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At least 1,315 records · Page 73

All sources NASA NTRS DOE OSTI

DOE OSTI2011

Towards a Scalable and Reliable Real Time In-Network Data Analysis Infrastructure

The smart grid applications requires real time analysis, response within the order of milliseconds and high-reliability because of the mission critical structure of the power grid system. The only way to satisfy these requirements is in network data analysis and build-in redundancy routing for failures. To achieve this, we propose a data dissemination system that builds routes using network flow algorithms, have in network processing of the data and utilize data encoding to cope with high latencies.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

PowerNet: Multi-agent Deep Reinforcement Learning for Scalable Powergrid Control

This paper develops an efficient multi-agent deep reinforcement learning algorithm for cooperative controls in powergrids. Specifically, we consider the decentralized inverter-based secondary voltage control problem in distributed generators (DGs), which is first formulated as a cooperative multi-agent reinforcement learning (MARL) problem. We then propose a novel on-policy MARL algorithm, PowerNet, in which each agent (DG) learns a control policy based on (sub-)global reward but local states and encoded communication messages from its neighbors. Motivated by the fact that a local control from one agent has limited impact on agents distant from it, we exploit a novel spatial discount factor to reduce the effect from remote agents, to expedite the training process and improve scalability. Furthermore, a differentiable, learning-based communication protocol is employed to foster the collaborations among neighboring agents. In addition, to mitigate the effects of system uncertainty and random noise introduced during on-policy learning, we utilize an action smoothing factor to stabilize the policy execution. To facilitate training and evaluation, we develop PGSim, an efficient, high-fidelity powergrid simulation platform. Here, experimental results in two microgrid setups show that the developed PowerNet outperforms the conventional model-based control method, as well as several state-of-the-art MARL algorithms. The decentralized learning scheme and high sample efficiency also make it viable to large-scale power grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2014

Frequency Regulation and Oscillation Damping Contributions of Variable-Speed Wind Generators in the U.S. Eastern Interconnection (EI)

The U.S. Eastern Interconnection (EI) is one of the largest electric power grids in the world and is expected to have difficulties in dealing with frequency regulation and oscillation damping issues caused by the increasing wind power. On the other side, variable-speed wind generators can actively engage in frequency regulation or oscillation damping with supplementary control loops. This paper creates a 5% wind power penetration simulation scenario based on the 16 000-bus EI system dynamic model and developed the user-defined wind electrical control model in PSS (R) E that incorporates additional frequency regulation and oscillation damping control loops. We evaluated the potential contributions of variable-speed wind generations to the EI system frequency regulation and oscillation damping, and simulation results demonstrate that current and future penetrations of wind power are promising in the EI system frequency regulation and oscillation damping.

17 WIND ENERGY↗

DOE OSTI2017

Electric Power Generation from Low to Intermediate Temperature Resourcces

The UND-CLR Binary Geothermal Power Plant was a collaborative effort of the U.S. Department of Energy (DOE), Continental Resources, Inc. (CRL), Slope Electric Cooperative (SEC), Access Energy, LLC (AE), Basin Electric Cooperative (BEC), Olson Construction, the North Dakota Industrial Commission Renewable Energy Council (NDIC-REC), the North Dakota Department of Commerce Centers of Excellence Program (NDDC-COE), and the University of North Dakota (UND). The primary objective of project was to demonstrate/test the technical and economic feasibility of generating electricity from non-conventional, low-temperature (90 ºC to 150 °C) geothermal resources using binary technology. CLR provided the access to 98 ºC water flowing at 51 l s-1 at the Davis Water Injection Plan in Bowman County, ND. Funding for the project was from DOE –GTO, NDIC-REC, NDD-COE, and BEC. Logistics, on-site construction, and power grid access were facilitated by Slope Electric Cooperative and Olson Construction. Access Energy supplied prototype organic Rankine Cycle engines for the project. The potential power output from this project is 250 kW at a cost of $3,400 per kW. A key factor in the economics of this project is a significant advance in binary power technology by Access Energy, LLC. Other commercially available ORC engines have efficiencies 8 to 10 percent and produce 50 to 250 kW per unit. The AE ORC units are designed to generate 125 kW with efficiencies up to 14 percent and they can be installed in arrays of tens of units to produce several MW of power where geothermal waters are available. This demonstration project is small but the potential for large-scale development in deeper, hotter formations is promising. The UND team’s analysis of the entire Williston Basin using data on porosity, formation thicknesses, and fluid temperatures reveals that 4.0 x 1019 Joules of energy is available and that 1.36 x 109 MWh of power could be produced using ORC binary power plants. Much of the infrastructure necessary to develop extensive geothermal power in the Williston Basin exists as abandoned oil and gas wells. Re-completing wells for water production could provide local power throughout the basin thus reducing power loss through transmission over long distances. Water production in normal oil and gas operations is relatively low by design, but it could be one to two orders of magnitude greater in wells completed and pumped for water production. A promising method for geothermal power production recognized in this project is drilling horizontal open-hole wells in the permeable carbonate aquifers. Horizontal drilling in the aquifers increases borehole exposure to the resource and consequently increases the capacity for fluid production by up to an order of magnitude.

