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At least 523 records · Page 29

Distributionally Robust Bilevel Optimization Model for Distribution Network With Demand Response Under Uncertain Renewables Using Wasserstein Metrics

Here, we consider a distribution network integrating demand response (DR) participants in the presence of uncertain renewable suppliers and outdoor temperatures. A bilevel optimization model is proposed to capture the intricate dynamics between price-incentivized DR participants and distribution system operations, including energy procurement and active/reactive power flows. The model is formulated as a distributional robust bilevel optimization using Wasserstein metrics. We show favorable data-driven properties including out-of-sample guarantee and asymptotic consistency. Furthermore, we present a tractable mixed-integer linear programming reformulation and characterize the worst-case distribution. Computational experiments are conducted on a modified 33-bus system. Our findings underscore the efficacy of the pricing strategies derived from the proposed bilevel optimization model. These strategies not only effectively manage DR participants' behavior but also bring equity considerations among households with various characteristics to light. The results contribute to a deeper understanding of the interplay between distribution system operators and DR participants.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Designing the PR100 Study: Puerto Rico Grid Resilience and Transition to 100% Renewable Energy

Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050, along with realizing interim goals of 40% by 2025, 60% by 2040, the phaseout of coal-fired generation by 2028, and a 30% improvement in energy efficiency by 2040 as established in Act 17. [1] To meet these goals and support widespread end-use electrification, the territory must explore how renewable energy and other generation technologies can be developed with energy storage, distributed generation, distribution control, electric vehicles, and energy efficient and responsive loads in each of Puerto Rico's cities and communities. To support Puerto Rico in reaching its renewable energy goals; help ensure energy system resilience against future extreme weather events; improve energy justice; and provide inputs to LUMA Energy's walk, jog, and run approach in its coordinated planning roadmap, the U.S. Department of Energy, National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Sandia National Laboratories propose to evaluate 100% renewable energy pathways through an integrated analysis process. This talk will present steps in designing a two-year study entitled Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy (PR100). [1] U.S. Energy Information Administration (EIA). 2020. Puerto Rico Territory Energy Profile.

100% renewable energy↗

Deep Learning Based Frequency Stability Assessment in Power Grid with High Renewables

Frequency stability assessment is one critical aspect of power system security assessment. Traditional N-1 screening method is based on the simulations of a few typical daily and seasonal operation scenarios. However, the increasing integration of inverter-based renewables and the retirement of conventional synchronous generators result in decreasing system inertia and growing complexity of system operating conditions. Selecting a few typical operation scenarios cannot cover all operating conditions, and the time-domain simulation of all operation conditions requires tremendous time. This paper proposes a more efficient frequency stability assessment method based on deep learning. The affinity propagation clustering algorithm is used to divide the dataset into different clusters, so the selected dataset for training can cover the diversified operating conditions as much as possible. Also, feature normalization is applied to both the training dataset and testing dataset in order to remove any unnecessary bias. Especially, trained model based on full dataset normalization has bounded error in the prediction. The case study on the reduced 240-bus WECC system demonstrates that the proposed method can predict accurate frequency nadir with limited training dataset. The deep learning model using the revised feature normalization can predict more accurate frequency nadir than that using the traditional feature normalization and has very small maximum prediction error.

affinity propagation↗

Characterizing the negative triangularity reactor core operating space with integrated modeling

