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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Double-Signal Retail Pricing Scheme for Acquiring Operational Flexibility from Batteries

Batteries can provide valuable operational flexibility to facilitate the system efficiency. However, there lacks market environments to effectively harness and monetize the value of these assets. Most existing works apply a profit-oriented single-signal pricing scheme, which mixes the value of energy and flexibility together and may ultimately raise the electricity bill. Therefore, this paper proposes a profit-neutral double-signal retail pricing scheme that distinguishes elastic market players (i.e., batteries) from inelastic market players (i.e., inflexible loads) and quantifies the value of energy and flexibility separately. Experimental results indicate that under the incentive provided by the proposed retail pricing scheme: 1) The system efficiency benefit aligns with benefits to both batteries and inflexible loads; 2) Value of operational flexibility, contributing to improve the energy efficiency, can be transparently priced and fairly allocated among batteries; and 3) The dominant role in which inflexible loads play on determining the market price is avoided.

25 ENERGY STORAGE↗
DOE OSTI2024

Retail Electricity Price and Cost Trends: 2024 Update [Slides]

Berkeley Lab’s "Retail Electricity Price and Cost Trends" summarizes recent trends in retail electricity price levels and price drivers in the United States. This report is intended to serve as a reference document for the diverse set of decision-makers impacted by changes in retail electricity prices and to provide a factual basis for assessing recent changes in retail electricity prices and key underlying drivers. National, regional, and state trends are reported for 2019 through 2023 using publicly-available data for: -Average retail electricity prices, retail sales, and utility revenues -Utility capital expenditures, operations and maintenance costs, and fuel and purchased power costs -Retail electricity sales impacts from behind-the-meter resources The report also includes qualitative case studies highlighting recent and/or regionally-specific issues contributing significantly to retail electricity price trends

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Factors influencing recent trends in retail electricity prices in the United States

This study analyzes the primary drivers of recent state-level trends in U.S. retail electricity prices. We summarize pricing trends, explore descriptive relationships, and employ regression models to quantify the influence of various factors. Although the recent national rise in retail prices has largely tracked inflation, state-level trends vary widely. We identify a number of factors that explain trends in subsets of states. States with the greatest price increases typically exhibited shrinking customer loads—partially linked to growth in net metered behind-the-meter solar—and had renewables portfolio standards (RPS) in concert with relatively costly incremental renewable energy supplies. By contrast, recent utility-scale wind and solar deployment that occurred outside RPS programs (but that benefited from tax incentives) had no discernible impact on increased retail prices. Hurricanes, storms and wildfires also contributed to sizable price increases in some states, most notably in California, where wildfire risk mitigation and liability insurance were major cost drivers. Fluctuations in natural gas prices—particularly following the onset of the Ukraine-Russia war—further contributed to sharp price increases through 2022–2023 in many states, with moderation in 2024. The relative influence of these factors varies across states and over time, and relationships may change in the future. Nonetheless, the findings underscore the diverse set of price determinants and highlight the need for continued research to inform effective policy and ensure customer affordability.

Customer load↗
DOE OSTI2019

The retailed gasoline price in China: Time-series analysis and future trend projection

This study introduces a method to systematically project retailed gasoline prices in China and provides projection results. Based on oil taxation and pricing mechanisms in China, this study establishes the statistical relationship between the retailed gasoline prices in China and international crude oil prices using error correction models (ECM), time-series models. Detailed comparison among asymmetric ECM, threshold ECM, and threshold asymmetric ECM are provided. By adopting the ECMs, the study projects the retailed gasoline prices from 2019 to 2050 based on the international crude oil prices from the Annual Energy Outlook provided by the U.S. Energy Information Administration. The results show that the asymmetric responsiveness and the threshold effect exist under current Chinese oil pricing policy with a lag of one month or even shorter in gasoline price adjustment. Moreover, the analysis informs one that, in the short-run, the retailed gasoline prices in China are more sensitive to international crude oil price increases; while in the long-run, the retailed gasoline prices are more sensitive to international crude oil price decreases. Compared with the national average gasoline price in China of 6.04 CNY/Liter in 2017, the national average gasoline price in China is projected to be about 7.64 CNY/Liter (2017 dollar) by 2050.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Case Study: Nuclear-Renewable-Water Integration in Arizona

