinated and power network-aware charging approach for PEVs in a community. This paper formulates a real-time electric vehicle charging scheduling problem as an mixed-integer linear program (MILP). The problem is to be solved by an aggregator, that provides charging service in a residential community. The proposed formulation maximizes the profit of the aggregator, enhancing the utilization of available infrastructure. With a prior knowledge of load demand and hourly electricity prices, the algorithm uses a moving time horizon optimization approach, allowing the number of vehicles arriving unknown. In this realistic setting, the proposed framework ensures that power system constraints are satisfied and guarantees desired PEV charging level within stipulated time. Numerical tests on a IEEE 13-node feeder system demonstrate the computational and performance superiority of the proposed MILP technique.

Moving horizon-based optimal scheduling of EV charging: A power system-cognizant approach

Abstract: The rapid escalation in plug-in electric vehicles (PEVs) and their uncoordinated charging patterns pose several challenges in distribution system operation. Some of the undesirable effects include overloading of transformers, rapid voltage fluctuations, and over/under voltages. While this compromises the consumer power quality, it also puts on extra stress on the local voltage control devices. These challenges demand for a well coordinated and power network-aware charging approach for PEVs in a community. This paper formulates a real-time electric vehicle charging scheduling problem as an mixed-integer linear program (MILP). The problem is to be solved by an aggregator, that provides charging service in a residential community. The proposed formulation maximizes the profit of the aggregator, enhancing the utilization of available infrastructure. With a prior knowledge of load demand and hourly electricity prices, the algorithm uses a moving time horizon optimization approach, allowing the number of vehicles arriving unknown. In this realistic setting, the proposed framework ensures that power system constraints are satisfied and guarantees desired PEV charging level within stipulated time. Numerical tests on a IEEE 13-node feeder system demonstrate the computational and performance superiority of the proposed MILP technique.