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DOE OSTI2020

Austin Sustainable and Holistic Integration of Energy Storage and Solar PV [Austin SHINES]. Final Report, Version 2

The Austin SHINES project and solution is a software management platform, for an electric grid with a high penetration of dispersed photovoltaic (PV) solar generation sites, which maintains the traditional power quality and reliability associated with grid service. This project developed and deployed the platform as a Distributed Energy Resource Management System (DERMS), engaging multiple advanced controls, to evaluate operation and optimization of a fleet of diverse DER assets, installed at several locations among Austin Energy’s customers and distribution system. The project also produced a methodology to create a replicable DERMS template, adaptable to other regions and market structures. Last, Austin SHINES aimed to demonstrate the solution’s methodology would enable the DER grid ecosystem to serve load at a technical cost (System Levelized Cost of Electricity, or System LCOE) of less than the U.S. Department of Energy SHINES program metric of $0.14/kWh, in a defined boundary, while enabling a high penetration of distributed PV. Research was categorized in 6 reports (Final Deliverables = FD) listed below, with titles and descriptions indicating which area of understanding was investigated: FD-1: System Levelized Cost of Electricity (System LCOE) Methodology The creation and use of the System LCOE to Serve Load metric that encompasses the holistic, system-level costs and benefits of all resources, and enables them to be evaluated based on their ability to support an efficient and low-cost integrated grid ecosystem. FD-2: Software Platform Product Description The creation of new DER control methodologies deployable within a utility-grade software platform that enable DER's to maximize their benefit within a grid, that is capable of serving load enabling a high penetration of distributed PV generation. FD-3: Optimal Design Methodology Optimal design methodologies for individual DER installations that enable utilities to determine the optimal combinations and sizing for individual DER sites. FD-4: Austin SHINES Ownership and Operation Models for DER System Performance A comparison of multiple DER aggregation and ownership methodologies including direct utility control, third-party aggregator, and autonomous. FD-5: Economic Modeling & Optimization A comparison of multiple DER technology mixes and configurations within the distribution system, providing insight into an optimal blend of technologies that best enable the distribution system to serve load at the lowest cost at high penetrations of solar. FD-6: Fielded Assets Deployed DER assets within the Austin Energy SHINES circuits. Austin SHINES provided an opening for state-of-the-art technology products to be deployed, providing a rich opportunity for improving how each of the products perform as stand-alone products, and in concert with other complementary products. The Austin SHINES project comprised of two key metrics for System LCOE: SystemLCOE_SHINES<$0.14/kWh Modeled ΔSystemLCOE_SHINES/ΔSystemLCOE_Base≥20% at same solar penetration The System LCOE calculation uses the costs of the utility-owned infrastructure as it exists today, the cost of the DERs that exist in the system today, and the cost of the purchase of energy from ERCOT wholesale markets over the course of the calendar year. All costs are on an annualized basis. The capital and operating costs are derived from the rate case, which produces a yearly cost. The net cost of energy and services imported to the system is integrated over the test year, as is the load served and solar penetration. The first metric was easily achieved by every scenario considered. The goal was set when the Department of Energy’s SHINES Funding Opportunity Announcement was written in 2015 and was a more difficult target at the time. Due mostly to rapidly declining costs for DERs and the significant decrease in the Electric Reliability Council of Texas (ERCOT) energy market prices, which results in lower net cost of energy purchases, the System LCOE is well below this target for all scenarios considered. A fleet of DERs can assume different mixtures, each of which serves the load at a different LCOE. The optimal mixture of DERs serves load at the smallest System LCOE. The second metric (hereinafter %delta metric) asks that the holistic DERMS controls reduce the incremental cost above the baseline of going to a high solar penetration future by at least 20% as compared to the case of a DER deployment with no sophisticated controls (autonomous). Many comparison sets were created throughout this project. Physical technology was installed for informing utility engineering and testing several types of operational control schemes, through the DERMS. The types of operational control which were compared for valuation of the System LCOE Metric were: Holistic control = using the full suite of the DERMS platform to decide and optimize how/why the systems operate depending on weather, market, and reliability signal input. Autonomous control = a local mode at the asset site, wherein a schedule operates the asset, with visibility into performance only No control = the baseline for comparing value against the other two types of control The types of ownership control included: Direct Utility control = the utility dispatches a signal to each asset Third-Party Aggregator = a third party aggregates a fleet of assets and the utility dispatches one signal for all Autonomous = a local mode is set for operation at the asset site, wherein a schedule operates the asset, with visibility into performance only The types of control methodologies deployable within a utility-grade software platform included: Utility Peak Load Reduction = Lower transmission cost obligation Day-Ahead Energy Arbitrage = Realize economic value through price differential Real-Time Price Dispatch = Realize economic value from real-time price spikes Voltage support = Reduce losses and increase solar generation Distribution Congestion Management = Increase local grid reliability Demand Charge Reduction = Lower customer bills and realize system benefit The fielded assets deployed for the project were: Utility Scale Kingsbery Energy Storage System: 1.5 MW / 3 MWh Li-Ion battery storage Mueller Energy Storage System: 1.75 MW / 3.2 MWh Li-Ion battery storage, 7 Energy Storage Units (250 kW each) La Loma Community Solar: 2.6 MW Commercial Scale Aggregated storage installations at 3 sites, with existing solar (300+ kW): One 18 kW / 36 kWh Li-Ion battery storage Two 72 kW / 144 kWh Li-Ion battery storage Residential Scale Aggregated storage installations: -Six stationary battery storage systems (10 kWh each) at homes with existing solar -One Electric Vehicle installed as Vehicle-to-Grid (V2G) Utility-Controlled Solar via Smart Inverters at 12 homes Autonomously-Controlled Smart Inverters at 6 homes Over the course of the project, Austin SHINES undertook installing more than 3 MW of distributed battery energy storage, smart PV inverters, a DER control platform, and other enabling technologies utilizing customer and utility locations and aggregation models. All of these resources were to be integrated and optimized at the utility level. DER assets and control methodologies were designed to achieve a credible pathway to a System LCOE for energy delivered to load of $0.14//kWh or less by 2020, while maximizing distributed solar generation and maintaining acceptable standards of power quality. The project also established a template for other regions to follow, to maximize the adoption of distributed solar PV in support of an economic and efficient grid. In total, the Austin SHINES project added value to the DER subject area in each layer of integration. From utility, to commercial to residential scales, the sheer hierarchy of communication and coordination was a significant accomplishment in addition to learnings from what these communications revealed was unique to each. Economically, the most effective method demonstrated was the criticality of planning phases. Contingencies and multiple projection scenarios helped guide the project to deploy optimal design as close as feasible, in real world conditions. The project and reports will serve public benefit by outlining specific areas of DER strategy and installation where many stakeholders and needs can be addressed with improved efficiency. Overall, communities and utilities should use the results to guide the increasing options available for powering the grid with DER, renewables, and carbon considerate energy.

