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DOE OSTI2024

A High-Fidelity Electromagnetic Transient Model of Inverter-based Resources Integrated to an IEEE-9 Bus System for Benchmarking Studies

An inverter-based resource (IBR) is a source of electricity that is asynchronously connected to the electrical grid via an electronic power converter. These power sources lack the intrinsic behaviors of the standard power plants, presenting specific challenges to system stability. These power sources lack the intrinsic behaviors of the standards power plants and their features are almost entirely defined by the control strategy used on them, presenting specific challenges to system stability as their penetration increases into the already fragile Bulk Power System (BPS). Utilizing renewable energy has a great upside but the electrical industry needs to understand the requirements like performing electromagnetic transient (EMT) simulation studies in planning and/or in interconnection studies. This paper presents the development of a high-fidelity EMT model based on commercial equipment and field parameters, which at the same time aims to study the increasing penetration of IBRs and their impact on the actual BPS. The open-source EMT model developed will be a benchmarking example that can be used to evaluate algorithms in the power grid (including evaluating grid-forming controls, power system monitoring and operation, etc.).

Martinez Montejano, Misael↗

DOE OSTI2023

Modeling of a Networked Community Microgrid with High Solar Penetration Considering Control Dynamics of Inverter-Based Resources

Microgrids help facilitate the integration of renewable energy in distribution-level grids and increase the resilience of the electric grid to extreme weather, especially in rural areas. Compared to traditional microgrids, a networked microgrid leverages multiple grid-forming sources to form a potential meshed grid and is more flexible in operation. This paper demonstrates the simulation modeling of an actual networked microgrid located in Adjuntas, Puerto Rico. The model contains representations of power inverters that connect the battery energy storage systems and photovoltaic generation systems to the networked microgrid and is capable of simulating fast grid transients as well as long-term operation of the networked microgrid. The modeling technique for power inverters allows the time-efficient simulation of the microgrid with a minimal penalty on model accuracy.

Li, Dingrui↗

DOE OSTI2020

Coordinated operation of electricity and natural gas systems from day-ahead to real-time markets

Power systems worldwide are becoming more reliant on energy from natural gas, wind, and solar, posing possible reliability and coordination challenges from the tighter coupling of these infrastructure systems. This paper proposes a framework for the market-based coordination of electricity and natural gas system operations. The proposed framework includes a power system model that accounts for flexibility in the commitment of power plants with short start-up and shut-down times, coupled with a dynamic gas model that simulates when gas cannot be delivered to generators. The capabilities of the framework are illustrated using real-world electric power and gas systems, including scenarios around wind and solar penetrations and the analysis of time-variant, “shaped flow” gas nominations. Our results indicate that coordination between power and gas systems improves total gas delivery and reduces out-of-merit order dispatch in the electricity system, and that shaped flows may reduce unserved gas in systems with high penetrations of wind and solar. Coordination can have mixed effects on carbon-dioxide emissions, with emissions increasing with coordination for current systems during high load weeks but decreasing for systems with high renewable penetrations, particularly during periods of high variability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Leveraging concentrating solar power plant dispatchability: A review of the impacts of global market structures and policy

Concentrating solar power (CSP) integrated with thermal energy storage delivers flexible and dispatchable power, which is an increasingly valuable quality as electricity systems integrate growing penetrations of variable renewable energy. Valuing and compensating CSP's dispatchability and flexibility requires electricity market structures and policies that appropriately remunerate generation during high-value portions of the day. In this paper, we review previous analyses of CSP economics and deployment, and we find that continued CSP growth will require valuation mechanisms that appropriately compensate for CSP's flexibility during both plant design and plant operation. We then review market structures that drive CSP operations and dispatch in jurisdictions where CSP is being developed, with perspectives from Spain, Chile, Australia, Morocco, South Africa, the United States, China, and the United Arab Emirates (Dubai). Despite broad agreement that CSP's dispatchability provides value to electricity grids, countries' policies for remunerating and leveraging such dispatchability varies widely. As deployment of CSP and variable renewable energy grows, it will be increasingly important to redesign current integration policies to signal the delivery of CSP's grid services more appropriately.

