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At least 667 records · Page 37

Projecting California Light-Duty Vehicle Attributes (2019-2035)

In this report, we estimated a set of future vehicle attribute scenarios for new light-duty vehicles for the California market using the Automotive Deployment Options Projection Tool (ADOPT). ADOPT starts simulations with all existing vehicle makes and models and endogenously creates new vehicle models over time based on assumed technology improvements and market conditions. For this study, we simulated four scenarios with varied technology, policy, and electric vehicle infrastructure assumptions. We aggregated simulation results into up to 30 vehicle classes (covering size and price classifications) for each powertrain, for six powertrains. We simulated model years 2019 to 2035. We present results for four vehicle attributes: vehicle acceleration, fuel economy (including electric and gasoline for plug-in hybrid electric vehicles [PHEVs]), vehicle range, and vehicle purchase price. We also present results showing the estimated number of vehicle models available in each vehicle class over time. In the Mid scenario, which contains conditions between our most conservative and most optimistic assumptions for emerging electric and hydrogen technologies, we observe improvements in acceleration, range (for battery-electric vehicles [BEVs]), and vehicle purchase price for electric and hydrogen powertrains. In some cases, we project that consumer preferences lead to trade-offs between vehicle attributes, such as reduced fuel economy in exchange for improved acceleration. Conventional vehicles show modest improvements in fuel economy in these scenarios due to the high numbers of BEV and PHEV sales, which reduce the improvements required in conventional vehicles to meet fleet fuel economy standards. In scenarios with advanced technology assumptions (including reduced battery price and improved energy density), we observe further improvements in BEV range and price relative to the improvements in the Mid scenario.

33 ADVANCED PROPULSION SYSTEMS↗

Modeled Results of Four Residential Energy Efficiency Measure Packages for Deriving Advanced Building Construction Research Targets

The Advanced Building Construction (ABC) Initiative from the U.S. Department of Energy Building Technologies Office is working to accelerate industrialized construction innovations for decarbonizing buildings. To inform performance and cost targets for research under the ABC Initiative, this analysis used the ResStock™ tool to evaluate the energy savings, utility bill impacts, and carbon emissions impacts of four simulated upgrade packages with specific target performance levels on a large sample of residential dwelling units (approximately 550,000) representative of the U.S. housing stock.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Modeling and Market Design Considerations for Conventional and Decarbonized Resources

The following paper reviews various market design issues that will need to be reconsidered due to anticipated changes in the resources that supply energy in wholesale electricity markets. As the energy supply continues towards decarbonization, the change in resource technologies will affect the fundamentals of production scheduling and the policies to address supply variability and uncertainty. We show through simple numerical examples that the existing market design approach based on fuel costs will result in $0/MWh prices with intermittent price spikes during reserve shortages, but that incorporating more granular reserve pricing, energy storage participation, and price-responsive demand participation can restore efficient market clearing with reasonable pricing outcomes. The market design approach fundamentally shifts from fuel based to opportunity cost based. We briefly review alternative market design frameworks that can support this shift, including intraday markets, decentralized markets, flexibility options, and swing contracts. Market designs may also be required to accommodate or support various out-of-market policies and agreements; ideally, these external factors can be integrated into the market design to facilitate efficient exchanges across longer time scales, between other markets, and in support of public policy goals. The paper concludes by discussing how decarbonization trends may affect the design and use of production cost models for short term operations and long term planning studies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Potential Availability of and Supply Curves for Low-Cost, Dispatch-Constrained Electricity

Among other changes, variable renewable energy (VRE) - primarily wind and solar photovoltaics - is achieving a growing share of total generation. High VRE penetrations may result in an increased level of curtailment and thus suppress the value of additional VRE. This VRE, that either would not be built due to price suppression or would be curtailed, can be considered a resource that we define as low-cost, dispatch-constrained electricity (LDE). LDE could be used for various applications which value low-cost electricity and can operate at reduced capacity factors. Examples include electrolytic hydrogen production and carbon capture. This report provides initial estimates of the quantity and availability of the potential LDE resource in the U.S. under scenarios with high VRE penetrations. It also provides supply curves that can be used in subsequent analysis of the opportunity to use the LDE. We modeled several scenarios using capacity expansion and production cost models for LDE prices ranging from $\$ $0/MWh to $\$ $30/MWh. These LDE prices, coupled with low renewable energy cost assumptions, resulted in VRE penetrations ranging from 48-66% in 2050. The resulting LDE supplies range from 100 - 300 TWh/yr at a price of $\$ $0/MWh to 3,500 - 4,200 TWh/yr at $\$ $30/MWh. Increasing LDE prices increases wind and photovoltaics deployment; however, other generation technology capacities do not decrease equivalently in our models. Thus, additional generation is available but the capacity of traditional dispatchable generation is only reduced slightly. The available LDE is concentrated in the central and southwest U.S. regions because of their high wind and solar resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Peer-to-peer communication control for resilient operations of networked cyberphysical systems

