NREL Capabilities for TMCES
This is a panel presentation covering NREL's capabilities in the thermal-mechanical energy storage space, including ARIES, component R&D, and modeling tools and datasets.
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This is a panel presentation covering NREL's capabilities in the thermal-mechanical energy storage space, including ARIES, component R&D, and modeling tools and datasets.
As renewable energy deployment grows, hybrid power plants (HPPs) combining photovoltaic (PV) and battery systems must evolve to offer both energy and grid stability services. These systems typically include a mix of grid-following (GFL) and grid-forming (GFM) inverters, presenting unique coordination and control challenges. This Department of Energy–funded project developed and validated a Unified Universal Control and Coordination (UUCC) framework for such PV + battery hybrid plants, enabling seamless and stable operation, including ultrafast black start, autonomous synchronization, and robust frequency and voltage regulation, under different grid conditions. The project significantly advanced the understanding of inverter-based resource (IBR) control by developing and validating three complementary system-level approaches for hybrid GFL/GFM operation: 1. A combined Virtual Resistance (VR)-based GFL and Virtual Oscillator Control (VOC)-based GFM method, where each inverter type is governed by a specialized control strategy. Together, these achieve stable, fast-response coordination, eliminating inrush current and enabling smooth black start and grid synchronization across a wide range of grid strengths. 2. A Deadbeat-based UUCC strategy, which uses discrete-time, switching-cycle-level control for both GFL and GFM inverters. This approach replaces traditional PI/PLL control with a control parameter-free, high-bandwidth framework that supports stable LVRT and instantaneous synchronization under all conditions. 3. A benchmark comparison with Siemens’ commercial GFM microgrid controller, which provided a fast baseline platform. The commercial approach decoupled v & f control was implemented on a commercial microgrid controller.The baseline commercial benchmark helped highlight superior transient response and black start performance offered by the deadbeat and VOC approaches. These technical contributions offer substantial improvements over conventional inverter control schemes, which often rely on slow phase-locked loop (PLL)-based synchronization, require careful control parameters tuning, and prone to unstable in weak grids with GFL inverters and in stiff grid with GFM inverters therefore challenging for hybrid GFL+GFM under all grid conditions. The deadbeat-based UUCC framework enables simpler, faster, and more robust operation of hybrid IBR systems using wide-bandgap (WBG) devices such as SiC power semiconductors. The rapid expansion of hybrid distributed energy resources (DERs), including residential and commercial PV-BESS installations such as Tesla Powerwall, PV with vehicle-to-grid (V2G) capability, and other integrated configurations, presents complex operational challenges for medium-voltage radial distribution feeders. These networks are subject to frequent disturbances such as faults, switching operations, rapid reclosing sequences, and feeder reconfigurations, all of which introduce dynamic stress on IBRs. In addition, planned feeder segmentation and deliberate islanding for resilience will require DERs that can autonomously perform blackstart, establish voltage and frequency references, and resynchronize with the main grid. The advanced deadbeat-based UUCC control and blackstart functionalities developed in this project directly address these requirements, enabling decentralized and autonomous operation of inverter-dominated DERs in distribution systems under a wide range of fault and reconfiguration scenarios. From a public benefit perspective, these innovations enable more reliable and cost-effective integration of renewable energy into distribution networks. The ability to autonomously black start and stabilize grids under varying grid conditions support accelerates recovery from outages and support decentralized resilient energy systems. By reducing system complexity and improving performance, this project lays critical groundwork for future inverter-dominated power grids that are clean, reliable, and accessible to all.
