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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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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Mitigating Voltage Instability in the Saudi Grid for a Decarbonized, Fully Solar Power System

Lately, solar photovoltaic (PV) has received significant interest due to its economic and environmental benefits. As the integration of renewable energy sources (RES) increases into existing power grids, challenges such as the decrease in short circuit ratio (SCR) are introduced. Here, this paper investigates a case study of the Saudi power grid, examining the voltage stability as the grid transitions from traditional power generation to 100% penetration of solar PV gradually. Moreover, the paper explores the relationship between the increase in solar penetration and the potential effects on the short circuit MVA (SCMVA), which could significantly impact the overall SCR of the system. To meet the North American Electric Reliability Corporation (NERC) recommendation of maintaining SCR at a particular level, synchronous condensers (SC)s were integrated into the grid. The effectiveness of utilizing SCs to maintain the system voltage at optimal levels in a fully solar grid is also considered. In addition, this paper covers the weak grid analysis via utilizing the Newton-Raphson load flow method, along with PV and QV curve analyses. The purpose behind that is to determine weak bus locations in need of voltage improvements, and to meet the amount of reactive power to be injected. Finally, the amount of power being delivered by SCs will be added progressively in three scenarios to show the enhancements on SCR more precisely.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Probabilistic Voltage Sensitivity based Preemptive Voltage Monitoring in Unbalanced Distribution Networks

With increasing penetration of renewable energy and active consumers, control and management of power distribution networks has become challenging. Renewable energy sources can cause random voltage fluctuations as their output power depends on weather conditions. Conventional voltage control schemes such as tap changers and capacitor banks lack the foresight required to quickly alleviate voltage violations. Thus, there is an urgent need for effective approaches for predicting and mitigating voltage violations as a result of random fluctuations in power injections. This work proposes a novel voltage monitoring approach based on low-complexity, data-driven probabilistic voltage sensitivity analysis. The usefulness of this work is not only in predicting voltage violations in unbalanced distribution grids, but also in opening up the door for optimal voltage control. Using system data and forecasts, the proposed approach predicts the distribution of system node voltages which is then used to to identify nodes that may violate the nominal operational limits with high probability. The method is tested on the IEEE 37 node distribution system considering integrated distributed solar energy sources. The method is validated against the classic load flow based method and offers over 95% accuracy in predicting voltage violations.

Abujubbeh, Mohammad↗
DOE OSTI2018

Network Reduction Algorithm for Developing Distribution Feeders for Real-Time Simulators

As advanced grid-support functions (AGF) become more widely used in grid-connected photovoltaic (PV) inverters, utilities are increasingly interested in their impacts when implemented in the field. These effects can be understood by modeling feeders in real-time simulators and test PV inverters using power hardware-in-the-loop (PHIL) techniques. This paper presents a novel feeder model reduction algorithm using a ruin & reconstruct methodology that enables large feeders to be solved and operated on real-time computing platforms. Two Hawaiian Electric feeder models in Synergi Electric's load flow software were converted to reduced order models in OpenDSS, and subsequently implemented in the OPAL-RT real-time digital testing platform. Smart PV inverters were added to the realtime model with AGF responses modeled after characterizing commercially available hardware inverters. Finally, hardware inverters were tested in conjunction with the real-time model using PHIL techniques so that the effects of AGFs on the feeders could be analyzed.

14 SOLAR ENERGY↗
DOE OSTI2020

Impacts of Ternary-Pumped Storage Hydropower on U.S. Western Interconenction with Extremely High Renewable Penetrations

In recent years, ternary pumped storage hydropower (T-PSH), as one of the advanced PSH technologies, has attracted more attention from the industry. The interest is because of the capability of providing fast power support for the future electric grid with high penetration of renewable energy (RE). This paper focuses on studying the impact of T-PSH on frequency response of the U.S. Western Interconnection under different penetration levels of RE, which are from 20% to 80%. The detailed model of T-PSH is developed and implemented in the Western Interconnection grid model based on the GE Positive Sequence Load Flow (PSLF) platform, which can capture the unique dynamics of hydraulic short-circuit (HSC) mode and fast mode switching of T-PSH. To reveal the dynamic benefit from T-PSH, the frequency response of the Western Interconnection has been compared with and without T-PSH. In addition, a new solution is discussed that uses T-PSH to improve system stability issues caused by high RE penetration.

