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Staying Current: A Community Readiness Framework for Marine Energy Applied to River Current Energy in Alaska

Marine energy-including wave, tidal, and river current energy-can provide a local energy source for rural and remote communities. Marine energy has the potential to bolster self-sufficiency and create economic opportunities while preserving ecological integrity. Communities may be interested in deploying, testing, and advancing these early-stage technologies to meet their needs. However, limited capacity, workforce constraints, and other barriers can challenge development. To better understand a community's interest in and preparedness for marine energy, we developed a suite of 150 'metrics of readiness.' Organized across seven categories-technical, social, environmental, strategic, governance, economic, financial-and 29 subcategories, the metrics provide a holistic perspective beyond the technical aspects of an energy device. We conducted a desktop application of the metrics of readiness for Igiugig, Alaska. The metrics were applied retrospectively for two points in time: before (2009) and after (2018) in-stream testing of a river current energy device. By documenting changes among categories and subcategories of the metrics, our results show the evolving nature of community readiness for river current energy. They also illustrate how our interdisciplinary framework captures the investment in environmental effects research and commitment to strategic planning that occurred in Igiugig. In future applications, we envision the framework could be used to foster public engagement in marine energy, collaborate with communities in project development, shape capacity building activities, prioritize investments, and inform research needs. While our study focuses on enabling river current energy in Alaska, the metrics of readiness have the potential to inform implementation of other renewable technologies with communities in new geographies.

13 HYDRO ENERGY↗

Nanoscale Hybrid Electrolytes with Viscosity Controlled Using Ionic Stimulus for Electrochemical Energy Conversion and Storage

As renewable energy is rapidly integrated into the grid, the challenge has become storing intermittent renewable electricity. Technologies including flow batteries and CO 2 conversion to dense energy carriers are promising storage options for renewable electricity. To achieve this technological advancement, the development of next generation electrolyte materials that can increase the energy density of flow batteries and combine CO 2 capture and conversion is desired. Liquidlike nanoparticle organic hybrid materials (NOHMs) composed of an inorganic core with a tethered polymeric canopy (e.g., polyetheramine (HPE)) have a capability to bind chemical species of interest including CO 2 and redox-active species. In this study, the unique response of NOHM-I-HPE-based electrolytes to salt addition was investigated, including the effects on solution viscosity and structural configurations of the polymeric canopy, impacting transport behaviors. The addition of 0.1 M NaCl drastically lowered the viscosity of NOHM-based electrolytes by up to 90%, reduced the hydrodynamic diameter of NOHM-I-HPE, and increased its self-diffusion coefficient, while the ionic strength did not alter the behaviors of untethered HPE. This study is the first to fundamentally discern the changes in polymer configurations of NOHMs induced by salt addition and provides a comprehensive understanding of the effect of ionic stimulus on their bulk transport properties and local dynamics. These insights could be ultimately employed to tailor transport properties for a range of electrochemical applications.

25 ENERGY STORAGE↗

Phonon-informed Neural Thermal Scattering (NeTS) Optimization for Crystalline Graphite and Beryllium Metal