Negative triangularity (NT) has received renewed interest as a fusion reactor regime due to its beneficial power-handling properties, including low scrape-off layer power and a larger divertor wetted area that facilitates simple divertor integration. NT experiments have also demonstrated core performance on par with positive triangularity (PT) high confinement mode (H-mode) without edge-localized modes (ELMs), encouraging further study of an NT reactor core. In this work, we use integrated modeling to scope the operating space around two NT reactor strategies. The first is the high-field, compact fusion pilot plant concept Modular, Adjustable, NT ARC (MANTA) and the second is a low field, high aspect ratio concept based on work by Medvedev et al. By integrating equilibrium, core transport, and edge ballooning instability models, we establish a range of operating points with less than 50 MW scrape-off layer power and fusion power comparable to PT H-mode reactor concepts. Heating and seeded impurities are leveraged to accomplish the same fusion performance and scrape-off layer exhaust power for various pressure edge boundary conditions. Scans over these pressure edge conditions accommodate any current uncertainty of the properties of the NT edge and show that the performance of an NT reactor will be extremely dependent on the edge pressure. The high-field case is found to enable lower scrape-off layer power because it is capable of reaching high fusion powers at a relatively compact size, which allows increased separatrix density without exceeding the Greenwald density limit. Adjustments in NT shaping exhibit small changes in fusion power, with an increase in fusion power density seen at weaker NT. Infinite-n ballooning instability models indicate that an NT reactor core can reach fusion powers comparable to leading PT H-mode reactor concepts while remaining ballooning-stable. Seeded krypton is leveraged to further lower scrape-off layer power since NT does not have a requirement to remain in H-mode while still maintaining high confinement. We contextualize the NT reactor operating space by comparing to popular PT H-mode reactor concepts, and find that NT exhibits competitive ELM-free performance with these concepts for a variety of edge conditions while maintaining relatively low scrape-off layer power.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

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↗

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↗

Hydropower Advantages over Batteries in Energy Storage of Off-Grid Systems: A Case Study

Microgrids are decentralized power production systems, where the energy production and consumption are very close to each other. Microgrids generally exploit renewable energy sources, encountering a problem of storage, as the power production from solar and wind is intermittent. This research presents a new integrated methodology and discusses a comparison of batteries and pumped storage hydropower (PSH) as energy storage systems with the integration of wind and solar PV energy sources, which are the major upcoming technologies in the renewable energy sector. We implemented the simulator and optimizer model (HOMER), which develops energy availability usage to obtain optimized renewable energy integration in the microgrid, showing its economic added value. Two scenarios are run with this model—one considers batteries as an energy storage technology and the other considers PSH—in order to obtain the best economic and technical results for the analyzed microgrid. The economic analysis showed a lower net present cost (NPC) and levelized cost of energy (LCOE) for the microgrid with PSH. The results showed that the microgrid with the storage of PSH was economical, with an NPC of 45.8 M€ and an LCOE of 0.379 €/kWh, in comparison with the scenario with batteries, which had an NPC of 95.2 M€ and an LCOE of 0.786 €/kWh. The role of storage was understood by differentiating the data into different seasons, using a Python model. Furthermore, a sensitivity analysis was conducted by varying the capital cost multiplier of solar PV and wind turbines to obtain the best optimal economic solutions.

Guruprasad, Prajwal↗

Application of Intelligent Load Control to Manage Building Loads to Support Rapid Growth of Distributed Renewable Generation

Electricity utilities are faced with the mounting challenge of providing a stable supply of power to meet the growing demand while also integrating rapid growth in distributed variable renewable generation. Traditional means of balancing short- and long-term supply and demand imbalance will be expensive. Alternative approaches of using flexible loads in buildings are needed to mitigate the imbalance at a lower cost. This paper shows how the intelligent load control (ILC) process can be used to manage loads in buildings by dynamically prioritizing loads for curtailment using both quantitative and qualitative criteria. The ILC process can be deployed on low-cost computing platforms without the need for any additional sensing. ILC was first validated in a simulation environment to provide two grid service use cases: (1) managing monthly peak electricity demand and (2) managing buildings’ electricity consumption during a capacity bidding event. After being successfully tested in a simulation environment, ILC was deployed on real buildings to manage electricity consumption to provide two different use cases under different outdoor operating conditions. Both the simulation tests and the real building experiments were deployed using VOLTTRON™, a distributed sensing and control platform. The results from the tests and experiments showed that ILC was able to manage the controllable loads (heat pumps) in the building to maintain the electricity consumption at the desired level without a significant impact on occupant comfort. Overall, the results demonstrate that the ILC allows coordination of the controllable loads and provides a more intelligent means of load management than the traditional duty-cycling approach.

