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DOE OSTI2021

Methods and systems for syngas production and for efficient, flexible energy generation

Methods for producing syngas (e.g., H2 and CO) include introducing a stream comprising H2O and CO2 to a high-temperature co-electrolysis (HTCE) unit. A CO2 sweep gas is also introduced to the HTCE unit. Both H2O and CO2 are reduced in the HTCE unit to form the syngas and to form O2 that is swept away from the HTCE unit by the CO2 sweep gas, and the O2 and CO2 are then introduced to a combustion device (e.g., a gasifier), which may be configured to generate electrical power, as a result of combusting a carbonaceous fuel in the presence of the O2 and CO2. The HTCE unit is powered at least in part by power from an electricity-generating sub-system (e.g., at least one nuclear power plant). Related systems are also disclosed.

O'Brien, James E.↗

DOE OSTI2023

Flexible wave energy converter

Disclosed herein are flexible wave energy converters that actuate electrical generators with dynamic strain (e.g., flexing, stretching, twisting, distension) to convert wave energy to electrical energy. The flexible wave energy converter utilizes flexible electric generators embedded throughout the wave-energy converter's flexible body.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2022

Flexible wave energy converter

16 TIDAL AND WAVE POWER↗

DOE OSTI2020

Flexible Nuclear Energy for Clean Energy Systems

As part of the Nuclear Innovation: Clean Energy Future initiative, this report describes flexibility in nuclear systems, the value it can bring, and international experiences surrounding flexible nuclear energy. Flexible nuclear energy for this report is defined as “The ability of nuclear energy generation to economically provide energy services at the time and location they are needed by end-users. These energy services can include both electric and non-electric applications utilizing both traditional nuclear power plants and advanced integrated systems.” Flexibility in nuclear systems is enabled by three main mechanisms: core ramping, integrated energy systems with multiple byproducts, and thermal storage. The value of this flexibility on a $\$$/MW and a $\$$/MWh basis can be estimated through a combination of physics and economics modeling. International agencies describe their experiences in operating flexible nuclear systems and describe their plans for increasing nuclear flexibility in a clean energy system, likely with a high penetration of variable renewable energy.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

Flexible Nuclear Energy for Clean Energy Systems

Clean low-emission energy systems will increasingly need flexible energy technologies tailored for an individual country's energy resources, infrastructure, and social objectives. While solutions may be unique, the diversity of experience from various countries can help create innovative approaches. Hybrid renewable and flexible nuclear energy systems are a solution explored by the countries and organizations of the Nuclear Innovation: Clean Energy Future (NICE Future) initiative of the Clean Energy Ministerial. We found that operational, product, and deployment flexibility could help expand clean energy systems globally.

Clean Energy Ministerial↗

DOE OSTI2026

Hybrid Power Purchase Agreements for Flexible 24/7 Energy Delivery – A Comprehensive Review of Current Practices and Research Pathways

Power Purchase Agreements (PPAs) are becoming increasingly preferred among large energy consumers, such as data centers, to secure cost-effective energy and meet accelerating demand growth. Traditionally, variable renewable energy (VRE)-based PPAs operate on a pay-as-produced basis, balancing supply and demand for a relatively longer duration (e.g., annually). However, the focus is shifting toward matching supply and demand on an hourly basis to fully meet energy needs. This shift requires the integration of flexible energy resources, such as hydropower, thermal generation, and energy storage, to complement VRE sources like wind and solar, forming the foundation for 24/7 PPA. This work contributes by: (i) reviewing emerging market trends and current practices in PPA procurement, supported by data on PPA prices and technology portfolios; (ii) synthesizing the existing literature on modeling approaches for contract pricing, quantities, hybrid resource procurement, and risk management in 24/7 PPA design, while identifying key research gaps; and (iii) proposing an integrated 24/7 PPA design framework along with two contracting mechanisms from the perspectives of both PPA providers and consumers. The proposed framework highlights critical modeling challenges, risk-allocation issues, and future research opportunities for 24/7 PPA design.

