Review of Challenges and Research Opportunities for Control of Transmission Grids
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24 POWER TRANSMISSION AND DISTRIBUTION↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Extended Frequency Divider for Bus Frequency Estimation Considering Virtual Inertia from DFIGs
Accurate estimation of local bus frequency is important for effectively controlling both synchronous and nonsynchronous generators. As the power grid evolves to accommodate essential reliability services such as virtual inertia from nonsynchronous generators, conventional techniques to estimate frequency face challenges. This paper proposes a new frequency estimation method that can effectively include the inertia contributions from double-fed wind generators (DFIGs). This is achieved through the proposed extended frequency divider formula (FDF) to include the contributions of DFIGs via Thevenin equivalents. The proposed extended FDF does not suffer from numerical issues as compared to existing phasor angle derivative-based approaches. Moreover, the knowledge of the rotor speeds of the synchronous machine and DFIGs as well as of the network admittance matrix allows estimating the frequencies of all buses in the grid, thereby significantly improving system situational awareness with a limited number of measurements. Numerical results on the IEEE 39-bus power system with DFIGs show that the proposed method achieves more accurate bus frequency estimations than the original FDF formula and other approaches based on the numerical derivation of the bus voltage phase angles.
double-fed induction generator↗
Blackstart Capability and Survivability of Wind Turbines with Fully Rated Converters
We report the blackstart capability of wind turbines is critical for the recovery of wind-dominant power systems from blackouts. If wind power plants are not able to restore a power system, the incorporation of wind resources into electric grids could be limited by blackstart capability. This paper tackles this problem by setting forth a grid-forming controller for Type 4 wind turbines which employ fully rated power converters. To this end, we engineer two-axis anti-windup proportional-integral regulators that serve to ride through restoration disturbances. We also design an active protection system to prevent wind turbines from stalling during recovery from blackouts. We demonstrate in a high-fidelity simulation environment that Type 4 wind turbines with the developed controllers and protection subsystem can: (i) re-energize a notional wind-dominant grid; (ii) ride through asymmetrical faults; and (iii) survive low wind speed events.
17 WIND ENERGY↗
Opportunities for Price Manipulation by Aggregators in Electricity Markets
Aggregators of distributed generation are playing an increasingly crucial role in the integration of renewable energy in power systems. However, the intermittent nature of renewable generation makes market interactions of aggregators difficult to monitor and regulate, raising concerns about potential market manipulation by aggregators. In this paper, we study this issue by quantifying the profit an aggregator can obtain through strategic curtailment of generation in an electricity market. We show that, while the problem of maximizing the benefit from curtailment is hard in general, efficient algorithms exist when the topology of the network is radial (acyclic). Further, we highlight that significant increases in profit are possible via strategic curtailment in practical settings.
Azizan Ruhi, Navid (ORCID:0000000242992963)↗
Machine Learning-based Intrusion Detection for Smart Grid Computing: A Survey
Machine learning (ML)-based intrusion detection system (IDS) approaches have been significantly applied and advanced the state-of-the-art system security and defense mechanisms. In smart grid computing environments, security threats have been significantly increased as shared networks are commonly used, along with the associated vulnerabilities. However, compared to other network environments, ML-based IDS research in a smart grid is relatively unexplored, although the smart grid environment is facing serious security threats due to its unique environmental vulnerabilities. In this article, we conducted an extensive survey on ML-based IDS in smart grids based on the following key aspects: (1) The applications of the ML-based IDS in transmission and distribution side power components of a smart power grid by addressing its security vulnerabilities; (2) dataset generation process and its usage in applying ML-based IDSs in the smart grid; (3) a wide range of ML-based IDSs used by the surveyed papers in the smart grid environment; (4) metrics, complexity analysis, and evaluation testbeds of the IDSs applied in the smart grid; and (5) lessons learned, insights, and future research directions.
SCADA↗
Pyroelectric Energy Scavenging Techniques for Self-Powered Nuclear Reactor Wireless Sensor Networks
Recent advances in technologies for harvesting waste thermal energy from ambient environments present an opportunity to implement truly wireless sensor nodes in nuclear power plants. These sensors could continue to operate during extended station blackouts and during periods when operation of the plant s internal power distribution system has been disrupted. The energy required to power the wireless sensors must be generated using energy harvesting techniques from locally available energy sources, and the energy consumption within the sensor circuitry must therefore be low to minimize power and hence the size requirements of the energy harvester. Harvesting electrical energy from thermal energy sources can be achieved using pyroelectric or thermoelectric conversion techniques. Recent modeling and experimental studies have shown that pyroelectric techniques can be cost competitive with thermoelectrics in self powered wireless sensor applications and, using new temperature cycling techniques, has the potential to be several times as efficient as thermoelectrics under comparable operating conditions. The development of a new thermal energy harvester concept, based on temperature cycled pyroelectric thermal-to-electrical energy conversion, is outlined. This paper outlines the modeling of cantilever and pyroelectric structures and single element devices that demonstrate the potential of this technology for the development of high efficiency thermal-to-electrical energy conversion devices.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Fragility Functions Resource Report: Documented Sources for Electricity and Water Resilience Valuation
Fragility curves provide the vulnerability between hazard intensity and an asset. Federal installations may include many different electricity and water infrastructure types (or assets) such as generators, wind turbines, solar PV, switch yards, substations and power lines as well as water distribution systems that could be affected by different hazards. The vulnerability of each asset is a function of its age, type of materials and maintenance. In addition, the vulnerability changes with the hazards intensity and has a probability distribution function associated with it. The fragility functions are used in conjunction with hazard probability and consequence valuations to determine the values at risk for examination of investment grade analyses of alternative mitigation strategies. This document provides examples of fragility functions and links to their sources for different electricity and water infrastructure assets by hazard type.