Kim, Woohyun↗

Geographically Distributed Co-Simulation for the Interplay of Integrated Energy Systems and Power Grid

The increased penetration of renewable generation induces unbalanced demand-supply on a power grid, while integrated energy systems (IES) can provide high part-load efficiency and high flexibility to support grid resilience. To study the transients and improve dynamic operability, it’s important to investigate the interplay between IES and power grid concurrently using real-time co-simulation approaches. In this presentation, we showed the previous co-simulation test between NETL and INL and discussed how this co-simulation can be beneficial for both IES and power grid research. In addition, we gave an overview about the SuperLab2.0 project, which was a federated national platform to address future power grid challenges. (Virtual presentation to the MILLENNIUM CLEAN and SUSTAINABLE POWER workshop 2025).

Co-simulation↗

Enabling Marine Energy Integration for Ocean Observing: Functional Requirements

Marine renewable energy (i.e., wave, tidal or ocean current, thermal gradient, and salinity gradient) or MRE can revolutionize ocean observing capabilities. Five use cases representing a range of ocean observing platforms were developed based on end-user feedback. Drawing from these use cases, common needs or functional requirements were developed to help guide the integration of MRE power delivery for ocean observation structures and functions. The functional requirements were determined from descriptions of the use cases, specifications of hardware that are used or closely associated with existing ocean observation platforms, and direct feedback from ocean observation sensor/platform developers and users. Twenty types of functional requirements were identified, including those associated with power and energy use; physical system requirements; temperature and depth; electrical, acoustic, and motion interference; and reliability. Each set of functional requirements is illustrated as features of the use cases. By defining functional requirements for MRE technology integration in ocean observing platforms, and focusing on end-user requirements, barriers to developing MRE-driven ocean observation missions can be reduced.

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

Energy Systems Decarbonization: Perspectives on Electric Vehicles and Grid Integration

The imperative for strong and rapid emissions reductions to mitigate global warming and enhance air quality necessitates a transition to net-zero emissions. This shift requires significant changes throughout the entire energy supply-demand ecosystems, tailored to various sectors. Transportation stands as the least-diversified energy sector and the largest source of U.S. GHG emissions. As the primary catalyst for vehicle decarbonization when paired with clean electricity, electric vehicles (EVs) will play a pivotal role in the future. EVs are poised to drive substantial growth in electricity demand and presents a unique opportunity to provide demand-side flexibility that is crucial for future renewable-dominated electricity systems. Smart integration of EVs can strengthen the grid, reducing costs and enhancing resilience. At NREL, laying the scientific groundwork to actualize this vision: our research is finding ways for EVs to support grid planning and operations across several timescales and to fully exploit the synergies between EVs and renewables.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗

Innovation in complementary energy technologies from renewable energy policies

Complementary renewable technologies support renewable energy use as they can help balance the intermittency of solar and wind generation. Previous research has shown that environmental policies directly targeting renewable energy can drive innovation in solar PV and wind technology. This study explores the impact of renewable policies on innovation in complementary renewable technology that assists with integration, including combustion with mitigation potential, efficient power transmission or distribution, and enabling technologies. We use negative binomial models and a panel of 25 OECD countries from 1997 to 2015 to evaluate these relationships. We are not able to find evidence that renewable policies incentivize innovation in complementary combustion or transmission and distribution technologies, and only limited evidence that demand-pull instruments are associated with increased innovation in smart grid technology. Technology-push policies, such as public research and development funds for renewable energy, have had limited impact on grid-supporting energy storage innovation. Our findings suggest that policymakers wishing to accelerate these complementary technologies need to go beyond policies targeting renewable energy in order to drive innovation in complementary fields.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Enabling Marine Energy Integration for Ocean Observing: Functional Requirements

Marine renewable energy (i.e., wave, tidal or ocean current, thermal gradient, and salinity gradient) or MRE can revolutionize ocean observing capabilities. Five use cases representing a range of ocean observing platforms were developed based on end-user feedback. Drawing from these use cases, common needs or functional requirements were developed to help guide the integration of MRE power delivery for ocean observation structures and functions. The functional requirements were determined from descriptions of the use cases, specifications of hardware that are used or closely associated with existing ocean observation platforms, and direct feedback from ocean observation sensor/platform developers and users. Twenty types of functional requirements were identified, including those associated with power and energy use; physical system requirements; temperature and depth; electrical, acoustic, and motion interference; and reliability. Each set of functional requirements is illustrated as features of the use cases. By defining functional requirements for MRE technology integration in ocean observing platforms, and focusing on end-user requirements, barriers to developing MRE-driven ocean observation missions can be reduced.

