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At least 559 records · Page 31

Impacts of Experimentally Obtained Harmonic Spectrums of Residential Appliances on Distribution Feeder: Preprint

This paper focuses on the harmonic load flow study for a set of residential loads and the impacts of the harmonic contents on the distribution feeder. Owing to the increased use of the power electronic based appliances and energy efficient home equipment like the lighting loads, the percentage of non-linear loads has increased in the distribution system which can impact the system performance, loss, and stability. Thus a comprehensive knowledge of their power quality and harmonic analysis is essential to improve the load models, voltage stability assessment, determining possible interactions at harmonic frequencies, protection planning, and the effect of the system impedance. For this study, the household appliances include the lighting, power electronics, resistive, and motor loads with a nominal supply voltage of 120 V single-phase or 240 V split-phase at a nominal frequency of 60 Hz. The harmonic spectrum as obtained from the experimental data is used to solve the harmonic load flow for a detailed secondary network including the distribution transformer extracted from a real distribution feeder's model. Additionally, the impact of the voltage harmonic on a three phase test load is presented through experimental results. The harmonic data of the transformer terminal voltage as obtained from the former load flow study is scaled to generate the source voltage for the three phase configuration of the grid simulator to make the test setup very similar to a real scenario.

24 POWER TRANSMISSION AND DISTRIBUTION↗

WBS 1.2.3.405 - Life Cycle Assessment of Storage Technologies

Recent commitments by the Biden administration have established targets to achieve a net-zero energy system by 2050. Meeting these targets will spur a rapid transition to clean energy technologies and a commensurate need to develop and deploy energy storage technologies at scale. Pumped Storage Hydro (PSH) is expected to be part of this solution because its ability to provide grid flexibility and stability and enable the dispatching of disparate variable renewable energy technologies. Despite PSH being a mature technology with a history of deployment dating back several decades, there is very little information on the greenhouse gas (GHG) implications of PSH as compared to other storage technologies. The objective of this project is to perform a full lifecycle assessment (LCA) of new PSH projects in the U.S. This LCA includes all project phases (resource extraction, construction, operation, maintenance, end-of-life). The functional unit for this study is 1 kWh electricity delivered by system to grid substation connection point and the estimated lifetime for our base case is 80 years. Data used in this study are based on over 30 potential PSH projects that are in preliminary planning phases and are represent a wide range of potential closed-loop PSH systems in terms of location, technology, and capacity. The project approach, data sources, and modeling assumptions have been informed by a technical review committee of stakeholders that include experts from academia, national and international government, industry, and utilities. The GHGs and energy return on investment (EROI) from PSH will be compared to other storage technologies (e.g., stationary battery storage). Results from this project will improve the PSH community's understanding of the environmental impacts and sustainability of new PSH projects and how PSH compares to other storage technologies. The approach used in this project relies on open-source programming. The analysis framework (source code and data) and will be made publicly available at the end of the project. In addition to reporting results for the base case, we will perform rigorous sensitivity analysis to identify the major drivers, understand impacts of different configurations, and future energy markets. Results from this project will be published in a suitable journal.

ENERGY PLANNING, POLICY, AND ECONOMY,HYDRO ENERGY↗

Scalable Truck Charging Demand Simulation for Cost-Optimized Infrastructure Planning

This project developed a scalable, high-resolution model to simulate medium- and heavy-duty (MHD) electric truck charging demand and assess its impact on grid infrastructure. Using generative modeling, simulation, and cost optimization, the project delivered an end-to-end software pipeline and a library of 96 real-world scenarios for the Dallas–Houston megaregion. We demonstrated a modular architecture for transportation and grid modeling, implemented cost-optimized infrastructure planning methods, and quantified grid capital, operational, and environmental costs across a wide range of truck electrification scenarios. The results have been adopted by major utility stakeholders and contributed to regional planning efforts.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Storage Futures Study: Key Learnings for the Coming Decades

The Storage Futures Study (SFS) is a multiyear research project that explored the role and impact of energy storage in the evolution and operation of the U.S. power sector. The SFS examined the potential impact of energy storage technology advancement on the deployment of utility-scale storage and the adoption of distributed storage, and the implications for future power system infrastructure investment and operations. The research findings and supporting data were published across a series of six reports, culminating in the final, seventh publication that draws upon findings from across the study, previous work, and additional analysis to identify eight key learnings about the coming decades. This presentation is from an NREL webinar to discuss the eight key learnings.