13 HYDRO ENERGY↗
DOE OSTI2020

Dynamic Modeling of Full Converter Adjustable-speed Pumped Storage Hydropower (FC AS-PSH)

Full converter adjustable-speed pumped storage hydropower (FC AS-PSH) technology, as one of advanced-PSH technology, is developed from wind turbine technology. By making the synchronous machine connect to the grid through a full-size converter, FC AS-PSH has a wider adjustment range of speed and a better reactive power control capability compared with a doubly-fed asynchronous generator AS-PSH technology. When it plays as an energy backup in the power system, FC AS-PSH can provide a much faster response than conventional-PSH (C-PSH) which makes this technology provide better ancillary service for a high renewable penetrated system. In this paper, the dynamic modeling of FC AS-PSH is fully studied. We develop a detailed model of this technology in the IEEE 14-bus system based on GE Positive Sequence Load Flow (PSLF) platform. Especially, the first governor model is developed based on the Engineer’s Program Control Language (EPCL) user-defined model in this platform. All operation modes are validated and studied under a system contingency. Besides, comparison cases between FC AS-PSH and C-PSH are studied to show advantages providing from FC AS-PSH when it works with renewable energy.

50 EE - Wind and Water Power Program - Water (EE-4↗
DOE OSTI2020

Analytical Voltage Sensitivity Analysis for Unbalanced Power Distribution System

Large scale integration of distributed energy resources and electric vehicles in a transactive energy environment present new challenges in terms of voltage stability and fluctuations in a power distribution system. The impact of different level of DER/EV penetration on the voltages across the network is typically quantified through voltage sensitivity analyses. Existing methods of voltage sensitivity analysis are computationally expensive and prior efforts to develop analytical approximation lacks generality and have not been effectively validated. The objective of this work is to provide a new analytical method of voltage sensitivity analysis that has low computational cost and also allows for stochastic analysis of voltage change. This paper first derives an analytical approximation of change in voltage at a particular bus due to change in power consumption at other bus in a radial three phase unbalanced power distribution system. Then, the proposed method is shown to be valid for different load configurations, which demonstrates its generality. The results from our analytical approach is validated via classical load flow simulation of the test system based on IEEE 37 bus network. The proposed method is shown to have good accuracy, and computation complexity is of order O(1), compared to O(n3) in classical sensitivity analysis approaches.

Munikoti, Sai↗
DOE OSTI2022

Impact of Quaternary Pumped Storage Hydropower on Frequency Response of U.S. Western Interconnection with High Renewable Penetrations

As renewable penetration increases in the United States, maintaining stability and reliability of low-inertia power grid by providing sufficient frequency control capability becomes a challenge. Advanced pumped storage hydro technologies (APSH) will be expected to play an important role for future grid as not only an energy supplier, but also as an ancillary services provider. This paper studies the impact of using quaternary pumped storage hydropower (Q-PSH), as one of the newly proposed APSH technology, to provide primary frequency response. To quantify the impact of Q-PSH on frequency response of the U.S. Western Interconnection, a user-defined dynamic model of Q-PSH is developed on the GE Positive Sequence Load Flow (PSLF) platform and is implemented in a set of detailed U.S. Western Electricity Coordination Council (WECC) planning cases in which renewable penetration levels are 20%, 40%, 60% and 80%. Simulation results show that Q-PSH can help improve frequency nadir and settling frequency comparing to the conventional PSH.

frequency response↗
DOE OSTI2018

Monte Carlo-Based Method for Parallelizing Quasi-Static Time-Series Power System Simulations: Preprint

Both commercial and open source power system simulators run quasi-static time-series (QSTS) simulations sequentially. For yearlong high-resolution load profiles this sequential execution of load flows incurs long computation times. Parallelizing QSTS simulations on multiple processors is one possible way to reduce the computation time. Parallelization however introduces errors in the simulation results as the initial state of the system at the beginning of each parallelized time period is not known. In this work a Monte Carlo-based approach has been proposed to estimate the initial state of the system for each parallel simulation run to mitigate the errors in the final results. Classical sequential QSTS simulation is the chosen base case against which all other methods have been compared. Results presented in this paper show that the proposed method improves the simulation results considerably. This paper also discusses possible sensitivities of the proposed method to a number of tunable parameters. Additionally, sensitivity analysis results for a number of parameters have also been presented in the results section.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

A Data-Driven Approach to Dynamic Var Compensator Placement for Local Voltage Stabilization on Feeders with High PV Penetration

Distribution feeders with a high penetration of distributed photovoltaic (PV) systems can experience voltage variability caused by the changing load flow injections corresponding to the availability of the solar resource. The rapid, uncontrolled voltage range fluctuations can affect the system. Tap-changing voltage regulators, switched capacitors, and smart inverter functions have been used to stabilize voltage. However, in some cases, when these options are insufficient or unavailable, dedicated reactive power control devices such as dynamic var compensators (DVCs) can be used for local voltage stabilization. This paper introduces a statistical framework to characterize voltage variability and stabilization, proposes a data-driven approach to DVC placement, and presents the results of a planning study on a real feeder using real data.

