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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

On the operational characteristics and economic value of pumped thermal energy storage

Pumped thermal energy storage (PTES) systems use an electrically-driven heat pump to store electricity in the form of thermal energy, and subsequently dispatch the stored thermal energy to generate electricity using a thermodynamic heat engine. Optimal day-ahead operational scheduling and annual value of a PTES system based on Joule-Brayton thermodynamic cycles and two-tank molten salt hot thermal storage is evaluated in this work. Production cost models, which simultaneously optimize commitment and dispatch schedules for an entire set of generators to minimize the cost of satisfying electricity demand, are employed to determine system-optimal operation and day-ahead energy value of the PTES system within each of six hypothetical near-future grid scenarios intended to approximately represent the U.S. Western Interconnection or the Texas Interconnection. Sensitivity to grid scenario (including the contribution of variable renewable energy sources), thermal storage capacity, relative heat pump and heat engine capacities, and startup/shutdown cycling costs are evaluated. PTES energy value and heat engine annual capacity factor increase strongly as the contribution of variable renewable resources increases, heat pump capacity increases relative to heat engine capacity, or PTES cycling costs decrease. Grid scenarios in which the contribution of variable renewable energy is dominated by solar photovoltaics (PV) vs. wind produce inherently different PTES operational patterns. Annual PTES energy value within PV-dominated scenarios increased with storage capacity only up to approximately seven hours of full-load discharge capacity, whereas that within wind-dominated scenarios exhibited a continual increase with storage duration up to at least 16 hours.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

GPU-resident sparse direct linear solvers for alternating current optimal power flow analysis

Integrating renewable resources within the transmission grid at a wide scale poses significant challenges for economic dispatch as it requires analysis with more optimization parameters, constraints, and sources of uncertainty. This motivates the investigation of more efficient computational methods, especially those for solving the underlying linear systems, which typically take more than half of the overall computation time. In this paper, we present our work on sparse linear solvers that take advantage of hardware accelerators, such as graphical processing units (GPUs), and improve the overall performance when used within economic dispatch computations. We treat the problems as sparse, which allows for faster execution but also makes the implementation of numerical methods more challenging. We present the first GPU-native sparse direct solver that can execute on both AMD and NVIDIA GPUs. We demonstrate significant performance improvements when using high-performance linear solvers within alternating current optimal power flow (ACOPF) analysis. Furthermore, we demonstrate the feasibility of getting significant performance improvements by executing the entire computation on GPU-based hardware. Finally, we identify outstanding research issues and opportunities for even better utilization of heterogeneous systems, including those equipped with GPUs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Parametric analysis on optimized design of hybrid solar power plants

There is increasing interest in utility-scale solar power plants with storage which can flexibly dispatch renewable energy to the grid. However, plant design possesses many degrees of freedom and non-obvious trade-offs in performance. Software tools can estimate or optimize the performance of a specific plant configuration under market and weather conditions of interest; the associated cost parameters and operating assumptions strongly influence estimates of plant performance and decisions regarding optimal sizing. We employ the National Renewable Energy Laboratory's Hybrid Optimization and Performance Platform, which incorporates optimal dispatch when evaluating plant performance, and investigate the sensitivity to weather and market conditions, operating limitations, and the presence of a capacity-based incentive. We demonstrate changes in plant performance and optimal sizing with respect to these inputs and discuss implications. Here results show that PV-with-battery designs are more profitable under our assumptions, but that designs including a concentrated solar power (CSP) system produce significantly greater annual energy; and that CSP-with-thermal energy storage designs maximizing the benefit-to-cost ratio have an input-dependent linear relationship between the CSP field solar multiple and the hours of storage as the project budget varies.