This report includes two main accomplishments of the peer-to-peer communication control for resilient operation of networked microgrids project in FY24, which include a scheme for cyberattack-aware coordination of networked microgrids for supporting voltages of bulk power systems and a scheme for price signal-based operations of EV-rich networked microgrids with mixed ownership. First, the cyberattack-aware scheme enables networked microgrids to distributedly determine the amount of reactive power injection to support the voltage of bulk power system (BPS) in a fair manner. In this scheme, a risk-informed algorithm is presented to generate the peer-to- peer (P2P) communication graph with minimal risk of attack on communication links. To deal with cyberattacks on MG controllers, the resilient consensus algorithm (CA) is utilized for MG controllers to robustly estimate the total reactive power headroom, from which the MGs can accurately provide the needed amount of reactive power injection for supporting the voltage of BPS. The CA implementation and performance within the P2P communication framework are demonstrated on the IEEE 39-bus system with 6 microgrids contained in the distribution feeder under different cyberattack scenarios. Second, the price-based scheme enables the usage of the real-time price signal for the operations of electric vehicle (EV)-rich networked-microgrids with mixed ownership, in which not all the microgrids can communicate with the distribution system operator (DSO). In this scheme, a max consensus is introduced to enable the real-time price signal to be propagated from the DSO to all the microgrids, from which each microgrid controller will manage the DERs to balance the load demand and the power injection from the EV charging stations within its microgrid. Numerical results over one day with 288 slots of 5-minute intervals on the modified 123-node test feeder including 3 microgrids with high penetration of EV are presented to evaluate how the price signal affects the operations of networked microgrids under different charging strategies of the EV charging stations. The result indicates that our proposed EVCS (dis)charging strategy, which leverages the flexibility of EVs to support the grid through discharging during peak demand, proves to be a cost-effective solution that reduces operational costs while improving the social welfare of EV charging.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Valuing the Future Electric Grid: A Bid-Based Approach

Energy storage resources (ESRs) and other zero marginal cost (ZMC) resources have unique characteristics that are not fully captured in today’s electricity planning and operations modeling tools. Because the modeling assumptions used in these tools are simplified approximations of how operations and investment decisions occur in the real-world, accurately representing cost and operational characteristics are key for determining how these resources impact price formation. Questions such as—Where should we build new transmission? Will a small modular reactor earn enough revenue to participate in the future electric grid? Is retrofitting a coal plant with carbon capture technology economically feasible?—all require accurate electricity prices, which aren’t available from today’s electricity planning and operations modeling tools. As an example, production cost models (PCMs) are heavily utilized tools that determine the cost and reliability of the electric system. However, as PCMs were developed to help thermal generators manage their fuel inventories, production cost modeling is largely based on fuel prices. Because ESRs do not incur fuel costs, they are often modeled as ZMC resources. In reality, ESRs incur opportunity costs as well as technology-specific (degradation) costs that are non-trivial to calculate but are important for price formation. In this research, we identify options to incorporate more realistic opportunity and degradation costs in ESR bidding algorithms. Expanding available bidding assumptions allows energy system modelers to develop more accurate economic valuations for ESRs, leading to more accurate price formation from leading energy system modeling tools.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Effects of the U.S. inflation reduction act on SMR economics

