Diagnostic Applications for Micro-Synchrophasor Measurements

This report articulates and justifies the preliminary selection of diagnostic applications for data from micro-synchrophasors (µPMUs) in electric power distribution systems that will be further studied and developed within the scope of the three-year ARPA-e award titled Micro-synchrophasors for Distribution Systems

Modeling and Detecting False Data Injection Attacks against Railway Traction Power Systems

Modern urban railways extensively use computerized sensing and control technologies to achieve safe, reliable, and well-timed operations. However, the use of these technologies may provide a convenient leverage to cyber-attackers who have bypassed the air gaps and aim at causing safety incidents and service disruptions. In this paper, we study false data injection (FDI) attacks against railways' traction power systems (TPSes). Specifically, we analyze two types of FDI attacks on the train-borne voltage, current, and position sensor measurements - which we call efficiency attack and safety attack -- that (i) maximize the system's total power consumption and (ii) mislead trains' local voltages to exceed given safety-critical thresholds, respectively. To counteract, we develop a global attack detection (GAD) system that serializes a bad data detector and a novel secondary attack detector designed based on unique TPS characteristics. With intact position data of trains, our detection system can effectively detect the FDI attacks on trains' voltage and current measurements even if the attacker has full and accurate knowledge of the TPS, attack detection, and real-time system state. In particular, the GAD system features an adaptive mechanism that ensures low false positive and negative rates in detecting the attacks under noisy system measurements. Extensive simulations driven by realistic running profiles of trains verify that a TPS setup is vulnerable to the FDI attacks, but these attacks can be detected effectively by the proposed GAD while ensuring a low false positive rate.Comment: IEEE/IFIP DSN-2016 and ACM Trans. on Cyber-Physical System

Distribution System State Estimation in the Presence of High Solar Penetration

Low-to-medium voltage distribution networks are experiencing rising levels of distributed energy resources, including renewable generation, along with improved sensing, communication, and automation infrastructure. As such, state estimation methods for distribution systems are becoming increasingly relevant as a means to enable better control strategies that can both leverage the benefits and mitigate the risks associated with high penetration of variable and uncertain distributed generation resources. The primary challenges of this problem include modeling complexities (nonlinear, non-convex power-flow equations), limited availability of sensor measurements, and high penetration of uncertain renewable generation. This paper formulates the distribution system state estimation as a nonlinear, weighted, least squares problem, based on sensor measurements as well as forecast data (both load and generation). We investigate the sensitivity of state estimator accuracy to (load/generation) forecast uncertainties, sensor accuracy, and sensor coverage levels.Comment: accepted for presentation at the IEEE 2019 American Control Conferenc

An Integrated Voltage Optimization Approach For Industrial Loads

Although Voltage Varying (VV) strategies like Conservation Voltage Reduction (CVR) are widely used by utilities to reduce the overall energy consumption and peak power demand of distribution feeders, it is aberrant among industrial customers. This research proposes a Voltage Varying (VV) strategy for industrial customers that takes into account their complex characteristics and unique set of constraints. Unlike VV strategies for Local Distribution Companies (LDC), those for an industrial customers are far more complex, and require specific c load modelling and process estimation to infer the optimal operating voltage for the industrial load. The proposed VV technique referred to as Voltage Optimization (VO), is a generic and comprehensive framework that seeks to reduce the energy consumption of the industrial load vis-~a-vis the bus voltage. It utilizes a Neural Network (NN) model of the industrial load, trained using historical operating data, to estimate the real power consumption of the load, based on the bus voltage and overall plant process. This load model, is incorporated into the proposed VO model, whose objective is the minimization of the energy drawn from the substation and the switching operations of Load Tap Changers (LTC). The proposed VO framework is tested on load models developed using simulated and real data. Results suggest that the proposed technique can be successfully implemented by industrial customers or plant operators to improve their energy savings, in comparison to existing VV techniques

Development of novel electrical power distribution system state estimation and meter placement algorithms suitable for parallel processing