14 SOLAR ENERGY↗
DOE OSTI2022

Failure Probability Constrained AC Optimal Power Flow

Despite cascading failures being the central cause of blackouts in power transmission systems, existing operational and planning decisions are made largely by ignoring their underlying cascade potential. This paper posits a reliability-aware AC Optimal Power Flow formulation that seeks to design a dispatch point which has a low operator-specified likelihood of triggering a cascade starting from any single component outage. By exploiting a recently developed analytical model of the probability of component failure, our Failure Probability-constrained ACOPF (FP-ACOPF) utilizes the system's expected first failure time as a smoothly tunable and interpretable signature of cascade risk. Here, we use techniques from bilevel optimization and numerical linear algebra to efficiently formulate and solve the FP-ACOPF using off-the-shelf solvers. Extensive simulations on the IEEE 118-bus case show that, when compared to the unconstrained and N-1 security-constrained ACOPF, our probability-constrained dispatch points can significantly lower the probabilities of long severe cascades and of large demand losses, while incurring only minor increases in total generation costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Quantifying the Economic and Grid Reliability Impacts of Improved Wind Power Forecasting

Wind power forecasting is an important tool in power system operations to address variability and uncertainty. Accurately doing so is important to reducing the occurrence and length of curtailment, enhancing market efficiency, and improving the operational reliability of the bulk power system. This research quantifies the value of wind power forecasting improvements in the IEEE 118-bus test system as modified to emulate the generation mixes of Midcontinent, California, and New England independent system operator balancing authority areas. To measure the economic value, a commercially available production cost modeling tool was used to simulate the multi-timescale unit commitment (UC) and economic dispatch process for calculating the cost savings and curtailment reductions. To measure the reliability improvements, an in-house tool, FESTIV, was used to calculate the system's area control error and the North American Electric Reliability Corporation Control Performance Standard 2. The approach allowed scientific reproducibility of results and cross-validation of the tools. A total of 270 scenarios were evaluated to accommodate the variation of three factors: generation mix, wind penetration level, and wind fore-casting improvements. The modified IEEE 118-bus systems utilized 1 year of data at multiple timescales, including the day-ahead UC, 4-hour-ahead UC, and 5-min real-time dispatch. The value of improved wind power forecasting was found to be strongly tied to the conventional generation mix, existence of energy storage devices, and the penetration level of wind energy. The simulation results demonstrate that wind power forecasting brings clear benefits to power system operations.

17 WIND ENERGY↗
DOE OSTI2017

Wind-Friendly Flexible Ramping Product Design in Multi-Timescale Power System Operations

With increasing wind power penetration in the electricity grid, system operators are recognizing the need for additional flexibility, and some are implementing new ramping products as a type of ancillary service. However, wind is generally thought of as causing the need for ramping services, not as being a potential source for the service. In this paper, a multi-timescale unit commitment and economic dispatch model is developed to consider the wind power ramping product (WPRP). An optimized swinging door algorithm with dynamic programming is applied to identify and forecast wind power ramps (WPRs). Designed as positive characteristics of WPRs, the WPRP is then integrated into the multi-timescale dispatch model that considers new objective functions, ramping capacity limits, active power limits, and flexible ramping requirements. Numerical simulations on the modified IEEE 118-bus system show the potential effectiveness of WPRP in increasing the economic efficiency of power system operations with high levels of wind power penetration. It is found that WPRP not only reduces the production cost by using less ramping reserves scheduled by conventional generators, but also possibly enhances the reliability of power system operations. Moreover, wind power forecasts play an important role in providing high-quality WPRP service.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Modeling and Integration of Flexible Demand in Heat and Electricity Integrated Energy System