decarbonization↗

A Comprehensive Assessment Tool for Low-TRL Current Energy Converters

Along with a market-competitive levelized cost of energy, a current energy converter technology strongly benefits from an extensive consideration of socioeconomic, environmental, and regulatory factors early in the design process. As part of a technology performance level assessment, a series of assessment questions and guidance are developed and presented to evaluate an early-stage current energy technology on holistic criteria considering the entire device lifecycle. The assessment represents an accumulation of industry and research experience to date and relies on regular updates to ensure alignment with industry best-practices, regulatory requirements, and up-to-date technical understanding. A cradle-to-grave (materials, manufacturing, installation and deployment, operations and maintenance, and end-of-life) assessment of capabilities and functional requirements (i.e., high, medium, and low) performance criteria for current energy converters deployed in tidal, ocean current, and/or river applications. Key considerations related to manufacturing and installation include supply chain robustness, manufacturability and related job creation in the end-user and/or adjacent communities, and the time-to-repayment of the embodied energy debt. During deployment and maintenance operations, the safety of the device and subsystems during disconnect or grid failure, the difficulty and frequency of offshore heavy-lift activities, the avoidance or mitigation of area-use conflicts, the sea-states and weather conditions that permit maintenance access, and the availability of contingency plans (should conditions change unexpectedly) are a portion of the considered assessment criteria. Results include the potential impact of early-stage design decisions on the socioeconomic, environmental, and regulatory performance of a technology that allows developers to increase the product value and probability of success, and minimize costly late-stage design iterations through early and broad consideration of factors affecting overall performance and acceptability.

life cycle analysis↗

Behind-the-Meter Energy Storage and Generation in Support of Electrified Rental Car Centers

Electrification of rental car centers at major airports is expected to generate tens of MW in additional power loads. The magnitude of these loads poses challenges including high utility costs, expensive and lengthy distribution capacity upgrades, and disruptions to traditional operation. Behind-the-meter stationary battery storage and onsite photovoltaic generation offer a viable solution to these challenges without impacting the operation and business model of rental car companies, defined by minimal fleet inventory and short vehicle dwell time. Using data-driven syn-thetic charging loads for the rental car center at the Dallas/Fort Worth airport in the United States, we show that optimally-designed and controlled behind - the- meter resources can reduce the lifecycle cost of electrified rental centers by an average 41 % and reduce peak grid demand by 64 %, deferring the need for distribution upgrades or potentially avoiding it altogether.

battery storage↗

Environmental life cycle assessment of treatment and management strategies for food waste and sewage sludge

A consequential life cycle assessment (LCA) was utilized to compare the environmental impacts of food waste and sewage sludge management strategies. The strategies included a novel two-phase anaerobic digestion (AD) system and alternatives including landfill, waste-to-energy, composting, anaerobic membrane bioreactor, and conventional AD (wet continuous stirred-tank reactor [CSTR]). The co-management of food waste with sewage sludge was also considered for the two-phase AD system and for a conventional AD reactor. Further, a multidimensional LCA approach was taken, considering the five-midpoint impact categories of global warming, smog, human health particulate, acidification, and eutrophication estimated using the U.S. EPA Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts. Co-management of food waste and sewage sludge using the novel two-phase AD system was shown to maximize energy recovery and had a net global warming benefit while reducing other environmental impacts compared with the alternative management strategies. It had similar relative environmental advantages across all categories as conventional AD, with the advantage of a smaller physical footprint. However, both approaches featured net environmental burdens when the background electric grid intensity fell below 0.25 kg CO 2 -eq kWh -1 , as could be expected in a decarbonized electric future. Upgrading the biogas produced from AD to renewable natural gas can displace the use of fossil natural gas for other non-electricity energy requirements that are difficult to decarbonize and may extend the time period of significant environmental benefits of utilizing AD for organic waste management. Treatment of the nutrient-rich supernatant generated by the novel two-phase AD system could be an obstacle for utilities with stringent nutrient discharge limits. Future research and full-scale implementation are needed to demonstrate the benefits of the two-phase AD system predicted through this analysis.