The U.S. Inflation Reduction Act (IRA) of 2022 provides a wide array of tax credits and other incentives for low-carbon energy. The technology-neutral clean generation production tax credit (PTC) (Section 45Y of the U.S. Internal Revenue Code) and the technology-neutral investment tax credit (ITC) (Section 48E) lower the net cost of new electricity generation projects with zero or negative greenhouse gas emission rates. We evaluate the impact of the IRA legislation—specifically the PTC and ITC—on the cost-competitiveness of small modular reactors (SMRs). We use the Argonne Low-carbon Energy Analysis Framework (A-LEAF) model to calculate the capacity factor of an SMR with a range of hypothetical variable operating and maintenance (O&M) costs in the Electric Reliability Council of Texas (ERCOT) electricity market. We selected ERCOT for market modeling because of its competitive structure, available data, and extensive use in prior literature. We use a discounted cash flow model to calculate the SMR’s net present value based on the market prices and capacity factors from A-LEAF, hypothetical ranges of capital and variable O&M costs, and other input parameters, with or without the IRA tax credits. We determine the SMR owner’s optimal choice of PTC or ITC for the hypothetical ranges of capital and variable O&M costs. We also evaluate potential shifts in the SMR owner’s optimal choice of PTC or ITC based on historical patterns of nuclear capital cost overruns in the United States. We also assess the sensitivity of our results to longer PTC period and electricity prices from the New England market, which tend to be higher than electricity prices in ERCOT. We find that even with the IRA tax credits, only SMRs with low capital and variable O&M costs would be economically feasible in the low-price ERCOT market scenario modeled. A longer PTC period and higher-price market such as New England, however, would significantly expand the economic feasibility of SMRs in the United States.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Dispatch Optimization, System Design and Cost Benefit Analysis of a Nuclear Reactor with Molten Salt Thermal Storage

Variable renewable energy availability has increased the volatility in energy prices in most markets. Nuclear power plants, with a large ratio of capital to variable costs, have historically operated as base load energy suppliers but the need for more flexible operation is increasing. We simulate the techno-economic performance of a 950 MWt nuclear power plant, based on the Westinghouse lead-cooled fast reactor, coupled with molten salt thermal storage as a method for flexible energy dispatch. We use the System Advisor Model to model the nuclear reactor thermal power input and power cycle operating modes. We combine this robust engineering model with a mixed-integer linear program model for optimized dispatch scheduling. We then simulate the coupled nuclear and thermal storage system under different market scenarios with varying price volatility. We find that the coupled plant outperforms the base plant under markets where energy price peaks fluctuate by a factor of two or more about the mean price. We show that a calculated power purchase agreement price for the plant improves by up to 10% when operating under California energy market conditions. Sensitivity analysis on the thermal storage cost shows that the optimal design remains unchanged even when doubling costs.

25 ENERGY STORAGE↗

A Fundamental Economic Assessment of Recovering Rare Earth Elements and Critical Minerals from Acid Mine Drainage Using a Network Sourcing Strategy

In recent years, acid mine drainage (AMD) has emerged as a promising unconventional source of rare earth elements (REEs) and other critical minerals (CMs) such as cobalt and manganese. In this regard, AMD provides a natural heap leaching effect that extracts and concentrates REE/CM from the host strata creating a partially enriched feedstock suitable for downstream extraction, separation, and recovery. While several prior studies have described processes and approaches for the valorization of AMD, very few have described the supply chain and infrastructure requirements as well as the associated economic assessment. To that end, this paper provides a fundamental economic assessment of REE/CM recovery from AMD using a network sourcing strategy in addition to a robust, flexible feedstock separations and refining facility. The methodology of this paper follows that of a typical techno-economic analysis with capital and operating costs estimated using AACE Class IV (FEL-2) guidelines. To demonstrate the range of possible outcomes, four pricing scenarios were modeled including contemporary prices (September, 2021) as well as the minimum and maximum prices over the last decade. In addition, five production scenarios were considered reflecting variations in the product suite, ranging from full elemental separation to magnet REE and CM production only (i.e., Pr, Nd, Tb, Dy, Y, Sc, Co, and Mn). The results of this analysis show that, with the exception of the minimum price scenario, all operational configurations have positive economic indicators with rates of return varying from 25% to 32% for the contemporary price scenario. The optimal configuration was determined to be production of Co, Mn, and all REEs except for mischmetal, which is not recovered. Sensitivity analysis and Monte Carlo simulation show that capital cost and HCl consumption are the two major factors influencing rate of return, thus indicating opportunities for future technology development and cost optimization. Implications of the study and a cooperative profit-sharing model for sourcing are also described.

42 ENGINEERING↗

Energy environment study

The international demand for and supply of oil between the years 1980 and 2000 is assessed and future world oil prices and their implications for the price of jet fuel are estimated. Three critical questions are investigated: (1) how long will the world supply of oil continue to keep pace with its demand under likely trends in its use and discovery; (2) at what price will demand and supply clear the world oil market; (3) what does the analysis imply about the price of jet fuel. Projection of oil price is based upon supply and demand, which is consistent with microeconomic analysis.