This paper is focused on utilizing customers' flexible energy demand, including both heat demand and electricity demand, to provide balancing resources and relieve the difficulties of integrating variable wind power with the combined heat and power. The integration of heat and electricity energy systems providing customers with multiple options for fulfilling their energy demand is described. Customer aggregators are introduced to supply downstream demand in the most economical way. Controlling customers' energy consumption behaviors enables aggregators to adjust their energy demand in response to supply conditions. Incorporating aggregators' flexible energy demand into the centralized energy dispatch model, a two-level optimization problem (TLOP) is first formed where the system operatormaximizes social welfare subject to aggregators' strategies, which minimize the energy purchase cost. Furthermore, the subproblems are linearized based on several reasonable assumptions. Optimal conditions of the subproblems are then transformed as energy demands to be described as explicit piecewise-linear functions of electricity prices corresponding to the demand bid curves. In this way, the TLOP is transformed to a standard optimization problem, which requires aggregators to only submit a demand bid to run the centralized energy dispatch program. All the parameters pertaining to the aggregators' energy consumption models are internalized in the bid curves. The proposed technique is illustrated in a modified testing system.

combined heat and power (CHP)↗
DOE OSTI2021

Secondary Frequency Regulation from Variable Generation through Uncertainty Decomposition: An Economic and Reliability Perspective

The rapid integration of variable generation (VG), such as photovoltaics (PV), necessitates an increase in the secondary frequency regulation (SFR) to handle the system intra-dispatch interval imbalance because of VG's variation. Although PV has the control capability to provide SFR, the main challenge is in guaranteeing the delivery of PV's energy and SFRs capacities in the automatic generation control (AGC) within each dispatch interval considering its uncertainty. This paper proposes a deliverable VG SFR provision model with endogenous VG's power uncertainty decomposition. First, the uncertainty of VG is decomposed using distributionally robust chance constraints through which the deliverable SFR provision is guaranteed. Next, the intra-interval frequency response of PV's SFR is validated with a user defined AGC model including the PV power plant. Finally, the economic benefits and the reliability improvements such as the frequency deviation reduction with PV providing SFRcan be integrated and evaluated. The proposed model is tested in a modified 18-bus system and in the Western Electricity Coordinating Council test system. Results demonstrate that with the deliverable SFR from PV, the system cost and the frequency reliability can be improved simultaneously. PV's SFR performance can be guaranteed with the proposed model.

14 SOLAR ENERGY↗
DOE OSTI2019

Flexible Geothermal Power Generation utilizing Geologic Thermal Energy Storage (Final Seedling Project Report)

This report concludes that there is a cost-effective strategy for seasonal storage of heat that will provide firm, but dispatchable, electrical generating capacity in times when other renewable energy is not available to meet demand. Deployment of the technology appears to require no new technology, but instead combines solar, geothermal, and conventional oil and gas drilling technologies in a novel way. The study basis is the use of sedimentary geologic formations as a medium for thermal energy storage (TES), specifically for heat collected in concentrating solar collectors. The study identifies methodologies that could be used to transport this heat into and out of the subsurface in order to produce dispatchable electrical power, and reports on initial optimization results. The GeoTES system (heat input, storage, heat recovery, and heat to electric conversion) described in this analysis has the potential to provide a unique pathway for increasing the grid penetration of renewable energy in large blocks of power and across many states and regions. Further, the system can be used both to meet the nation’s flexible energy needs while also improving grid stability and reliability. The present study evaluated the use of a large number of dedicated wells to store and recover the heat, essentially creating a synthetic geothermal reservoir. The use of sedimentary geology allows the wells to be drilled at low cost. Dedicated hot and cold wells are used, arranged in a five-spot well pattern with each hot or cold well surrounded at an appropriate distance by the opposite type of well. In large numbers this becomes alternating rows of hot and cold wells. Each hot and cold well is operated using a push-pull strategy. This configuration provides the ability to immediately recover stored hot fluid from a GeoTES reservoir, or to store the heat over many months for recovery at low loss when needed. This is a practical approach for managing the system’s fluid inventory and reducing parasitic load. The production and injection power requirements are reduced because the rows of wells operating in “push” mode provide help to the wells operating in “pull” mode, and vice-versa. Initial charging of a GeoTES system increases the heat recovery temperature. Increasing the duration of the charging period decreases the magnitude of the temperature fluctuations that occur following prolonged system operation. Because of direct contact of the heated water with the reservoir formation, the production of both hot water and steam from the TES, and the temperature ranges of the recovered fluid (190 – 230°C or 375 – 445°F), conventional geothermal power cycles were used to convert the stored heat to electricity. A power cycle configuration for the GeoTES system was selected following a screening study of a number of flash, and flash/binary hybrid options. This analysis concluded that, of the configurations evaluated, a dual-stage flash steam cycle provides the lowest capital costs per unit net power generation with an acceptable hot brine inlet fluid flow rate. The evaluation included the power plant cost estimate, the cost and number of wells and the associated parasitic loads. Annual power generation performance was simulated to evaluate capacity factor and LCOE. The LCOE calculated for the inherently high capacity GeoTES system was $\$$0.13/kWhe. This value was calculated for the case where the solar thermal collector was sized in such a way that the solar collectors permitted an annual power plant capacity factor of up to 97%. The power cycle was able to provide power to the grid every night of the year, and flexible base-load power during the winter, if needed. This LCOE value compares favorably with reported values for solar photovoltaic plus battery energy storage (PV+BES) systems in the open literature, i.e. $\$$0.148/kWhe for a PV+BES system with 4 hours of electrochemical battery energy storage capacity. Addition of battery energy storage with more hours of storage would further increase PV+BES system LCOE and increase the separation between GeoTES and PV+BES. A GeoTES system would therefore provide superior economics for high capacity and long duration solar energy storage.