54 ENVIRONMENTAL SCIENCES↗

Downscaling SSP-consistent global spatial urban land projections from 1/8-degree to 1-km resolution 2000–2100

Abstract Long-term, spatial urban land projections that simultaneously offer global coverage and local-scale empirical accuracy are rare. Recently a set of such projections was produced using data-science-based simulations and the Shared Socioeconomic Pathways (SSPs). These projections update at decadal time intervals from 2000 to 2100 with a spatial resolution of 1/8 degree, while many socio-environmental studies customarily run their analysis and modelling at finer spatial resolutions, e.g. 1-km. Here we develop and validate an algorithm to downscale the 1/8-degree spatial urban land projections to the 1-km resolution. The algorithm uses an iterative process to allocate the decadal amount of urban land expansion originally projected for each 1/8-degree grid to its constituent 1-km grids. The results are a set of global maps showing urban land fractions at the 1-km resolution, updated at decadal intervals from 2000 to 2100, under five different urban land expansion scenarios consistent with the SSPs. The data can support studies of potential interactions between future urbanization and environmental changes across spatial and temporal scales.

97 MATHEMATICS AND COMPUTING↗

RU Net for Automatic Characterization of TRISO Fuel Cross Sections

TRistructural ISOtropic (TRISO) particle fuel is a type of nuclear fuel known for its high-temperature and high-burnup performance. Each sub-millimeter diameter TRISO particle consists of uranium-oxycarbide (UCO) or UO2 fuel kernel, coated with buffer, inner pyrolytic carbon (IPyC), silicon carbide (SiC), and outer pyrolytic carbon (OPyC) layers. The SiC layer acts as the main containment barrier for the TRISO particle to retain the fission products, while the IPyC and OPyC layers provide additional barriers to the release of fission products, especially fission gases. During irradiation, phenomena like kernel swelling, buffer densification, and IPyC fracture may impact fuel performance. Post-irradiation microscopy on entire compact cross sections or samples of individual particles deconsolidated from compacts is often used to identify these irradiation-induced changes in morphology. However, each fuel compact generally contains thousands of TRISO particles. To get statistical information on these phenomena, it is cumbersome work if done manually. For example, to get information about swelling/densification behaviors of different layers or kernels after irradiation, researchers previously manually measured the perimeter of each TRISO layer in hundreds of particles after four rounds of iterative grinding and polishing encompassing more than 2000 cross-section images for a total of four fuel compacts. To attempt to reduce the subjectivity inherent in that process and accelerate data analysis, we conducted a study on the automatic TRISO layer segmentation on cross-sectional microscopic images using Convolutional Neural Networks (CNNs). CNNs are a class of machine learning algorithms specifically designed for processing structured grid data that have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we have generated the large irradiated TRISO layer dataset with more than 2000 cross-section TRISO microscopic images and the corresponding annotated images. Based on these annotated images, we have employed different CNNs for automatic segmentation of different TRISO layers. These include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net has the best performance in terms of intersection-over-union (IoU). Through the aid of these CNN models, we can expedite the analysis of TRISO particle cross-sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

Convolutional Neural Networks↗

WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model

Abstract. Urban overheating and its ongoing exacerbation due to global warming and urban development lead to increased exposure to urban heat and increased thermal discomfort and heat stress. To quantify thermal stress, specific indices have been proposed that depend on air temperature, mean radiant temperature (MRT), wind speed, and relative humidity. While temperature and humidity vary on scales of hundreds of meters, MRT and wind speed are strongly affected by individual buildings and trees and vary on the meter scale. Therefore, most numerical thermal comfort studies apply microscale models to limited spatial domains (commonly representing urban neighborhoods with building blocks) with resolutions on the order of 1 m and a few hours of simulation. This prevents the analysis of the impact of city-scale adaptation and/or mitigation strategies on thermal stress and comfort. To solve this problem, we develop a methodology to estimate thermal stress indicators and their subgrid variability in mesoscale models – here applied to the multilayer urban canopy parameterization BEP-BEM within the Weather Research and Forecasting (WRF) model. The new scheme (consisting of three main steps) can readily assess intra-neighborhood-scale heat stress distributions across whole cities and for timescales of minutes to years. The first key component of the approach is the estimation of MRT in several locations within streets for different street orientations. Second, mean wind speed and its subgrid variability are downscaled as a function of the local urban morphology based on relations derived from a set of microscale LES and RANS simulations across a wide range of realistic and idealized urban morphologies. Lastly, we compute the distributions of two thermal stress indices for each grid square, combining all the subgrid values of MRT, wind speed, air temperature, and absolute humidity. From these distributions, we quantify the high and low tails of the heat stress distribution in each grid square across the city, representing the thermal diversity experienced in street canyons. In this contribution, we present the core methodology as well as simulation results for Madrid (Spain), which illustrate strong differences between heat stress indices and common heat metrics like air or surface temperature both across the city and over the diurnal cycle.

