Results for “battery inverter”

DOE OSTI2023

Battery inverter experimental data

The increase in power electronic based generation sources require accurate modeling of inverters. Accurate modeling requires experimental data over wider operation range. We used 30 kW off-the-shelf grid following battery inverter in the experiments. We used controllable AC supply and controllable DC supply to emulate AC and DC side characteristics. The experiments were performed at NREL's Energy Systems Integration Facility. Inverter is tested under 100%, 75%, 50%, 25% load conditions. In the first dataset, for each operating condition, controllable AC source voltage is varied from 0.9 to 1.1 per unit (p.u) with a step value of 0.025 p.u while keeping the frequency at 60 Hz. In the second dataset, under similar load conditions (100%, 75%, 50%, 25% ), the frequency of the controllable AC source voltage was varied from 59 Hz to 61 Hz with a step value of 0.2 Hz. Voltage and frequency range is chosen based on inverter protection. Voltages and currents on DC and AC side are included in the dataset.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Power-Hardware-in-the-Loop Experiments of a Microgrid With a Grid-Forming Battery Inverter: Preprint

Microgrids continue to proliferate, and they are transitioning away from using conventional generating resources to increasingly relying on inverter-based resources (IBRs) as the voltage and frequency leaders. It is crucial to evaluate the capability of IBRs to provide microgrid stability and resilience. Hardware-in-the-loop (HIL) experiments were conducted to de-risk the field deployment of the San Diego Gas & Electric Company Borrego Springs Microgrid, where a battery inverter was upgraded with grid-forming (GFM) capability to serve as the island leader. This paper presents the HIL experimental results from an HIL test bed that uses a power-hardware-in-the-loop (PHIL) interface with a power inductor that was previously developed for PHIL simulations of microgrids where the inverters need to switch modes, i.e., between grid-following and GFM as the microgrid transitions between grid-connected and islanded operation. This paper presents more details on the interface and HIL simulation results of the planned islanding and load steps in islanded operation to show the effectiveness of the inverters in managing the voltage and frequency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Power-Hardware-in-the-Loop Experiments of a Microgrid with a Grid-Forming Battery Inverter

Microgrids continue to proliferate, and they are transitioning away from using conventional generating resources to increasingly relying on inverter-based resources (IBRs) as the voltage and frequency leaders. It is crucial to evaluate the capability of IBRs to provide microgrid stability and resilience. Hardware-in-the-loop (HIL) experiments were conducted to de-risk the field deployment of the San Diego Gas & Electric Company Borrego Springs Microgrid, where a battery inverter was upgraded with grid-forming (GFM) capability to serve as the island leader. This paper presents the HIL experimental results from an HIL test bed that uses a power-hardware-in-the-loop (PHIL) interface with a power inductor that was previously developed for PHIL simulations of microgrids where the inverters need to switch modes, i.e., between grid-following and GFM as the microgrid transitions between grid-connected and islanded operation. This paper presents more details on the interface and HIL simulation results of the planned islanding and load steps in islanded operation to show the effectiveness of the inverters in managing the voltage and frequency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Study of Inverter Control Strategies on the Stability of Low-Inertia Microgrid Systems

This paper investigates the stability of low-inertia microgrid systems with two control strategies that have different percentages of grid-forming (GFM) inverters. The first control strategy has approximately 50% GFM inverters, and all the battery inverters are working in GFM control mode. Originally, the second control strategy has approximately 10% GFM inverters, with only two battery inverters working in GFM control mode and the rest working in grid-following (GFL) PQ control mode based on current control, which cannot stabilize the microgrid system. Then, the second control strategy is modified to change the GFM inverters from droop control to isochronous control and the GFL battery inverters from traditional current control to voltage control for power control. Both control strategies can maintain system stability; however, the first control strategy can better handle contingency events. The study indicates that 1) a microgrid system with a higher percentage of GFM inverters has better stability; and 2) a microgrid with a lower percentage of GFM inverters can have poor stability, but improved control strategies in inverters can improve system stability. This study improves the understanding of how different percentages of GFM inverters and inverter control strategies affect the system stability of low-inertia microgrids.