Hydropower technologies bolster high penetration of variable renewable energies (VREs) in the net zero emissions scenarios. Nevertheless, there are various challenges to meeting the ambitious goal, such as stability, reliability, resiliency, security, lack of reactive power, voltage support and inertia, large-scale storage deployment and coordination, interconnectedness, demand-side response, higher thermal cycles with increased start/stops, and inadequate Levelized Cost of Energy (LCOE) for system-wise VRE integration and profitability. This survey conducts a bottom-up analysis to unveil the opportunities to utilize hydropower facilities and disentangle the nested problem for intertwining design features, control algorithms, operation, optimization approaches, incentives, services, and market mechanisms using a three-pillar framework perspective: grid owners, power producers, and machine designers. The survey identified emerging trends in real-time and capacity markets, flexible power systems, and enhanced grid capabilities, including advanced voltage support and updated grid codes. These developments present significant opportunities for hydropower, such as achieving super-flexibility through hybridization, expanded reactive power capabilities, and advanced operational modes like a synchronous condenser and power adequator functionalities. These opportunities require novel design philosophies — including new winding, stator, and rotor configurations, optimized ventilation, and active cooling systems — to enhance performance under stressed grid and climate conditions. Finally, integrating climate and energy models for multi-basin optimization with finer spatial and temporal granularity enhances the planning accuracy for water management of hydropower while addressing environmental challenges. The review delivers helpful prospective suggestions and tools that would serve researchers, power engineers, and stakeholders in making decisions about hydropower technologies and services in 2050 and beyond.
Seaports are vital economic hubs that allow the United States to compete on a global scale. But the heavy vehicles and cargo equipment that enable their operations also emit harmful air pollutants and greenhouse gas emissions. For nearly two decades, National Renewable Energy Laboratory (NREL) researchers have worked toward comprehensive seaport decarbonization. They fuse world-class analysis with deep vehicle and transportation systems knowledge to guide strategic deployment of low- and zero-emissions vehicles, charging and refueling infrastructure, and grid improvements. Together, these capabilities can enable sustainable port operations. This fact sheet outlines major seaport and airport decarbonization capabilities across the laboratory, including: fleet research, energy data, and insights for decarbonization; comprehensive hydrogen infrastructure deployment; optimized charging through grid integration; strategic blueprinting for clean, optimized technology deployment; and integrating diversity, equity, inclusion, and accessibility considerations into decarbonization efforts.
The following article details a model predictive control (MPC) to improve grid resilience when faced with variable generation resources. This topic is of significant interest to utility power systems where distributed intermittent energy sources will increase significantly and be relied on for electric grid ancillary services. Previous work on MPCs has focused on narrowly targeted control applications such as improving electric vehicle (EV) charging infrastructure or reducing the cost of integrating Energy Storage Systems (ESSs) into the grid. In contrast, this article develops a comprehensive treatment of the construction of an MPC tailored to electric grids and then applies it integration of intermittent energy resources. To accomplish this, the following article includes a description of a reduced order model (ROM) of an electric power grid based on a circuit model, an optimization formulation that describes the MPC, a collocation method for solving linear time-dependent differential algebraic equations (DAEs) that result from the ROM, and an overall strategy for iteratively refining the behavior of the MPC. Next, the algorithm is validated using two separate numerical experiments. First, the algorithm is compared to an existing MPC code and the results are verified by a numerically precise simulation. It is shown that this algorithm produces a control comparable to existing algorithms and the behavior of the control carefully respects the bounds specified. Second, the MPC is applied to a small nine bus system that contains a mix of turbine-spinning-machine-based and intermittent generation in order to demonstrate the algorithm’s utility for resource planning and control of intermittent resources. This study demonstrates how the MPC can be tuned to change the behavior of the control, which can then assist with the integration of intermittent resources into the grid. The emphasis throughout the paper is to provide systematic treatment of the topic and produce a novel nonlinear control compatible design framework applicable to electric grids and the control of variable resources. This differs from the more targeted application-based focus in most presentations.