Fast neutrons born from fission lose energy through scattering interactions in the process of slowing-down. As neutrons thermalize to the order of $k$ $b$ $T$ (where $k$ $b$ is the Boltzmann constant, and $T$ is the temperature of the medium), their de Broglie wavelength and energy approaches the order of inter-atomic spacing and quantized lattice vibrations, i.e., phonons. At thermal energies, the thermal scattering law (TSL), i.e., $S$($α, β$), captures crystal binding contributions to the total reaction rate, or cross section. This dimensionless material property describes the energy ($β$) and momentum ($α$) exchanges available in a medium. Currently, $S$($α, β$) is evaluated in the Full Law Analysis Scattering System Hub (FLASSH) code for discrete inputs and stored as ENDF/B File 7 for 0-phonon elastic (MT 2) and n-phonon inelastic (MT 4) processes. Further processing recasts $S$($α, β$) into cumulative distribution functions for sampling post-collision scattering kinematics. In practice, interpolation schemes are employed to access data between tabulated values. An improvement to this juncture of the nuclear data pipeline is supplying cross sections on-the-fly (OTF), as has been developed for the un-resolved resonance region to minimize non-physical interpolation errors. This capability may improve simulation accuracy for accident and transient analyses, where rapidly varying changes in temperature and pressure are difficult to predict beforehand. To do so, deep artificial neural networks (ANNs) can be employed which collapse non-linear, complex data into a lightweight dictionary of neural weights and biases. This has been successfully demonstrated for the hydrogen in light water $S$($α, β$) dataset in the form of a Neural Thermal Scattering (NeTS) module. In this work, the NeTS framework is extended to consider the impact of material-dependent dynamical features on optimal neural pre-processing and architecture design decisions, such as number of neurons per hidden layer, residual skip connections and neural depth. New NeTS modules for crystalline graphite and beryllium metal illuminate a novel correlation between dynamical nonlinearity and optimal neural parametrization when deploying $S$($α, β$) on-the-fly.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Assessing the Reliability Benefits of Energy Storage as a Transmission Asset

Utilizing energy storage solutions to reduce the need for traditional transmission investments has been recognized by system planners and supported by federal policies in recent years. This work demonstrates the need for detailed reliability assessment for quantitative comparison of the reliability benefits of energy storage and traditional transmission investments. First, a mixed-integer linear programming expansion planning model considering candidate transmission lines and storage technologies is solved to find the least-cost investment decisions. Next, operations under the resulting system configuration are simulated in a probabilistic reliability assessment which accounts for weather-dependent forced outages. The outcome of this work, when applied to TPPs, is to further equalize the consideration of energy storage compared to traditional transmission assets by capturing the value of storage for system reliability.

co-optimization↗

Polarization consistent dielectric screening in polarizable continuum model calculations of solvation energies

A polarization consistent framework, where dielectric screening is affected consistently in polarizable continuum model (PCM) calculations, is employed for the study of solvation energies. The computational framework combines a screened range-separated-hybrid functional (SRSH) with PCM calculations, SRSH-PCM, where dielectric screening is imposed in both PCM self-consistent reaction field (SCRF) iterations and the electronic structure Hamiltonian. We begin by demonstrating the impact of modifying the Hamiltonian to include such dielectric screening in SCRF iterations by considering the solutions of electrostatically embedded Hartree–Fock (HF) exact exchange equations. Long-range screened HF-PCM calculations are shown to capture properly the linear dependence of gap energy of frontier orbitals on the inverse of the dielectric constant, whereas unscreened HF-PCM orbital energies are fallaciously semi-constant with respect to the dielectric constant and, therefore, inconsistent with the ionization energy gaps. Similar trends affect density functional theory (DFT) calculations that aim to achieve predictive quality. Importantly, the dielectric screened calculations are shown to significantly affect DFT- and HF PCM-based solvation energies, where screened solvation energies are smaller compared to the unscreened values. Importantly, SRSH-PCM, therefore, appears to reduce the tendency of DFT-PCM to overestimate solvation energies, where we find the effect to increase with the dielectric constant and the polarity of the molecular solute, trends that enhance the quality of DFT-PCM calculations of solvation energy. Understanding the relationship of dielectric screening in the Hamiltonian and DFT-PCM calculations can ultimately benefit on-going efforts for the design of predictive and parameter free descriptions of solvation energies.