14 SOLAR ENERGY↗
DOE OSTI2019

Analysis of Differential Financial Impacts of LWR Load-Following Operations. Revision 1

This document reports the application of HERON (Holistic Energy Resource Optimization Network), a newly-developed RAVEN (Risk Analysis Virtual ENvironment) plugin for grid and capacity optimization, to a case study conducted in collaboration with Arizona Public Service (APS). The study is a work in progress; this report presents a description of current models and corresponding results for a particular consideration. APS is anticipating several operational challenges. The first is rapid growth of Variable Renewable Energy (VRE) sources such as wind and solar power providing energy to the grid in the APS service region. This creates challenges for baseload operation of the Palo Verde Generating Station (PVGS), a nuclear power plant co-owned and operated by APS. The second challenge for APS is a change in the cooling water acquisition contract with the Sub Regional Operating Group (SROG). The existing contract is expiring soon, and a renewal is only available for a significantly higher price of water. These two challenges represent a difficulty in maintaining profitability for PVGS as local area demand is highly fluctuant and water prices may increase. Furthermore, excess production at PVGS is currently traded on the Palo Verde energy Hub (PVH), which occasionally offers very low or negative locational marginal prices (LMP) for electricity. This analysis considers the potential benefits of occasional curtailment of PVGS as a method to mitigate unprofitable production hours. Similar to load following, optional daily curtailment would allow APS to elect curtailment of PVGS as low as 70% of its nominal operating level between the hours of 08:00 and 16:00 provided local area demand is met and it is profitable to do so. This document reports a stochastic differential analysis of the Net Present Value (NPV) of PVGS as operated by NPS as a result of optional curtailment operation. To model this differential case, HERON has been designed from previous efforts in this study as a generic tool to accelerate the design and execution of RAVEN workflows for technoeconomic analysis of grid energy systems. HERON leverages both RAVEN and the CashFlow plugin for RAVEN to stochastically explore or optimize a response surface with energy grid system production capacities as inputs and mean NPV as a goal function. HERON performs these evaluations by stochastically sampling market, weather, and demand events using RAVEN’s ARMA reduced-order model capability to generate boundary conditions for dispatch optimization. The algorithm performs the dispatch optimization for each of the synthetic scenarios. For this case, HERON designs workflows to simulate behavior of the PVH, wind, solar, and APS local area demand, and use these synthetic scenarios to stochastically evaluate the differential benefit of optional curtailment for each scenario. While this study finds optional curtailment to be a potential source of revenue, the magnitude of the differential NPV is sufficiently small that it is unlikely a priority for increasing the profitability of PVGS. Further, the differential NPV shrinks throughout the simulated years, suggesting the long-term benefit of such operation given current assumptions is negligible.