droop control↗

DOE OSTI2022

Study of Inverter Control Strategies on the Stability of Low-Inertia Microgrid Systems: Preprint

This paper investigates the stability of low-inertia microgrid systems with two control strategies that have different percentages of grid-forming (GFM) inverters. The first control strategy has approximately 50% GFM inverters, and all the battery inverters are working in GFM control mode. Originally, the second control strategy has approximately 10% GFM inverters, with only two battery inverters working in GFM control mode and the rest working in grid-following (GFL) PQ control mode based on current control, which cannot stabilize the microgrid system. Then, the second control strategy is modified to change the GFM inverters from droop control to isochronous control and the GFL battery inverters from traditional current control to voltage control for power control. Both control strategies can maintain system stability; however, the first control strategy can better handle contingency events. The study indicates that 1) a microgrid system with a higher percentage of GFM inverters has better stability; and 2) a microgrid with a lower percentage of GFM inverters can have poor stability, but improved control strategies in inverters can improve system stability. This study improves the understanding of how different percentages of GFM inverters and inverter control strategies affect the system stability of low-inertia microgrids.

droop control↗

DOE OSTI2022

Study of Inverter Control Strategies on the Stability of Low-Inertia Microgrid Systems

This paper investigates the stability of low-inertia microgrid systems with two control strategies that have different percentages of grid-forming (GFM) inverters. The first control strategy has approximately 50% GFM inverters, and all the battery inverters are working in GFM control mode. Originally, the second control strategy has approximately 10% GFM inverters, with only two battery inverters working in GFM control mode and the rest working in grid-following (GFL) PQ control mode based on current control, which cannot stabilize the microgrid system. Then, the second control strategy is modified to change the GFM inverters from droop control to isochronous control and the GFL battery inverters from traditional current control to voltage control for power control. Both control strategies can maintain system stability; however, the first control strategy can better handle contingency events. The study indicates that 1) a microgrid system with a higher percentage of GFM inverters has better stability; and 2) a microgrid with a lower percentage of GFM inverters can have poor stability, but improved control strategies in inverters can improve system stability. This study improves the understanding of how different percentages of GFM inverters and inverter control strategies affect the system stability of low-inertia microgrids.

droop control↗

DOE OSTI2025

Scalable Ultra Power-Dense Extended Range (SUPER) Inverter (Final Technical Report)

Battery electric vehicles have gained significant ground in the high-volume vehicle sales arena. However, this is a rapidly evolving marketplace, and refined technologies for the next generation of electric drives are already at an advanced stage of development. Therefore, we can expect to see the major components – batteries, inverters, and electric motors – reduce further in size yet become even safer and more efficient in operation.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Stabilizing Inverter-Based Transmission Systems: Power Hardware-in-the-Loop Experiments with a Megawatt-Scale Grid-Forming Inverter

This article presents what the authors believe to be the first experimental verification of the ability of grid-forming (GFM) inverters to stabilize a transmission electric power system that is otherwise unstable. The experiments described here were performed using power hardware-in-the-loop (PHIL) simulation to connect a megawatt-scale battery inverter to a real-time electromagnetic transient (EMT) simulation of the near-future Maui power system. This allows the dynamic interactions between the inverter and the power system to be observed without putting the real power system at risk. The ability to use the actual inverter hardware removes the need to rely on a computer model approximation of the inverter's behavior.

electromagnetic transient simulations↗

DOE OSTI2025

Interoperable, Inverter - Based Distributed Energy Resources Enable 100% Renewable and Resilient Utility Microgrids