Chemistry↗

2H(p, gamma) 3He cross section measurement using high-energy-density plasmas

An absolute cross section for the radiative capture reaction 2H(p, γ ) 3He has been measured at the OMEGA laser facility using inertially confined plasmas. These high-temperature plasmas are created by imploding a fuel containing capsule using laser ablation, and are advantageous in that they better mimic astrophysical systems. We measure an S factor for this reaction of 0.429 ± 0.026stat ± 0.072sys eV b at Ec.m. = 16.35 ± 0.40 keV, which is higher than the adopted evaluations. This reaction is important as a source of nuclear energy in protostars and brown dwarfs. It is also a critical reaction during big-bang nucleosynthesis, and an accurate cross section can be used as a constraint on cosmology.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Methods for Computing Physically Realistic Estimates of Electric Water Heater Demand Response Resource Suitable for Bulk Power System Planning Models

Demand response is commonly called on to reduce load during system peak times or to respond to contingency events. In future power systems with higher shares of wind and solar generation (which we describe together as variable generation [VG]), demand response could have more opportunities to provide energy shifting or operating reserve services. This report evaluates the ability of residential electric water heaters, both electric resistance water heaters (ERWHs) and heat pump water heaters (HPWHs), to provide such services starting from detailed whole-building energy models that realistically represent New England single family home stock. We use a parsimonious surrogate model to represent operational flexibility in a form suitable for linear and mixed integer programming. This enables relatively fast determination of aggregate contingency reserve resource, price-taking energy shifting outcomes, and in some cases the determination of aggregate models at the megawatt (MW) scale that can be directly included in large-scale grid models. After selecting modeling methods and parameters through various computational experiments, we find interquartile ranges of contingency reserve resource in ISO-NE for about 603,400 ERWHs of 45 MW - 69 MW for Claim10 (50 minute responses provided with 10 minutes of advanced notification) and 65 MW - 102 MW for Claim30 (30 minute responses provided with 30 minutes of advanced notification), and for about 619,000 HPWHs of 48 MW - 88 MW for Claim10 and 52 MW - 90 MW for Claim30. The overall reserve resource is up to 32% of total load for ERWHs providing Claim10 service, 47% for ERWHs providing Claim30 service, 93% for HPWHs providing Claim10 service, and 97% for HPWHs providing Claim30 service. More work is required to determine if HPWHs are inherently more suitable than ERWHs for providing contingency reserve or if these results reflect idiosyncrasies of the single family home stock model used in this study. The value of this contingency resource in a Near-term VG model of ISO-NE is $\$ 0.40$ to $\$1.20$ per water heater-year, and significantly larger, $\$ 3.80$ to $\$ 5.30$ per water heater-year in a Mid-term VG model of ISONE. Aggregating surrogate models to the MW-scale for energy shifting service is more challenging than for contingency service and we only present such results for ERWHs, because we were unable to determine satisfactory ways to deal with HPWHs' time-varying and path dependent operational characteristics. Individual surrogate models suitable for evaluating the energy shifting resource from both ERWHs and HPWHs are created, however, and dispatched against day-ahead prices from the Near-Term VG and Mid-Term VG models of ISO-NE. The individual surrogate models are able to access and potentially shift all 640 GWh of HPWH load and 1,547 GWh of ERWH load we modeled in two different single family home stock models. In contrast, the most effective model of aggregate ERWH shifting resource we created only captured 34.7% of the total ERWH load. Energy shifting affected by price-taking dispatch against modeled day-ahead energy prices produces per water heater year profits of $\$19.44$ - $\$22.93$ for individual HPWHs, $\$39.11$ - $\$40.54$ for individual ERWHs, and up to $\$4.00$ - $\$4.24$ for aggregated ERWHs, with the variations mainly due to grid conditions (more or less VG). When the supply-side response to these changes is accounted for, the per water heater year production cost savings for ISO-NE are $\$7.50$ to $\$17.70$ for the most effective set of endogenously dispatched aggregate ERWHs, $\$15.60$ to $\$15.70$ for individual ERWHs dispatched against the DA prices, and $\$10.70$ to $\$11.20$ for individual HPWHs dispatched against DA prices. Those ranges primarily represent the difference between Near-Term VG and Mid-Term VG grid conditions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Direct Air Capture (DAC) Deployment Assessment in Deep Mitigation Pathways Toward 2075 in the U.S.: MARKAL-NETL Modeling Results

Presentation made at the 2024 Annual International Pittsburgh Energy and Carbon Management Conference (PECMC) OCTOBER 7 - 9, 2024 (virtual). The presentation summarized the methodology and results from energy market scenario analyses of the deployment of Direct Air Capture technologies under net-zero CO2 requirements by 2050. The results showed strong deployment of DAC under all scenarios, with increased value of the technology when other CO2 reduction pathways were unavailable or minimized.