15 GEOTHERMAL ENERGY↗

DOE OSTI2013

Ames Lab 101: Reinventing the Power Cable

Ames Laboratory researchers are working to develop new electrical power cables that are stronger and lighter than the cables currently used in the nation's power grid. Nano Tube animation by Iain Goodyear

36 MATERIALS SCIENCE↗

DOE OSTI2026

Enhancing Synchronous Condenser Operation of Hydrogenerators

Hydropower plants are sometimes dispatched below capacity or even shut down to meet water regulations. These can temporarily be repurposed to operate as synchronous condensers. To enable this capability, this paper proposes a design that allows hydrogenerators to safely operate as synchronous condensers, providing fast voltage and reactive power support under both normal and boost conditions. The proposed design integrates capability curves with hydrogenerators’ excitation systems through modifications using proposed MVA-field current curve, current controller, and limiter. The design is implemented locally at the machine for rapid response. Simulation results demonstrate the effectiveness of the proposed design and using hydrogenerators as synchronous condensers in power grids.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Security and Cloud Outsourcing Framework for Economic Dispatch

The computational complexity and problem sizes of power grid applications have increased significantly with the advent of renewable resources and smart grid technologies. The current paradigm of solving these issues consist of inhouse high performance computing infrastructures, which have drawbacks of high capital expenditures, maintenance, and limited scalability. Cloud computing is an ideal alternative due to its powerful computational capacity, rapid scalability, and high cost-effectiveness. A major challenge, however, remains in that the highly confidential grid data is susceptible for potential cyberattacks when outsourced to the cloud. In this work, a security and cloud outsourcing framework is developed for the Economic Dispatch (ED) linear programming application. As a result, the security framework transforms the ED linear program into a confidentiality-preserving linear program, that masks both the data and problem structure, thus enabling secure outsourcing to the cloud. Results show that for large grid test cases the performance gain and costs outperforms the in-house infrastructure.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Nonlinear multiobjective and dynamic real-time predictive optimization for optimal operation of baseload power plants under variable renewable energy

Considering the increase of disruptive variable renewable energy penetration into the power grid, this article focuses on the investigation of a multiobjective and dynamic real-time optimization framework to address the cycling of large-scale power plants under renewable penetration. In this framework, a parallelized particle swarm optimization step is first performed to generate feasible initial points. Then, a multiobjective and dynamic real-time optimization formulation generates optimal trajectories. Further, the benefit of predictive capability is investigated for the dynamic component, which introduces the novel nonlinear multiobjective and dynamic real-time predictive optimization approach. Two multiobjective formulations to obtain Pareto front optimal in real time are explored: the modified Tchebycheff-based weighted metric and ϵ-constraint methods. Economic and environmental objectives are considered in this study. A novel topical discussion on the intersection of dynamic real-time optimization with model predictive control is also presented. The developed framework is successfully applied to a baseload coal-fired power plant with postcombustion CO 2 capture. Results indicate that the approach can be deployed for a large-scale system if automatic differentiation, model reduction, and parallelization are adopted to improve computational tractability, with computational improvement up to 120-folds after performing these steps. Finally, market and carbon policies showed an impact on the optimal compromise between the objectives with an additional 63 ton of CO 2 captured under favorable market conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

Transmission system protection screening for integration of offshore wind power plants

This paper develops an efficient methodology for protection screening of large-scale transmission systems as part of the planning studies for the integration of offshore wind power plants into the power grid. This methodology avails to determine whether any upgrades are required to the protection system. The uncertainty is considered in form of variability of the power generation by offshore wind power plant. This paper uses the integration of a 1000 MW offshore wind power plant operating in Lake Erie into the FirstEnergy/PJM service territory as a case study. This study uses a realistic model of a 63,000-bus test system that represents the U.S. Eastern Interconnection.