This document reports the application of the N-R HES software framework to a case study for Arizona Public Service (APS); the manager and part owner of the Palo Verde (PV) nuclear power plant. The case study is a work in progress of which this report presents a detailed description of the current model input data, assumptions and the corresponding results produced by the developed software framework. The goal of the report is, that with this information APS (together with INL) should be able to identify where more detailed data and more accurate model assumptions are necessary to reproduce all driving physical and economic phenomena in order to capture enough complexity of the reality to allow APS to use the results for their strategic decisions. The N-R HES software framework started being developed at INL two years ago [ref]. The framework has reached some level of maturity so that it can be applied to more than simple demonstration cases, e.g. real industry problems. Nevertheless, more capabilities are constantly added to accommodate the special needs of these challenging real life problems. The N-R HES framework is built on top of the RAVEN code [ref] and uses it as driver and workflow manager for all calculations. The framework has specifically been developed for the economic assessment of N-R HES systems. There are four main cornerstones of the N-R HES simulation framework: 1) generation of stochastic time series, 2) a probabilistic analysis and optimization set of algorithms available in RAVEN, 3) a set of models for representation of the physical behavior of N-R HES, and 4) a RAVEN plug-in that maps physical performance into economic performance called CashFlow. Within this framework, a broad spectrum of questions related to N-R HES can be addressed. One of the challenges currently of high interest is that the increasing penetration of variable renewables is altering the profile of the net demand (demand after removing all non curtailable renewable energy sources), with which the other generators on the grid have to cope. The N-R HES software framework is capable to analyze the potential feasibility of mitigating the resultant volatility in the net electricity demand. One possible solution to that problem currently intensively studied by the energy industry is adding stabilizing loads to the grid. These loads can be external industrial processes that are able to ramp production up and down quickly or adding variable internal loads that will lift the base load of the power plant. The latter is a possible solution currently studied by APS. APS if currently anticipating several challenges that will likely arise in the near future. One of them is, as mentioned, coping with the rapid growth of variable renewable energy (VRE) sources put on the grid. Although APS can sell its electricity for a fixed retail price to cover the local demand first, it also sells electricity in excess of the local demand at the Palo Verde energy hub. Due to the growing VRE penetration, the Palo Verde hub electricity spot price is negative more and more frequently. To mitigate this price volatility, APS is seeking to add more base load, so that the quantity of excess energy to be sold for prices potentially less than the internal retail price or even negative prices at the hub is reduced. A second challenge APS is facing is that their cooling water acquisition contract with the Sub Regional Operating Group (SROG) will expire soon and a renewal can only be done for a significantly higher price of the water. Therefore, APS is also seeking for alternative sources for their cooling water. An opportunity currently under investigation is to pump a limited quantity of brackish water from the regional ground water. Although much cheaper than the water from the new SROG contract, the salinity of the brackish water is so high that a blend of brackish and SROG water would need additional treatment to improve its quality for use in the cooling towers. An on-site reverse osmosis (RO) desalination plant is envisaged to reduce the salinity to an acceptable level. This report investigates the economic impact of such an RO plant. As one can see, the RO plant would help with both problems APS is facing: First, it would rise the APS base load helping to mitigate VRE induced hub price volatility. From this perspective, the RO plant can be seen as a stabilizing load on the grid as would be any other industrial process. Second, the RO’s goods, e.g. the clean water produced can be used by APS itself for a (hopefully) lower cost than 100% SROG water would be. The report will first describe the APS water procurement strategy in detail and lay out the possible alternative scenarios studied in this document. This is covered in Chapter 2. Next, in Chapter 3, the APS case model developed within the N-R HES software framework is described. This chapter includes also a description of the needed framework developments to accommodate the APS study.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Explainable AI for a No-Teardown Vehicle Component Cost Estimation: A Top-Down Approach