Victor, Nadejda↗

A Model of Large Scale Electrochemical Direct Ocean Capture Under Variable Power

Since limiting warming to 1.5 degrees C by 2100 will not only require an energy transition but also billions of tons of carbon dioxide (CO2) removal per year, it is essential to expand these efforts. This can be done offshore via electrochemical direct ocean capture (eChem DOC) which extracts CO2 from seawater that can later be stored underground or converted to products. Deployments of eChem DOC will be powered by renewable energy and therefore need to function with variable power inputs. This project aims to support future large-scale deployments by developing a model of eChem DOC operation, informed by industry and literature, and assessing its performance under variable power and varying designs. Initial analysis suggests that discretizing the eChem system has a higher impact on increasing overall capture than storing the chemical solutions to continue capture during periods of lower power availability, but this is likely situation dependent. Future work will use more realistic power profiles.

direct ocean capture↗

A simulation-based model studying monoethanolamine and aprotic heterocyclic anion ionic liquid (AHA-IL) mixtures for carbon capture

Capturing of waste CO 2 , particularly from large industrial point sources, is necessary for either permanent storage or CO 2 utilization. Amine solvents used for carbon capture have certain drawbacks, particularly the high energy required by the reboiler for solvent regeneration and degradation of the amine with absorption/regeneration cycling. These challenges may be overcome using ionic liquids (ILs) that can be tailored for operating under typical flue gas stream conditions (8–10% CO 2 , 18–20% H 2 O, 2–3% O 2 , and 67–72% N 2 ). ILs, however, oftentimes suffer from high viscosities, leading to diffusion limitations when compared to amine solvents. This work models the combinations of aprotic heterocyclic anion ILs (AHA-IL) with monoethanolamine (MEA) and studies the carbon capture effectiveness of these mixtures. Furthermore, this study found that all AHA-IL/MEA mixtures exhibited 32 % lower enthalpy of reaction (compared to MEA) and 64 % lower viscosity (compared to AHA-IL), which are desirable characteristics for CO 2 capture solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling Advanced Strippers for CO2 Capture from Gas-Fired Power Plants using Aqueous Piperazine

Energy performance of 5 m piperazine was evaluated with an advanced stripper at the pilot scale, accounting for heat loss. Modeling studies indicated that heat loss at locations other than the heat source impacted the heat duty. For strippers with excess packing, the column was the most important source of heat loss, and values as low as 0.03 GJ/hr can cause pinch and reabsorption of CO2. Solvents like 5 m PZ are more affected by heat loss in the column due to a top-side temperature pinch at high lean loading. Heat loss impacts NGCC CO2 capture more than coal-based CO2 capture. Surface temperature measurements pilot plants showed that heat loss was 50-75% controlled by natural convection. Measured heat loss was correlated with steam flowrate and wind speed and ranged from 8126 to 219668 Btu/hr, representing 35% of the measured heat rate on average. Net heat duty linearly varied with CO2 removal at low lean loading and was similar for coal and NGCC conditions at fixed removal. At 90% removal, net heat duty was about 2.5 GJ/t with 4 and 12% CO2 in the flue gas. 7 At NGCC conditions, strippers with finite packing can benefit from a flashing feed to the top of the column by using a hot bypass. A flashing feed was linked to a reduction in irreversibility of the stripper from temperature driving forces. It also reduces heat duty by up to 6% at fixed packing height and reduces packing requirement for a fixed steam heater size compared to a warm bypass. Lean loading and lean solvent rate were effective handles to maximize profitability of a fixed stripper design at low gas price. High ambient temperature operation can benefit from low pressure stripping to about 0.18 lean loading at 150 ℃ to maintain the cyclic capacity at reduced rich loading. At low gas price, the capture plant was able to maximize profitability even with a high heat duty of 2.7-3.1 GJ/t at a lean loading of 0.2-0.22 mol/mol. Heat recovery by partial water vapor condensation in a gas-liquid exchanger can be replaced by a direct contact condenser (DCC). The DCC improved gas cooling and reduced heat duty compared to the CO2 exchanger at 0.2 lean loading. The DCC when used with a 150 ℃/5.5 bar stripper can reduce the cost of capture compared to the base case by $3- 4/tonne at 15 ft of packing (optimum) but increases cost of capture by $6/tonne with a 120 ℃/2 bar stripper and 10 ft of packing (optimum). The DCC can work effectively with a solvent with a high heat of absorption and thermal stability.