Geology↗

Low-temperature solar thermal-power systems for residential electricity supply under various seasonal and climate conditions

In this work, the performance of low-temperature (<100 degrees C) solar thermal-power systems to satisfy residential electric loads was analyzed. The solar-driven system was designed to provide a fraction of the total electricity demand in a complementary operation with the electric grid. The analysis was conducted for an coperation during seven days each season, considering real solar and climate variables and residential loads at different climate zones in the United States. The efficiency of the system strongly depends on the solar radiation profile and the ambient temperature. Maximum efficiencies of around 9.5% were obtained in the cold and marine climate zones due to the high solar energy input and low heat dissipation temperatures. In these two zones, the system could supply more than 98% of the electricity demand all seasons. At mixed-humid and hot-humid regions, the system supplied around 50% of the electric load in three of the four seasons, but it only supplies about 27% of the electricity needs in the mixed-humid zone during summer and hot-humid zone during winter. The effect of the solar collector field area and the tank volume was also analyzed. In general, larger solar fields positively impact the efficiency. However, the impact of the tank volume varies depending on the solar radiation profile and the load requirements. Average efficiencies for the seven-day operation can be larger than 6% with a proper selection of the solar collector area and tank volume for an Organic Rankine Cycle with a capacity of about 2.6 kW. Finally, an economic analysis of the system was conducted, and the results were compared with a solar PV + battery system of similar capacity. It is expected that the cost for the analyzed solar-thermal system decreases in the coming years with the increased interest on low temperature applications.

14 SOLAR ENERGY↗

SpecSims: A Scalable Speculative Tree-based Simulation Cloning Framework for Finite Memory Machines

Simulation cloning is a technique in which cloned simulations whose state spaces differ partially from their parent simulation due to intervening events are spawned at runtime and concurrently advanced. It is a powerful method to carry out what-if analysis by speculatively exploring and evaluating the impact of various permutations of intervening cascade of events. Due to the exponential growth in the number of possible clones even for a small number of distinct intervening events, the practical efficacy of the approach is often severely limited by the maximum available memory of the computing host. In this paper, we introduce a novel speculative simulation cloning framework that executes a simulation cloning campaign capable of efficiently exploring an exponentially large space of clone simulations created by permutation of intervening events under a finite memory constraint. We provide a theoretical analysis of the runtime characteristics of our proposed approach and highlight its novel advantages such as memory-aware and as-long-as-needed execution. Furthermore, in support of our analytical findings and to demonstrate its practical feasibility, we implement a prototype of the cloning framework on a shared memory system and report its performance characteristics in the context of a heat diffusion simulation, and a power grid simulation subject to cascading disruptions from geomagnetic disturbances.

Simulation framework↗

Peak Demand Impacts From Electricity Efficiency Programs

Quantification of the costs and benefits of electricity efficiency programs have focused largely on the economic value of annual energy reductions. State public utility commissions PUCs and utilities are increasingly interested in assessing peak demand impacts of these programs. The U.S. Energy Information Administration defines peak demand as "The maximum load during a specified period of time." In practice, utilities and grid operators use a wide range of definitions for peak demand. With increasing need for a more flexible and resilient electricity system, and changing costs for generation, utilities and other efficiency program administrators must take into account all characteristics of efficiency programs — including peak demand reduction — to ensure a reliable system at the most affordable cost. In this study, Berkeley Lab explored a new metric, the program administrator (PA) cost of saving peak demand (PA CSPD). We collected data on costs, energy savings and peak demand savings for electricity efficiency programs for 36 investor-owned utilities and other PAs in nine states (Arizona, Arkansas, California, Colorado, Illinois, Massachusetts, Maryland, New York and Texas) for 2014 to 2017. While some utilities report demand reductions for their electricity efficiency programs, there has been little sustained effort in the United States to gather peak demand reduction data or benchmark the cost of achieving peak demand impacts. As a first of its kind analysis, we developed a framework for analyzing peak demand savings across utilities and states and begin to quantify the cost of saving peak demand.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Computational Review of Privacy-Preserving Mechanisms for the Smart Grid