14 SOLAR ENERGY↗

DOE OSTI2024

Cognitive Grid Optimization

This project laid the foundation to include a security constrained economic dispatch (SCED) within one of the leading simulators which is used to train system operators who keep the lights on for over 150 million people in USA. The SCED is designed to handle very high penetrations of renewable generation as well as battery storage. As a follow on the this project, a Trusted Source Model of the North American Electric Interconnections will be built from public GIS data. The various North American Markets will be emulated. This Trusted Source Model will grow the software developers for the next generation of power applications that are needed to transition to all green generation while everything is electrified.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Machine Learning-Based PV Reserve Determination Strategy for Frequency Control on the WECC System

Frequency control from photovoltaic (PV) power plants has great potential to address the frequency response challenge of the power system with high penetrations of renewable generation. Using model-based approaches to determine the optimal PV headroom reserve, however, requires significant online computation and is intractable for an interconnection level system. This paper proposes a machine learning based strategy, that is suitable for real-time operation, to determine the optimal PV reserve for frequency control. The proposed machine learning algorithm is trained and tested on 1,987 offline simulations of a 60% renewable penetration Western Electricity Coordinating Council (WECC) system. Furthermore, the proposed reserve determination strategy is applied on a realistic 1-day operation profile of the WECC system and demonstrates a savings of more than 40% PV headroom compared to a conservative approach. It is evident that the proposed strategy can efficiently and effectively determine the optimal PV frequency control reserve for realistic interconnection systems.

frequency control↗

DOE OSTI2021

Techno-economic analysis of long-duration energy storage and flexible power generation technologies to support high-variable renewable energy grids

As variable renewable energy penetration increases beyond 80%, clean power systems will require long-duration energy storage or flexible, low-carbon generation. Here, we provide a detailed techno-economic evaluation and uncertainty analysis of applicable technologies and identify challenges and opportunities to support electric grid planning. We show that for a 120-h storage duration rating, hydrogen systems with geologic storage and natural gas with carbon capture are the least-cost low-carbon technologies for both current and future capital costs. These results are robust to uncertainty for the future capital cost scenario, but adiabatic compressed air and pumped thermal storage could be the least-cost technologies in the current capital cost scenario under uncertainty. Finally, we present a new storage system using heavy-duty vehicle fuel cells that could reduce the levelized cost of energy by 13%–20% compared with the best previously considered storage technology and, thus, could help enable very high (>80%) renewable energy grids.

25 ENERGY STORAGE↗

DOE OSTI2022

Ultra-Short-Term Spatiotemporal Forecasting of Renewable Resources: An Attention Temporal Convolutional Network Based Approach

The rapid increase in the penetration of renewable energy resources characterized by high variability and uncertainty is bringing new challenges to the power system operation. To ensure the efficient and reliable operation of electric grid, an accurate and general short-term forecasting algorithm with interpretability is desired. Moreover, the extensive off-site information provided by the proliferation of new renewable plants stimulates the interests in the spatiotemporal forecasting. In this paper, an attention temporal convolutional network, which is built on stacked dilated causal convolutional networks and attention mechanisms, is proposed to perform the ultra-short-term spatiotemporal forecasting of renewable resources. Compared with the existing spatiotemporal forecasting methods, the presented model needs no domain knowledge and can be applied to different forecasting tasks such as solar generation and wind speed forecasting. Here, the attention mechanism improves the interpretability. The algorithm can be used to produce both point and probabilistic forecasts. Numerical results on the data sets from National Renewable Energy Laboratory show superior performance over five baselines, in terms of skill scores. Compared with the baselines, the average improvements of accuracy introduced by the proposed method for the point and probabilistic forecasting are 15.08% and 15.85%, respectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Frequency Stability Enhancement in a Fully Solar Power Grid: A Case Study on the Saudi Model

Recently, renewable energy sources (RES) such as solar photovoltaic (PV) have been recognized for their significant potential. Several studies have explored the issue of frequency stability with high RES penetration. A significant observation related to this issue is the decline in the weighted short circuit ratio (WSCR), which has the potential to adversely affect system stability. This research uniquely focuses on the gradual transition of the Saudi Electricity Company (SEC) system to a fully integrated solar PV grid, offering insight and methodology that can be adapted for other power systems. While a variety of mitigation methods are available, synchronous condensers (SC) were used in this study to stabilize grid frequency, and their implementation has been shown to improve the overall performance of the system. In response to the observed decline in WSCR, a comprehensive short circuit analysis was applied across all regions in the Saudi power grid model to evaluate the reduction in short circuit power and highlight areas requiring enhancement. Finally, scenarios illustrating frequency response with a gradual increase in SCR were analyzed, with the objective of establishing a stable, fully solar PV power system that is resilient to sudden power grid disturbances.