17 WIND ENERGY↗

DOE OSTI2023

Distributed Software-Defined Network Architecture for Smart Grid Resilience to Denial-of-Service Attacks

An important challenge for smart grid security is designing a secure and robust smart grid communications architecture to protect against cyber-threats, such as Denial-of-Service (DoS) attacks, that can adversely impact the operation of the power grid. Researchers have proposed using Software Defined Network frameworks to enhance cybersecurity of the smart grid, but there is a lack of benchmarking and comparative analyses among the many techniques. In this work, a distributed three-controller software-defined networking (D3-SDN) architecture, benchmarking, and comparative analysis with other techniques is presented. The selected distributed flat SDN architecture divides the network horizontally into multiple areas or clusters, where each cluster is handled by a single Open Network Operating System (ONOS) controller. A case study using the IEEE 118-bus system is provided to compare the performance of the presented ONOS-managed D3-SDN, against the POX controller. In addition, the proposed architecture outperforms a single SDN controller framework by a tenfold increase in throughput; a reduction in latency of > 20%; and an increase in throughput of approximately 11% during the DoS attack scenarios.

Agnew Jr., Dennis↗

DOE OSTI2025

PowerModel-AI: A First On-the-Fly Machine-Learning Predictor for AC Power Flow Solutions

The real-time creation of machine-learning models via active or on-the-fly learning has attracted considerable interest across various scientific and engineering disciplines. These algorithms enable machines to build models autonomously while remaining operational. Through a series of query strategies, the machine can evaluate whether newly encountered data fall outside the scope of the existing training set. In this study, we introduce PowerModel-AI, an end-to-end machine learning software designed to accurately predict AC power flow solutions. We present detailed justifications for our model design choices and demonstrate that selecting the right input features effectively captures load flow decoupling inherent in power flow equations. Our approach incorporates on-the-fly learning, where power flow calculations are initiated only when the machine detects a need to improve the dataset in regions where the model’s suboptimal performance is based on specific criteria. Otherwise, the existing model is used for power flow predictions. This study includes analyses of five Texas A&M synthetic power grid cases, encompassing the 14-, 30-, 37-, 200-, and 500-bus systems. The training and test datasets were generated using PowerModels.jl, an open-source power flow solver/optimizer developed at Los Alamos National Laboratory, NM, USA.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Coordination of thermostatically controlled loads

Apparatus and methods for a market-based control framework to coordinate a group of autonomous thermostatically controlled loads (TCL) to achieve system-level objectives with pricing incentives is disclosed. In one example of the disclosed technology, a method of providing power to a load via a power grid by submitting bids to a coordinator includes determining an energy response relating price data for one or more energy prices to quantity data for power to be consumed by the load, sending a bid for power for a finite time period based on the energy response to the coordinator, and receiving a clearing price based on: the bid, on bids received from a plurality of additional loads, and a feeder power constraint. In some examples, the energy response is based at least in part on an equivalent thermal parameter model and a control policy indicating one or more power states for the load.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Coordination of thermostatically controlled loads

Lian, Jianming↗

DOE OSTI2023

WEC-GRID

WEC-GRID is an open-source Python library crafted to simulate the integration of Wave Energy Converters (WECs) and Current Energy Converters (CECs) into renowned power grid simulators like PSS®E & PyPSA.

Barajas-Ritchie, Alexander↗

DOE OSTI2024

Early Exploration of a Flexible Framework for Efficient Quantum Linear Solvers in Power Systems

The rapid integration of renewable energy resources presents formidable challenges in managing power grids. While advanced computing and machine learning techniques offer some solutions for accelerating grid modeling and simulation, there remain complex problems that classical computers cannot effectively address. Quantum computing, a promising technology, has the potential to fundamentally transform how we manage power systems, especially in scenarios with a higher proportion of renewable energy sources. One critical aspect is solving linear systems of equations, crucial for power system applications like power flow analysis, for which the Harrow-Hassidim-Lloyd (HHL) algorithm is a well-known quantum solution. However, HHL quantum circuits often exhibit excessive depth, making them impractical for current Noisy-Intermediate-Scale-Quantum (NISQ) devices. In this paper, we introduce a versatile framework, powered by NWQSim, that bridges the gap between power system applications and quantum linear solvers available in Qiskit. This framework empowers researchers to efficiently explore power system applications using quantum linear solvers. Through innovative gate fusion strategies, reduced circuit depth, and GPU acceleration, our simulator significantly enhances resource efficiency. Power flow case studies have demonstrated up to a eight-fold speedup compared to Qiskit Aer, all while maintaining comparable levels of accuracy.