Smart grid technologies have rapidly become one of the largest and most comprehensive sources of data for the modern utility. For the most part, data streams are seen as an essential tool that enable utilities to carry their day-to-day business operations, but they also create the need for efficient and secure data management strategies. In the context of the smart grid, ensuring data privacy is becoming an increasing concern due to a combination of factors that range from shifts in operational paradigms and rapid technology evolution to changes in legislation. Furthermore, researchers have highlighted the risks associated with improperly protected energy records. For example, energy consumption data from homes could be used to infer the behaviors and habits of home occupants through activity recognition or user profiling (Fan, 2017), which may lead to unfair service pricing, targeted advertising, or other personal security violations. Similarly, Electric Vehicles’ (EVs) charging metadata could be used to reveal private information about the owner such as their payment methods, preferred charging stations, and other locational and timing information that could be used to reconstruct the vehicle owner’s behaviors. The privacy of user data, even when used for statistical analysis or machine learning training processes, also needs to be carefully considered, as an individual’s private traits may still be vulnerable if their inclusion/exclusion greatly impacts the result or could be linked to a public dataset through cross-reference. The breach of user privacy also has severe impacts for organizations that store, transmit, or work on the data in the form of diminishing the public’s trust in them while potentially incurring legal consequences (e.g., fines and suspensions under the European Union General Data Protection Regulation, Health Insurance Portability and Accountability Act, etc.). Because of these risks, several privacy-preserving mechanisms are available to help organizations comply with privacy legislations and prevent the unauthorized and malicious use of user data. In light of these concerns, this report focuses on performing a computational review of privacy-preserving mechanisms that have received a significant amount of interest in literature. It specifically focuses on 1) homomorphic encryption, 2) zero-knowledge proofs, 3) differential privacy, and 4) federated learning. It is worth noting that although many of the methods presented in this document rely on cryptographic primitives, their intent is not to provide perfect secrecy, but rather to enable users to maintain privacy, and thus they shall not be compared or equated to other constructs that are aimed to address cybersecurity constructs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Convex Relaxations of Maximal Load Delivery for Multi-Contingency Analysis of Joint Electric Power and Natural Gas Transmission Networks

Recent increases in gas-fired power generation have engendered increased interdependencies between natural gas and power transmission systems. These interdependencies have amplified existing vulnerabilities in gas and power grids, where disruptions can require the curtailment of load in one or both systems. Although typically operated independently, coordination of these systems during severe disruptions can allow for targeted delivery to lifeline services, including gas delivery for residential heating and power delivery for critical facilities. To address the challenge of estimating maximum joint network capacities under such disruptions, we consider the task of determining feasible steady-state operating points for severely damaged systems while ensuring the maximal delivery of gas and power loads simultaneously, represented mathematically as the nonconvex joint Maximal Load Delivery (MLD) problem. To increase its tractability, we present a mixed-integer convex relaxation of the MLD problem. Then, to demonstrate the relaxation’s effectiveness in determining bounds on network capacities, exact and relaxed MLD formulations are compared across various multi-contingency scenarios on nine joint networks ranging in size from 25 to 1191 nodes. The relaxation-based methodology is observed to accurately and efficiently estimate the impacts of severe joint network disruptions, often converging to the relaxed MLD problem’s globally optimal solution within ten seconds.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Enabling Staged Pressurized Oxy-Combustion: Improving Flexibility and Performance at Reduced Cost