14 SOLAR ENERGY↗
DOE OSTI2020

Demand Response Optimization and Management System for Real-TIme (DROMS-RT)

To design and demonstrate DROMS-RT, a highly distributed Demand Response Optimization and Management System for Real-Time (DROMS-RT) power flow control to support large scale integration of distributed renewable generation into the grid. AutoGrid developed a novel control and communications platform to allow highly dispatchable demand response (DR) services in time frames suitable for providing ancillary services to the transmission grid. These services will be substantially less expensive and more efficient than other forms of ancillary services options currently available to manage the intermittency associated with large-scale renewable integration. DROMSRT successfully leveraged Automated Demand Response (ADR) by fundamentally re-thinking the architecture of the DR platform from the ground up and by developing innovative new technologies in a number of areas related to DR. DROMS-RT leveraged the low-cost, open, interoperable DR signaling technology, OpenADR, and low-cost, internet-protocol based telemetry solutions to reduce the cost of hardware. This allowed DROMS-RT to provide dynamic price signals to millions of OpenADR clients. Statistically rigorous signal processing techniques were developed to reliably detect even small load reductions in the presence of noisy baseline profiles. Novel forecasting engines based on modern online machine learning algorithms enabled accurate individualized forecasts for customer loads in the presence of dynamic pricing signals, and a real-time decision engines enabled continuous optimization and optimal dispatch of DR resources across a large portfolio of heterogeneous loads that respond at varying time-scales. Moreover, the real-time optimization conducted by the decision engine can utilize grid physics to maximize load reduction at the transmission system in addition to the distribution sites, for more efficient grid operation. Finally, the Software-as-a-Service (SaaS) availability of the DROMS-RT platform has reduced the cost of deployment and enable participation of small commercial and residential customers in DR who otherwise would not be able to do so.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Concurrent Optimization of Capital Cost and Expected O&M

Concentrating solar power (CSP) technologies can utilize heat from concentrated sunlight from a field of tracking mirrors to generate electricity, reform fuel, provide process heat, or augment fossil plant heat sources. Electricity-generating power tower systems focus light from thousands of independent heliostats onto a thermal receiver, which uses the focused light to warm a heat transfer fluid (HTF), typically, a molten nitrate salt. The HTF is then sent to a power generation cycle or diverted into thermal energy storage (TES) for later use. Thermal storage is – in principle – a straightforward proposition. However, optimal utilization of a TES resource is complex and multi-faceted: thermal energy may be dispatched to produce electricity immediately upon first availability, or thermal energy may be reserved for next-day peak periods at risk of filling storage and dumping energy, or a portion of the thermal energy can be reserved to maintain equipment temperatures, reducing power cycle startup time, etc. Many possible dispatch permutations variously emphasize producing peak power, operating through transients, expediting daily startup, etc. The best operation strategy can change day-to-day throughout the year, depending on the weather and market pricing forecasts. The project we describe in this report develops a software package that allows users to explore design optimization, operations decisions, and performance characterization of concentrating solar power tower plants. Users interface with the tool through a scripting language, and results are reported in time series tables, plots, runtime logs, and design outputs. Users choose from a list of variables such as tower height, solar multiple, design-point irradiance, thermal storage size, etc., and specify information about the system using a list of parameters. The software can then optimize the specified variables to reduce the cost of energy produced by the system while meeting certain production requirements, accounting for uncertain weather and electricity price forecasts, and correcting for equipment failures or repair time. The software we develop is the first comprehensive design tool of its kind to incorporate all of these aspects while being deployed as open source.