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Micro-Transfer Printing of Repeaters on Passive Interposer
Silicon-based sensors are central to particle physics experiments and particle tracking detectors. New-generation Large Focal Plane Arrays (LFPAs) cover areas that extend beyond several square meters. Distributing power and transporting data across such areas while maintaining good signal integrity is a complicated challenge. Tiling the detector on an organic interposer would be far too expensive and take too much space while offering little to no advantage regarding signal integrity. Passive silicon interposers are much less expensive and more integrable but would worsen signal integrity because of their inherent higher dielectric constant. Active interposers are a good compromise from the economic and signal integrity standpoint; unfortunately, their yield trends to zero for areas greater than a reticle size, making this technology incompatible with our application. NHanced proposes to duplicate the behavior of a high-yield, low-cost active interposer by printing active microcomponents on a passive interposer with our die-to-wafer micro-transfer printing (MTP) technology. This resolves the signal integrity and power distribution limitations. In Phase I, we designed and simulated analog and digital repeaters to be MTPed onto a passive silicon interposer test wafer.
2.5D↗
Options Impacting the Electric System of the Future (ESF); NREL (National Renewable Energy Laboratory)
As utilities are faced with adapting to new technologies, technology and policy due diligence are necessary to ensure the development of a future grid that brings greater value to utilities and their consumers. This presentation explores the different kinds of future directions the power industry could consider to create, discussing key components necessary for success. It will also discuss the practical application and possible strategies for utilities and innovators to implement smart technologies that will enable an ultimate ‘intelligent’ grid capable of two-way communication, interoperability, and greater efficiency and system resiliency.
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SMART-DS: Synthetic Models for Advanced, Realistic Testing: Distribution Systems and Scenarios
This presentation provides a Smart-DS project overview and status update for the ARPA-e GRID DATA program meeting 2017, including distribution systems, models, and scenarios, as well as opportunities for GRID DATA collaborations.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Energy Transition and Reliability Challenges in Modern Power Grids
This presentation provides an overview of energy transition and reliability challenges in modern electric power grids.
24 POWER TRANSMISSION AND DISTRIBUTION↗
DATA-DRIVEN ALGORITHMS FOR DISTRIBUTION SYSTEM OPERATION AND CONTROL
Transactive energy systems are an alternative solution for the problems that distribution system operators face due to an increase in the use of distributed energy resources(DERs) and resulting much required scalability in managing active distribution system. To meet the reliability, sustainability and security requirement, ecient management and control of DERs including distributed generators, energy storage systems, and demand response is necessary. DERs can provide services such as reactive power compensation, voltage control, energy balancing, peak load reduction. These edge resources can also be used for system restoration after the extreme events within regulatory bound and enabling resiliency of the electric grid. While there are numbers of related work focused on solving these problems, availability of additional data resources has not been utilized to its potential to enable the reliable, sustainable and resilient electric grid. In order to address these challenges, data-driven algorithms have been proposed in this dissertation, including a) Volt/Var control, b) activity aware demand response and c) estimation of behind the meter distributed energy resources. Results indicate satisfactory performance of the developed algorithms.
ZHANG, YUE↗
Finite-time correlations boost large voltage angle fluctuations in electric power grids
Abstract Decarbonization in the energy sector has been accompanied by an increased penetration of new renewable energy sources in electric power systems. Such sources differ from traditional productions in that, first, they induce larger, undispatchable fluctuations in power generation and second, they lack inertia. Recent measurements have indeed reported long, non-Gaussian tails in the distribution of local voltage frequency data. Large frequency deviations may induce grid instabilities, leading in worst-case scenarios to cascading failures and large-scale blackouts. In this article, we investigate how correlated noise disturbances, characterized by the cumulants of their distribution, propagate through meshed, high-voltage power grids. For a single source of fluctuations, we show that long noise correlation times boost non-Gaussian voltage angle fluctuations so that they propagate similarly to Gaussian fluctuations over the entire network. However, they vanish faster, over short distances if the noise fluctuates rapidly. We furthermore demonstrate that a Berry–Esseen theorem leads to the vanishing of non-Gaussianities as the number of uncorrelated noise sources increases. Our predictions are corroborated by numerical simulations on realistic models of power grids.