The broader ambition of this article is to popularize an approach for the fair distribution of the quantity of a system's output to its subsystems while allowing for underlying complex subsystem level interactions. Particularly, we present the use of this framework on a very specific (but generalizable) application, interesting for a more general AI audience. Here, we detail a data-driven approach to vehicle price modeling and its component price estimation by leveraging a combination of concepts from machine learning and game theory. We show an alternative to common teardown methodologies and surveying approaches for component and vehicle price estimation at the manufacturer's suggested retail price (MSRP) level that has the advantage of bypassing uncertainties involved in gathering teardown data, the need to perform expensive and biased surveying, and the need to perform retail price equivalent or indirect cost multiplier adjustments to mark up direct manufacturing costs to MSRP. This novel exercise not only provides accurate pricing of the technologies at the customer level, but also shows the, a priori known, large gaps in pricing strategies between manufacturers, vehicle classes, market segments, etc. There is also clear interaction between the price of technologies and other specifications present in vehicles. Those results are indication that old methods of manufacturer-level component costing, aggregation, and application of flat and rigid adjustment factors should be carefully examined. The findings are based on a database developed by Argonne, which includes over 64,000 vehicles covering MY1990 to MY2020 with hundreds of vehicle specs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Incorporating Experience Curves in Appliance Standards Analysis

The technical analyses in support of U.S. energy conservation standards for residential appliances and commercial equipment have typically assumed that manufacturing costs and retail prices remain constant during the projected 30-year analysis period. There is, however, considerable evidence that this assumption does not reflect real market prices. Costs and prices generally fall in relation to cumulative production, a phenomenon known as experience and modeled by a fairly robust empirical experience curve. Using price data from the Bureau of Labor Statistics, and shipment data obtained as part of the standards analysis process, we present U.S. experience curves for room air conditioners, clothes dryers, central air conditioners, furnaces, and refrigerators and freezers. These allow us to develop more representative appliance price projections than the assumption-based approach of constant prices. These experience curves were incorporated into recent energy conservation standards for these products. The impact on the national modeling can be significant, often increasing the net present value of potential standard levels in the analysis. In some cases a previously cost-negative potential standard level demonstrates a benefit when incorporating experience. These results imply that past energy conservation standards analyses may have undervalued the economic benefits of potential standard levels.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Preliminary Assessment of Spatial Competition in the Market for E85

The Preliminary Assessment of Spatial Competition in the Market for E85 presentation and supplementary report from the U.S. Department of Energy’s National Renewable Energy Laboratory examine how the spacing of E85 fueling stations impacts E85 retail pricing. The analysis finds an inverse correlation between station density and E85 prices, with local competition putting downward pressure on E85 prices. A gas station with E85 whose nearest competitor is within a 0.5 mile radius is associated with a lower E85 price per gallon than an otherwise identical station with E85 whose nearest competitor is farther away. The analysis also finds a higher level of correlation between E85 and both E10 and wholesale gasoline prices than with ethanol costs. This indicates that E85 may, in fact, be priced with respect to its substitute fuel, and not based on the cost of its inputs. These findings help identify key trends and barriers in E85 markets and highlight data gaps that, if addressed, could help enable competitive E85 markets. The analysis was released in February 2017 and uses national and Minnesota-specific price data.

E85, retail pricing, vehicles, fuels, fuel station↗
DOE OSTI2021

Markets and Economic Requirements for Fission Batteries and Other Nuclear Systems