Introduction: The staged pressurized oxy-combustion (SPOC) process, developed by Washington University in St. Louis (WUSTL), is an oxy-combustion carbon capture technology that employs a steam power cycle to generate electricity. As with atmospheric-pressure oxy-combustion processes, carbon dioxide (CO 2 ) capture rates of 90% or higher can be achieved. The staged-combustion approach of the SPOC process, when operated at elevated gas pressure, allows for near elimination of flue gas recycle (FGR) and leads to significant improvements in efficiency and reduced costs. The primary goal of this project was to investigate the potential for SPOC for flexible operation beyond the capabilities of conventional coal-fired power plants, particularly those employing carbon capture and storage (CCS). Oxy-combustion differs from conventional coal combustion in that the combustion of coal is carried out using oxygen as opposed to air. The resultant flue gas is a mixture of primarily CO 2 and water, greatly simplifying CO 2 capture. As SPOC does the oxy-combustion process under pressure, it is higher efficiency and lower cost than atmospheric oxy-combustion. The project was led by the Electric Power Research Institute, Inc., with the assistance of WUSTL, Doosan Babcock (DBL – boiler plant original equipment manufacturer), and Air Liquide (AL – air separation experts). The specific objectives of the project were to: (1) Evaluate the SPOC concept and develop a risk-based approach to the heating surface layout ensuring that performance (gas and steam side), manufacturing, transportation, and plant erection considerations were fully accounted for in the system design. (2) Improve the technology to ensure its performance and cost potential are substantially better than today’s baseline pulverized coal power plant with post-combustion capture (PCC) or atmospheric oxy-combustion, and show progress toward performance commensurate with projected commercial operation, including 90% or more CO 2 capture. (3) Address critical technology gaps and improving overall system performance for the technology. (4) Perform combustion tests at scale under commensurate pressure to the commercial operating system validate combustor and advance the SPOC combustion modeling tools that will facilitate full-scale design. Combustion Testing: Testing was initially carried out at atmospheric pressure with methane to ensure that all systems were correctly operating. Following this, the testing then proceeded to moderate pressure operation at 4 bara, where different stoichiometric conditions were used across an extended heat input range, showing that a stable flame could be maintained. Testing then proceeded at 10 and 15 bara where it was shown that the ignition system needed to be replaced at these operating conditions. When testing recommenced, a similar stable flame shape was achieved, without any methane support, and the full 100 kWth coal oxy-combustion was demonstrated. Heat flux measurements showed 400 kW/m 2 (0.126 MMBtu/hr-ft 2 ) from the flame, within the 450 kW/m 2 (0.142 MMBtu/hr-ft 2 ) preferred limit defined by DBL for the full-scale design case. Carbon monoxide and carbon-in-ash measurements showed that complete combustion was possible with ultra-low excess oxygen at 1 vol % in the product flue gas. This allowed the full-scale models to be calculated based on this level of excess oxygen, improving the performance of the system as lower feed oxygen is produced in the air separation unit (ASU), saving auxiliary power. Full-Scale Design: The full-scale design is sized to deliver 550 MWe net electrical power output to allow direct comparison with the National Energy Technology Laboratory (NETL) baseline cases using the same Montana Powder River Basin (PRB) fuel. The cases used for direct comparison are: Case S12A (supercritical [SC] coal without CO 2 capture), Case S12B (SC coal with PCC at 90% CO 2 capture, and Case S12F (atmospheric oxy-combustion SC coal with 90% CO 2 capture). The SPOC stages were configured to be identical arrangements, allowing for a more straightforward design, construction, and control strategy. Each stage consists of two PVs, the first being the combustor PV module and the second being the convective PV module. The combustor module is the tallest vessel, with local coal feeding equipment and the burner FGR and oxygen plenums at the top and ash management at the bottom. The combustor module is effectively an open cross section with membrane tubes around the circumference – this unobstructed slender profile ensures that the relatively slower burnout mechanism needed for the low-speed turbulent mixing burner can proceed unimpeded and that molten ash will not attach to any surfaces at an angle to the predominant flue gas flow. The steam turbine used in the SPOC design is essentially the same unit utilized in the atmospheric oxy-combustion case except the degree of heat recovery possible allows the low-pressure (LP) feedwater heater train to be eliminated. This is a result of being able to capture the latent heat of evaporation of the moisture produced in the combustion (normally lost to the stack). The SPOC system outperforms the NETL atmospheric oxy-combustion baseline case by 3.3% points and the PCC case by 7.5% points. This performance increase is mainly a result of the improved heat recovery possible from the product flue gas and from the reduced auxiliary power consumption from the ASU and the CO 2 compression and purification unit over the atmospheric equivalent. The combined improvement in boiler efficiency and reduction in the steam turbine heat rate resulted in a net improvement in the overall plant efficiency by 0.61%, to 35.6% on a HHV basis. This relatively small improvement in plant efficiency between sub-bituminous and bituminous