Search NASA⌕ Search

SEARCH · Search NASA

Results for “Distributed Power Generation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22

Fairness-Aware Distributed Energy Coordination for Voltage Regulation in Power Distribution Systems

The accelerating deployment of solar photovoltaics into low-voltage distribution networks can cause reverse power flow and overvoltage problems. However, if coordinated properly, the real and reactive power flexibility of these resources enables distribution operators to manage their networks more efficiently. Existing literature is rich in droop-based control (Volt-Watt and Volt-VAr) and optimization-based distributed energy coordination for four-quadrant control of photovoltaics to prevent overvoltage issues. While optimal coordination can effectively mitigate overvoltage, it tends to treat resources at sensitive parts of the grid unfairly. Here, to address this concern, we propose a distributed optimal power flow formulation that incorporates fairness in curtailing photovoltaic generation and utilizes the reactive power capability of smart inverters. The proposed distributed formulation allows for scalable resource aggregation that can be leveraged to achieve fairness within a certain segment of the grid and/or fairness across the entire network. Fair curtailment of photovoltaic systems is demonstrated with aggregation at each of two layers in a distribution network: 1) area-level fairness and 2) feeder-level fairness. To explore the trade-off between fairness and optimal utilization, the fairness-aware control actions are compared against the performance of a centralized controller that aims to maximize the aggregate PV generation without incorporating fairness. Simulation results show that introducing area-level fairness increased curtailment by 0.0101 percentage points and feeder-level fairness increased curtailment by 0.0458 percentage points compared to a fairness-agnostic control.

Poudel, Shiva↗

A Hybrid-Learning Algorithm for Online Dynamic State Estimation in Multimachine Power Systems

With the increasing penetration of distributed generators in the smart grids, having knowledge of rapid real-time electromechanical dynamic states has become crucial to system stability control. Conventional Supervisory Control and Data Acquisition (SCADA)-based dynamic state estimation (DSE) techniques are limited by the slow sampling rates, while the emerging phasor measurement units (PMUs) technology enables rapid real-time measurements at network nodes. Using generator bus terminal voltages, we propose a hybrid-learning DSE (HL-DSE) algorithm to estimate the synchronous machine rotor angle and speed in real time. The HL-DSE takes the power system model into account and trains neuroestimators with real-time data in an online manner. Compared with traditional DSE methods, the HL-DSE overcomes limitations by using a data-driven approach in conjunction with the physical power system model. The time efficiency, accuracy, convergence, and robustness of the proposed algorithm are tested under noises and fault conditions in both small- and large-scale test systems. Simulation results show that the proposed HL-DSE is much more computationally efficient than widely used Kalman filter (KF)-based methods while maintaining comparable accuracy and robustness. In particular, HL-DSE is over 100 times faster than square-root unscented KF (SR-UKF) and 80 times faster than extended KF (EKF). The advantages and challenges of the HL-DSE are also discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Comparison of Probabilistic Forecasts for Predictive Voltage Control

This paper explores predictive cooperative voltage control in distribution systems with highly variable sources such as photovoltaics (PV). The goal is to maintain the voltage profile within the limits despite the fluctuations due to sudden changes in solar power generation. The predictive voltage control method relies on probabilistic solar power and load forecasts to select the optimum Voltage Regulator (VR) taps appropriately. VR taps are selected to minimize the risk of voltage violation. A modified version of the IEEE 123 system is used as the case study. A 100% penetration of solar power is assumed for the distribution system with profiles for solar generation and loads added to the system. Three different probabilistic forecast models (Quantile Regression (QR), Gaussian distribution and volatility forecasting using Generalized Autoregressive Conditional Heteroskedasticity (GARCH)) are explored in this study. The results for the VR taps and Voltage Deviation Index (VDI) are compared to find the most effective forecast model.

Panamtash, Hossein↗

Machine Learning Based Network Parameter Estimation Using AMI Data

The expansion of distribution power system and the growing penetration of distributed energy resources present new challenges for situational awareness. Calibrating the extended system model with sensor measurements and maintaining the usability is critical for utilities. This paper presents a distribution network parameter estimation (DNPE) approach using machine learning (ML) and metering data that improve the quality of extended distribution power system modeling. The reliability model can improve the ability of endpoint data to be translated into network-level situational awareness in real time and help distribution system operators (DSOs) solve branch flow and voltage problems. In addition, a data analytic and automate processing scheme is proposed to improve the sensor data quality and prevent misleading information. The effectiveness of the proposed method is verified with actual advanced metering infrastructure (AMI) data on a real utility feeder model, while considering the higher penetration of photovoltaic power generation. The test of DNPE and study results are demonstrated in this paper.