Suresh Babu, Athreya↗

Development of Self-Assembly Supports Enabling Transformational Membrane Performance for Cost-Effective Carbon Capture

This final technical report describes work conducted by Membrane Technology and Research, Inc. (MTR) for the U.S. Department of Energy (DOE), National Energy Technology Lab (NETL) on the development of membranes with transformational performance for carbon capture under award number DE-FE0031596. The work was performed from June 1, 2018 through May 31, 2024. For more than a decade, MTR has worked in partnership with DOE to develop an innovative membrane-based CO 2 capture process. This effort has included the first test of membrane modules with coal-fired flue gas at the Arizona Public Services (APS) Cholla plant in 2010; the accumulation of >11,000 hours of flue gas operation for Polaris modules on a bench-scale 1 tonne/day (TPD) system at the National Carbon Capture Center (NCCC); scale-up of first-generation (Gen-1) Polaris to a 20 TPD small pilot system, and successful operation of this system on a flue gas slipstream at NCCC and in integrated boiler testing at Babcock & Wilcox (B&W). Through continued development efforts, a second-generation (Gen-2) version of the Polaris membrane has been scaled-up to pilot production. This membrane offers 70% higher CO 2 permeance with similar selectivity to the base case Polaris. MTR also developed planar modules designed specifically for the low-pressure, high-volumetric flow rate process conditions of flue gas operation. These new modules have significantly lower pressure-drop values compared to the type originally used (spiral-wound modules), which results in significant energy savings. The goal of the work described in this report was to improve on the Polaris Gen-2 membrane with the ultimate aim to reduce the cost of carbon capture. The majority of the effort was to develop improved support membranes for the multi-layer composite structure of MTR’s Polaris membrane. Earlier work at MTR had identified the support structure as limiting membrane permeances, not because the support itself represents a permeation resistance, but because the distribution of pores at the surface of the support imposes a geometric restriction to diffusion in the layers above it. Support membranes were prepared from a range of polymers, including commercially available block copolymers and a custom synthesized block copolymer alternative. The best support membranes developed in this project reduced the geometric restriction by a factor of two to three. These supports then were used to produce Polaris composite membranes with improved permeances. The second topic was to create a high-selectivity version of the Polaris membrane. The high-selectivity version uses a novel selective polymeric material and high selectivities were confirmed in experiments at MTR. The material is not easily made into very thin films. Consequently, the permeances are significantly lower than the Polaris Gen-2 membrane. The utility of this membrane is therefore limited to the carbon dioxide purification step that produces liquid CO 2 . A Technical and Economic Analysis (TEA) was performed for a carbon capture system that uses both advanced membrane types. The TEA shows the novel advanced membranes reduce the cost of capture by 10%, from $63.32/tonne CO 2 to $56.90/tonne CO 2 (2022 USD). Most of the development work was carried out with laboratory-scale casting and coating equipment. A number, but not all, of the improvements identified have been implemented on commercial-scale manufacturing equipment. The focus of future work at MTR is to incorporate the advancements made into the Polaris membrane manufacturing process.

