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At least 1,153 records · Page 64

Control of energy storage to reduce electric power system off-nominal frequency deviations

A hybrid power generation system is formed by the combination of an energy storage system (ESS) and a rotating synchronous power generator (SPG). Energy is stored in or released from the ESS in response to measurements of the at least one angle parameter, selected from rotor, torque, or power angle of the SPG, to provide active frequency damping of electrical power output. The control of ESS energy exchange increases the stabilizing impact of the SPG inertia on the frequency of electricity in an electrical network or power grid. The hybrid power generation system can have an effective equal area criterion for stability limit that is greater than that of the SPG operating without the ESS. The hybrid power generation system can enable the electrical network to have a greater proportion of variable or distributed energy resource (DER) power generation systems without otherwise exceeding stability limits.

Vartanian, Charles K.↗

Q-Learning-Based Impact Assessment of Propagating Extreme Weather on Distribution Grids

The increasing number of power outage events due to extreme weather conditions is hampering us socioeconomically. Preparing in advance for the extreme weather event is critical. It can help utility operators to reduce grid damages, restore grid service quickly, allocate energy resources and repair crews strategically, and hence dramatically increase grid resilience. In this paper, we propose a method to identify the sequence of worst impact zones in the power grid caused by extreme weather events based on Q-learning (a reinforcement learning algorithm). To quantity the weather severity and its effect on the grid, we model the impact of extreme weather on the grid as a function of intensity, vulnerability, and exposure. A modified IEEE 123-node distribution feeder is presented in a mesh grid and experimented for sequences of zones identification. Finally, simulation results present the identified sequences and their associated impacts on the grid caused by extreme weather events.

distribution system↗

Q-Learning Based Impact Assessment of Propagating Extreme Weather on Distribution Grids: Preprint

Increasing number of power outage events due to extreme weather condition is hampering us socioeconomically. Preparing in advance for the extreme weather event is critical and can help utility operators to reduce grid damages, restore grid service quickly, allocate energy resources and repair crews strategically, and hence dramatically increase grid resilience. In this paper, we propose a method to identify the sequence of worst impact zones in the power grid caused by extreme weather events based on Q-learning (a reinforcement learning algorithm). To quantify weather severity and it’s effect on the grid, we model the impact of extreme weather on the grid as a function of intensity, vulnerability and exposure. A modified IEEE 123-node distribution feeder is presented in a mesh grid and experimented for sequences of zones identification. Finally, simulation results present the identified sequences and their associated impacts on the grid caused by the extreme weather events.

distribution system↗

Quantum computing in power systems

Electric power systems provide the backbone of modern industrial societies. Enabling scalable grid analytics is the keystone to successfully operating large transmission and distribution systems. However, today's power systems are suffering from ever-increasing computational burdens in sustaining the expanding communities and deep integration of renewable energy resources, as well as managing huge volumes of data accordingly. These unprecedented challenges call for transformative analytics to support the resilient operations of power systems. Recently, the explosive growth of quantum computing techniques has ignited new hopes of revolutionizing power system computations. Quantum computing harnesses quantum mechanisms to solve traditionally intractable computational problems, which may lead to ultra-scalable and efficient power grid analytics. This paper reviews the newly emerging application of quantum computing techniques in power systems. We present a comprehensive overview of existing quantum-engineered power analytics from different operation perspectives, including static analysis, transient analysis, stochastic analysis, optimization, stability, and control. We thoroughly discuss the related quantum algorithms, their benefits and limitations, hardware implementations, and recommended practices. We also review the quantum networking techniques to ensure secure communication of power systems in the quantum era. Finally, we discuss challenges and future research directions. This paper will hopefully stimulate increasing attention to the development of quantum-engineered smart grids.

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Perturbation-Based Diagnosis of False Data Injection Attack Using Distributed Energy Resources

Modern smart grid relies on various sensor measurements for its operational control. In a successful false data injection attack, the attacker manipulates the measurements from the grid sensors such that undetected errors are introduced into the estimates of the system parameters leading to catastrophic situations. This paper proposes a novel perturbation based false data injection attack detection mechanism that utilizes inverter based distributed energy resources (DERs) to create low magnitude perturbation signal in the distribution system voltage that is inconsequential to the normal grid operation. Two voltage sensitivity analysis based algorithms are designed to identify the optimal set of DERs that can create the voltage perturbation signal of desired magnitude. An analytical method of voltage sensitivity analysis is used to compute the magnitude of voltage perturbation signal at each node in a computationally efficient manner. Then, a detection mechanism is developed that checks for the presence of the perturbation sequence in each sensor measurement. A sensor measurement is deemed authentic if the voltage perturbation signal is present in the data. In case of sensor malfunction or cyber-attack, the perturbation signal will not be present in the measurement data. Performance of the proposed attack detection mechanism is validated via simulation of the IEEE 69 bus test system.