Fission Batteries (FBs) are nuclear reactors defined by five characteristics which enable large-scale deployment: cost competitive, standardized sizes for economic mass production, easy installation and removal, secure and safe unattended operation with high reliability. FBs are not defined by technology or power level. Technical and market considerations suggest that most FBs will produce 20 to 30 MWt. This proceedings reports on the outcomes of two workshops that were held in January 2021 to better define markets and economic challenges for FBs. Three major markets were identified. The largest market is the industrial and commercial heat market. There are about 4000 industrial users (excluding utilities) that require more than one megawatt of heat. The number of customers versus size of heat demand was determined. In a low-carbon world there is the potential for many additional customers—including expanded biofuels production and district heat. The second market is for non-grid electricity. This includes co-generation plants that produce heat and electricity for a single customer. The third market is the maritime market with ~100,000 ships worldwide. In the United States, natural gas is the low-cost energy option today and will remain so unless constraints or taxes impact its use. If restrictions on greenhouse gas emissions, the FB competition includes natural gas with carbon capture, biofuels, hydrogen and grid electricity. Natural gas with carbon capture is not economically viable on a small scale. Biofuels may be expensive but may be the economically preferred option for locations with small energy demands of a few megawatts. Hydrogen is a potential competitor with many of the characteristics of natural gas. Grid electricity is not a competitive source of heat. For FBs to be economically competitive, the price of delivered heat must be $20-50/MWh ($6-15/million BTU). The economically competitive range for non-grid electricity is estimated at $70-100/MWh. These electricity prices are competitive with the retail prices of electricity in many parts of the United States for the customer. FBs are not expected to be competitive selling wholesale electricity to the grid. To achieve the aforementioned cost targets for heat and electricity markets, FB designers must (1) maximize the power output within the constraints of a FB (e.g., truck transportability, passive decay heat removal), (2) drastically reduce the size of onsite staff, (3) adopt core designs with low fuel costs (enrichment and fabrication), and (4) develop a system design that is efficiently manufactured in factories. The business case depends upon more than being just a replacement for natural gas. The largest incentives for adoption of FBs is where they create new markets and new sources of revenue. An example is the paper and pulp industry that burns biomass wastes to provide heat and electricity to make paper. An external heat source could meet the demand for heat and electricity by the paper process and enable converting waste biomass into liquid biofuels rather than burning to provide heat. Other markets, such as data centers, are driven by special energy requirements such as extreme reliability. Most customers are not in the energy business but need heat and electricity to produce a product—a manufactured good, education, retail sales (shopping malls), marine transport or some other product. As a consequence, there will be large incentives to lease rather than own FBs. Leasing avoids the regulatory challenges that remain with the owner of the FB. Leasing creates large incentives for FP standardization of sizes and transportability to maintain the value of the FB at the end of the lease—similar to the leasing of jet engines and aircraft. The economic constraints combined with technical constraints suggest competitive FBs will likely have outputs exceeding 10 MWt. There appear to be little incentives for very long-lived reactor cores because such machines require much larger inventories of fuel. Maintenance requirements and the options to provide technology updates may favor shorter lifetimes (~5 years). The assessment is that there is the potential for FBs to be economically viable and play a major role in global decarbonization in three markets: heat, non-grid electricity and maritime applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

The Case for Natural Gas Fueled Solid Oxide Fuel Cell Power Systems for Distributed Generation

Natural-gas-fueled solid oxide fuel cell (NGSOFC) power systems yield electrical conversion efficiencies exceeding 60% and may become a viable alternative for distributed generation (DG) if stack life and manufacturing economies of scale can be realized. Currently, stacks last approximately 2 years and few systems are produced each year because of the relatively high cost of electricity from the systems. If mass manufacturing (10,000 units per year) and a stack life of 15 years can be reached, the cost of electricity from an NGSOFC system is estimated to be about 7.7 ¢/kWh, well within the price of commercial and residential retail prices at the national level (9.9-10¢/kWh and 11-12 ¢/kWh, respectively). With an additional 5 ¢/kWh in estimated additional benefits from DG, NGSOFC could be well positioned to replace the forecasted 59-77 gigawatts of capacity loss resulting from coal plant closures due to stricter emissions regulations and low natural gas prices.

distributed generation↗
DOE OSTI2015

Riding the Electricity Market as an Energy Management Strategy: Savings from Real-Time Pricing

Dynamic pricing of electricity, in which retail prices facing customers are responsive to changes in the underlying wholesale markets, represents a step towards economic efficiency in that customers get exposed to some or all of the costs facing wholesale market players. But what do customers who opt for this greater exposure – available in the roughly 15 “de-regulated” states, as well as, to some extent, from some regulated utilities – get in return for their risks? The U.S. General Services Administration (GSA) took a retrospective eight-year look at what the savings would have been had they let the loads for which they purchase electricity in the Washington, DC area buy electricity on the real-time pricing (RTP) market – the dynamic pricing option with the highest risk – as opposed to the strategy they chose in actuality, which was fixing flat prices with 3rd-party providers. We found that opting for RTP for the eight years of the study (2005 through 2012) would have resulted in 17% savings, or almost a quarter of a billion dollars, relative to GSA’s actual prices from the 3rd-party suppliers. This is particularly astonishing given that GSA appeared to have timed the market well during the study period, consistently beating the standard offer products provided by the distribution utilities. The issue of budgetary predictability poses an obstacle for customers (especially government ones) considering RTP and, to a lesser extent, other dynamic pricing options. Indeed, GSA would have lost money with RTP in two of the eight years, one of them substantially. But the magnitude of the savings is indisputably compelling and, even if it may be somewhat aberrational due to high congestion in the DC market, begs consideration by large electricity users currently paying to “lock in” fixed flat prices.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Customer Rate and Tariff Design

