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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Impact of Aggregated PV on Subsynchronous Torsional Interaction: Preprint

This paper investigates induced oscillation (specifically subsynchronous torsional interactions) in power systems arising from photovoltaic (PV) power modulation. Time domain simulations of a modified IEEE first-benchmark system are presented and analyzed. In the IEEE benchmark system, a PV generator was added at the same bus where the synchronous generator is connected. The impact of different parameters of the PV inverters volt-volt-ampere reactive (volt-var) curve on SSTI is examined. The most severe impact found arises from the time response of the inverters reactive power change. A second-order time response with natural frequency matching the rotor speed deviation oscillation frequency and low-damping ratio quickly drives the system to an unstable region. Although it is highly unlikely that conditions necessary for distributed energy resource-induced oscillations would occur in the field, with knowledge of this vulnerability in mind, inverters' control parameters can be designed to avoid it.

aggregated↗
DOE OSTI2020

Impact of Aggregated PV on Subsynchronous Torsional Interaction

This paper investigates induced oscillation (specifically subsynchronous torsional interactions) in power systems arising from photovoltaic (PV) power modulation. Time domain simulations of a modified IEEE first-benchmark system are presented and analyzed. In the IEEE benchmark system, a PV generator was added at the same bus where the synchronous generator is connected. The impact of different parameters of the PV inverters’ volt-volt-ampere reactive (volt-var) curve on SSTI is examined. The most severe impact found arises from the time response of the inverter’s reactive power change. A second-order time response with natural frequency matching the rotor speed deviation oscillation frequency and low-damping ratio quickly drives the system to an unstable region. Although it is highly unlikely that conditions necessary for distributed energy resource-induced oscillations would occur in the field, with knowledge of this vulnerability in mind, inverters' control parameters can be designed to avoid it.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2019

Estimating PV power from aggregate power measurements within the distribution grid

The increased integration of photovoltaic (PV) systems in distribution grids reduces visibility and situational awareness for utilities because the PV systems' power production is usually not monitored by them. To address this problem, a method called Contextually Supervised Source Separation (CSSS) has been recently adapted for real-time estimation of aggregate PV active power generation from aggregate net active and reactive power measurements at a point in a radially configured distribution grid (e.g., substation). In its original version, PV disaggregation is formulated as an optimization problem that fits linear regression models for the aggregate PV active power generation and true substation active power load. This paper extends the previous work by adding regularization terms in the objective function to capture additional contextual information such as smoothness, by adding new constraints, by introducing new regressors such as ambient temperature, and by investigating the use of time-varying regressors. Furthermore, we perform extensive parametric analysis to study tuning of the objective function weighting factors in a way that maximizes performance and robustness. The proposed PV disaggregation method can be applied to networks with either a single PV system (e.g., megawatt scale) or many distributed ones (e.g., residential scale) connected downstream of the substation. Simulation studies with real field recorded data show that the enhancements of the proposed method reduce disaggregation error by 58% in winter and 35% in summer compared to previous CSSS-based work. When compared against a commonly used transposition model based approach, the reduction in disaggregation error is more pronounced (78% reduction in winter and 45% in summer). Additional simulations indicate that the proposed algorithm is also applicable for PV systems with time-varying power factors. In conclusion, overall, our results show that—with appropriate modeling and tuning—it is possible to accurately estimate the aggregated PV active power generation of a distribution feeder with minimal or no additional sensor deployment.

14 SOLAR ENERGY↗
DOE OSTI2022

Reducing Uncertainty of Fielded Photovoltaic Performance (Final Technical Report)