14 SOLAR ENERGY↗

DOE OSTI2020

Contributions of Solar + Storage to Future Power Needs

The costs of solar photovoltaics (PV) have been dropping in recent years, leading to increasing installations of solar PV systems and growing interest in how the technology will impact the electric grid. Additionally, as battery costs decline, there is increasing interest in understanding the benefits and limitations of battery storage for the grid as well as potential co-benefits of coupling battery storage and photovoltaics. This paper presents recent methodological developments to more accurately represent the value and limitations of coupled PV and battery systems in capacity expansion models. These are demonstrated using the Resource Planning Model (RPM), which co-optimizes capacity investments, transmission investments, and reduced-order dispatch through 2045. We simulate the evolution of the generation and transmission system in the Western Interconnection both with and without a coupled PV and battery technology option under two core scenarios - a baseline scenario and a high renewable penetration scenario - coupled with sensitivities assuming low and mid PV and battery cost projections. We analyze the degree to which a variety of configurations of coupled PV + Battery systems are able to meet future electricity needs, under which system conditions this coupled technology becomes beneficial to the electric grid and identify the displaced technologies when coupled solar and storage is introduced into the model. We find that capturing the benefits of co-locating these systems becomes increasingly important as the penetration of solar PV rises, and that in particular it is important to accurately capture the ability of these technologies to shift energy, provide firm capacity, and reduce expected curtailment.

14 SOLAR ENERGY↗

DOE OSTI2019

Seminar 13 - Advanced Methods for Grid Integration of High-Performance Residential Communities

High-performance residential communities such as net-zero energy (NZE) and NZE-ready communities are emerging across the United States as many cities and states have committed to achieve ambitious energy efficiency and renewable energy goals between now and 2050. The achievement of these goals will transform the nation's communities into the holistic paradigms consisting of pervasive solar photovoltaics (PVs) and other renewable distributed energy resources, energy storage and flexible loads. However, integrating residential communities with high PV penetration may bring many challenges to the grid. For example, during many hours of the year, electric power is flowing out of PV-enabled homes and back into the grid. When this happens simultaneously in many nearby homes, distribution feeder voltage can be raised significantly. Intermittent solar power can also cause voltage flickers, leading to potential damages on both distribution feeder and home appliances. Existing solutions, such as PV curtailment, battery storage, and direct load control, are not able to address all the challenges in a cost-effective way. Better understanding is needed on how to deploy rooftop PV, how to predict building loads, and how to coordinate the homes in a community to enhance grid reliability. This seminar consists of four integral presentations that cover different aspects of a solution to these challenges. First, we will present an automated method to identify the best surfaces to deploy PV and size PV according to the PV penetration goals in a community. Second, we will present a streamlined way to create gray-box building models that are suitable for large-scale building-grid co-simulation. Next, we will present a data-driven method to estimate the end-use energy consumption to better coordinate the behind-the-meter resources to reduce utility cost, provide grid services, and improve renewable energy integration. Lastly, we will present a hierarchical control system that integrates the building models and the estimated non-dispatchable loads into the decision-making process to enhance the reliability and resilience of the residential community. Simulation results from an NZE-ready community in Fort Collins, Colorado will be presented in all four presentations and the guidelines on better grid integration of residential communities will be provided.

14 SOLAR ENERGY↗

DOE OSTI2025

Machine Learning-Assisted Distribution System Network Reconfiguration Problem

High penetration from volatile renewable energy resources in the grid and the varying nature of loads raise the need for frequent line switching to ensure the efficient operation of electrical distribution networks. Operators must ensure maximum load delivery, reduced losses, and the operation between voltage limits. However, computations to decide the optimal feeder configuration are often computationally expensive and intractable, making it unfavorable for real-time operations. This is mainly due to the existence of binary variables in the network reconfiguration optimization problem. To tackle this issue, we have devised an approach that leverages machine learning techniques to reshape distribution networks featuring multiple substations. This involves predicting the substation responsible for serving each part of the network. Hence, it leaves simple and more tractable Optimal Power Flow problems to be solved. This method can produce accurate results in a significantly faster time, as demonstrated using the IEEE 37-bus distribution feeder. Compared to the traditional optimization-based approaches, a feasible solution is achieved approximately ten times faster for all the tested scenarios.

deep neural networks↗

DOE OSTI2025

Nuclear—thermal energy storage configurations for industrial combined heat and power supply—conceptual and thermodynamic study with high temperature gas-cooled reactor

