Every Moment Counts: Synchrophasors for Distribution Networks with Variable Resources

Chapter 34 in the textbook, "Renewable Energy Integration: Practical Management of Variability, Uncertainty and Flexibility

Time-Synchronized Full System State Estimation Considering Practical Implementation Challenges

As phasor measurement units (PMUs) are usually placed on the highest voltage buses, many lower voltage levels of the bulk power system are not observed by them. This lack of visibility makes time-synchronized state estimation of the full system a challenging problem. We propose a Deep Neural network-based State Estimator (DeNSE) to overcome this problem. The DeNSE employs a Bayesian framework to indirectly combine inferences drawn from slow timescale but widespread supervisory control and data acquisition (SCADA) data with fast timescale but local PMU data to attain sub-second situational awareness of the entire system. The practical utility of the proposed approach is demonstrated by considering topology changes, non-Gaussian measurement noise, and bad data detection and correction. The results obtained using the IEEE 118-bus system show the superiority of the DeNSE over a purely SCADA state estimator, a SCADA-PMU hybrid state estimator, and a PMU-only linear state estimator from a techno-economic viability perspective. Lastly, the scalability of the DeNSE is proven by performing state estimation on a large and realistic 2000-bus Synthetic Texas system

Scenarios for the development of smart grids in the UK: literature review

Smart grids are expected to play a central role in any transition to a low-carbon energy future, and much research is currently underway on practically every area of smart grids. However, it is evident that even basic aspects such as theoretical and operational definitions, are yet to be agreed upon and be clearly defined. Some aspects (efficient management of supply, including intermittent supply, two-way communication between the producer and user of electricity, use of IT technology to respond to and manage demand, and ensuring safe and secure electricity distribution) are more commonly accepted than others (such as smart meters) in defining what comprises a smart grid. It is clear that smart grid developments enjoy political and financial support both at UK and EU levels, and from the majority of related industries. The reasons for this vary and include the hope that smart grids will facilitate the achievement of carbon reduction targets, create new employment opportunities, and reduce costs relevant to energy generation (fewer power stations) and distribution (fewer losses and better stability). However, smart grid development depends on additional factors, beyond the energy industry. These relate to issues of public acceptability of relevant technologies and associated risks (e.g. data safety, privacy, cyber security), pricing, competition, and regulation; implying the involvement of a wide range of players such as the industry, regulators and consumers. The above constitute a complex set of variables and actors, and interactions between them. In order to best explore ways of possible deployment of smart grids, the use of scenarios is most adequate, as they can incorporate several parameters and variables into a coherent storyline. Scenarios have been previously used in the context of smart grids, but have traditionally focused on factors such as economic growth or policy evolution. Important additional socio-technical aspects of smart grids emerge from the literature review in this report and therefore need to be incorporated in our scenarios. These can be grouped into four (interlinked) main categories: supply side aspects, demand side aspects, policy and regulation, and technical aspects.

Software Defined Networks based Smart Grid Communication: A Comprehensive Survey

The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. This article serves as a comprehensive survey on SDN-based SGC. In this article, we first discuss taxonomy of advantages of SDNbased SGC.We then discuss SDN-based SGC architectures, along with case studies. Our article provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.Comment: Accepte

Application of synchrophasor measurements for improving situational awareness of the power system

The paper focuses on the application of synchrophasor measurements that present unprecedented benefits compared to SCADA systems in order to facilitate the successful transformation of the Nordic-Baltic-and-European electric power system to operate with large amounts of renewable energy sources and improve situational awareness of the power system. The article describes new functionalities of visualisation tools to estimate a grid inertia level in real time with monitoring results between Nordic and Baltic power systems

Parallel detrended fluctuation analysis for fast event detection on massive PMU data

("(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.")Phasor measurement units (PMUs) are being rapidly deployed in power grids due to their high sampling rates and synchronized measurements. The devices high data reporting rates present major computational challenges in the requirement to process potentially massive volumes of data, in addition to new issues surrounding data storage. Fast algorithms capable of processing massive volumes of data are now required in the field of power systems. This paper presents a novel parallel detrended fluctuation analysis (PDFA) approach for fast event detection on massive volumes of PMU data, taking advantage of a cluster computing platform. The PDFA algorithm is evaluated using data from installed PMUs on the transmission system of Great Britain from the aspects of speedup, scalability, and accuracy. The speedup of the PDFA in computation is initially analyzed through Amdahl's Law. A revision to the law is then proposed, suggesting enhancements to its capability to analyze the performance gain in computation when parallelizing data intensive applications in a cluster computing environment

A Novel Approach for Security Analysis using Shift Factors for Limited Synchrophasor Observability

The adoption of synchrophasor technology has increased rapidly in the past decade. Many system operators have made synchrophasor applications available to operators, to reveal hidden operating conditions, and increase grid resiliency. The development of Linear State Estimation provided an innovative method to solve system states linearly at a faster rate, and serve as a backup to EMS should the conventional State Estimator fail to solve. Advanced applications were developed to take advantage of LSE solution to provide operators with alternative contingency analysis applications using synchrophasors data [6]. However, currently explored applications are presumed to run iteratively every couple of minutes, and therefore not taking advantage of high resolution of measurements available in synchrophasors. This work proposes a method to monitor system limits by leveraging linearization methods for contingency analysis, to better utilize the benefits of synchrophasors. Also, a practical approach is proposed to handle lack of full observability, to ensure tool operability with the industry infrastructure

Visualization And Mining Of Phasor Data From Optimally Placed Synchrophasors In A Smart-Grid

Synchrophasors, or also known as Phasor Measurement Units (PMUs), are the state- of-the-art measurement sensor that gather key sensor parameters such as voltage, frequency (f), current (i), and phase angle (ϕ) to monitor the state of an electric grid. The significant feature of a synchrophasor is in its ability to provide real-time streaming data from smart grid. The sampling rate of PMUs ranges from 30 samples to a maximum of 120 samples per second. With such large date-rate, the operations of the power-grid is known with high granularity. However, utilities face certain challenges with synchrophasor measurements. One of the common challenge with synchrophasor is the selection of location to place them in the grid. A synchrophasor placed on a bus is capable of measuring currents, voltages, phasor and frequency information on the entire transmission line incident to that bus. Furthermore, neighboring buses also become observable (i.e. adjacent bus voltage equations are solvable) using Ohm’s law, Kirchhoff’s Voltage Law (KVL) and Kirchhoff’s Current Law (KCL). Thus, it is not necessary to place PMUs on every single bus of the power-grid. Synchrophasors are expensive units and depending on vendor type, the number of measurement channels and features, the cost per unit can increase. There are several optimal solutions proposed to minimize the cost function to place the synchrophasors. Studies often ignored other metrics such as reliability, and security. This can jeopardize the reliability of the power-grid. Thus, this thesis work focus on a multi-objective problem that include reliability, cost, energy, and distance. This research proposes a criteria called as Optimal Redundancy Criterion (ORC) based on Linear Programming (LP) methods to find an optimal solution for the placement problem. Although, synchrophasors provide real-time information about the grid, the system operators need to identify, classify and analyze fault or anomalies in the power-grid. Such detection of the faults will improve the situational awareness of the power-grid. This research addresses such challenges by developing data mining algorithms for effective visualization and control of data. The secondary goal is accomplished by implementing a Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to IEEE test system and phasor data from openPDC framework. The scalability and decision making process for large scale utility test systems using DBSCAN is also investigated