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe increasing penetration of distributed generation, responsive loads and emerging smart metering technologies will continue the transformation of distribution systems from passive to active network conditions. In such active networks, State Estimation (SE) tools will be essential in order to enable extensive monitoring and enhanced control technologies. In future distribution management systems, the novel electrical power distribution system SE requires development in a scalable manner in order to accommodate small to massive size networks, be operable with limited real time measurements and a restricted time frame. Furthermore, a significant phase of new sensor deployment is inevitable to enable distribution system SE, since present-day distribution networks lack the required level of measurement and instrumentation. In the above context, the research presented in this thesis investigates five SE optimization solution methods with various case studies related to expected scenarios of future distribution networks to determine their suitability. Hachtel's Augmented Matrix method is proposed and developed as potential SE optimizer for distribution systems due to its potential performance characteristics with regard to accuracy and convergence. Differential Evolution Algorithm (DEA) and Overlapping Zone Approach (OZA) are investigated to achieve scalability of SE tools; followed by which the network division based OZA is proposed and developed. An OZA requiring additional measurements is also proposed to provide a feasible solution for voltage estimation at a reduced computation cost. Realising the requirement of additional measurements deployment to enable distribution system SE, the development of a novel meter placement algorithm that provides economical and feasible solutions is demonstrated. The algorithm is strongly focused on reducing the voltage estimation errors and is capable of reducing the error below desired threshold with limited measurements. The scalable SE solution and meter placement algorithm are applied on a multi-processor system in order to examine effective reduction of computation time. Significant improvement in computation time is observed in both cases by dividing the problem into smaller segments. However, it is important to note that enhanced network division reduces computation time further at the cost of accuracy of estimation. Different networks including both idealised (16, 77, 356 and 711 node UKGDS) and real (40 and 43 node EG) distribution network data are used as appropriate to the requirement of the applications throughout this thesis.‘High Performance Computing Technologies for Smart Distribution Network Operation' (HiPerDNO) project under Grant FP7 - 248135/2007-2013 (European Community's Seventh Framework Programme)

Optimal Sizing of Voltage Control Devices for Distribution Circuit with Intermittent Load

We consider joint control of a switchable capacitor and a D-STATCOM for voltage regulation in a distribution circuit with intermittent load. The control problem is formulated as a two-timescale optimal power flow problem with chance constraints, which minimizes power loss while limiting the probability of voltage violations due to fast changes in load. The control problem forms the basis of an optimization problem which determines the sizes of the control devices by minimizing sum of the expected power loss cost and the capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments on a circuit with high-performance computing (HPC) load show that the proposed sizing and control schemes significantly improve the reliability of voltage regulation on the expense of only a moderate increase in cost.Comment: 10 pages, 7 figures, submitted to HICSS'1

Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: a review

YesDistributed generators (DGs) are a reliable solution to supply economic and reliable electricity to customers. It is the last stage in delivery of electric power which can be defined as an electric power source connected directly to the distribution network or on the customer site. It is necessary to allocate DGs optimally (size, placement and the type) to obtain commercial, technical, environmental and regulatory advantages of power systems. In this context, a comprehensive literature review of uncertainty modeling methods used for modeling uncertain parameters related to renewable DGs as well as methodologies used for the planning and operation of DGs integration into distribution network.This work was supported in part by the SITARA project funded by the British Council and the Department for Business, Innovation and Skills, UK and in part by the University of Bradford, UK under the CCIP grant 66052/000000

Optimization Techniques for the Developing Distribution System

The most rapidly changing part of today’s power grid is the distribution system. Many new technologies have emerged that revolutionize the way utilities provide, and now sometimes receive, power to and from their customers. To an extent, the push for de-regulation of utilities has also led to an increased focus on reliability and efficiency. These changes make design and operation of power systems more complex causing utilities to question if they are operating optimally. Operations Research (OR) is an area of mathematics where quantitative analysis is used to provide a basis for complex decision making. The changing landscape in electric distribution makes it a prime candidate for the application of OR techniques. This research seeks to develop optimization methods that can be applied to any distribution feeder or group of feeders that allows for optimal decisions to be made in a reasonable time frame. Two specific applications identified in this thesis are optimal reconfiguration during outage situations and optimal location of Battery Energy Storage Systems (BESS). Response to outages has traditionally relied on human-in-the-loop approaches where a dispatcher or a crew working the field decides what switching operations are needed to isolate affected parts of the system and restore power to healthy ones. This approach is time consuming and under-utilizes the benefits provided by widely-adopted, remotely-controlled switching technologies. Chapters Two and Three of this thesis develop a partitioning method for determining the switching operations required to optimize the amount of load that is restored during an event. Most people would agree that renewable forms of Distributed Generation (DG) provide great benefits to the power industry, especially through reduced impact on the environment. The variable nature of renewables, however, can cause many issues for operation and control of a utilities’ system, especially for distribution interconnections. Storage technologies are thought to be the primary solution to these issues with much research focused on sizing and control of BESSs. Equally important for integration, but often overlooked, is the location at which the device is connected. Chapter Four explores this idea by drawing conclusions about optimal BESS location based on well-studied ideas of optimal capacitor location