Parameter estimation, machine learning, power dist↗

Large eddy simulation of wind farm performance in horizontally and vertically staggered layouts

This numerical investigation employs Large Eddy Simulation (LES) coupled with Actuator Disk Model (ADM) to evaluate wind farm layout optimization strategies. The study presents a systematic analysis of aligned, horizontal staggering, vertical staggering, and mixed (combination of horizontal and vertical) staggering configurations, aiming to establish optimal design parameters for enhanced power production. The investigation examines key performance metrics including mean velocity distributions, turbulence intensity characteristics, and power generation efficiency. Results demonstrate better performance of both horizontal and vertical staggering patterns compared to conventional aligned configurations, with horizontal staggering exhibiting notably higher power output than vertical arrangements. Our findings also suggest that mixed configurations, incorporating both horizontal and vertical staggering, can offer optimal performance characteristics. As a result, this research advances the understanding of wake interactions in complex wind farm layouts and provides design guidelines for maximizing wind farm power generation efficiency through strategic turbine positioning.

17 WIND ENERGY↗

Utilizing grid–supportive load response to shape resilient frequency control of the power grid

The increasing penetration of renewable energy sources and the retirement of conventional generation units have decreased system inertia, making power systems more vulnerable to resilience and stability issues. To address this problem, this paper proposes a novel approach using grid-supportive loads (GSLs) to provide a fast and concise primary frequency response and a deep deterministic policy gradient agent-based secondary controller to restore the system frequency to the nominal value. The proposed method is evaluated on the single-area and multi-area test systems. The simulation results demonstrate that using GSLs enhances the power system's stability and resilience. Compared to conventional controllers, the frequency nadir is improved with GSLs. Additionally, the proposed method effectively enhances resilience even with high penetration. These findings indicate that the proposed approach can improve the resilience and stability of power systems and provide a promising solution for future power systems. The results of this study underscore the importance of utilizing innovative approaches to enhance the stability and resilience of power systems in the context of high penetration of renewable energy sources and the retirement of conventional generation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Electric power for space satellites

The development of electric power systems for satellites is discussed as an evolutionary process requiring the integration of power generation, power storage, and power control and distribution. The growth of space electric power systems is traced. The capabilities and limitations of the various elements (i.e. silicon solar cells) are discussed together with their impact on future technological growth.

Mackenzie, C. M.↗

Electrical power technology for robotic planetary rovers

Power technologies which will enable a range of robotic rover vehicle missions by the end of the 1990s and beyond are discussed. The electrical power system is the most critical system for reliability and life, since all other on board functions (mobility, navigation, command and data, communications, and the scientific payload instruments) require electrical power. The following are discussed: power generation, energy storage, power management and distribution, and thermal management.

Bankston, C. P.↗

Spacecraft Power Systems Engineering: Solutions for NASA's Manned Space Program

An overview of spacecraft power systems is presented, with a focus on applications in the manned space program. The topics include: 1) History; 2) State-of-the-art; 3) Development directions; 4) Focus on applications in the manned space program led from JSC; 5) Power Systems Engineering Trade Space; 6) Power Generation and Energy Storage; 7) Power Distribution and Control; and 8) Actuation

Scott, John H.↗

Puerto Rico Grid and Recovery Post Hurricane Maria

This presentation discusses the impact of and recovery from Hurricanes Irma and Maria in Puerto Rico. The hurricanes hit two weeks apart in 2017, resulting in damage to all elements (generation, distribution, and transmission) of Puerto Rico's already fragile energy system.

demand response↗

Coupling CTF to MPACT for Improved Thermal-Hydraulic Feedback for Transients

As computational power and techniques continue to advance, reactor analysis codes are afforded the opportunity to employ a more detailed physics model. One area where this has manifested is with coupled neutron kinetics and thermal-hydraulics codes for transient analysis, in which the feedback is critical for accurate modeling. The Michigan Parallel Characteristics Transport (MPACT) code is a 3-D method of characteristics neutron transport code capable of generating sub-pin level power distributions being developed by the University of Michigan through the Consortium for Advanced Simulation of LWRs (CASL) program. Currently, MPACT handles thermal-hydraulic feedback with an internal 1-D radial heat transfer model assuming constant moderator temperature. While this relatively simple treatment of thermal-hydraulic feedback has been shown to accurately model transients where Doppler feedback is the dominant feedback mechanism, coupling MPACT to a detailed thermal-hydraulic code will greatly expand the range of transient problems that can be accurately modeled. COBRA-TF (CTF) is a 3-D two-phase flow, subchannel thermal-hydraulics code maintained by Penn State University through CASL. CTF is based upon the Semi-Implicit Method for Pressure-Linked Equations, and it is especially well suited to model heat transfer and fluid flow phenomena associated with a nuclear reactor through a wide range of conditions. We present an initial effort coupling MPACT to CTF for transients, which provides a wider range of transient problems that can be modeled with increased accuracy. We have successfully coupled the thermal-hydraulics code CTF to the neutronics code MPACT for transient calculations by implicit and Crank-Nicolson methods, which have been demonstrated with single pin and 3x3 configurations. This capability extends the ability of MPACT to accurately model transients through a wider range of conditions than the existing thermal-hydraulic feedback, which is severely limited by the assumption of constant moderator temperature and density. By employing CTF for the thermal- hydraulic feedback, the transient physics can be described more completely at minimal computational expense. (authors)