01 COAL, LIGNITE, AND PEAT↗

Gerischer Electrochemistry Today

Semiconductor photoelectrochemistry is a dynamic and interdisciplinary field at the forefront of research in solar fuels, energy conversion, and catalysis. Here, this Perspective captures the collective insights from the second Gerischer Electrochemistry Today Symposium, held at Colorado State University in Fort Collins, CO, in August 2024, which convened leading researchers, early-career scientists, and industry partners to define the critical next steps for the field. Through interactive sessions, technical talks, panel discussions, and training initiatives─including a Semiconductor Electrochemistry Bootcamp─the symposium emphasized three pillars of advancement: (i) facilitating the exchange of new ideas in semiconductor electrochemistry and charge separation; (ii) fostering the development of future researchers, research topics, and participation in the semiconductor workforce; and (iii) building community. This Energy Focus distills key themes from the meeting and identifies major knowledge gaps in the following areas: mechanisms of charge separation and recombination, role of defects and disorder, dynamic and operando characterization methods, interfacial chemistry and surface passivation, theoretical and modeling limitations, and standardization and benchmarking. The inclusive and collaborative structure of the symposium enabled the generation of this comprehensive report that will serve as a roadmap for fundamental and applied research in the rapidly evolving field of semiconductor electrochemistry over the next decade.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Energy System Transitions and Low-Emission Pathways in Australia, Brazil, Canada, China, EU-28, India, Indonesia, Japan, Republic of Korea, Russia, and United States

The Paris Agreement invited Parties to submit long-term, low-emission development strategies. This study presents national low-emission scenarios to inform such strategies for Australia, Brazil, Canada, China, EU, India, Indonesia, Japan, Russia, Republic of Korea and the USA. The study uses country-level energy–economy and integrated assessment models (IAMs) that incorporate detailed and disaggregated representations of the energy demand and supply systems that are difficult to capture in global IAMs. Models were used to explore low-carbon pathways up to 2050, providing insights in their implications for country emissions, energy system restructuring, energy–economy indicators and system costs. The analysis shows that the low-carbon scenarios of most economies studied here are consistent with pathways limiting global warming to below 2 °C.

Fragkos, Panagiotis↗

Leveraging System Dynamics to Predict the Commercialization Success of Emerging Energy Technologies: Lessons from Wind Energy

The United States urgently needs to tackle the climate crisis while enhancing energy security and resiliency. The complexity of the U.S. energy system, with its interconnected elements, makes predicting future states challenging, especially with the introduction of novel energy systems like wind, solar, clean hydrogen, and advanced nuclear technologies. Modern systems engineering methods and tools can provide deeper insights into these dynamics and future behaviors. This research aims to develop a comprehensive model that captures the main elements and behaviors of new energy technologies within the existing energy system. We hypothesized that the market uptake of novel energy systems is influenced by multiple diverse factors, such as technological learning, availability of resources, and economic incentives; examined the history of electricity generation using land-based wind technologies; and developed a system dynamics model to investigate the relationships between capacity growth and influencing factors, both internal and external. The developed model yielded outcomes that confirmed the hypothesized dynamics of wind energy system diffusion through a quantitative comparison of installed capacity and highlighted the significant influence of resource availability, federal incentives (production tax credits), and technological learning on capacity growth and cost reduction. This research aims to support informed decision-making for investments in novel energy systems and aid in developing effective policies for technology deployment.