Reiman, Andrew P.↗
DOE OSTI2018

Chance-constrained Service Restoration for Distribution Networks with Renewables

Power systems operation is facing great challenges from natural disasters and cyber-attacks. It is critical but also difficult to enhance the reliability and resilience against extreme events. To better response to inevitable outages or blackouts, service restoration in distribution networks is important to minimize the disastrous impacts of catastrophic events. The increasing penetration of distributed energy resources (DERs) provides new opportunities to expedite the restoration process. However, the coordination with conventional distribution system control devices and the uncertainty and variability of intermittent renewable energy resources requires new operation and control strategies for distribution service restoration (DSR). This paper develops an optimal bottom-up DSR strategy by coordinating DERs with voltage regulators and capacitor banks. The chance-constrained (CC) programming approach is used to model the probabilistic output limit of solar radiation and PV generation. The Markov's inequality and Latin hypercube sampling techniques are applied to convert and incorporate the chance constraints into the DSR optimization problem. The CC-DSR problem is formulated as a mixed integer convex programming problem, considering various operational cost functions and bidirectional three-phase unbalanced load flow. Simulation results on the modified IEEE 13-node test feeder system demonstrate the effectiveness and flexibility of the bottom-up DSR strategy.

Chance constrained optimization, Distribution serv↗
DOE OSTI2018

Variable Time-Step Implementation for Rapid Quasi-Static Time-Series (QSTS) Simulations of Distributed PV

Distribution system analysis with high penetrations of distributed PV require quasi-static time-series (QSTS) analysis to model the variability introduced on the distribution system, but current QSTS algorithms are prohibitively burdensome and computationally intensive. This paper proposes a variable timestep algorithm to calculate the critical time periods when QSTS simulations should be solved at higher or lower time-resolution and to backtrack for any critical periods that were missed. This variable time-step solver is a new method of performing timeseries simulations with high accuracy while performing the simulation more than 50 times faster. The scalability of the algorithm is demonstrated using a real utility distribution system model with thousands of buses.

14 SOLAR ENERGY↗
DOE OSTI2025

Using Artificial Intelligence to Improve Reliability and Operational Efficiency of Small-Scale Hydroelectric Distributed Generation

Reliability and resilience are critical concerns for distributed generation (DG) at the rural electric level. The integration of renewable energy sources, such as small-scale hydroelectric distributed generators (hydro DGs), introduces operational challenges, particularly regarding aging infrastructure and grid stability. Artificial Intelligence (AI)-driven Machine Learning (ML) models and applications of Large Language Models (LLMs) offer promising solutions for optimizing DG operations and enhancing resilience. This paper explores AI-based models for improving efficiency, fault resolution, and outage mitigation in small-scale hydro DGs. Furthermore, it highlights the development of a centralized, AI-powered information portal for rural electric cooperatives and municipalities. The research evaluates hydro DG plant models and discusses the applicability of AI-powered question-answering tools for real-time operations, focusing on statistical data, load flow, voltage regulation, and generation power. The findings demonstrate AI’s potential to transform DG management to ensure greater stability and resilience in rural electric grids.

Bhattacharyya, Arjun [ORNL] (ORCID:000900060976046↗
DOE OSTI2020

Integration Study of Converter-Interfaced Combined Heat and Power Plants

Combined Heat and Power (CHP) systems, as a proven technology, provide numerous benefits to the plant owner by saving electricity bill, reducing carbon dioxide emissions, and improving electricity service reliability. However, their integration into the distribution grid faces many barriers including the complexity of grid code requirements and the lack of technical expertise in commercial and small industrial plants to interface with the utility and accelerate the interconnection process. To solve these issues, this study proposes a converter-interfaced solution for CHP integration. Simulations including various fault scenarios and load flow under different grid conditions are carried out to compare technical performances of the proposed solution with directly-coupled CHP. Results show that the generator size of converter-interfaced CHP can be reduced by approximately 25% and it also provides advantageous features such as reduced stress level under fault conditions and a better dynamic stability margin. In addition, a power factor controller is designed and reactive power from CHP is dispatched in such a way that the CHP plant is compliant with power factor requirements from utilities under all operating conditions.