24/7↗

DOE OSTI2021

Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency

Behind-the-meter distributed energy resources (DERs), including building solar photovoltaic (PV) technology and electric battery storage, are increasingly being considered as solutions to support carbon reduction goals and increase grid reliability and resiliency. However, dynamic control of these resources in concert with traditional building loads, to effect efficiency and demand flexibility, is not yet commonplace in commercial control products. Traditional rule-based control algorithms do not offer integrated closed-loop control to optimize across systems, and most often, PV and battery systems are operated for energy arbitrage and demand charge management, and not for the provision of grid services. More advanced control approaches, such as MPC control have not been widely adopted in industry because they require significant expertise to develop and deploy. Recent advances in deep reinforcement learning (DRL) offer a promising option to optimize the operation of DER systems and building loads with reduced setup effort. However, there are limited studies that evaluate the efficacy of these methods to control multiple building subsystems simultaneously. Additionally, most of the research has been conducted in simulated environments as opposed to real buildings. This paper proposes a DRL approach that uses a deep deterministic policy gradient algorithm for integrated control of HVAC and electric battery storage systems in the presence of on-site PV generation. The DRL algorithm, trained on synthetic data, was deployed in a physical test building and evaluated against a baseline that uses the current best-in-class rule-based control strategies. Performance in delivering energy efficiency, load shift, and load shed was tested using price-based signals. The results showed that the DRL-based controller can produce cost savings of up to 39.6% as compared to the baseline controller, while maintaining similar thermal comfort in the building. The project team has also integrated the simulation components developed during this work as an OpenAIGym environment and made it publicly available so that prospective DRL researchers can leverage this environment to evaluate alternate DRL algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Building and grid system benefits of demand flexibility and energy efficiency

The global electricity system is undergoing a dramatic transformation. Technology advancements in clean energy generation (e.g., solar photovoltaics and wind) and electrified demand (e.g., transportation and building heating) are providing a cost-competitive pathway to mitigate the urgent and severe consequences associated with a changing climate. In addition, as extreme events continue to increase in frequency and magnitude, solutions are needed for adapting to the current climate. Through energy efficiency and demand flexibility, buildings play a prominent role in meeting these challenges; recently in Joule, a paper by Langevin et al. provides clear insight into the magnitude of buildings’ technical potential.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

WBS: 2.2.1.407 Flexible Wave Energy Converters (FlexWEC)

Using distributed embedded energy converters (DEECs) to create flexible ocean wave energy converters (flexWECs), could revolutionize how we conceptualize ocean wave energy conversion and how we view and evaluate ocean waves as a viable source of renewable energy. Nevertheless, flexWEC research and development is nascent in nature and needs greater understanding and evaluation of its potential. The overall goals of this project, therefore, are to understand the scientific and engineering merit of flexWECs and to assess how flexWECs could be best utilized to create effective and viable converters of marine renewable energy.

DEEC-Tec↗

DOE OSTI2021

Actions to Enable Flexible Nuclear Energy

This fact sheet includes key findings and possible actions identified by the Nuclear Innovation: Clean Energy Future (NICE Future) initiative’s Flexible Nuclear Campaign (FNC).

ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Hierarchical Flexibility Offering Strategy for Integrated Hybrid Resources in Real-time Energy Markets

This paper proposes a hierarchical model for determining the energy flexibility offering strategy of integrated hybrid resources (IHRs) in power distribution systems to participate in real-time energy markets. The proposed model utilizes the scalability, fast response time, and uncertainty observation of deep reinforcement learning (DRL) to overcome the scalability issue of operating numerous flexible resources and deliverability of energy flexibility to the real-time markets in the presence of the network constraints. To that end, the power distribution system is divided into multiple IHRs, where different types of flexible loads, energy storage systems, and solar plants with controllable inverters are operated through local IHR controllers, trained by deep deterministic policy gradient (DDPG) algorithm. Active power request and reactive power capacity of IHRs are then transmitted to a central flexibility controller, where a quadratic optimization model ensures the deliverability of the energy flexibility to the real-time energy market by satisfying the distribution network constraints. The proposed model is implemented on the 123-bus test power distribution system, demonstrating the capability of DRL-based hierarchical model for scalable operation of IHRs in order to offer deliverable energy flexibility to the real-time energy market.

