Resilient Networks
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ItemState Estimation in Low-Observable Distribution Systems Using Matrix Completion( 2019-01-08)The need for distribution system state estimation is on the rise because of the increased penetration of distributed energy resources and flexible load. To manage the distribution systems in real time, operators need to firstly overcome the challenge of low observability in distribution systems. Also, because of the amount of data present from smart meters, distributed generation measurements, switches, etc., the ideal distribution state estimation methods need to be able to process heterogeneous data. In this paper, an algorithm is developed for voltage phasor estimation in low-observability distribution systems. The algorithm is based on the matrix completion approach from signal processing. The traditional matrix completion formulation is augmented with power-flow constraints to improve results while requiring less data. This method can also use all types of measurements (voltage magnitude, voltage angle, real power, reactive power) to complete the state matrix.
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ItemRobust Look-ahead Three-phase Balancing of Uncertain Distribution Loads( 2019-01-08)Increasing penetration of highly variable components such as solar generation and electric vehicle charging loads pose significant challenges to keeping three-phase loads balanced in modern distribution systems. Failure to maintain balance across three phases would lead to asset deterioration and increasing delivery losses. Motivated by the real-world needs to automate and optimize the three-phase balancing decision making, this paper introduces a robust look-ahead optimization framework that pursues balanced phases in the presence of demand-side uncertainties. We show that look-ahead moving window optimization can reduce imbalances among phases at the cost of a limited number of phase swapping operations. Case studies quantify the improvements of the proposed methods compared with conventional deterministic phase balancing. Discussions on possible benefits of the proposed methods and extensions are presented.
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ItemMicrogrid Disaster Resiliency Analysis: Reducing Costs in Continuity of Operations (COOP) Planning( 2019-01-08)The electric grid serves a vital role in the supply chain of nearly all industrial and commercial organizations. A Microgrid infrastructure can provide this service and beneficial non-emergency services including a variety of generation/energy sources. To demonstrate the applicability of microgrids for energy resiliency, we present a microgrid resiliency case study for United Parcel Service’s (UPS) three separate shipping facilities. The goal, to enhance energy security, minimize cost and prevent cascading losses within other related business units. The impacts and consequences of which are quantified in this study using a Mean Failure Cost (MFC) risk assessment measure. MFC accounts for the potential loses to identified stakeholders that may result from a set of identified failures due to a set of identified threats. In this case, our study uses a method we call All Hazards Econometric System (AHES). AHES incorporates the cost of COOP using a strategy that considers the payback period of microgrid installation as compared to other energy delivery strategies.
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ItemOptimal Operator Training Reference Models for Human-in-the-loop Systems( 2019-01-08)The human operator is an integral part of a stable and safe power system. While there is increasing attention paid to automation improvements, the importance of understanding and training human operators may be understated. This paper discusses a project to enhance operator training programs by evaluating human performance relative to a reference operator model identified using optimal control theory. Along with establishing a simple computer-based operator workstation for future training purpose, this paper describes the optimal control response design methodology for a human-in-the-loop power system experiment. The overall system model is presented. An optimal controller synthesis methodology is applied to the model system and the optimal controller is designed. The performance of the optimal controller is then compared to human subject performance.
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ItemProbabilistic Bounds on the Impact of Potential Data Integrity Attacks in Microgrids( 2019-01-08)Microgrids are being increasingly adopted in electric power distribution systems to facilitate distributed energy resource integration and to provide resilient operations. Modern microgrids rely on sophisticated cyber communications and controls to maintain stable operation. Attacks on this cyber infrastructure can cause the system to undertake a potentially destabilizing control action. In this work, we present the results of a reachability analysis in which we determine whether a potential attack vector can result in actions that make an unstable state "reachable" in some time interval from the current state. Specifically, our analysis must be executed on a timescale that heads off the destabilizing system states due to malicious attacks. To that end, we propose a sensitivity analysis that assesses the worst-case impact of attack scenarios of interest while identifying reachable unstable states in the required time budget. This concept can be used to develop a tool to support DER control decisions under adverse conditions. Numerical tests are provided to validate the effectiveness of the attack reachability analysis.
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ItemData Privacy in the Smart Grid: A Decentralized Approach( 2019-01-08)
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ItemValidating the OPA Cascading Blackout Model on a 19402 Bus Transmission Network with Both Mesh and Tree Structures( 2019-01-08)The OPA model calculates the long-term risk of cascading blackouts by simulating cascading outages and the slow process of network upgrade in response to blackouts. We validate OPA on a detailed 19402 bus network model of the Western Electricity Coordinating Council (WECC) interconnection with publicly available data. To do this, we examine scalings on a series of WECC interconnection models with increasing detail. The most detailed, 19402 bus network has more tree structures at the edges of the main mesh structure, and we extend the OPA model to account for this. The higher-risk cascading outages are the large cascades that extend across interconnections, so validating cascading models on large networks is crucial to understanding how the real grid behaves. Finally, exploring networks with mixed mesh and tree like structure has implications for the risk analysis for both the transmission grid and other network infrastructures.
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ItemSpatially Aware Ensemble-Based Learning to Predict Weather-Related Outages in Transmission( 2019-01-08)This paper describes the implementation of prediction model for real-time assessment of weather related outages in the electric transmission system. The network data and historical outages are correlated with variety of weather sources in order to construct the knowledge extraction platform for accurate outage probability prediction. An extension of logistic regression prediction model that embeds the spatial configuration of the network was used for prediction. The results show that developed algorithm has very high accuracy and is able to differentiate the outage area from the rest of the network in 1 to 3 hours before the outage. The prediction algorithm is integrated inside weather testbed for real-time mapping of network outage probabilities using incoming weather forecast.
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ItemIntroduction to the Minitrack on Resilient Networks( 2019-01-08)