Strangways, R.↗

The Jet Propulsion Laboratory low-cost solar array project, 1974-1986

The overall objective of the photovoltaic program is to ensure that photovoltaic conversion systems play a significant role in the nation's energy supply by stimulating an industry capable of providing approximately 50 GWe of installed electricity generating capacity by the year 2000. In order to achieve this overall objective, several time-phased program goals have been defined. Near-term goals are to achieve photovoltaic flat-plate module or concentrator array prices of $2 per peak watt (1975 dollars) at an annual production rate of 20 peak megawatts in 1982. At this price level, energy costs should range from 100 to 200 mills/kwh. Mid-term goals are to achieve photovoltaic flat-plate module or concentrator array prices of $0.50 per peak watt (in 1975 dollars), and an annual production rate of 500 peak megawatts in 1986. Studies project that photovoltaic systems will begin to compete for both distributed and larger load-center utility-type applications and thereby open up significant markets for large-scale photovoltaic systems. Far term goals are to achieve the photovoltaic flat-plate module or concentrator array price goal of $0.10 to $0.30 per peak watt in 1990 (in 1975 dollars), and an annual production rate of 10 to 20 peak gigawatts in 2000. At this price range, energy cost should be in the range of 40 to 60 mills. kwh and be cost effective for utility applications. Achievement of these goals can make photovoltaic systems economically competitive with other energy sources for dispersed on-site applications as well as for central power generation.

Maycock, P. D.↗

Straw man trade between multi-junction, gallium arsenide, and silicon solar cells

Multi-junction (MJ), gallium arsenide (GaAs), and silicon (Si) solar cells have respective test efficiencies of approximately 24%, 18.5% and 14.8%. Multi-junction and gallium arsenide solar cells weigh more than silicon solar cells and cost approximately five times as much per unit power at the cell level. A straw man trade is performed for the TRMM spacecraft to determine which of these cell types would have offered an overall performance and price advantage to the spacecraft. A straw man trade is also performed for the multi-junction cells under the assumption that they will cost over ten times that of silicon cells at the cell level. The trade shows that the TRMM project, less the cost of the instrument, ground systems and mission operations, would spend approximately $552 thousand dollars per kilogram to launch and service science in the case of the spacecraft equipped with silicon solar cells. If these cells are changed out for gallium arsenide solar cells, an additional 31 kilograms of science can be launched and serviced at a price of approximately $90 thousand per kilogram. The weight reduction is shown to derive from the smaller area of the array and hence reductions in the weight of the array substrate and supporting structure. If the silicon solar cells are changed out for multi-junction solar cells, an additional 45 kilograms of science above the silicon base line can be launched and serviced at a price of approximately $58 thousand per kilogram. The trade shows that even if the multi-junction arrays are priced over ten times that of silicon cells, a price that is much higher than projected, that the additional 45 kilograms of science are launched and serviced at $182 thousand per kilogram. This is still much less than original $552 thousand per kilogram to launch and service the science. Data and qualitative factors are presented to show that these figures are subject to a great deal of uncertainty. Nonetheless, the benefit of the higher efficiency solar cells for TRMM is far greater than the uncertainties in the analysis.

Gaddy, Edward M.↗

Cost and Business Analysis Module (CABAM)

In the recent couple of decades, due to international competition, the US launchers lost a considerable amount of market share in the international space launch industry'. Increased international competition has continuously affected the US dominance to eventually place great pressure on future US space launch programs. To compete for future payload and passenger delivery markets, new launch vehicles must first be capable of reliably reaching a number of desired orbital destinations with customer-desired payload capacities. However, the ultimate success of a new launch vehicle program will depend on the launch price it is capable of offering it's customers. Extremely aggressive pricing strategies will be required for a new domestic launch service to compete with low-price international launchers. Low launch prices, then, naturally require a tight budget for the launch program economy. Therefore, budget constraints established by low-pricing requirements eventually place pressure on new launch vehicles to have unprecedentedly low Life Cycle Costs (LCC's).