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Event‐Based Training in Label‐Limited Regimes

Abstract The distribution of attributes assigned using data on independent sensors for a specific source, for example, magnitude, can be richly descriptive for final event characterization and associated uncertainty. Attribute distributions can also provide powerful context for event characterization in the absence of comprehensive annotation. This work develops a way to leverage distributional information across a set of sensors in the absence of comprehensive annotation as a domain‐informed regularization term applied during gradient‐based learning. The regularization term is the basis of event‐based training which I show can be a powerful semi‐supervised learning (SSL) approach. I first use a simple feed forward neural network and a toy data set to outline how data set structure interacts with the assumptions inherent to many semi‐supervised learning approaches. I then demonstrate the effectiveness of event‐based training using a deep convolutional neural network for seismic event classification in Utah, which increases SSL accuracy from 92% to 97% on event classification with a limited number of training labels.

Linville, Lisa M.↗

Evaluating the Impact of Off-Design CHP Performance on the Optimal Sizing and Dispatch on Hybrid Renewable-CHP Distributed Energy Resources

The maturation of distributed energy resources (DER) has prompted the exploration of their deployment in commercial building applications due to their potential to supply energy at lower costs and emissions rates compared to centralized generation. While several software tools exist for evaluating the techno-economic potential of integrated renewable energy and combined heat and power (CHP) systems for distributed generation applications, many suffer from poor accuracy in capturing off-design (part load and changes in ambient air temperature and pressure) performance characteristics of microturbines, combustion turbines, or internal combustion engines. Thus, this paper presents a methodology for integrating these off-design characteristics in the mixed-integer linear program within REopt, a hybrid DER screening tool. The economic impact of the CHP off-design performance is observed through several application studies of various hybrid system configurations in different climates. Each study indicates how CHP off-design performance influences optimal sizing and dispatch decisions and therefore overall system economic value. We observe through case studies that modeling without the off-design effects, depending on the CHP prime mover and site, can result in Net Present Value predictions of hybrid systems that can be overoptimistic in frequently hot climates (up to 52%), too conservative in frequently cold climates (up to 11%), or unaffected (+/-1%) in temperate climates. Cases also highlight several advantages of hybrid systems relative to non-hybrid systems such as total economic value and the systems' ability to mitigate potentially negative consequences attributed to off-design performance.

ambient de-rate↗

Optimal Distribution System Voltage Regulation using State Estimation and DER Grid-Support Functions

Increasing solar energy penetrations may create challenges for distribution system operations because production variability can lead to large voltage deviations or protection system miscoordination. Instituting advanced management systems on distribution systems is one promising method for combating these challenges by intelligently controlling distribution assets to regulate voltage and ensure protection safety margins. While it is generally not the case today, greater deployment of power system sensors and interoperable distributed energy resources (DER)e.g., photovoltaic (PV) inverters, energy storage systems (ESS), electric vehicles (EVs)will enable situational awareness, control, and optimization of distribution systems. In this work, a control system was created which measures power system parameters to estimate the status of a feeder, forecasts the distribution state over a short-term horizon, and issues optimal set point commands to distribution-connected equipment to regulate voltage and protect the system. This two-year project integrated multiple research innovations into a management system designed to safely allow PV penetrations of 50% or greater. The integrated software was demonstrated through extensive real-time (RT) and power hardware-in-the-loop studies and a field demonstration on a live power system with a 684 kVA PV system.

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Stability Impact of IEEE 1547 Operational Mode Changes Under High DER Penetration in the Presence of Cyber Adversary

The IEEE 1547 standard addresses the integration of Distributed Energy Resources (DER) into Area Electric Power Systems (AEPS). The updated standard, released in 2018 with revisions ongoing, specifies the need for more flexible settings, requiring the DER to remain connected during certain disturbances and provide voltage support via active and reactive power modes. With these increased capabilities comes increased risks, and our analysis of the standard has produced potential settings combinations, which, while allowable under the standard, may actually create instability. This contradicts the main purpose of the revised standard. Since the DER must support a communication interface through which the AEPS operator can change settings, adversarial mode changes are possible via a cyberattack. This concern is heightened as DER penetration increases, where under a reasonable threat model, an attacker could affect multiple DER simultaneously. We have conducted a simulation analysis of potentially adverse combinations of mode change and ridethrough parameters on a hypothetical AEPS with varying degrees of DER penetration. We conclude that certain adverse mode changes, whether through error or cyberattack, can lead to unstable conditions with DER penetrations as low as 24% of the AEPS system capacity.