Improved analysis and reporting of photovoltaic (PV) field performance increases the certainty of owners and financiers that systems will perform as expected. Advanced module technologies (e.g., PERC, HJT, and bifacial) introduce new degradation mechanisms and performance characteristics. The FY19-21 Reducing Uncertainty project leveraged data from the ever-increasing PV fleet to develop models and understanding of the field performance of existing and new technologies. Specifically, we accomplished: report on field performance and degradation rates for high-efficiency silicon (HJT, PERC, IBC) and more conventional technologies; developed automated analysis techniques to quantify system performance (performance ratio, energy yield) and production shortfalls (soiling, degradation, availability); refined the RdTools software toolkit to bring standard, validated analysis techniques to bear on third-party data; analyzed and reported on large datasets including Treasury data and Lawrence Berkeley National Laboratory's Utility-Scale dataset to expand the high-quality degradation-rate histogram published previously; worked with industry partners and the DuraMAT data hub to enable private parties to share and aggregate PV production data anonymously, leveraging cloud-based data analysis infrastructure and publishing on US fleet-scale performance comprising over 7GW of operating systems. (https://www.nrel.gov/pv/fleet-performance-data-initiative.html). Through our industry collaborations we have engaged in NDA-covered data transfer with twelve PV fleet owners as of January 2022, with more agreements in negotiation. Our scalable cloud-based time series database contains over 30 billion rows (20TB) of PV time series data, representing over 1700 commercial and utility-scale systems, and over 7.2 GW of DC capacity (Fig 1). Initial field performance results have been distributed in several public reports. Because our fleet composition and data quality methods are continually improving, annual updates to these results are published to our PV Fleet webpage [ https://www.nrel.gov/pv/fleet-performance-data-initiative.html ] and DuraMAT data hub [DOI: 10.21948/1842958]. Another existing dissemination channel used for observed soiling losses is a map we maintain for soiling losses. Additional products developed include a report detailing fleet-wide performance index, availability, startup loss and snow loss factors, a detailed report on the 1603 grant dataset comprising over 100,000 PV systems with failure and performance details and a utility-scale report coauthored with LBNL on 31 GW of system performance.

14 SOLAR ENERGY↗
DOE OSTI2017

Model Reduction for Fast Assessment of Grid Impact of High Penetration PV

A key challenge in properly analyzing the impact of solar photovoltaics (PV) during planning, interconnection and operation in the distribution grid is computational complexity. Such studies require the use of Quasi-Steady-Time-Series (QSTS) power flow to capture the complex interaction of PV with voltage regulating equipment and protection devices and a large number of scenario studies are needed to capture location specific constraints and uncertainties. In addition, a typical distribution feeder can have thousands of nodes and there can be thousands of such feeders in a given utility system. To solve this problem, a new and systematic method for distribution network reduction is proposed. The objective is to reduce the size of distribution systems by more than 80% while preserving the accuracy of power flow results. To this end, an extended Ward-equivalent method has been proposed to create an equivalent circuit. Moreover, load and PV aggregation based on the backward sweep method has been developed to further simplify the feeder. The proposed method is tested with a modified IEEE 123-node distribution test system. The simulation results demonstrate the high efficiency and accuracy of the proposed approach for distribution network reduction.

reduced order systems, load flow, load modeling, v↗
DOE OSTI2023

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↗
DOE OSTI2018

Analysis of Solar Energy Aggregation Under Various Billing Mechanisms

Ongoing reductions in the cost of solar photovoltaic (PV) systems are driving increased installations by residential households. Various incentive programs such as feed-in tariff, net metering, net purchase, and sale that allow the prosumers to sell their generated electricity to the grid are also powering this trend. In this paper, we investigate sharing of PV systems among a community of households, who can also benefit further by pooling their production. Using cooperative game theory, we find conditions under which such sharing decreases their net total cost. We also develop allocation rules such that the joint net electricity consumption cost is allocated to the participants. These cost allocations are based on the cost causation principle. The allocations also satisfy the standalone cost principle and promote PV solar aggregation. Here, we also perform a comparative analytical study on the benefit of sharing under the mechanisms favorable for sharing, namely net metering, and net purchase and sale. The results are illustrated in a case study using real consumption data from a residential community in Austin, TX, USA.

14 SOLAR ENERGY↗
DOE OSTI2023

Model Predictive Voltage Control of Large-Scale PV or Hybrid PV-BESS Plants

Increased penetration level of inverter-based resources (IBRs) and renewable energy in the power grid has called for more requirements from the control of IBRs. In this paper, the voltage-reactive power control of a photovoltaic (PV) power plant or hybrid PV-battery energy storage system (BESS) plant connected to a bulk power grid, whilst meeting the grid requirements, is studied. In this paper, a continuous-set model predictive control (MPC) formulation is proposed for voltage-reactive power control. For the same, an aggregated dynamic PV plant model is developed based on the recursive system equivalencing method. The formulation is then implemented in PSCAD simulation on a 125 MW PV plant or hybrid PV-BESS plant. The MPC implementation achieves 10.13% voltage improvement based on PSCAD simulation results in a balanced fault case study. Simulation results further demonstrate that MPC provides improved voltage support over the conventional proportional-integral (PI) controller post-fault occurrence.