This webinar covers and introduction to customer rates and tariff design, drivers of utility costs, impacts of evolving grids on rate design, retail price signals, and methods for evaluating rates.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Clean Cities 2012 Vehicle Buyer's Guide

The expanding availability of alternative fuels and advanced vehicles makes it easier than ever to reduce petroleum use, cut emissions, and save on fuel costs. The Clean Cities 2012 Vehicle Buyer's Guide features a comprehensive list of model year 2012 vehicles that can run on ethanol, biodiesel, electricity, propane or natural gas. Drivers and fleet managers across the country are looking for ways to reduce petroleum use, fuel costs, and vehicle emissions. As you'll find in this guide, these goals are easier to achieve than ever before, with an expanding selection of vehicles that use gasoline or diesel more efficiently, or forego them altogether. Plug-in electric vehicles made a grand entrance onto U.S. roadways in model year (MY) 2011, and their momentum in the market is poised for continued growth in 2012. Sales of the all-electric Nissan Leaf surpassed 8,000 in the fall of 2011, and the plug-in hybrid Chevy Volt is now available nationwide. Several new models from major automakers will become available throughout MY 2012, and drivers are benefiting from a rapidly growing network of charging stations, thanks to infrastructure development initiatives in many states. Hybrid electric vehicles, which first entered the market just a decade ago, are ubiquitous today. Hybrid technology now allows drivers of all vehicle classes, from SUVs to luxury sedans to subcompacts, to slash fuel use and emissions. Alternative fueling infrastructure is expanding in many regions, making natural gas, propane, ethanol, and biodiesel attractive and convenient choices for many consumers and fleets. And because fuel availability is the most important factor in choosing an alternative fuel vehicle, this growth opens up new possibilities for vehicle ownership. This guide features model-specific information about vehicle specs, manufacturer suggested retail price (MSRP), fuel economy, and emissions. You can use this information to compare vehicles and help inform your buying decisions. This guide includes city and highway fuel economy estimates from the U.S. Environmental Protection Agency (EPA). The estimates are based on laboratory tests conducted by manufacturers in accordance with federal regulations. EPA retests about 10% of vehicle models to confirm manufacturer results. Fuel economy estimates are also available on FuelEconomy.gov. For some newer vehicle models, EPA data was not available at the time of this guide's publication; in these cases, manufacturer estimates are provided, if available.

02 PETROLEUM↗
DOE OSTI2011

Analysis of Minimum Efficiency Performance Standards for Residential General Service Lighting in Chile

Minimum Efficiency Performance Standards (MEPS) have been chosen as part of Chile's national energy efficiency action plan. As a first MEPS, the Ministry of Energy has decided to focus on a regulation for lighting that would ban the sale of inefficient bulbs, effectively phasing out the use of incandescent lamps. Following major economies such as the US (EISA, 2007) , the EU (Ecodesign, 2009) and Australia (AS/NZS, 2008) who planned a phase out based on minimum efficacy requirements, the Ministry of Energy has undertaken the impact analysis of a MEPS on the residential lighting sector. Fundacion Chile (FC) and Lawrence Berkeley National Laboratory (LBNL) collaborated with the Ministry of Energy and the National Energy Efficiency Program (Programa Pais de Eficiencia Energetica, or PPEE) in order to produce a techno-economic analysis of this future policy measure. LBNL has developed for CLASP (CLASP, 2007) a spreadsheet tool called the Policy Analysis Modeling System (PAMS) that allows for evaluation of costs and benefits at the consumer level but also a wide range of impacts at the national level, such as energy savings, net present value of savings, greenhouse gas (CO2) emission reductions and avoided capacity generation due to a specific policy. Because historically Chile has followed European schemes in energy efficiency programs (test procedures, labelling program definitions), we take the Ecodesign commission regulation No 244/2009 as a starting point when defining our phase out program, which means a tiered phase out based on minimum efficacy per lumen category. The following data were collected in order to perform the techno-economic analysis: (1) Retail prices, efficiency and wattage category in the current market, (2) Usage data (hours of lamp use per day), and (3) Stock data, penetration of efficient lamps in the market. Using these data, PAMS calculates the costs and benefits of efficiency standards from two distinct but related perspectives: (1) The Life-Cycle Cost (LCC) calculation examines costs and benefits from the perspective of the individual household; and (2) The National Perspective projects the total national costs and benefits including both financial benefits, and energy savings and environmental benefits. The national perspective calculations are called the National Energy Savings (NES) and the Net Present Value (NPV) calculations. PAMS also calculate total emission mitigation and avoided generation capacity. This paper describes the data and methodology used in PAMS and presents the results of the proposed phase out of incandescent bulbs in Chile.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Preliminary Assessment of Spatial Competition in the Market for E85: Presentation Supplement