Nuclear systems are promising candidates for delivering resilient heat and power for future energy security and independence. Traditionally, nuclear plants have been used for baseload electricity production and cogeneration of heat has seen relatively limited application utilizing typically only small portion of a reactor's thermal output. This paradigm may shift due to the increasing penetration of intermittent renewables and need for resource flexibility, various decarbonization efforts aimed at both electricity and heat demands, along with the perspective of small modular nuclear reactor applications, which can be sized based on local industrial needs. Here, this study provides a comprehensive guide for the nuclear and industrial sectors, emphasizing controllability in the combined heat and power configuration options for high temperature gas-cooled reactor and process steam supply. It investigates the integration of thermal energy storage to improve nuclear energy's responsiveness to varying industrial demands. The study emphasizes placing thermal energy storage between the nuclear primary loop and steam cycle to achieve greater efficiency and flexibility in power and heat output, surpassing traditional combined heat and power systems and avoiding efficiency losses seen in other thermal energy storage integration approaches.

combined heat and power (CHP)↗

DOE OSTI2021

A Technical and Economic Assessment of LWR Flexible Operation for Generation and Demand Balancing to Optimize Plant Revenue

With increased penetration of subsidized variable renewable energy (VRE) resources and competition from low natural gas prices, existing light water reactor (LWR) nuclear power plants (NPPs) are struggling to remain economically competitive. This work examines the potential economic competitiveness of various thermal energy storage (TES) technologies when coupled directly or indirectly with a NPP. To highlight their relative economic competitiveness, we contrast several energy storage solutions in stochastic dispatch optimization. We leverage data from recent work analyzing a range of TES technologies with varying capital costs, performance, and technology readiness level (TRL) to establish our case. We explore inserting these technologies into an electricity market with existing nuclear generation and large projected variable renewable energy (VRE) penetration. Although these technologies' projected capital costs may make them unlikely candidates in their current state, this analysis demonstrates a high-fidelity techno-economic analysis of energy storage. Furthermore, as the projected cost of energy storage technologies evolves, this analysis sets a precedent for similar future investigations. One region with projected trends that may be unfavorable for existing nuclear capacity is the New York Independent System Operator (NYISO) market. New York state’s baseload generation has been historically provided by fossil-fired and nuclear assets. However, amid economic pressures from subsidized VREs and low natural gas prices, the state has recently deactivated Indian Point nuclear power plant units 2 and 3. Furthermore, the state plans to meet its zero-emission generation target by 2040 by replacing fossil-fired capacity with significant investments in VRE resources like wind and solar photovoltaic (PV) and battery storage. Increased intermittent resource penetration lowers the baseload power requirement, adding further economic pressure to the state’s three remaining NPPs still in operation. With three NPPs still in operation in New York, this work analyzes potential economic benefits to NPPs on the New York grid when directly or indirectly coupled with various TES technologies. This work requires two modeling steps to analyze the potential economic benefits of various system configurations of the TES directly or indirectly coupled with nuclear. First, this analysis leverages capacity expansion modeling by experts at the Electric Power Research Institute (EPRI). Using their deterministic capacity expansion model, U.S. Regional Economy, Greenhouse Gas, and Energy (US-REGEN), EPRI analysts evaluated the capacity and generation evolution of the New York state energy market under four projection scenarios. These four projection scenarios were developed to represent the potential evolution of the capacity and generation in NYISO from 2015 to 2050 under various economic, technology, and policy constraints. The results from these capacity expansion models are then used as boundary conditions in the second modeling step. The second modeling step uses the Holistic Energy Resource Optimization Network (HERON) for a set of stochastic techno-economic analyses (STEAs) to investigate the potential increase in the economic viability of various configurations of the TES. With no current capacity expansion capabilities, HERON takes the data generated from US-REGEN for 2050 to generate synthetic load, solar, and wind data. Then HERON economically optimizes the capacity and dispatch of the various TES configurations. The potential economic benefit is the differential net present value (NPV) of the TES configurations from the no-TES baseline. As a stochastic techno-economic analysis package, HERON introduces uncertainty into the economic metrics, while US-REGEN trades resolution for reduced computational complexity. Using HERON also allows the modeling of direct thermal coupling, a feature not common in capacity and dispatch models. As expected, with high capital costs, the costs of introducing energy storage for all the technologies considered outweighed the potential economic benefit of this strategy for flexible plant operation. The benefit of this analysis is primarily in demonstrating a workflow that examines innovative solutions to increase NPP revenue via TES coupling. HERON’s stochastic capacity and dispatch optimization process used in this work has proven an effective tool in observing and evaluating the impact of introducing storage technologies in a grid energy system.