14 SOLAR ENERGY↗
DOE OSTI2022

Savings in Action: Lessons from Observed and Modeled Residential Solar Plus Storage Systems

The electric grid is rapidly evolving as small-scale, demand-side resources play increasingly important roles in grid operations and decarbonization. Maximizing the potential of demand-side resources involves incentivizing electricity customers to use those resources in ways that benefit the broader electrical grid. These incentives depend largely on the electricity cost savings that customers can realize from demand-side resource adoption. Determining these potential cost savings is a complex task. Cost savings depend on numerous factors, including the characteristics of different technologies, the algorithms that control these devices, system performance, customer behavior, electricity rate structures, and climatic factors. Another challenge is that estimated cost savings are frequently based on modeled rather than observed system performance, particularly in the academic literature. In this study, we begin to fill the gap in empirical research of demand-side resources using data from a new construction residential community equipped with rooftop solar and storage (S+S) in Arizona. We use these data to analyze the factors that determine customer electricity cost savings and emissions impacts of S+S in the real world. We then compare these data to modeled system performance to understand how models deviate from real-world outcomes. Based on these findings, we explore ways to improve such models and, conversely, use modeled results to suggest improvements to actual S+S deployment. The results of these analyses can be summarized in four key findings: 1) rate structures play a central role in the grid and customer value of demand-side resources; 2) certain customers can benefit more from demand-side resource adoption than others; 3) modeled battery dispatch and sizing reveals opportunities for additional cost savings; and 4) optimal dispatches can reduce grid emissions while maximizing bill savings.

14 SOLAR ENERGY↗
DOE OSTI2025

Probabilistic Deliverability Assessment of Distributed Energy Resources via Scenario-Based AC Optimal Power Flow

As electric grids decarbonize and distributed energy resources (DERs) become increasingly prevalent, interconnection assessments must evolve to reflect operational variability and control flexibility. This paper highlights key modeling limitations observed in practice and reviews approaches for modeling uncertainty. It then introduces a Probabilistic Deliverability Assessment (PDA) framework designed to complement and extend existing procedures. The framework integrates scenario-based AC optimal power flow (AC OPF), corrective dispatch, and optional multi-temporal constraints. Together, these form a structured methodology for quantifying DER utilization, deliverability, and reliability under uncertainty in load, generation, and topology. Outputs include interpretable metrics with confidence intervals that inform siting decisions and evaluate compliance with reliability thresholds across sampled operating conditions. A case study on Puerto Rico’s publicly available bulk power system model demonstrates the framework’s application using minimal input data, consistent with current interconnection practice. Across staged fossil generation retirements, the PDA identifies high-value DER sites and regions requiring additional reactive power support. Results are presented through mean dispatch signals, reliability metrics, and geospatial visualizations, demonstrating how the framework provides transparent, data-driven siting recommendations. The framework’s modular design supports incremental adoption within existing workflows, encouraging broader use of AC OPF in interconnection and planning contexts.

14 SOLAR ENERGY↗
DOE OSTI2020

Batteries in SAM 2020.2.29: Behind-the-Meter Systems

Provide an overview of behind the meter dispatch methods in the SAM 2020.2.29 software for analysis of residential, commercial, and generic battery systems. Discuss the details of SAM's automatic peak shaving and manual energy arbitrage dispatch options.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2023

Experimental Analysis of Distribution Network Voltage Regulation Using Smart Inverters: Preprint

Smart inverters (SI) have huge potential in providing grid services which has not been fully realized yet. One of these grid services, distribution network voltage regulation by SI, can improve the network voltage by regulating the SI reactive and active power output. Voltage regulation by SI is much faster compared to traditional voltage regulating devices, e.g. tap changing transformer, capacitor banks. However, there is gap in available published literature on the characteristics of SIs when the SI is controlled by local controller or external control signal. This paper presents the experimental study to characterize SI reactive power regulation response to two different control methods: autonomous control method and remote dispatch method. It was found that IS reactive power regulation response could be significantly different in terms of delay, and ramp rate for these two methods. Finally, Power-Hardware-in-The-Loop (PHIL) tests were conducted to evaluate the performance of these two methods. The PHIL tests results show that SI response characteristics for autonomous control method and remote dispatch method need to be considered during planning for distribution network voltage regulation using SI.