The combination of increased electric load growth across all sectors, deferred electrical infrastructure investment, and other factors resulting in variable electric power supply, has created technical challenges to maintaining a resilient and reliable grid. Many federal, regional, and local efforts are in play to modernize the electric grid, including advancing building technologies and distributed energy resources (DERs) that are utilizing smarter controls to become responsive to both occupant and grid needs. This report reviews ten pilot projects demonstrating how groups of buildings combined with behind-the-meter (BTM) DERs such as electric vehicle (EV) charging, battery storage, flexible HVAC and domestic hot water systems, and photovoltaic systems can reliably and cost effectively provide grid services. Each of the ten pilot projects aim to deliver both energy efficiency and demand flexibility (DF) while supporting load growth. The ten demonstration teams are piloting flexible DER packages across diverse communities of residential and commercial buildings to address a variety of regional grid needs. The outcomes of these pilot projects will be used to inform future scaling through utility program development. This paper characterizes the ten teams, showcasing the decision-making process used by each group to develop their packages (Section 2), the grid services they plan to deliver (Section 3), the types of DER packages selected for deployment within building sectors (Section 4) and trends between building sector, DER types, and grid services In order to achieve community scale benefits, the pilot projects must utilize aggregated control mechanisms for coordinating buildings and DERs together. Several types of coordinated control architectures have evolved amongst the teams, influenced by use type, existing market conditions, and integration type. Three coordinated controls architectures have been characterized, highlighting their use cases, benefits, challenges, and tradeoffs in their design. These insights can aid utilities, control vendors, and developers in scaling community-level energy systems (Paul, 2024). Ultimately, the technology packages selected by the ten teams will be coordinated to provide power system services, also known as grid services. Insights from these demonstrations will be useful for grid operators, regulators, aggregators and other stakeholders as they look to deploy demand flexible resources as grid services in the future. The grid services that each team is targeting for demonstration are described in Section 3 and Section 4. Methods for evaluating the grid services have been described in the paper Metrics for Evaluating Grid Service Provision from Communities of Grid-interactive and Efficient Buildings and other DER (MacDonald, 2023). To identify technology packages for demonstration, Section 2 shows that project teams used a range of analysis approaches, including building energy modeling, AMI data analysis, cost-benefit frameworks, and utility pilot data. Some teams emphasized technical modeling to quantify grid impacts and demand reduction potential, while others prioritized economic evaluations, stakeholder input, or exploratory pilots to inform deployment decisions. This diversity reflects the need to tailor selection methods to project goals, available data, and organizational context. Section 5 discusses trends between the DER technologies deployed and the grid service provisions from each team. Residential buildings (multifamily and single family) lean towards technologies that enhance energy efficiency (e.g. weatherization upgrades, smart thermostats) and onsite power generation integration (e.g. solar PV). Commercial building demonstrations prioritize technologies that ensure operational reliability (e.g. battery storage) and centralized energy management systems and optimization solutions. Teams that are deploying controllable storage-based technologies are more likely to provide grid services that require a near real-time response. Teams incorporating load shifting technologies like smart thermostats with HEMs are likely to include energy markets participation and customer bill management offerings. Campus demonstrations are adopting diverse sets of DERs to emphasize renewable generation, paired with centralized control. This section also describes technologies that were considered during project planning but ultimately excluded from final deployment. These demonstrations reveal that effective DER package design should be tailored to building type, customer segment, and construction vintage. Multifamily buildings benefit from centralized HVAC upgrades and supervisory controls, while single-family homes are well-suited for individualized technologies like solar, storage, and smart home energy monitors. Commercial and campus settings prioritize EMIS integration and load optimization. New construction enables cost-effective integration of DER-ready infrastructure, whereas retrofits require deployments aligned with owner and tenant value streams. For utility program planners, early coordination with developers and building owners, paired with segmented and modular program offerings, can improve adoption, scalability, and grid impact.
The intermittent and stochastic nature of Renewable Energy Sources (RESs) necessitates accurate power production prediction for effective scheduling and grid management. This paper presents a comprehensive review conducted with reference to a pioneering, comprehensive, and data-driven framework proposed for solar Photovoltaic (PV) power generation prediction. The systematic and integrating framework comprises three main phases carried out by seven main comprehensive modules for addressing numerous practical difficulties of the prediction task: phase I handles the aspects related to data acquisition (module 1) and manipulation (module 2) in preparation for the development of the prediction scheme; phase II tackles the aspects associated with the development of the prediction model (module 3) and the assessment of its accuracy (module 4), including the quantification of the uncertainty (module 5); and phase III evolves towards enhancing the prediction accuracy by incorporating aspects of context change detection (module 6) and incremental learning when new data become available (module 7). This framework adeptly addresses all facets of solar PV power production prediction, bridging existing gaps and offering a comprehensive solution to inherent challenges. By seamlessly integrating these elements, our approach stands as a robust and versatile tool for enhancing the precision of solar PV power prediction in real-world applications.