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Evaluating the Risk of Enabling Energy Storage Systems to Provide Multiple Services

Battery energy storage systems (BESS) are emerging as a promising, versatile technology for modern power grids due to their inherent distributed nature, their ability to inject bidirectional power flows and to provide multiple grid services. With the proliferation of intermittent renewable energy resources, the BESS procurement is also expected to increase, thereby creating systematic and strategic opportunities for BESS to various revenue streams for providing multiple grid services. Utilizing a co-simulation architecture, this work presents evaluation framework for enabling Utility-scale BESS with simultaneous provision of multiple services. The proposed framework is implemented on a real-life feeder modeled in GridLAB-D, leveraging multi-service grid support. A Risk-Aware control strategy is also implemented in this work that that takes into account the uncertain nature of some of the stochastic services and ensures the BESS to deliver their service commitments. This promotes overall grid reliability and encourages BESS implementation through the revenue streams from providing multiple grid services.

Theisen, John↗

Guide to Developing Energy Services Interfaces

This document provides guidance to develop communications interfaces that are highly interoperable and adhere to a set of energy services interface (ESI) principles. It can be applied in the context of information and communications technology interface standards and implementation profiles that enable the integration of a facility with responsive distributed energy resources (DER) into an electric power system consistent with the fundamental ESI principles. In this context, a DER facility may consist of a single DER with a communicating controller or may be as complex as a microgrid campus with several buildings and many DERs. This document is not a technical interface standard, but the requirements described can be used to check that existing, augmented, or new interface standards meet the interoperability requirements of the ESI concept. In this way, this guide for the ESI specification can support future advancements in developing interoperability standards and implementation profiles. The intended audience for this document is DER integration practitioners and ecosystem groups that are in the business of developing and implementing communications interfaces for DER integration. It is intended that these groups apply the information and processes in this document to develop communications standards and implementation profiles that are consistent with fundamental ESI principles.

2030.5↗

Megawatt-Class, High-Voltage SiC Power Electronics Converters for Advanced Manufacturing with Grid Support Services

DE-EE0009135 aimed to push the 10kV SiC MOSFET based power electronics to 3-phase 13.8kV 10MW to be used as a Megawatt Class Medium-Voltage Power Conditioning Systems – PCS – to enable “Resilient Distribution through Grid-dispatching and Uninterrupted Quality Power to Manufacturing Facilities” during transitory grid disturbances. As a stretch to those goals, Eaton added the load power peak shaving opportunity.

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FLISR in the Presence of DERs ADMS Test Bed Use Case

Fault location, isolation, and restoration (FLISR) is one of the distribution automation applications that utilities are most interested in. It operates groups of switches on distribution feeders to improve the reliability of power delivery after localizing outages. FLISR is an essential function for enabling a self-healing grid, and it directly affects grid reliability and resilience. The presence of DERs brings both new opportunities and challenges for FLISR applications. For instance, some DERs can work as backup generation sources and help energize local networks so more switching options can be achieved with the coordination of FLISR operations; however, the existence of DERs also brings new challenges. The bidirectional power flow resulting from DERs might require dynamic changes to protective devices' fault current settings, and thus the FLISR application will need to dynamically adjust its operations in coordination with the dynamic protection settings. Also, some FLISR applications make their service restoration decisions and close tie-switches based on predefined rules; however, the presence of DERs and their impact on altering net loads on the local feeder network are not considered. For this use case, the project team is using the FLISR application of the Survalent ADMS operating on a real-time simulation of a feeder from Central Georgia EMC, a cooperative electric utility. The performance of the FLISR application is being evaluated for different locations and combinations of DERs, including grid-forming battery energy storage systems.

ADMS↗

Novel artificial neural network model for instantaneous power losses and operational efficiency mapping of MW-scale vanadium redox flow battery for improved technoeconomic analysis

A novel data-driven, machine-learning-based method for modeling the instantaneous power losses of a distribution-sited 2 MW/8MWh vanadium redox flow battery (VRFB), a grid-scale electrochemical storage technology, is introduced and compared against benchmark empirical modeling approaches, including symmetric and asymmetric models, as well as a recent convex hull modeling approach. The novel loss modeling method introduces several advantages over the benchmark models and over simplistic efficiency estimates, the most significant of which is that the model can accurately reflect the stepwise and non-linear parasitic losses associated with the duty cycles of mechanical auxiliary systems like pump motor drives and blower fans. Residuals of the models are compared; the proposed data driven model features significantly improved accuracy over the benchmark models. The model's coefficient of determination is also improved relative to that of the benchmark models. Furthermore, a novel method for visualization of operational efficiency of the grid-scale storage technology is introduced. To demonstrate the benefits of the novel data-driven method for modeling the VRFB, the benchmark models and the proposed models are embedded into an Open DSS distribution network model to study two applications of the grid-scale electrical storage system: load leveling for grid support and energy arbitrage. This article demonstrates that the accuracy of the instantaneous power loss model significantly impacts the understanding of the state of charge of the VRFB. In turn, the accuracy of the efficiency modeling of the VRFB impacts the understanding of the potential economic value and technical benefits to the distribution network operators. In conclusion, the presented power loss modeling approach is, therefore, highly relevant for utility-stakeholders, battery asset owners, system engineers, system designers, and financial planners interested in evaluating or optimizing the operation of grid-scale VRFBs.