Majidi, Majid↗

DOE OSTI2022

Vehicle-to-manufacturing (V2M) system: A novel approach to improve energy demand flexibility for demand response towards sustainable manufacturing

The U.S. manufacturing sector accounts for 77% of the industrial energy consumption, but its participation in demand response (DR) programs is largely lagged behind. The limited flexibility in production scheduling under high capacity utilization and the lack of DR schemes that incorporate energy demand flexibility measures are deemed as major barriers. In this study, a framework of the interactive vehicles-to-manufacturing (V2M) energy sharing system is proposed to improve the energy demand flexibility of the aggregated system and enhance the DR effectiveness for manufacturers. The V2M-based DR scheme aims to reduce the energy cost by load shifting through joint production and energy sharing control, which can eventually promote manufacturing DR implementation even under high capacity utilization requirements and dynamic real-time electricity prices. The V2M system is modeled based on a discrete-Markov chain considering the complex interconnections among various manufacturing resources and multi-directional energy flows among manufacturing facilities, electric vehicles, and the power grid. Based on the system model, a mixed-integer nonlinear programming (MINLP) problem is formulated to identify the optimal DR scheme. The effectiveness of the proposed approach is validated through comparisons with traditional manufacturing DR schemes. Finally, the results show that a 2.1 to 6.5 times energy demand flexibility improvement and an additional 4.7% to 6.9% energy cost reduction can be achieved by the proposed approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Ultrahigh-power-density flexible piezoelectric energy harvester based on freestanding ferroelectric oxide thin films

Flexible piezoelectric nanogenerators are emerging as a promising solution for powering next-generation flexible electronics by converting mechanical energy into electrical energy. However, traditional ferroelectric ceramics, despite their excellent piezoelectric properties, lack flexibility; while piezoelectric polymers, although highly flexible, have low piezoelectricity. The quest to develop materials that combine high piezoelectricity with exceptional flexibility has thus become a research focus. Herein, we present a breakthrough in this field with the fabrication of freestanding (111)-oriented PbZr 0.52 Ti 0.48 O 3 single crystalline thin films, which exhibit remarkable flexibility and a high converse piezoelectric coefficient (~585 pm/V). This is achieved through water-soluble sacrificial layer to relieve substrate clamping and controlling the crystal orientation to further enhance the piezoelectric response. Our nanogenerators, constructed using these freestanding nanoscale membranes, demonstrate a record-high output power density (~63.5 mW/cm 3 ), excellent flexibility (with a strain tolerance >3.4%), and superior mechanical stability in cycling tests (>60,000 cycles). These advancements pave the way for high-performance, flexible electronic devices utilizing ferroelectric oxide thin films.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Prototype and Codesign of Nascent Flexible Wave Energy Converter Concepts

Prevailing mainstream ocean wave energy converter (WEC) archetypes are often relatively large monolithic rigid bodies with singular means of power take-off (e.g., relative motion between rigid bodies) and solo prime mover mechanisms (e.g. a rotary generator, a hydraulic piston). These mainstream WEC archetypes have existed for decades with some having histories spanning more than a century of significant investments and interests. As an alternative to the domain of mainstream WEC archetypes is the domain of distributed embedded energy converter technologies (also known as DEEC-Tec). Use of DEEC-Tec to create WECs - often called flexWECs - is a nascent domain of research and development that centers itself upon the interconnection of many relatively small energy converters - very small energy transducers - that interconnect and combine to create a much larger, overall, energy converting structure. The DEEC-Tec domain enables promising possibilities such as: direct in situ ocean wave energy harvesting and conversion throughout the volume of an entire flexWEC; inherent broad-banded ocean wave energy capture and conversion arising from near semi-continuous structural degrees of freedom; an innate absence of focusing and concentrating of ocean wave energy into a single prime mover and/or transmission system; and built-in implicit redundancy. As such, the DEEC-Tec domain could revolutionize how we conceptualize ocean wave energy conversion - both in terms of ocean wave energy converter design and what we view as viable environments and circumstances for ocean wave energy conversion. The research and development opportunities for the DEEC-Tec domain, therefore, are vast compared to the prevailing mainstream ocean wave energy converter domain. Correspondingly, there are ample opportunities to invest time and money into the DEEC-Tec domain with an aim to enable a paradigm shift in how ocean waves can be utilized as a more viable form of renewable energy. To that end, two seedling efforts have been enacted providing a very cursory investigation into the DEEC-Tec domain: (1) a preliminary simple fabrication/prototyping effort and (2) a preliminary co-design effort. The prototype seedling centers upon the design of a fabrication and evaluation rig for individual DEEC-Tec transducers; e.g., dielectric elastomer generators. The co-design seedling centers upon the analysis of those methods suitable for DEEC-Tec, ocean wave energy conversion, and fluid-structure interaction co-design efforts.