Converter, Combined heat and power, Distributed en↗
DOE OSTI2020

Voltage positioning using co-optimization of controllable grid assets in radial networks

With increasing penetration of solar PV, some distribution feeders are experiencing highly variable net-load flows and even reverse flows. To optimize distribution systems under such conditions, the scheduling of mechanical devices, such as OLTCs and capacitor banks, needs to take into account forecasted solar PV and actual grid conditions. However, these legacy switching assets are operated on a daily or hourly timescale, due to the wear and tear associated with mechanical switching, which makes them unsuitable for real-time control. Therefore, there is a natural timescale- separation between these slower mechanical assets and the responsive nature of inverter-based resources. In this paper, we present a network admissible convex formulation for holistically scheduling controllable grid assets to position voltage optimally against solar PV. An optimal hourly schedule is presented that utilizes mechanical resources to position the predicted voltages close to nominal values, while minimizing the use of inverter-based resources (i.e., DERs), making them available for control at a faster time-scale (after the uncertainty reveals itself). A convex, inner approximation of the OPF problem is adapted to a mixed-integer linear program that minimizes voltage deviations from nominal (i.e., maximizes voltage margins). Here, the resulting OPF solution respects all the network constraints and is, hence, robust against modeling simplifications. Simulation based analysis on IEEE distribution feeders validates the approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Decentralized Low-Rank State Estimation for Power Distribution Systems

This article considers the low-observability state estimation problem in power distribution networks and develops a decentralized state estimation algorithm leveraging the matrix completion methodology. Matrix completion has been shown to be an effective technique in state estimation that exploits the low dimensionality of the power system measurements to recover missing information. This technique can utilize an approximate (linear) load flow model, or it can be used with no physical models in a network where no information about the topology or line admittance is available. The direct application of matrix completion algorithms requires solving a semi-definite programming (SDP) problem, which becomes computationally challenging for large networks. We therefore develop a decentralized algorithm that capitalizes on the popular proximal alternating direction method of multipliers (proximal ADMM). The method allows us to distribute the computation among different areas of the network, leading to a scalable algorithm. By doing all computations at individual control areas and only communicating with neighboring areas, the algorithm eliminates the need for data to be sent to a central processing unit and thus increases efficiency and contributes to the goal of autonomous control of distribution networks. We illustrate the advantages of the proposed algorithm numerically using standard IEEE test cases.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2020

Developing of Quaternary Pumped Storage Hydropower for Dynamic Studies

Quaternary pumped storage hydropower (Q-PSH) technology, as one of the new advanced-PSH technology, has been developed by taking advantage of Conventional-PSH (C-PSH) and Adjustable Speed-PSH (AS-PSH). By combining adjustable-speed pump unit and conventional hydropower turbine unit in the quaternary configuration, Q-PSH has the more competitive capability of providing fast power support in the future high renewable penetrated power system. Acting as energy storage (ES), Q-PSH provides promising power supply to deal with the uncertainty and variability from renewable energy generation. This paper focuses on the dynamic modeling of Q-PSH technology employing full-converter machine and the impact of Q-PSH on the frequency response in a system. The detailed model of Q-PSH is developed and implemented in the IEEE 14-bus system based on GE Positive Sequence Load Flow (PSLF) platform, which captures the dynamic of multiple operation modes, especially hydraulic short-circuit (HSC) operation mode. Several cases are set up to reveal the advantages of Q-PSH technology when power electronic based renewable energy generation is deployed in the system. Sensitivity studies of the controller in pump governor show the impact of parameters in pump response performance. The comparison case illustrates the impact of frequency response provided by the Q-PSH in the system.

dynamic modeling↗
DOE OSTI2022

Master State Distributed Estimator (masde)

The MSE technology provides a distributed state estimation scheme for power utilities by making it a real time dynamic system, versus the static snapshot method used today. This will allow utilities to verify power grid readings and identify false data on the communication network. The prevailing method of estimation takes all the data from the system into a single load flow equation at the utilities command center. This becomes a large algorithm that is very time consuming to solve, providing the engineers only snap shots of the system. The MFD distributes an algorithm to devises that are already installed at various locations on the power grid. This allows for much faster computer times because the algorithms contain magnitudes less data. When each distributed estimator completes its calculation, it sends the results back to the master device to check against all other distributed estimators.

Reen, DylanW.↗