Multiple US regions have announced new electricity transmission plans, are actively revisiting the future role of transmission, and could benefit from findings from recent national-scale transmission studies. A review of seven national studies shows that significant transmission expansion is cost-optimal for serving new demand, integrating additional resources, and supporting grid reliability. A majority of the reviewed scenarios, which span a range of policy and technology assumptions, include at least a doubling of the transmission system by 2050. The national studies find substantial net system cost savings from transmission expansion and high benefit-cost ratios for transmission investments. The results are derived through multi-value, nationally coordinated, co-optimized, multi-scenario modeling, which is an approach that could yield lower-cost pathways compared to current industry planning practices.
With the increasing urgency to decarbonize power systems, while mitigating extreme events, capacity expansion models can play a vital role in reliably planning the expansion of power systems and facilitating the integration of renewable energy sources. Optimizing capacity expansion generally involves selecting surrogate representative days from forecasts of load and the generation profiles of variable renewable energy resources. To properly select those representative days, we propose a novel input-based approach in combination with the k-means clustering algorithm that utilize three unique operational inputs: load shedding, renewable curtailment, and transmission congestion. The proposed method allows for more robust and cost-effective capacity planning. The method is validated using a capacity expansion model and a production cost model based on California Independent System Operator (CAISO)'s decarbonization goals, and results in reduced costs and drastically lower load shedding.
This report describes a computer-based information system designed to assist in the integration of commonly available spatial data for regional planning and resource analysis. The Resource Analysis Program (RAP) provides a variety of analytical and mapping phases for single factor or multi-factor analyses. The unique analytical and graphic capabilities of RAP are demonstrated with a study conducted in Windsor Township, Eaton County, Michigan. For this study, soil, land cover/use, topographic and geological maps were used as a data base to develop an eleven map portfolio. The major themes of the portfolio are land cover/use, nonpoint water pollution, waste disposal, and ground water recharge.
Integrated planning holds the promise of unlocking lower total system cost solutions by connecting previously siloed planning processes. This article summarizes the state of bulk and local grid planning today and details multiple new analytical approaches that can enable more holistic planning methods to develop comprehensive solutions to generation, transmission, distribution, and distributed energy resource needs. These include both iterative approaches as well as cooptimization techniques. In addition to the benefits of these methods, the technical and institutional challenges and associated solutions are also discussed.
Distributed energy resources (DERs) offer flexibility and community benefits in both blue- and black-sky conditions. Outside of a power disruption, they can provide significant cost savings and reduce grid stress during times of high demand. During a disruption to the central grid, these technologies can meet critical energy needs through the use of battery storage. However, communities must consider many planning and design dimensions and tradeoffs to integrate energy systems that meet financial and resilience goals. This presentation, given at the 2026 State Energy Conference of North Carolina, defines resilience in an energy context, discusses strategies and best practices for planning resilient energy systems and sites, including resilience hubs and microgrids, highlights NLR tools and capabilities for helping communities in this space, and features successful case studies in North Carolina related to energy resilience.
This guide was developed through the U.S. Department of Energy (DOE) Energy Transitions Initiative Partnership Project (ETIPP) technical assistance (TA) projects for Nikolski and St. George. Both communities had wind turbine projects that failed due to integration and maintenance issues. Due to these failures, Nikolski and St. George sought help to investigate renewable energy alternatives and associated integration strategies, with a focus on technologies that could be easily maintained within the community. The primary objective of this guide was to interview subject matter experts and document lessons learned to address potential renewable energy and storage integration issues in remote Alaskan communities. This guide is intended to provide information to rural Alaskan communities considering renewables with the purpose of sharing best practices and case studies to facilitate the successful implementation of future renewable energy projects.