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Model-Free Dynamic Voltage Control of Distributed Energy Resource (DER)-Based Microgrids

In this paper, we present a new control technique for sustaining dynamic voltage stability by effective reactive power control and coordination of distributed energy resources (DERs) in microgrids. The proposed control technique is based on model-free control (MFC), which has shown successful operation and improved performance in different domains and applications. This paper presents its first use in the voltage stability of a microgrid setting employing multiple synchronous generator (SG)-based and power electronic (PE)-based DERs. MFC is a computationally efficient, data-driven control technique that does not require modelling of the different components and disturbances in the power system. It is utilized as an online controller to achieve the dynamic voltage stability of a microgrid system under different disturbances and fault conditions. A 21-bus microgrid system fed by multiple DERs is considered as a case study and the overall dynamic voltage stability is investigated using time-domain dynamic simulations. Numerical results show that the proposed MFC provides improvements on the dynamic load bus voltage profiles and requires less computational time as compared to the traditional enhanced microgrid voltage stabilizer (EMGVS) scheme. Due to its simplicity and low computational requirement, MFC can be easily implemented in resource-constrained computing devices such as smart inverters.

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Voltage Optimization

Voltage optimization refers to a volt-var optimization technique which was originally designed to minimize energy consumption and improve end-use efficiency on the distribution system. This reduces source voltage at a substation, which lowers generation demand, reduces system losses, and improves system stability. This has been the conventional implementation of voltage optimization: focusing on regulation of voltages throughout the distribution system via coordinated adjustments of load tap changers, line-voltage regulators, switched shunt compensation, and the targeted placement of new shunt compensation. These methods have received increased focus following a growth in distributed-energy resources (DERs) interconnecting at the distribution level, given their developing capability to participate in voltage regulation. This is paired with the intermittency challenges they pose, load imbalances, and voltage fluctuations. Voltage optimization has long been an area of extensive research within the distribution system, with various strategies and philosophies demonstrating a range of effects. The conventional focus on the distribution system owes to the typical operation of transmission systems, which assumes firm local resources and flows strictly from generation resources to loads. The strategies employed in distribution have also been optimized for this typically radial configuration and operation of the distribution system.

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Citadels Final Report (GMLC 2.2.1: Citadels)

This is the final project report for the Grid Modernization Laboratory Consortium (GMLC) Resilient Distribution System (RDS) Citadels project. The primary goal of this GMLC project was to increase the operational flexibly of power systems by engaging microgrids distributedly, coordinated using consensus algorithms. The primary goal was successfully achieved. The primary goal was divided into three areas: Implement peer-to-peer control between microgrid controllers using the Open Field Message Bus (OpenFMB) approach; Develop and implement consensus algorithms on commercially available hardware that allows a group of microgrids to distributedly implement operational controls; Develop the architectures and controls to enable groups of microgrids to coordinate their operations to support the bulk power system during abnormal events, and end-use loads in the event the bulk power systems fail.

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State Estimation-Based Distributed Energy Resource Optimization for Distribution Voltage Regulation in Telemetry-Sparse Environments Using a Real-Time Digital Twin

Real-time state estimation using a digital twin can overcome the lack of in-field measurements inside an electric feeder to optimize grid services provided by distributed energy resources (DERs). Optimal reactive power control of DERs can be used to mitigate distribution system voltage violations caused by increased penetrations of photovoltaic (PV) systems. In this work, a new technology called the Programmable Distribution Resource Open Management Optimization System (ProDROMOS) issued optimized DER reactive power setpoints based-on results from a particle swarm optimization (PSO) algorithm wrapped around OpenDSS time-series feeder simulations. This paper demonstrates the use of the ProDROMOS in a RT simulated environment using a power hardware-in-the-loop PV inverter and in a field demonstration, using a 678 kW PV system in Grafton (MA, USA). The primary contribution of the work is demonstrating a RT digital twin effectively provides state estimation pseudo-measurements that can be used to optimize DER operations for distribution voltage regulation.

Darbali-Zamora, Rachid↗