autonomous control↗
DOE OSTI2023

Preconceptual Designs of Coupled Power Delivery between a 4-Loop PWR and 100-500 MWe HTSE Plants

This study develops a preconceptual design for the integration between a large-scale high-temperature electrolysis facility and a NPP. Two hydrogen facility sizes are considered: 100 MWnom and 500 MWnom. Both steam supply designs use cold reheat steam extraction as a heat source. A reboiler inside the protected area of the power plant transfers steam heat to the demineralized water supply for the hydrogen plant. After the heat transfer, the extracted steam condenses and returns to the condenser while the process steam routes out of the protected area to the electrolyzers. Electrical power is tapped off from the high voltage side of the GSU transformer, where it is then transported via a 345-kV transmission line to the hydrogen facility. Circuit breakers and disconnects are located at both ends of the transmission line. Step down transformers and miscellaneous switchgear/buses are located at the end of the transmission line inside the HTEF boundary. Control capabilities for the steam interfacing equipment and electrical dispatch are accessible from the Main Control Room, and protective relays for the transmission line are located inside the Relay Room. Computer modeling was performed for the thermal and electrical designs. PEPSE analysis provided the steady-state parameters for thermal extraction from the turbine cycle. These parameters were used to inform transients and size equipment in combination with Applied Flow Technology (AFT) Arrow and AFT Fathom modeling for steam and water piping, respectively. Electrical transients were analyzed using PSCAD. An ETAP model was used to evaluate power flow and short circuit, which enabled the sizing of transformers and protective equipment. A cost estimate was developed for both integration designs when considering plant separation distances of 250 m and 500 m. From these estimates, the modifications for thermal and electrical interfacing of a first-of-a-kind nuclear-integrated hydrogen facility are anticipated to cost between $60–250/kWnom., where the subscript “nom” refers to the nominal size of the hydrogen plant. On a thermal power basis, the thermal power has a cost of approximately $8/MWth for a 500 MWnom high temperature electrolysis plant located 500 m distant from the NPP. That value decreases to approximately $7.5/MWth for a 250 m separation distance between the hydrogen plant and the NPP. This value is lower than previous estimates of the cost of heat extracted from NPPs primarily because in this work the steam is extracted from cold reheat instead of the main steam line, which reduces the cost of the dispatched steam by approximately $3.5/MWth. Nuclear steam extraction can provide a profit avenue for many plants and is not restricted to hydrogen production. Ammonia production, oil refining, and paper production, among other industrial processes all require thermal energy, which can be provided by NPPs. Future work should look further at the details of thermal extraction for a variety of use cases. This can include increased levels of extraction and multiple simultaneous users. Additionally, site-specific studies should be performed to develop industry experience and improve cost accuracy.

08 HYDROGEN↗
DOE OSTI2016

Cybersecurity Awareness in the Power Grid

We report on a series of interviews and observations conducted with control room dispatchers in a bulk electrical system. These dispatchers must react quickly to incidents as they happen in order to ensure the reliability and safe operation of the power grid. They do not have the time to evaluate incidents for signs of cyber-attack as part of their initial response. Cyber-attack detection involves multiple personnel from a variety of roles at both local and regional levels. Smart grid technology will improve detection and defense capabilities of the future grid, however, the current infrastructure remains a mixture of old and new equipment which will continue to operate for some time. Thus, research still needs to focus on strategies for the detection of malicious activity on current infrastructure as well as protection and remediation.

Scholtz, Jean↗