Anecdotal evidence suggests retail E85 prices may track retail gasoline prices rather than wholesale costs. This indicates E85 prices may be higher than they would be if priced on a cost basis hence limiting adoption by some price-sensitive consumers. Using publicly available and proprietary E85 and regular gasoline price data, we examine pricing behavior in the market for E85. Specifically, we assess the extent to which local retail competition in E85 markets decreases E85 retail prices. Results of econometric analysis suggest that higher levels of retail competition (measured in terms of station density) are associated with lower E85 prices at the pump. While more precise causal estimates may be produced from more comprehensive data, this study is the first to our knowledge that estimates the spatial competition dimension of E85 pricing behavior by firms. This technical report elaborates on a related presentation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Preliminary Assessment of Spatial Competition in the Market for E85

Anecdotal evidence suggests retail E85 prices may track retail gasoline prices rather than wholesale costs. This indicates E85 prices may be higher than they would be if priced on a cost basis hence limiting adoption by some price-sensitive consumers. Using publicly available and proprietary E83 and regular gasoline price data, we examine pricing behavior in the market for E85. Specifically, we assess the extent to which local retail competition in E85 markets decreases E85 retail prices. Results of econometric analysis suggest that higher levels of retail competition (measured in terms of station density) are associated with lower E85 prices at the pump. While more precise causal estimates may be produced from more comprehensive data, this study is the first to our knowledge that estimates the spatial competition dimension of E85 pricing behavior by firms. This is an initial presentation; a related technical report is also available.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Assessing Customer Experience and Business Models around Price-to-Device Communication and Smart Control Pathways in CalFlexHub

California is facing three major challenges in electrical grid operation: renewable overgeneration, steep evening ramping, and growing peak demand. The state has identified dynamic retail price response as a key strategy evidenced by CPUC’s Dynamic Rates proceeding and CEC’s Load Management Standards. Furthermore, the CEC launched a $16M “California Load Flexibility Research and Deployment Hub (CalFlexHub)” administered by Berkeley Lab to accelerate price-response flexible load technologies in buildings and EV charging. There are more than 16 laboratory and field demonstration projects in CalFlexHub, each demonstrating innovative automated price-response technologies. CalFlexHub tests various pathways through which hourly price signals and triggered control commands are communicated to load-flexible devices such as smart thermostats, heat pumps, water heaters, and EVs. We identified seven unique communication and control pathways, which involve combinations of third-party cloud, device OEM’s cloud, building central gateway, and local controller in between the price server and the load-flexible devices. It is important for utilities and policy makers to understand the long-term implications of each pathway in designing future programs and creating related policies and mandates for market transformation. We propose an evaluation framework including the following aspects: ● Functionality: connectivity and uptime, resilience, and optimization; ● Customer experience: simplicity in setup, troubleshooting support, continuity, customer choice, first cost, and ongoing cost; ● Business model and scalability: advance interoperability, holistic solution, bridge unique gap, customer base, and value streams and pricing structures. In this paper, we identify emerging business models associated with each communication pathway and discuss their positive features and challenges from the above aspects.

Liu, Jingjing↗