coals shows the value of useful moisture latent heat recovery offered by the SPOC system when using low rank fuels. Flexibility and Turndown: The SPOC system has inherent high turndown capabilities because of a demonstrated high range of combustion stability and the ability to bypass stages, thereby reducing steam generation rates proportionally without altering firing rates in operating stages. ASU units do not generally offer significant turndown opportunities as they are limited by the performance of the compression plant. The baseline SPOC design has a 2-train ASU configuration, needed to be able to meet the 10,500 tonnes per day duty, that can deliver efficient turndown points between 85–100% load with both trains operating, and at 45–50% load with a single train operating. Outside these operating points, the flexibility and efficiency are limited and may be uncompetitive at loads below 45% as the ASU systems are unable to turndown beyond 85% for the base case and 70% for the flexible case. The ASU cold box for the flexible case was designed to operate at loads between 40-100%, below this operating range the purity of the produced oxygen cannot be guaranteed, resulting in additional load for the CPU equipment. The additional power consumption of these cases yields an uneconomic operating condition with poor efficiency when operating at low loads such as 25% and 12%. To address this flexibility constraint, AL evaluated how the ASU configuration could be altered to deliver efficient oxygen supply over the load range. This involved integrating the compressor duties across both ASU trains into a shared duty arrangement with multiple compressors, strategically sized to deliver the duty required across all load ranges between 40–100% by enabling different combinations of the main air compressors and the booster air compressors. The oxygen purity cannot be guaranteed below 40% load for each train – the power consumption at 25% and 12% loads were estimated based on the multi-compressor configuration at maximum turndown as these load cases were not considered in the flexible ASU design. With a different cold box configuration, i.e. number of trains, the entire load range could be delivered within oxygen purity specifications. Although there is a small efficiency reduction at full load, there are significant improvements in overall plant performance during low-load operation. The exact ASU configuration needed will therefore be dependent on the expected operating profile of the unit. Economic Analysis: Cost estimates for the baseline and the flexible cases were developed using NETL baseline case data for common BOP items and an Association for the Advancement of Cost Engineering International Class 5 (conceptual/screening study) assessment of key components unique to the SPOC system. The capital, operating, and maintenance costs were assessed along with the first-year power cost, levelized cost of electricity, and CO 2 captured and avoided cost for the SPOC cases were compared against the relevant NETL baseline cases in January 2019 dollars. Both SPOC cases achieve a lower cost that the alternative NETL baseline cases (with the flexible SPOC case being slightly higher than the baseline SPOC case due to the compounded impact of higher capital costs and lower efficiency at full load). The SPOC cases deliver a lower cost of CO 2 avoided than the NETL baseline cases due to greater efficiency in generating low-carbon power. However, the cost of CO 2 captured is higher because the higher efficiency of the SPOC process generates less CO 2 , hence less needs to be captured, resulting in a high capital cost being shared over a reduced CO 2 quantity. The flexible ASU adds 1.6% overall to the plant cost in comparison to the baseline case, but the efficiency improvements at loads below 50% are significant. Subsequently, depending on the plant load-profile expectation, the flexible ASU would be beneficial if the plant spends a significant portion of its operating life below 50% load. This kind of operating profile is likely to be required for all fossil plants when more renewable electricity generators are installed on the local grid, particularly solar power that can be predicted ahead of time, allowing for appropriate pricing signals to be incorporated into the diurnal cycle. R&D Recommendations: SPOC, while a promising technology, is a relatively recent concept and, as such, operability issues of combustor design and steam-side integration for such systems at a scale relevant to commercial deployment have not been evaluated. WUSTL has conducted extensive small pilot-scale (100 kWth) research to understand and advance pressurized oxy-combustion processes, including investigation of combustion and flame characteristics, radiative heat flux, burner operability, turn down, char burnout, ash characteristics, water-wash column operation, etc. for pressurized oxy-combustion systems. Nonetheless, at this stage in the development of the SPOC process, what is needed is a large-scale pilot plant that can serve to study pressurized oxy-combustion systems and components at a scale commensurate with the maturity of the technology. A scale of 10 MWth, which includes steam-side integration and two stages would yield essential information with respect to heat transfer characteristics both in the radiative and convective sections of the pressure vessels, and the ability to operate the fuel staging process. In addition, while modeling results indicate that combustion and flame characteristics improve with scale, direct studies of the combustor at this scale will ensure that the models can be relied upon for scale up to commercial scale. Furthermore, a detailed analysis must be performed to understand the scaling aspects of key components and systems.