50 EE - Wind and Water Power Program - Water (EE-4↗

DOE OSTI2022

Estimating Energy Market Schedules Using Historical Price Data: Preprint

The global climate crisis is expected to reshape the energy generation landscape in the coming decades. Increasing integration of non-dispatchable renewable energy resources into energy infrastructures and markets increases uncertainty and creates new opportunities for flexible energy systems. To conduct proper economic evaluation of flexible energy systems, such as integrated energy systems (IES), advancements in modelling of market interactions, such as bidding, is crucial. This work presents a shortcut algorithm which uses two mixed integer linear programs to compute dispatch schedules (e.g., hourly power production targets) that are constrained by the resource's bid information and characteristics (e.g., minimum up and down times) based on historical locational marginal price (LMP) data. This is orders of magnitude less data than required for a market clearing calculation with a full production cost model (PCM). We find the shortcut simulator recapitulates generator dispatch signals for the Prescient PCM with approximately 4% error for the RTS-GMLC test system.

electricity generation↗

DOE OSTI2023

Energy Flexibility-Environmental Outcomes Tradeoffs Workshop Report and Research Roadmap

The U.S. Department of Energy (DOE) and Norway’s Royal Ministry of Petroleum and Energy signed an Annex to a previously signed memorandum of understanding (MOU) in February 2020 to collaborate on hydropower research and development (R&D). This MOU Annex has brought together the DOE’s Office of Energy Efficiency and Renewable Energy Water Power Technology Office and the Norwegian Research Center for Hydropower Technology (HydroCen) to plan and coordinate hydropower R&D activities to increase our understanding of hydropower’s role in the future energy grid and how to minimize and mitigate the subsequent environmental impacts. As part of this MOU Annex, hydropower researchers from the U.S. and Norway have come together to conduct collaborative research on hydropower markets and value, hydropower plant capabilities and constraints, monitoring and control technologies, environmental design solutions, environmental impacts and tradeoffs, flexible operation and planning, and technology innovations. This report presents background information on hydropower environmental regulation in the U.S. and Norway and summarizes content and conclusions from this series of two, three-hour workshops on hydropower generation flexibility and environmental outcomes, that included structured discussions used to identify research priorities and collaborative research opportunities.

13 HYDRO ENERGY↗

DOE OSTI2022

Estimating Energy Market Schedules using Historical Price Data

The global climate crisis is expected to reshape the energy generation landscape in the coming decades. Increasing integration of non-dispatchable renewable energy resources into energy infrastructures and markets creates uncertainty as well as new opportunities for flexible energy systems. To conduct proper economic evaluation of flexible energy systems, such as integrated energy systems (IES), advancements in modelling of market interactions, such as bidding, is crucial. This work presents a shortcut algorithm which uses two mixed integer linear programs to compute dispatch schedules (e.g., hourly power production targets) that are constrained by the resource's bid information and characteristics (e.g., minimum up and down times) based on historical locational marginal price (LMP) data. The proposed algorithm is approximately 100 times faster and uses orders of magnitude less data than a full production cost model (PCM). We find the shortcut simulator recapitulates generator dispatch signals for the Prescient PCM with approximately 4% error for the RTS-GMLC test system.

electricity generation↗

DOE OSTI2026

Wattchmen: Watching the Wattchers – High Fidelity, Flexible GPU Energy Modeling

Modern GPU-rich HPC systems are increasingly becoming energy-constrained. Thus, understanding an application’s energy consumption becomes essential. Unfortunately, current GPU energy attribution techniques are either inaccurate, inflexible, or outdated. Therefore, we propose Wattchmen, a flexible methodology for measuring, attributing, and predicting GPU energy consumption. We construct a per-instruction energy model using a diverse set of microbenchmarks to systematically quantify the energy consumption of GPU instructions, enabling finer-grain prediction and energy consumption breakdowns for applications. Compared with the state-of-the-art systems like AccelWattch (32%) and Guser (25%), across 16 popular GPGPU, graph analytics, HPC, and ML workloads, Wattchmen reduces the mean absolute percent error (MAPE) to 14% on V100 GPUs. Furthermore, we show that Wattchmen provides similar MAPEs for water-cooled V100s (15%) and extends to later architectures, including air-cooled A100 (11%) and H100 (12%) GPUs. Finally, to further demonstrate Wattchmen ’s value, we apply it to applications such as Backprop and QMCPACK, where Wattchmen ’s insights enable energy reductions of up to 35%.

Tran, Brandon [University of Wisconsin, Madison] (↗