Lee, Michael Hosung↗

Cost Trade Between Multi-Junction, Gallium Arsenide, and Silicon Solar Cells

Multi-junction (MJ), gallium arsenide (GaAs), and silicon (Si) solar cells have respective test efficiencies of approximately 24%, 18.5% and 14.8%. Multi-junction and gallium arsenide solar cells weigh more than silicon solar 2 cells and cost approximately five times as much per unit power at the cell level. A trade is performed for the TRMM spacecraft to determine which of these cell types would have offered an overall performance and price advantage to the spacecraft. A trade is also performed for the multi-junction cells under the assumption that they will cost over ten times that of silicon cells at the cell level. The trade shows that the TRMM project, less the cost of the instrument, ground systems and mission operations, would spend approximately $552,000 dollars per kilogram to launch and suppon3science in the case of the spacecraft equipped with silicon solar cells. If these cells are changed out for gallium arsenide solar cells, an additional 31 kilograms of science can be launched and serviced at a price of approximately $90 thousand per kilogram. The weight reduction is shown to derive from the smaller area of the array and hence reductions in the weight of the array substrate and supporting structure. ff the silicon solar cells are changed out for multi-junction solar cells, an additional 45 kilograms of science above the silicon base line can be launched and supported at a price of approximately $58,000 per kilogram. The trade shows that even if the multi-junction cells are priced over ten times that of silicon cells, a price that is much higher than projected, that the additional 45 kilograms of science are launched and serviced at $180,000 per kilogram. This is still much less than the original $552,000 per kilogram to launch and service the science. Data and qualitative factors are presented to show that these figures are subject to a great deal of uncertainty. Nonetheless, the benefit of the higher efficiency solar cells for TRMM is far greater than the uncertainties in the analysis.

Gaddy, Edward M.↗

Data Movement Dominates: Final Report

Over the past three years in this project, what we have observed is that the primary reason for data movement in large-scale systems is that the per-node capacity is not large enough—i.e., one of the solutions to the data-movement problem (certainly not the only solution that is required, but a significant one nonetheless) is to increase per-node capacity so that inter-node traffic is reduced. This unfortunately is not as simple as it sounds. Today’s main memory systems for datacenters, enterprise computing systems, and supercomputers, fail to provide high per-socket capacity [Dirik & Jacob 2009; Cooper-Balis et al. 2012], except at extremely high price points (factors of 10–100x the cost/bit of consumer main-memory systems) [Stokes 2008]. The reason is that our choice of technology for today’s main memory systems—i.e., DRAM, which we have used as a main-memory technology since the 1970s [Jacob et al. 2007]—can no longer keep up with our needs for density and price per bit. Main memory systems have always been built from the cheapest, densest, lowest-power memory technology available, and DRAM is no longer the cheapest, the densest, nor the lowest-power storage technology out there. It is now time for DRAM to go the way that SRAM went: move out of the way for a cheaper, slower, denser storage technology, and become a cache instead. This inflection point has happened before, in the context of SRAM yielding to DRAM. There was once a time that SRAM was the storage technology of choice for all main memories [Tomasulo 1967; Thornton 1970; Kidder 1981]. However, once DRAM hit volume production in the 1970s and 80s, it supplanted SRAM as a main memory technology because it was cheaper, and it was denser. It also happened to be lower power, but that was not the primary consideration of the day. At the time, it was recognized that DRAM was much slower than SRAM, but it was only at the supercomputer level (For instance the Cray X-MP in the 1980s and its follow-on, the Cray Y-MP, in the 1990s) that could one afford to build ever- larger main memories out of SRAM—the reasoning for moving to DRAM was that an appropriately designed memory hierarchy, built of DRAM as main memory and SRAM as a cache, would approach the performance of SRAM, at the price-per-bit of DRAM [Mashey 1999]. Today it is quite clear that, were one to build an entire multi-gigabyte main memory out of SRAM instead of DRAM, one could improve the performance of almost any computer system by up to an order of magnitude—but this option is not even considered, because to build that system would be prohibitively expensive. It is now time to revisit the same design choice in the context of modern technologies and modern systems. For reasons both technical and economic, we can no longer afford to build ever-larger main memory systems out of DRAM. Flash memory, on the other hand, is significantly cheaper and denser than DRAM and therefore should take its place. While it is true that flash is significantly slower than DRAM, one can afford to build much larger main memories out of flash than out of DRAM, and we show that an appropriately designed memory hierarchy, built of flash as main memory and DRAM as a cache, will approach the performance of DRAM, at the price-per-bit of flash. In our studies as part of this project, we have investigated Non-Volatile Main Memory (NVMM), a new main-memory architecture for large-scale computing systems, one that is specifically designed to address the weaknesses described previously. In particular, it provides the following features: non-volatility: The bulk of the storage is comprised of NAND flash, and in this organization DRAM is used only as a cache, not as main memory. Furthermore, the flash is journaled, which means that operations such as checkpoint/restore are already built into the system. 1+ terabytes of storage per socket: SSDs and DRAM DIMMs have roughly the same form factor (several square inches of PCB surface area), and terabyte SSDs are now commonplace. performance approaching that of DRAM: DRAM is used as a cache to the flash system. price-per-bit approaching that of NAND: Flash is currently well under $0.50 per gigabyte; DDR3 SDRAM is currently just over $10 per gigabyte [Newegg 2014]. Even today, one can build an easily affordable main memory system with a terabyte or more of NAND storage per CPU socket (which would be extremely expensive were one to use DRAM), and our cycle- accurate, full-system experiments show that this can be done at a performance point that lies within a factor of two of DRAM.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Customer Engagement in AEP gridSMART Residential Transactive System