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Optimization-Based Deconfliction of Distribution System Applications
Power distribution systems are transitioning towards a future with large numbers of controllable grid-edge devices and distributed generation, as well as more complex operational objectives. This evolution requires a new distribution management approach, and modular applications can play a significant role. Thus, new strategies to coordinate independent applications with diverging operational goals are necessary. In this paper, we propose a novel optimization-based deconflictor to facilitate coordination in future advanced distribution management systems.
application deconfliction, power system optimizati↗
Synthetic data generation for machine learning model training for energy theft scenarios using cosimulation
Abstract Technical and non‐technical losses in distribution circuits result in significant economic costs to power utilities. One type of non‐technical loss is energy theft by various means including illegal tapping of feeders, bypassing the meter, and billing fraud. These losses are usually hard to detect, and can remain undetected for long periods of time. Machine learning models have been proven effective in detecting these conditions, but rely on the availability of large, good‐quality training data sets. The problem is exacerbated by the imbalanced nature of data related to these conditions—energy theft, though costly, is very rare. The available data sets generally have very few samples of theft with most of the data pertaining to normal operation. Such data sets are generally not suitable to train machine learning models. In this paper, an overview of energy theft detection techniques, the challenges with their data needs, and the limitations of current techniques to bridge such data limitations is presented. A co‐simulation framework is proposed to generate reliable training data for machine learning algorithms for theft detection. An example scenario is presented and a machine learning model is built to detect certain kinds of energy theft.
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A Real-Time Testbed for Smart Inverter Cyber Security Studies
Distributed energy resources (DER) have become a popular solution to modern-day issues surrounding the efficiency and reliability of power generation, as well as climate change concerns. Energy centers are shifting towards incorporating smart inverters with embedded functionalities such as high voltage ride through (HVRT), low voltage ride through (LVRT), active and reactive power compensation. However, the integration of smart inverters leave DER systems highly vulnerable to cybersecurity threats. The distributed network protocol 3 (DNP3) is a common method of communication between grid-tied hardware. Despite its popularity, the level of security leaves all hardware connected to the grid at risk of severe cyber-attacks. Thus, it is important to study any potential cybersecurity threats towards grid-tied smart inverters to mitigate cybersecurity vulnerabilities and refine existing cyber-security protections. This report describes the proposed testbed design to study cybersecurity threats to smart inverters. The testbed utilizes a real-time simulation case in RSCAD that includes a grid-tied wind turbine (WT) topology featuring two back-to-back two-level voltage source converters (BTB,2L-VSCs) and a permanent magnet synchronous machine (PMSM). The simulated case runs within the NovaCor real time digital simulator (RTDS). This report focuses on the design and implementation of a single module of the GTNETx2 card as a distributed network protocol and the configuration of an IEEE 1518 DNP database file that includes input and output variables mapped to different connection points in the grid that transmit and receive discrete, analog, and binary signals on command. This allows realistic emulation of the communication between the smart inverter and the grid for cybersecurity studies.
97 MATHEMATICS AND COMPUTING↗
Toward a subhourly net zero energy district design through integrated building and distribution system modeling
A modeling framework integrating both building energy modeling and power system modeling is introduced for the design of net zero energy (NZE) districts for the simultaneous selection of both demand-side efficiency measures and supply-side generation technologies. A novel district control scheme is proposed for pursuing NZE on a subhourly basis while mitigating potential grid impacts such as power backfeeding and voltage violations. As a case study, Pena Station NEXT, a new 100-building, mixed-use district on a 1200-node distribution feeder in Denver, Colorado, is modeled in the integrated framework. An exhaustive scenario analysis is conducted for sizing the district's distributed energy resources, considering multiple objectives such as capital cost, net energy import, and equipment violations. Here, when trying to achieve annual NZE, the district incurs frequent operating violations, and achieving NZE on a 15-min basis is also limited by seasonal fluctuations in photovoltaic output, illustrating the need for diverse generation or seasonal storage. As a practical compromise, both annual and 15-min district import can be reduced by ~78% without significant violations.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Implementation of Parallel Dynamic Simulation on Shared-Memory vs. Distributed-Memory Environments
Power system dynamic simulation computes the system response to a sequence of large disturbance, such as sudden changes in generation or load, or a network short circuit followed by protective branch switching operation. It consists of a large set of differential and algebraic equations, which is computational intensive and challenging to solve using single-processor based dynamic simulation solution. High-performance computing (HPC) based parallel computing is a very promising technology to speed up the computation and facilitate the simulation process. This paper presents two different parallel implementations of power grid dynamic simulation using Open Multi-processing (OpenMP) on shared-memory platform, and Message Passing Interface (MPI) on distributed-memory clusters, respectively. The difference of the parallel simulation algorithms and architectures of the two HPC technologies are illustrated, and their performances for running parallel dynamic simulation are compared and demonstrated.
dynamic simulation↗