Cavagnaro, Robert J.↗

Integrated protonic ceramic electrochemical cell for sustainable energy economy using water-energy nexus framework

Reliance on fossil fuels will continue for the next decades even though there are global pushes away from it to mitigate the overarching climate challenge, most especially by its highest consumers and availability. While there is a hastening global shift away from fossil fuel, integrating its assets into this technology helps limit the risk and future losses of stranded assets and reduce the cost of investment in the new technologies. Moreover, the generation of electricity from intermittent renewable sources like solar and wind has witnessed a significant surge in recent years, leading to a pressing demand for practical energy storage systems. Electrical energy storage is anticipated to play a pivotal role in the future global energy system, facilitating load-leveling operations to support the greater integration of renewable and distributed generation. Reversible electrochemical cells (RECs) offer a promising option for addressing the fossil fuel assets integration and energy storage challenges through the interconversion between electrical and chemical energy and concurrent utilizing carbon emission. In their electrolysis mode, the RECs convert electricity into durable, storable, and portable valuable chemical fuels such as syngas and methane. Conversely, the produced chemical fuels can be used as reactants in the fuel cell mode to generate electricity on demand with minimal (hydrocarbons) or zero when H2 or NH3 is used emissions. However, a challenging goal for this type of technology remains to achieve optimal operation and high roundtrip efficiencies, which has hindered the deployment of previous electrochemical cells. This dissertation demonstrates how reversible protonic ceramic electrochemical cells (RePCECs) can be integrated with fossil fuel power plants and renewable energy sources as a potential energy storage system. In this work, integrated RePCEC systems are designed and examined using computational modeling at scales to determine appropriate system configurations and operating conditions that achieve high roundtrip efficiencies. Cell level design of the PCEC is the first approach, several cells are assembled for the stack level model that is integrated into combined cycle powerplant and solar photovoltaic for the system level model. After critical literature review, this answered the operational and integration research questions proposed to address these challenges. The designed systems perform two functions, utilizing captured CO2 and storing renewable energy through co-electrolysis of steam and CO2. The co-electrolysis reaction involves endothermic water electrolysis and exothermic methanation reaction. To enhance high roundtrip efficiency, there is a need for thermal balance and management in the electrolysis mode. This involves operating the RePCEC stack under conditions that favor methane production to balance out heat needed by water electrolysis, it crucial for the RePCEC system operation. Methanation is enhanced by low temperatures. Leveraging on fabricated BCZYYb-electrolyte RePCEC, the cell model designed revealed that the optimum temperature for methane production is 450℃ at atmospheric pressure. Thus, to achieve optimum system performance, operating in the temperature range 450-525℃ is recommended at the given configuration, combining between the optimum temperature for methane production and temperature for the optimum stack roundtrip efficiency. Configuration with carbon capture system and purge stream is the optimum configuration from the seven conceptualized and evaluated. The modeling outcomes include a thermodynamic examination of integrated RePCEC systems, calibration of cell and stack level models, and steady-state simulation and integration into a 600MW combined cycle power plant retrofitted with two two-stage membrane-based carbon capture system and a wastewater treatment and recovery unit. At 100% powerplant loading, the stack and system roundtrip efficiencies are 72% and 51.37% respectively. Adding a purge stream for produced hydrogen at the system downstream improves the efficiencies to 74 and 55.48% respectively. At atmospheric pressure and 525℃, the system model suggests that a stack roundtrip of 82% is achievable, and overall system efficiency increases by reducing the energy consumption by the balance of plant components for steam generation and storage. Economic analysis of the process gives levelized cost of methane as $2.24/MMBtu lower than the conventional production route that range between $3.46/MMBtu and $9.85/MMBtu. The lifecycle analysis shows that the global warming potential for the production of methane and hydrogen from the RePCEC system is 3.83 kg CO2 eq which is lower than 9.35 kg CO2 eq emission during steam methane reforming for hydrogen production. This answered both the environmental and economic concerns in the raised research question. The proposed RePCEC configuration and analysis carried out in this dissertation to address the surge in renewable energy and challenges with PCEC technology hold significant potential in achieving large-scale energy storage while simultaneously reducing carbon emissions. These advancements, coupled with suitable governmental policies and incentive programs, have the potential to economically disrupt the natural gas industries by using RePCEC systems for methane production, thereby making them more favorable for eventual implementation and commercialization.