25 ENERGY STORAGE↗

DOE OSTI2025

Resilience of the Electric Grid Through Trustable IoT-Coordinated Assets

The electricity grid has evolved from a physical system to a cyberphysical system with digital devices that perform measurement, control, communication, computation, and actuation. The increased penetration of distributed energy resources (DERs) including renewable generation, flexible loads, and storage provides extraordinary opportunities for improvements in efficiency and sustainability. However, they can introduce new vulnerabilities in the form of cyberattacks, which can cause significant challenges in ensuring grid resilience. We propose a framework in this paper for achieving grid resilience through suitably coordinated assets including a network of Internet of Things devices. A local electricity market is proposed to identify trustable assets and carry out this coordination. Situational Awareness (SA) of locally available DERs with the ability to inject power or reduce consumption is enabled by the market, together with a monitoring procedure for their trustability and commitment. With this SA, we show that a variety of cyberattacks can be mitigated using local trustable resources without stressing the bulk grid. Multiple demonstrations are carried out using a high-fidelity cosimulation platform, real-time hardware-in-the-loop validation, and a utility-friendly simulator.

distributed energy resources↗

DOE OSTI2024

Factors Influencing Grid-connected Heat Pump Water Heater Performance in the Southeast U.S.

Grid-connected heat pump water heaters (HPWH) can shift electrical load while minimizing impacts to hot water availability for occupants. This capability provides a flexible grid resource to utilities seeking to manage peak loads Such load control also can feasibly improve renewable utilization within the utility electric production mix, for instance using off-peak generation during periods with high renewable energy generation. It also offers lower electric bills to customers through increased energy efficiency of HPWH and cuts greenhouse gas emissions. In particular, the Southeast U.S. due to its high penetration of electric water heating presents a promising opportunity for grid-connected HPWHs. This paper builds upon the results of an extensive HPWH load shifting field study conducted in 51 occupied homes in Florida using EcoPort technology (Butzbaugh et al, 2022). In 2022, only an initial evaluation was available. Here, long term load results are available as well as examination of various control strategies and influences. Analysis is conducted for HPWH energy use and load shifting performance based on home occupancy (i.e., low and high) and water heater location (i.e., conditioned and unconditioned) across different temperature profiles. An unexpected outcome of this analysis was the poor performance of HPWHs located in conditioned spaces, possibly because of inadequate air volume from improper installation. We did find higher demand reductions from 2-hour load ups and slightly improved for critical peak signals in the afternoon control periods. As expected, higher occupancy households showed great load reductions.

Fenaughty, Karen↗

DOE OSTI2020

Impact of High PV Penetration on Voltage Stability

Photovoltaics (PV) are becoming increasingly relevant in modern power systems. With this increase also comes reliability concerns as photovoltaics behave differently than conventional generators. One reliability concern is voltage stability. In this paper, voltage stability of the Austin area in the Electric Reliability Council of Texas (ERCOT) system is studied using dynamic models with varying levels of photovoltaic penetration. The base case is set at 0% renewable penetration. Additional cases include 15% wind penetration and up to 65% photovoltaic penetration. The study results show that voltage/var control capacity is critical to voltage stability, which PV lacks. Voltage regulation of photovoltaics may cause over-voltage and voltage collapse may be more abrupt under high regional photovoltaic penetration.

Till, Jeremy↗

DOE OSTI2022

New Industry Partnerships: Solar Energy Technologies Office Support for Early Projects in the Energy Systems Integration Facility: An Agreement Closeout Summary Report

The U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE) Solar Energy Technologies Office (SETO)-funded New Industry Partnerships (NIPs) agreement established multiple new cooperative research projects with industry partners. Each project demonstrated the use of the National Renewable Energy Laboratory's Energy Systems Integration Facility (ESIF) as a national asset for research and development, testing, and validation of new technologies to support high penetrations of solar energy on the electric grid. The agreement was launched in 2013 and represented the SETO portion of the DOE EERE-wide Integrated Network Testbed for Energy Grid Research and Technology Experimentation (INTEGRATE) program. The focus of INTEGRATE was on multi-energy system testing and on testing the interactions of energy systems with information technology, communications, and telecommunications (ICT) systems. The NIPs agreement was a bit different from traditional research projects because it was specifically structured to enable partnerships for ESIF testing and as such required at least a 1:1 funds-in cost share from industry partners. In the end, the project engaged six different industry partnerships and resulted in testing a large number of innovative technologies. These included tiny inverters; power-to-gas technologies; and advanced simulation, analysis, and power-hardware-in-the-loop testing techniques. The agreement also provided significant impact for both research and industrial communities. This summary report provides a brief, high-level overview of these projects and their highlights along with lists of citations and other impacts. Readers are referred to the corresponding project reports for more in-depth information.

14 SOLAR ENERGY↗