Abu rub, Omar↗
DOE OSTI2018

Expanding PV Value: Lessons Learned from Utility-led Distributed Energy Resource Aggregation in the United States

Distributed PV capacity in the United States has increased from about 0.4 Gigawatts (GW) in 2010 to 10.5 GW in 2017 (GTM Research and SEIA 2018). When distributed PV is coupled with other emerging distributed energy resources (DERs) like battery storage and electric vehicles (EVs) they can provide demand response, voltage regulation, and other grid services. When many DERs are aggregated and called upon to provide these services simultaneously they may offer the same or more value than large, centralized power producers. In the United States, utility efforts to aggregate DERs are in the nascent stage. If initial DER aggregation programs prove successful, it could open new value streams for PV and other emerging DERs, thereby expanding deployment and transforming the energy market. The literature on the scope, performance, and lessons learned from utility-led DER aggregation programs is limited. This report fills this research gap, first by surveying utility-led DER aggregation programs nationwide, and then providing a deeper analysis of five utility pilots. We compare lessons learned across the five cases to develop a list of common challenges and related solutions that other utilities might consider when developing next generation programs.

14 SOLAR ENERGY↗
DOE OSTI2016

Appendix

AWS Truepower - SWIFT Forecasting Details Appendix to Distributed Resource Energy Analysis & Management System (DREAMS) Development for Real-time Grid Operations

14 SOLAR ENERGY↗
DOE OSTI2018

Load Aggregation Methods for Quasi-Static Power Flow Analysis on High PV Penetration Feeders

This paper focuses on developing load aggregation methodologies for analyzing quasi-static power flows on high photovoltaic penetrated distribution feeders so statistics of the transformer loading levels, voltage ramping events, and voltage violation events can be properly quantified. A load profile aggregation algorithm is presented to construct 24-hour, minute-by-minute load profiles at each load node on the test feeder so the aggregation of those load profiles matches the load profile measured at the feeder head. A quasi-static power flow analyses are conducted to obtain minute-by-minute power flow results that can be used to quantify transformer overloads and voltage issues in distribution systems. To demonstrate the effectiveness of the developed methodology, the IEEE-123 test feeder model and residential load profiles collected from the PECAN street project are used in the case studies. Simulation results show that the method is effective in producing the required operation statistics.

Load aggregaton, PV integration, quasi-static powe↗
DOE OSTI2019

Coordinative Real-time Sub-Transmission Volt-VAr Control for Reactive Power Regulation between Transmission and Distribution Systems

This paper introduces an integrated voltage regulation approach to coordinate the Volt-VAr control between transmission and distribution systems. Distributed photovoltaic (PV) systems are aggregated as a virtual power plant (VPP). At the sub-transmission level, a Coordinated Real-time Sub-Transmission Volt-VAr Control Tool (CReST-VCT) is introduced to coordinate the operation of the shunt devices and the reactive power provided by the VPPs. The CReST-VCT uses an enhanced Volt-VAr control algorithm with weighted voltage control objects that include minimizing losses, maintaining the voltage within desirable levels, and minimizing the number of mechanical switching of shunt elements. The algorithm runs every 5 minutes and is solved using AC optimal power flow (OPF) solution technique. The outputs include the settings for each sub-transmission-level Volt-VAr control devices and the reactive power generation requirements for each VPP. Then, each VPP will run a distribution Volt-VAr control algorithm to select the PV inverters that provide the Volt-VAr control services considering the distribution network topology. The goal of the VPP reactive power control is to meet the transmission level service requirements while maintaining the voltage and line flow in the distribution system within limits. Each VPP will update its voltage regulation capacity every 5 minutes to allow the CReST-VCT to formulate the optimization problem for the next dispatch interval. The proposed tool is simulated on Duke Energy Carolina system to demonstrate the capability of providing voltage support service by dispatching of reactive power of distributed PV as VPP.