Geothermal resources have delivered renewable electricity for more than 100 years, and renewable heat for far longer, but recent research and advancements have shown that geothermal is more than a 24/7 clean energy source. With the ability to also provide cooling and storage - plus the potential to access critical minerals, capture and sequester carbon, produce green hydrogen, and more - geothermal technologies and resources are emerging as key solutions to the climate crisis. In fiscal year 2024 (FY24), the National Renewable Energy Laboratory (NREL) broadened its research, development, demonstration, and deployment (RDD&D) portfolio and partnerships with exciting innovations such as next-generation geothermal technologies for power, geothermal energy networks for heating and cooling, subsurface thermal energy storage, well repurposing, and more. In support of the U.S. Department of Energy (DOE) Geothermal Technologies Office's (GTO) mission to increase geothermal energy deployment through research, development, and demonstration of innovative technologies that enhance exploration and production, NREL led impactful research in geothermal technologies and resources, market acceleration, and grid integration while also demonstrating leadership in the sector and increasing stakeholder engagement and outreach efforts.
United States electricity markets, planning mechanisms, and operational procedures are currently evolving in concert with three key trends. First, a range of new resources—solar, wind, energy storage, hybrid co-located storage, and distributed energy—are coming online and require new solutions to ensure they are efficiently integrated into existing systems. Second, consumers now face more opportunities to participate in markets by providing demand response and engaging in two-way interactions with the grid. Third, there is an increasing need for enhanced coordination between generation and transmission planning as well as across transmission and distribution systems.
Efficient and reliable scheduling of maintenance for power generation and transmission infrastructure is essential for minimizing operational costs and ensuring grid stability. This paper introduces an integrated optimization framework for coordinated maintenance scheduling of generators and transmission lines under resource and reliability constraints. The model minimizes a composite cost function including maintenance and generation costs, as well as penalties for delayed maintenance, while satisfying N−1 security constraints, operational limits, and crew availability. Case studies on the IEEE 300-bus test system demonstrate the effectiveness of the proposed approach in producing feasible and cost-effective maintenance schedules. To address scalability and combinatorial complexity, the model is mapped into a Quadratic Unconstrained Binary Optimization (QUBO) problem, enabling exploration of solution approaches based on Quantum Imaginary Time Evolution (QITE). While the QUBO reformulation provides a foundation for future quantum-inspired optimization, this study focuses primarily on the development and demonstration of the classical optimization framework and illustrates the potential applicability of QITE in large-scale maintenance scheduling.
To meet 2050 decarbonization targets, widespread building electrification is a critical complement to clean power generation. Behind-the-meter storage (BTMS) (e.g., battery electric energy storage [EES] and thermal energy storage [TES]) integrated with buildings or building end uses to store and supply energy at optimal times can minimize burdens associated with operation, planning, and upgrades to the electrical grid sometimes triggered by building electrification. Such BTMS systems can serve the dual purpose of providing enhanced resilience at the building and grid level, and support the deployment of renewable generation needed for wide-scale decarbonization. While TES can cost-effectively shed and shift thermal loads, it cannot generally backup or shift non-thermal building end uses. EES, by contrast, is more expensive, but applicable to all end uses (i.e., thermal and electrical loads). Combined together, these storage systems can be traded off against one another to perform optimally in meeting demand flexibility, decarbonization goals, and energy resilience of the buildings at a lower total system cost. This paper proposes a framework to define BTMS benefits, provides four illustrative electrification scenarios using TES and EES, and discusses the combined TES/EES benefits with building energy modeling results. The paper also highlights potential barriers to adoption of BTMS and a path forward.
A computer-based information system is described designed to assist in the integration of commonly available spatial data for regional planning and resource analysis. The Resource Analysis Program (RAP) provides a variety of analytical and mapping phases for single factor or multi-factor analyses. The unique analytical and graphic capabilities of RAP are demonstrated with a study conducted in Windsor Township, Eaton County, Michigan. Soil, land cover/use, topographic and geological maps were used as a data base to develope an eleven map portfolio. The major themes of the portfolio are land cover/use, non-point water pollution, waste disposal, and ground water recharge.