17 WIND ENERGY↗

Energy Intensity Baselining and Tracking Guidance

Each company joining the U.S. Department of Energy’s (DOE’s) Better Buildings, Better Plants Program (Better Plants) commits to establishing an energy consumption and energy intensity (EI) baseline and to tracking its energy performance over a 10-year period against that baseline. The baseline must reflect a company’s energy consumption over a 12-month period, covering all its U.S.-based operations. Energy consumption is calculated by fuel type in terms of primary energy (also known as source energy). EI is broadly defined as the amount of energy consumed per unit of output produced. For this guidance document and for the program, the term energy performance represents an evaluation of a facility’s capacity to use energy efficiently. Metrics used to assess a facility’s energy performance can include EI, energy consumption, improvements in EI, etc. Establishing an energy baseline and tracking system is a critical first step in effectively managing energy use. Developing a baseline can help a company understand energy use within the corporation and give it a point of comparison to evaluate future efforts to improve energy performance. It can also support efforts to validate a company’s energy management activities, improve comparative analyses when using benchmarks, and help in predicting future energy needs. In addition, a company that normalizes its performance data can determine highly defensible measures of energy savings generated through implemented energy efficiency projects. Establishing a baseline and tracking energy performance is also a requirement for ISO 50001 certification. Although basic energy data can be collected through utility bills, most manufacturers will have to perform additional analyses to develop accurate and robust energy baselines and tracking systems. Energy is consumed in many ways within the manufacturing sector and can come from multiple sources. Energy is sometimes generated and sold to other parties or captured and reused on-site. External events can exert a significant impact on a facility or company’s energy use independent of any purposeful efforts to improve energy efficiency. Operational changes, such as production shifts—which may be inevitable for some companies over the 10-year period covered by the program—can also make a big difference in energy use. Since Better Plants asks companies to account for all their U.S.-based operations, mergers, acquisitions, and divestitures can also have significant implications for a company’s energy metrics. This document aims to demystify the sometimes complex baselining process. It devotes special attention to the task of normalizing and adjusting energy consumption to account for external factors, such as weather and production changes. A key recommendation is that companies use regression analysis to normalize their energy consumption data whenever possible. Regression analysis is a statistical technique that estimates the dependence of a variable (i.e., energy use in the context of Better Plants) on one or more independent variables such as ambient temperature, while controlling for the influence of other variables at the same time. A properly developed regression analysis can provide a reliable estimate of energy savings resulting from energy improvement strategies and projects by accounting for the effects of variables such as annual production levels and weather. DOE has developed a companion Energy Performance Indicator software tool (EnPI) to simplify the baselining process. This tool can run regression models, calculate changes in EI at the facility level, and automatically compile facility-level data into a corporate-wide metric. Note that although the relevant equations used to calculate EI are provided in this document, the EnPI tool will automatically perform most calculations for the user. Additionally, Better Plants Partners (Partners) can call on their Technical Account Manager (TAM) to help them establish a baseline and assist with the necessary calculations to track progress.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Renewable Energy for Industrial Environmental Management

Costs for renewable energy technologies have declined rapidly in the past decade and their use for residential, commercial, and utility scale electricity has grown exponentially as they become cost competitive. Simultaneously, industrial and manufacturing processes have been increasingly seeking ways to reduce emissions and operational costs in highly competitive sectors. With these combined drivers of lower cost and reduced environmental impact, renewable energy may become a viable energy provider for industrial processes such as oil and gas, mining, chemical refining, food production, and manufacturing. Renewable energy technologies may also partner with other reduced emission energy sources, such as small modular nuclear reactors and carbon capture and utilization, to create cleaner and circular industrial systems for reduced resource use. The Joint Institute for Strategic Energy Analysis (JISEA), which is a partnership of the National Renewable Energy Laboratory (NREL) and five universities and others, has been studying to potential for application of clean energy technologies to the heterogenous energy demands in industry. Dr. Jill Engel-Cox will present an overview of NREL and JISEA, the status and potential future of renewable energy technologies, and collaborations with the oil and gas industry and other industrial sectors to improve their environmental performance and reduce operational costs.

ENERGY PLANNING, POLICY, AND ECONOMY↗