20 FOSSIL-FUELED POWER PLANTS↗

A protocol and analysis of year-long simulations of global storm-resolving models and beyond

We propose a protocol to evaluate and analyze year-long simulations of global storm-resolving models (GSRMs). The proposed protocol complements an earlier 40-day simulation protocol under the DYAMOND (DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains) project to allow the analysis of the seasonal cycle and associated climatic relevant phenomena. This intercomparison aims to reveal how GSRMs, which can simulate mesoscale convective systems (MCSs) in the global domain, reproduce atmospheric large-scale structures related to convection beyond month-long simulations. The intercomparison for one-year simulations is conducted by either atmosphere-only models or atmosphere–ocean coupled models with atmospheric horizontal mesh sizes less than 5 km. We recommend the continuous four seasons from March 2020 to February 2021 as a target period for the intercomparison but with options for many groups to join more flexibly. The output variables are collected at 0.25° resolution, and archives of a small set of native grid variables are encouraged to analyze tropical cyclones and MCSs. Through the proposed global storm-resolving simulation, we will evaluate the climatological distributions of the atmospheric large-scale circulations, such as the Intertropical Convergence Zone (ITCZ), monsoon, midlatitude jets, their time evolution, and the upscale impacts on them. We present sample analyses from a one-year simulation using the 3.5 km mesh Nonhydrostatic Icosahedral Atmospheric Model (NICAM), revealing the realistic zonal contrast of tropical precipitation, no double ITCZ structure, the reasonable midlatitude jet position and intensity but a weak bias of storm track activities, and a warm bias over the Eurasia during boreal winter. We also clarify the cross-scale interaction, such as the effects of cold pools on mean precipitation over the Maritime Continent through the precipitation diurnal cycle and the effects of resolved gravity waves on midlatitude mean flows. The proposed one-year simulation protocol is referred to as the “Sendai Protocol.” This protocol is not unique or definite for evaluating GSRMs; we prospect a hierarchical set of experiments from short-term to multi-year simulations as GSRM intercomparisons.

54 ENVIRONMENTAL SCIENCES↗

Cyber–physical vulnerability and resiliency analysis for DER integration: A review, challenges and research needs

High penetration of renewable and sustainable Distributed Energy Resources (DER) into the traditional distribution system requires a well-coordinated control strategy for the improvement of system-wide reliability and resiliency. Implementation of such a holistic control architecture requires a flexible, near real-time, and bi-directional communication framework for facilitating the participation of various agents in a multi-vendor heterogeneous smart grid. While the sustainability of energy generation is ensured, this exposes the smart grid to extrinsic cyber threats, and appropriate defense mechanism(s) must be deployed to guarantee continued reliability and resiliency of the power grid. Further, the comprehensive literature review presented in this paper discusses the latest trends in the DER control schemes with fast communication requirements and their accompanying cyber–physical vulnerabilities. These control schemes are compared and contrasted for various traits. A three-level DER system architecture has been depicted, facilitating the deployment of these control schemes. The current developments of standard communication protocols, key security mechanisms, and best practices along major standards and guidelines are explored. The impacts of different attack types with miscellaneous DER functions based on various control schemes and associated mitigation solutions are also provided. Finally, challenges and future research directions for limiting cyber-power susceptibility to enhance resiliency are summarized. The work presented here will help us enabling a cyber-resilient and sustainable smart electric grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