— In 2013, AEP Ohio (AEP) operated a 5-minute real-time price (RTP) electricity market system on 4 distribution feeders as part of their gridSMART® demonstration project. The RTP households were billed for their electricity usage according to an RTP tariff approved by the Public Utility Commission of Ohio. They were given the incentive that their annual bill would be no greater than if they were on the flat-rate tariff, but they had financial incentives to shift consumption from high price periods to low price periods. Incentives were also available for response under high prices from local events, such as reaching the distribution feeder capacity or a critical peak pricing event. An analysis of this transactive system experiment was completed in early 2014. This paper describes the incentive provided to the customer, the nature of their interaction with the smart thermostat that provided automated response to the transactive signal, and their level of satisfaction with the program.

Widergren, Steven E.↗

Optimizing Biorefinery Design and Operations via Linear Programming Models

The ability to assess and optimize economics of biomass resource utilization for the production of fuels, chemicals and power is essential for the ultimate success of a bioenergy industry. The team of authors, consisting of members from the National Renewable Energy Laboratory (NREL) and the Idaho National Laboratory (INL), has developed simple biorefinery linear programming (LP) models to enable the optimization of theoretical or existing biorefineries. The goal of this analysis is to demonstrate how such models can benefit the developing biorefining industry. It focuses on a theoretical multi-pathway, thermochemical biorefinery configuration and demonstrates how the biorefinery can use LP models for operations planning and optimization in comparable ways to the petroleum refining industry. Using LP modeling tools developed under U.S. Department of Energy's Bioenergy Technologies Office (DOE-BETO) funded efforts, the authors investigate optimization challenges for the theoretical biorefineries such as (1) optimal feedstock slate based on available biomass and prices, (2) breakeven price analysis for available feedstocks, (3) impact analysis for changes in feedstock costs and product prices, (4) optimal biorefinery operations during unit shutdowns / turnarounds, and (5) incentives for increased processing capacity. These biorefinery examples are comparable to crude oil purchasing and operational optimization studies that petroleum refiners perform routinely using LPs and other optimization models. It is important to note that the analyses presented in this article are strictly theoretical and they are not based on current energy market prices. The pricing structure assigned for this demonstrative analysis is consistent with $4 per gallon gasoline, which clearly assumes an economic environment that would favor the construction and operation of biorefineries. The analysis approach and examples provide valuable insights into the usefulness of analysis tools for maximizing the potential benefits of biomass utilization for production of fuels, chemicals and power.

09 BIOMASS FUELS↗

Do energy costs really affect commercial mortgage default risk? New results and implications for energy efficiency investments [PowerPoint]

This paper presents new results on the link between energy factors and commercial mortgage default. First, we summarize results from an empirical analysis of the impact of source energy use intensity (EUI) and electricity prices on mortgage default. We used a unique data set that merges building-level energy use data from city benchmarking ordinances and financial data for commercial mortgages on the same buildings. We found that building source EUI and electricity price are statistically and economically associated with commercial mortgage defaults. Next, we present five case studies on the impact of energy use and price variations on default risk: three office buildings, a hotel, and a multi-family residential building. We use the empirical model coefficients to compute the default risk impacts due to variations in source EUI and electricity price over the course of the mortgage term. We found that variations in source EUI could raise or lower the default rates in these properties by between 5% and 40%, depending on the property type and geography. Electricity pricing has an even greater effect – roughly 60% change in default rate in the Denver area and nearly 90% in northern California. Finally, we propose an energy risk score that lenders can use to assess energy risk and inform mortgage terms. The score is being developed and piloted in collaboration with three mortgage lenders. We conclude with implications of this score as a market signal and mechanism for incentivizing energy efficiency investments through the commercial mortgage channel.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