25 ENERGY STORAGE↗

A 2023 Perspective: What Is the Value of Hybridization?

This report takes a wind developer's perspective and provides a summary of the current and future state of hybrid facilities, and ultimately seeks to answer the question: "Are hybrid power plants a pivotal tool for meeting future energy and decarbonization targets?" The intention is not to provide an in-depth system-level technical analysis of hybrid facilities, but to showcase a high-level overview of the hybrid facility ecosystem and its potential future directions. Lastly, the authors acknowledge and recognize that non-renewable generation technologies can be integrated into a hybrid facility, however these technologies are outside the scope of this report.

17 WIND ENERGY↗

Validated Feasibility Study of Integrally Stiffened Metallic Fuselage Panels for Reducing Manufacturing Costs

The continual need to reduce airframe cost and the emergence of high speed machining and other manufacturing technologies has brought about a renewed interest in large-scale integral structures for aircraft applications. Applications have been inhibited, however, because of the need to demonstrate damage tolerance, and by cost and manufacturing risks associated with the size and complexity of the parts. The Integral Airframe Structures (IAS) Program identified a feasible integrally stiffened fuselage concept and evaluated performance and manufacturing cost compared to conventional designs. An integral skin/stiffener concept was produced both by plate hog-out and near-net extrusion. Alloys evaluated included 7050-T7451 plate, 7050-T74511 extrusion, 6013-T6511 extrusion, and 7475-T7351 plate. Mechanical properties, structural details, and joint performance were evaluated as well as repair, static compression, and two-bay crack residual strength panels. Crack turning behavior was characterized through panel tests and improved methods for predicting crack turning were developed. Manufacturing cost was evaluated using COSTRAN. A hybrid design, made from high-speed machined extruded frames that are mechanically fastened to high-speed machined plate skin/stringer panels, was identified as the most cost-effective manufacturing solution. Recurring labor and material costs of the hybrid design are up to 61 percent less than the current technology baseline.

Pettit, R. G.↗

A Perspective on Solar-Driven Electrochemical Routes for Sustainable Methanol Production

The transition towards sustainable and renewable energy sources is imperative in mitigating the environmental impacts of escalating global energy consumption. Methanol, with its versatile applications and potential as a clean energy carrier, a precursor chemical, and a valuable commodity, emerges as a promising solution within the realm of renewable energy technologies. This work explores the integration of electrochemistry with solar power to drive efficient methanol production processes, focusing on electrochemical reduction (ECR) of CO 2 and methane oxidation reaction (MOR) as pathways for methanol synthesis. Through detailed analysis and calculations, we evaluate the thermodynamic limits and realistic solar-to-fuel (STF) efficiencies of ECR and MOR. Our investigation encompasses the characterization of multijunction light absorbers, determination of thermoneutral potentials, and assessment of STF efficiencies under varying conditions. We identify the challenges and opportunities inherent in both ECR and MOR pathways, shedding light on catalyst stability, reaction kinetics, and system optimization, thereby providing insights into the prospects and challenges of solar-driven methanol synthesis, offering a pathway towards a cleaner and more sustainable energy future.

30 DIRECT ENERGY CONVERSION↗

Developing Southeast Asia Solar Resource Data to Support the Clean Energy Transition in the Region

This fact sheet describes the development and release of a high-fidelity solar time series data set for the entire Southeast Asia region, which can be used to drive energy sector investment, support enabling policies to support solar energy market expansion, and inform prospecting, renewable energy auctions, target-setting, grid integration and other high impact decisions, ranging from the micro to macro scale, to accelerate renewable energy deployment throughout SE Asia. This data is available on the enhanced and expanded RE Data Explorer (RE Explorer) platform.

Advanced Energy Partnership for Asia↗