As microgrids transition away from use of conventional generating resources and increasingly rely on renewable resources towards decarbonization goals, it is crucial to evaluate the capability inverter-based resources to provide microgrid stability and resilience. Particularly, microgrids with a high contribution of intermittent solar photo voltaic generation and higher load variability present unique challenges requiring fast voltage and frequency support. At the San Diego Gas & Electric Company(R) (SDG&E(R)) Borrego Springs Microgrid, a battery inverter was upgraded with grid-forming (GFM) capability to serve as island leader, transitioning responsibility away from diesel generators. An interoperable microgrid control scheme was developed, coordinating GFM and grid-following (GFL) inverters. Hardware-in-the-loop (HIL) simulations using relevant power and controller HIL interfaces between real-time simulators and field equipment are being conducted to de-risk field deployment.

battery energy storage↗

DOE OSTI2022

A High-Voltage High-Reliability Scalable Architecture for Electric Vehicle Power Electronics (Final Report)

This project developed and demonstrated new composite converter technologies that lead to high power density (> 20 kW/L) at power levels of 10s of kW, 100s of kW, or possibly higher, with fundamental advances in converter efficiency and Q that lead to substantial increases in mean time to failure (MTTF). These advantages were realized through development of new composite converter topologies that perform buck, boost, or other conversion functions and that are scalable to higher voltage and power levels through sharing of voltage and current stresses among multiple dissimilar partial-power converter modules. The project led to experimental demonstration of a125 kW multifunction electric vehicle power conversion system having in-creased dc bus voltage (950 V nominal, 1200 V peak) that interfaces a 200 V to 400 V battery pack, and that includes integrated level 2 wired charging and wireless charging functions. The project incorporated SiC MOSFET modules having switching frequencies in excess of 100 kHz, planar magnetics, a hierarchical control architecture that enables scaling to higher voltages and powers with additional converter modules, and a high-power density in excess of 20 kW/L. The research demonstrated how a more complex converter approach can increase mean-time-to-failure, even though the number of elements is increased. This is achieved through significant reduction of temperature rise through fundamentally superior converter circuit topologies. The research also demonstrated new high power planar magnetics that increase power density. The technology is appropriate to a variety of applications including EV power trains, EV charging, PV inverters, battery storage, and similar areas. These systems potentially can be manufactured in the U.S.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2025

Securing the Modern Grid: Federal Investments, Digitization, and Supply Chain Strategy

Across the United States (U.S.) grid expansion and modernization is underway, paving the way for accelerated load growth and intelligent resource management. Digitization of the grid is supported by several state and federal programs, providing support for utilities installing advanced metering infrastructure (AMI), AI-powered analytics systems, battery energy storage systems (BESS), and distributed energy resource management systems (DERMS) to transform the grid from a one-way power delivery system into an intelligent, responsive network that will enable faster load growth and power expansion of data centers for advanced artificial intelligence (AI) applications. The digital transformation of America's grid presents opportunity for increased efficiency and resiliency but also introduces new digital risks that require careful management. Digital equipment often contains several vulnerabilities such as unencrypted communication protocols, and persistent remote access capabilities that could be exploited to manipulate device settings, coordinate service disruptions, or inject false data into grid operations. These digital risks become particularly important as the grid must rapidly scale to support AI-driven data centers, which the administration has identified as essential for maintaining U.S. technological leadership and economic competitiveness. These vulnerabilities are compounded by supply chain realities: Chinese manufacturers currently produce 70-90% of essential grid components including inverters, batteries, and control systems, with the U.S. lacking domestic manufacturing capacity for critical assets like extra-high voltage transformers. Recent federal legislation has established Foreign Entity of Concern (FEOC) restrictions to address these risks, requiring projects to achieve escalating thresholds of non-FEOC content to receive tax credits while utilities work to expand sourcing channels for their supply chains and strengthen security measures. These restrictions arrive precisely when utilities face unprecedented electricity demand growth driven by the rapid growth in data centers, creating a considerable challenge: rapidly expanding infrastructure while navigating complex compliance requirements while lacking viable alternatives for many critical components. Idaho National Laboratory (INL) and its partners have developed practical approaches to help utilities navigate these intersecting challenges as they leverage federal investment to strengthen and grow the grid. These solutions include Cyber-Informed Engineering (CIE) principles that build resilience directly into systems, the Cirrus tool for secure cloud migration, and enhanced procurement guidance that embeds security requirements throughout equipment lifecycles. Federal initiatives, such as the Technical Assistance for Digital Assurance (TADA) project, provide direct support to utilities implementing these approaches while facilitating knowledge sharing across the industry. While these tools and frameworks cannot eliminate all risks inherent in foreign supply chain dependencies, they offer pragmatic pathways for strengthening security posture without sacrificing the deployment momentum essential to meeting surging electricity demand. Ultimately, securing America's digital energy infrastructure demands dedicated coordination across multiple fronts: building domestic supply chains, implementing robust digital assurance practices, and maintaining the aggressive modernization timeline necessary for reliability, resilience, and energy independence.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Development and testing of residential micro-CHP powered by opposed piston engine (CRADA Final Report)