Ke, Xinda↗
DOE OSTI2025

Pricing Strategy of Electric Vehicle Aggregators Based on Locational Marginal Price to Minimize Photovoltaic (PV) Curtailment

The global climate crisis demands urgent action to mitigate global warming. Using renewable energy sources, such as solar and wind power, for electricity generation is crucial. This shift from centralized to distributed power systems, however, brings challenges, including voltage fluctuations and renewable energy curtailment. The rapid growth of the electric vehicle (EV) industry adds complexity, increasing overall electricity demand and straining the power supply during peak charging times. This paper proposes a scheduling strategy for EV aggregators to reduce renewable energy curtailment and stabilize grid operation by strategically scheduling EV charging. Using Multi -Agent Transport Simulation (MATSim), a traffic simulation tool, EV driving data in Denver, Colorado, USA, were modeled. The EV aggregator adjusts charging fees based on locational marginal prices, encouraging EVs to charge at different stations according to pricing. Simulations on an IEEE 33-bus system with distributed energy resources and EV charging stations validate the proposed algorithm, demonstrating its effectiveness in reducing curtailment by 12.55% and stabilizing grid operation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Consensus-Based Approach for Active Power Control and Reserve Estimation in Distributed PV Systems

With the increased adoption of distributed energy resources (DER), they are expected to contribute to power system reliability services and enhance power system stability. This paper presents a distributed consensus control approach for the real-time active power reserve estimation and power management in distributed PV (photovoltaic) systems. The proposed method estimates the cumulative active power reserve from numerous PV generators using only the sparse communication network for a DER aggregator to provide active power regulation services. The real-time active power reserve estimation using the proposed approach can be used by DER aggregators to manage curtailment in distributed PV systems to maintain stipulated reserves and further to provide power system frequency regulation. Using the proposed approach, the DER aggregator only requires measurements at the feeder substation and it does not require information from individual DER units, thereby improving system resiliency. The proposed distributed consensus control method is validated on IEEE 123 testbed using PSCAD simulations.

active power reserve↗
DOE OSTI2022

Consensus-Based Approach for Active Power Control and Reserve Estimation in Distributed PV Systems: Preprint

With the increased adoption of distributed energy resources (DER), they are expected to contribute to power system reliability services and enhance power system stability. This paper presents a distributed consensus control approach for the real-time active power reserve estimation and power management in distributed PV (photovoltaic) systems. The proposed method estimates the cumulative active power reserve from numerous PV generators using only the sparse communication network for a DER aggregator to provide active power regulation services. The real-time active power reserve estimation using the proposed approach can be used by DER aggregators to manage curtailment in distributed PV systems to maintain stipulated reserves and further to provide power system frequency regulation. Using the proposed approach, the DER aggregator only requires measurements at the feeder substation and it does not require information from individual DER units, thereby improving system resiliency. The proposed distributed consensus control method is validated on IEEE 123 testbed using PSCAD simulations.

active power reserve↗
DOE OSTI2024

Advancing Our Understanding of System Availability through the PV Fleet Performance Data Initiative

The PV Fleet Performance Data Initiative partners with photovoltaic (PV) fleet owners to collect time-series data of PV production data and publishes aggregated anonymized results of system performance metrics. With an extensive dataset drawn from over 2,200 PV systems across the United States, comprising 8.5 GW and 24,000 separate inverter data channels, this initiative aims to ensure that systemic risks in the US PV fleet are detected. The current work explores system availability, revealing a pronounced dependence on time, especially within the initial 6 months of system performance. Following this start-up period, the average system availability stabilizes. Statistical analyses illustrate a median (P5O) monthly availability of 0.991 and a dependence on system size with a negative trend in availability with increasing system size. This finding indicates that larger systems experience lower availability compared to their smaller counterparts.

inverter availability↗
DOE OSTI2021

Optimal Demand Response Incorporating Distribution LMP with PV Generation Uncertainty

The utilization of aggregated demand-side flexibility via demand response (DR) has become a promising pathway for the integration of renewable energy resources in power systems. Nowadays, there are several management strategies for DR such as the price-based transactive control strategies. However, many of such existing price-based control strategies neglect the physics and operational constraints of the underlying distribution networks when computing the price, raising concerns regarding their theoretical and practical values. This paper studies this issue and investigates optimal DR (ODR) by incorporating the distribution locational marginal price (DLMP). In particular, we discuss DR in connection with DLMPs and propose a multiperiod bilevel optimization problem to find the ODR strategy. Here, the objective is to minimize the peak load, load fluctuation, and payments of load aggregators. In addition, a robust bilevel ODR model is formulated to provide a robust ODR strategy while minimizing operating costs under the worst-case realization of uncertainties; this mitigates the impact of forecasting errors on renewable energy resources. Then, we propose an efficient solution approach by employing the Karush-Kuhn-Tucker conditions and strong duality. Simulation results are presented to illustrate the mutual impacts of the interaction between DR and DLMP and the benefits of the robust ODR strategy.

24 POWER TRANSMISSION AND DISTRIBUTION↗