quantum computing, Harrow-Hassidim-Lloyd, high-per↗

DOE OSTI2017

Adaptive RAS/SPS System Settings for Improving Grid Reliability and Asset Utilization through Predictive Simulation and Controls

Remedial Action Schemes (RAS) or Special Protection Schemes (SPS) are used throughout the bulk transmission system as a non-wires method of increasing transmission transfer capability. However, as the population grows within the Western Interconnection, more power needs to be transferred with less ability to build lines. This leads to a greater number of RAS, and the subsequent interaction between these disparate schemes can have unintended consequences. While the large number of RAS within the Western Electricity Coordinating Council (WECC) protect for different things, which can range from the violation of thermal limitations to transient stability issues, they can be described by common methods of operation. In order to understand these methods, a survey was sent out to members of the WECC Modeling & Validation Working Group (MVWG). The response received provides a necessary base in which to understand and build models that can be used within WECC. This report provides information on the survey results regarding RAS/SPS modeling practices for planning and operational studies within the WECC footprint, which is foundational for on-going and future work on RAS. Pacific Northwest National Laboratory (PNNL) and its industry partners are developing innovative methods for adaptively setting RAS parameters based on realistic and near real-time operational conditions to improve power grid reliability and grid asset utilization.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Safe and Private Forward-trading Platform for Transactive Microgrids

Power grids are evolving at an unprecedented pace due to the rapid growth of distributed energy resources (DER) in communities. These resources are very different from traditional power sources, as they are located closer to loads and thus can significantly reduce transmission losses and carbon emissions. However, their intermittent and variable nature often results in spikes in the overall demand on distribution system operators (DSO). To manage these challenges, there has been a surge of interest in building decentralized control schemes, where a pool of DERs combined with energy storage devices can exchange energy locally to smooth fluctuations in net demand. Building a decentralized market for transactive microgrids is challenging, because even though a decentralized system provides resilience, it also must satisfy requirements such as privacy, efficiency, safety, and security, which are often in conflict with each other. As such, existing implementations of decentralized markets often focus on resilience and safety but compromise on privacy. In this article, we describe our platform, called TRANSAX, which enables participants to trade in an energy futures market, which improves efficiency by finding feasible matches for energy trades, enabling DSOs to plan their energy needs better. TRANSAX provides privacy to participants by anonymizing their trading activity using a distributed mixing service, while also enforcing constraints that limit trading activity based on safety requirements, such as keeping planned energy flow below line capacity. We show that TRANSAX can satisfy the seemingly conflicting requirements of efficiency, safety, and privacy. We also provide an analysis of how much trading efficiency is lost. Trading efficiency is improved through the problem formulation, which accounts for temporal flexibility, and system efficiency is improved using a hybrid-solver architecture. Lastly, we describe a testbed to run experiments and demonstrate its performance using simulation results.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Hydroclimate-coupled framework for assessing power system resilience under summer drought and climate change

Extreme drought, exacerbated by climate change, increasingly threatens power system resilience, and a systematic assessment of such impacts is challenging due to the unpredictability of drought and their associated modeling complexity. Here, to address the challenge, this research develops a hydroclimate-coupled power system resilience assessment framework that enables systematic modeling of drought and climate change impacts on generation, transmission, and demand sectors. Applying the framework to the 2025 Eastern U.S. power grid — comprising 6,055 at-risk generators — under climate-induced summer drought scenarios (including SSP126, SSP245, SSP370, and SSP585) from 2023 to 2100, the study finds that climate-induced droughts could jeopardize the power system’s reliability to a greater extent than historical events, potentially leading to widespread load shedding. More specifically, the study reveals that under the twenty-one representative drought scenarios, the loss of load expectation (LOLE) of the grid could range from 34.77 to 91.48 days per summer. The simulations indicate that implementing resilience enhancement strategies is crucial to ensure reliable system operation, which encompasses initiatives such as demand response, upgrading open cooling systems, and transmission expansion. In all, these findings underscore the urgent need for proactive planning and investment in resilient U.S. power systems to mitigate the impacts of extreme drought events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