A micro–combined heat and power (mCHP) prototype powered by innovative opposed piston engine technology was developed to simultaneously provide electricity and heat to residential or light commercial buildings. The mCHP prototype targeted at residential applications includes an opposed-piston four-stroke (OP4S) engine, generator, rectifier, inverter, battery energy storage system, 52 gal water tank, and application accessories for hot water supply and space heating. The OP4S engine can use renewable or regular natural gas, as well as hydrogen, to generate mechanical power and waste heat in form of hot coolant and exhaust gas simultaneously. The waste heat is recovered and stored in the water tank and can be used as a regular hot water supply and/or for space heating application. The tests show that the mCHP prototype enabled power outputs in the range of 3.2 –7.4 kW with up to 26.4% of AC electricity efficiency and up to 93.1% of the overall mCHP efficiency under stoichiometric combustion modes λ=~1.0. The mCHP was also run under lean combustion mode conditions at λ=~1.3. The lean mode operation enables more than 30% improvement in electrical energy efficiency. The maximum AC efficiency of the lean combustion mode attained was 35.2%, with the engine efficiency is approaching 40%. The exceptional electrical efficiency breaks the typical upper boundary of 30% for ICE-based mCHP. The engine exhaust temperatures in the lean modes are substantially less than in the stoichiometric modes. Moreover, the lean cases achieve high overall mCHP efficiencies: the overall mCHP efficiencies are all greater than 93%. Considering the mCHP prototype can achieve low-cost, flexible matching of thermal and electrical loads through reducing the complexity of distribution and installation, and high efficiency the novel technology will promote mCHP acceptance in the US residential and light commercial markets.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

A Comprehensive Strategy for Grid Forming Control in DC Coupled Photovoltaic and Battery Energy Storage Inverters

This paper presents an integrated DC-DC and DCAC grid-forming control strategy for DC-coupled photovoltaic (PV) plus battery energy storage systems, considering the effect of DC link voltage variations caused by direct PV connections. A power reference algorithm determines power distribution between the PV and battery to the grid while observing device power ratings to prevent the over-rating of components and keep the battery's state of charge within an acceptable range. The simulated utility-scale model in MATLAB/Simulink illustrates its ability against extreme phase angle variation contingencies in the grid while controlled through grid-forming control with a fast dynamic on DC link voltage. The simulation results confirm the effectiveness of the proposed control in integrating PV plus battery configurations with grid forming control and maintaining reliable grid operation under severe grid disturbances.

battery, boost, control, energy storage, grid form↗

DOE OSTI2023

A Robust Method to Secure Multi-Inverter Grid Tied PV and Battery Energy Storage Systems Against Cyber Intrusions

This paper details a robust method to secure a multi-inverter grid tied system that interfaces photovoltaic (PV) and battery energy storage against potential cyber-attacks. The method can be applied to any third-party inverter systems without a need to modify their internal controls. A small random private excitation signal termed "watermark" is injected into the DC input voltage terminals (via a series transformer) connected to the PV/battery inverter system. An external robust cyber intrusion detector (CID) hardware consisting of a digital signal processor (DSP) generates the "watermark" and also receives the sensor signals that control the setpoints of the PV/battery grid tied system. The CID algorithm is shown to detect all possible cyber intrusions (such as false data injection(FDI)) on external sensor signals such as P and Q measured by a smart meter that control the overall system operation. The proposed CID computes online system ID and two variance tests in real time on each sensor signal and is able pinpoint intrusion location in a multi-inverter system. Results on a hardware in the loop (HIL) of a two-inverter grid connected system demonstrate effectiveness of the proposed CID system for FDI and unobservable FDI. Test results on a laboratory prototype will be discussed in the conference presentation.