42 ENGINEERING↗

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.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Nationwide assessment of potential output from wind-powered generators

A method for computing the actual expected power for a wind-powered generator from a given observed speed distribution is described and applied to estimate the potential output for different locations in the continental U.S. A contour map of generator capacity factor values (fraction of the rated output realizable) is obtained for wind-powered generator systems with a cut-in speed of 3.6 m/sec and a rated speed of 8.0 m/sec, and for a unit with hypothetical values for the 1 MW class (cut-in speed, 6.7 m/sec; rated speed, 13.4 m/sec). Results indicate that in the central U.S. and in certain areas of the New England coast at a height of 61 m, over 60% of the rated output power could be obtained on an annual average. In these areas capacity factors of over 20% could be obtained with the 1MW system.

Justus, C. G.↗

Real-Time Distributed Control of Smart Inverters for Network-level Optimization

The limitations of centralized optimization methods in managing electric power distribution systems operations have led to the distributed paradigm of computing and decision-making. Unfortunately, the existing distributed optimization algorithms are limited in their applicability to managing fast varying phenomena such as those resulting from highly variable Distributed Energy Resource (DER) generation patterns. They require a large number of communication rounds (in the order of 10 2 to 10 3 ) among the computing agents to solve one instance of the optimization problem. Related real-time distributed control methods are equally limited in their applications to power distribution systems with fast-changing DER generation; they require hundreds of rounds of communication and thus are slow in tracking the network-level optimal solutions. In this paper, we propose a novel distributed voltage controller that provides a fast-tracking of rapidly varying DER generation profiles while simultaneously converging to network-level optimal solutions within a few communication rounds. The proposed control algorithm leverages the radial topology of the system, which reduces the required communication rounds to reach the network-level optimum solution by order of magnitude. The novelty lies in carefully reducing the electrical network model from the perspective of each distributed controller and enabling appropriate data sharing among upstream and downstream nodes to achieve fast convergence. The simulation results demonstrate the effectiveness of the proposed approach in minimizing the feeder losses while maintaining the node voltage within the pre-specified limits.

voltage control, optimization, reactive power, inv↗

Optimal hybrid power plants for electric vehicle charging demand

Transmission constraints, increasing motivations to decarbonize, and concerns over peak electric vehicle (EV) load impacts on local grids have driven electric customers to consider behind-the-meter, hybrid power plant generation and storage at the distributed-grid level for EV charging. In this study, we develop capabilities to optimize hybrid power plant component capacities for EV charging. We then demonstrate these capabilities in a case study for Boulder, Colorado, using public EV charging data as well as wind and solar resource data. Our results show system designs that balance the cost of energy with load-meeting and peak shaving performance. Within the case study, systems designed for wind, solar photovoltaic (PV), and storage resulted in lower cost of energy than those optimized for PV and storage only. This indicates that in areas where wind resource exists, hybrid power plants that include wind, PV, and battery assets can better meet EV charging loads (including peak loads that are prone to overloading local grids) than PV and battery assets alone. Future work to address limitations in this paper include extending cost modeling to include performance losses (e.g., based on operations or weather) and charging station costs to estimate levelized cost of charging, and quantifying uncertainty and error in our aggregation methods for estimating EV charging loads at the hourly timescale.

14 SOLAR ENERGY↗

Analytical evaluation of jet noise source location technique utilizing an acoustically hard baffle with aperture

An analytical investigation was conducted on the experimental technique that uses shielding by an acoustically hard baffle to determine the location of noise sources in a jet. The jet exhausts through a circular hole in the baffle and the radiated acoustic power is considered to be generated by a distributed source along the jet axis. It is found that the effect of the baffle on the radiated power can be neglected only when the size of the source is on the order of a wavelength of the emitted sound or larger. Since noise sources in a jet are compact, the experimental technique is insufficient to identify these sources.

Norum, T. D.↗

Informing Mexico's Distributed Generation Policy with System Advisor Model (SAM) Analysis

The Government of Mexico recognizes the potential for clean distributed generation (DG) to meaningfully contribute to Mexico's clean energy and emissions reduction goals. However, important questions remain about how to fairly value DG and foster inclusive and equitable market growth that is beneficial to investors, electricity ratepayers, electricity distributors, and society. The U.S. National Renewable Energy Laboratory (NREL) has partnered with power sector institutions and stakeholders in Mexico to provide timely analytical support and expertise to help inform policymaking processes on clean DG. This document describes two technical assistance interventions that used the System Advisor Model (SAM) to inform Mexico's DG policymaking processes with a focus on rooftop solar regulation and policy.

14 SOLAR ENERGY↗