Ibrahim, Hasan↗

DOE OSTI2023

Validation of the Fault Ride-Through Response of a Generic EMT Inverter Model by Laboratory Testing

This paper presents the validation of the fault ride-through response of a large-scale inverter model using laboratory testing of a commercial inverter. First, we present the generic inverter model specifications. The generic inverter control is developed based on the fault ride-through response performance requirements of IEEE Std 2800-2022 for inverter-based resources. Next, we present laboratory tests that emulate voltages at the inverter terminal resulting from balanced and unbalanced faults on the transmission system. The tests are performed on a commercia12.2 MVA battery storage inverter at the U.S. National Renewable Energy Laboratory. Comparisons of the model's response to the laboratory measurements show the generic model presented can predict the controlled response of the commercial equipment. The differences between the model's response and the laboratory measurements during the initial transient at fault inception are discussed.

fault ride-through↗

DOE OSTI2023

Two-Stage Deep Reinforcement Learning for Distribution System Voltage Regulation and Peak Load Management

The growing integration of distributed solar photovoltaic (PV) in distribution systems could result in adverse effects during grid operation. This paper develops a two-agent soft actor critic-based deep reinforcement learning (SAC-DRL) solution to simultaneously control PV inverters and battery energy storage systems for voltage regulation and peak demand reduction. The novel two-stage framework, featured with two different control agents, is applied for daytime and nighttime operations to enhance control performance. Comparison results with other control methods on a real feeder in Western Colorado demonstrate that the proposed method can provide advanced voltage regulation with modest active power curtailment and reduce peak load demand from feeder's head.

deep reinforcement learning↗

DOE OSTI2022

Transactive Campus Energy Systems: An R&D Testbed for Renewables, Integration, Efficiency, and Grid Services (CRADA 356 / Amendment 1)

The Clean Energy and Transactive Campus (CETC) work described in this report was done as part of Amendment 1 to Campus Cooperative Research and Development Agreement (CRADA) 356, the Transactive Campus CRADA with the Washington State Department of Commerce (Commerce) between the U.S. Department of Energy’s (DOE’s), Pacific Northwest National Laboratory (PNNL) and the Commerce through the Clean Energy Fund (CEF). The original project team consisted of PNNL, the University of Washington (UW) and Washington State University (WSU), to connect the PNNL, UW, and WSU campuses to construct and operate the testbed as both a regional flexibility resource and as a platform for research and development (R&D) for buildings/grid integration. Building on the foundational transactive system established by the Pacific Northwest Smart Grid Demonstration (PNWSGD), the purpose of the project was to construct the testbed as both a regional flexibility resource and as a platform for R&D on buildings/grid integration and information-based energy efficiency. The testbed supports the integration of renewables and other regional needs, using the flexibility provided by building loads, energy storage, and smart inverters for batteries and photovoltaic (PV) solar systems, at four physical scales: multiple campuses, campus, microgrid and building.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Two-Stage Deep Reinforcement Learning for Distribution System Voltage Regulation and Peak Load Management: Preprint

The growing integration of distributed solar photovoltaic (PV) in distribution systems could result in adverse effects during grid operation. This paper develops a soft actor critic-based deep reinforcement learning (SAC-DRL) solution to simultaneously control PV inverters and battery energy storage systems for voltage regulation and peak load demand shaving. The novel two-stage framework, featured with two different control agents, is applied for daytime and nighttime operation to enhance the control performance. Comparison results with other control methods on a real feeder in Western Colorado demonstrate that the proposed method can provide advanced voltage regulation with modest active power curtailment for peak demand reduction.

deep reinforcement learning↗