14 SOLAR ENERGY↗
DOE OSTI2020

Pumped Storage Hydropower FAST Commissioning Technical Analysis

This report is designed to address barriers and solutions to modern pumped storage hydropower (PSH) development by establishing baseline project development knowledge, defining key aspects of project development, and identifying opportunities to reduce project timelines, costs, and risks. This report’s scope includes post-licensing activities and excludes factors related to permitting or licensing. The U.S. PSH fleet is composed of 43 projects providing the majority (95%) of utility-scale electricity storage in the US. However, only one new PSH facility has become operational in the past 20 years. Several factors contribute to diminishing PSH growth in the US, including the magnitude of project costs and financing interest during development and construction; the length of time from project investment until project revenue; permitting challenges and construction risks; competition from other storage technologies; and unrecognized energy storage valuation. Although innovative PSH concepts (including underground, small, and modular systems) have been investigated, widespread application has yet to occur. In short, the time, cost, and risk associated with modern PSH development has resulted in limited recent growth in the United States, despite the rising energy storage demand from increased deployment of variable renewable technologies. To address these challenges, the US Department of Energy’s (DOE) Water Power Technologies Office initiated the PSH Furthering Advancements to Shorten Time to (FAST) Commissioning project, aimed at catalyzing new solutions, designs, and strategies to accelerate PSH development. This report uses available data from previous license applications, ongoing project cost data, and other global PSH project information based on a typical closed-loop PSH project.

13 HYDRO ENERGY↗
DOE OSTI2021

Managing Solar Photovoltaic Integration in the Western United States: Resource Adequacy Considerations

This study examines the impact of reserve margin-based reliability assessment, as commonly used in capacity expansion models, on planning resource-adequate power systems under high penetrations of solar photovoltaics (PV). As a generation resource, PV is operationally different from the conventional dispatchable resources for which most capacity expansion models were designed. The question this study attempts to answer is whether large amounts of PV on a system (in this case, the Western Interconnection of North America) would bias the results of conventional reserve margin-based capacity expansion modeling towards an over- or under-provisioning of resource adequacy. This analysis used NREL’s Resource Planning Model (RPM) for capacity expansion modeling and NREL’s Probabilistic Resource Adequacy Suite (PRAS) for resource adequacy assessment. RPM uses a reserve margin requirement to enforce resource adequacy. PRAS, a collection of tools for studying the resource adequacy of power systems and the adequacy contributions of individual resources on a probabilistic basis, was used to compute multiple resource adequacy metrics across a number of simulated scenarios and system representations with differing regional detail. In all cases, including high PV penetrations (up to 33% annual generation from PV, interconnection-wide), RPM was able to produce resource-adequate systems as measured by normalized expected unserved energy and loss-of-load expectation results from PRAS. The accuracy of reserve margin approaches depends heavily on the underlying assumptions informing the capacity credit assigned to variable and energy-limited resources, particularly when such resources are abundant in the modeled system. RPM’s standard methodology for estimating variable and flexible resources’ capacity contributions, which is based on the top 100 hours of net load, did not appear to systematically undervalue or overvalue variable generation relative to a more rigorous equivalent firm capacity assessment using PRAS, although both over- and under-valuations were observed in specific scenarios. In the worst cases, the top 100 hour method underestimated the equivalent firm capacity of PV by two percentage points, and overestimated the equivalent firm capacity of PV by five percentage points. Calculating capacity contributions based on the top 10 hours of net load systematically underestimated equivalent firm capacities at more modest PV penetrations, but was often a better approximation of equivalent firm capacity than the existing 100-hour approach in scenarios with higher PV penetrations.

14 SOLAR ENERGY↗
DOE OSTI2021

Distributed Solar Adoption in Orlando: A Household-Level Model for Distribution Resource Planning

Potential for rooftop solar in Florida is massive (47% of retail sales, 3rd overall nationally), yet adoption lags (12th nationally). A 2018 Florida Public Service Commission ruling authorizing solar third-party ownership (leasing) has substantially increased attention on distributed solar in the state. The city of Orlando has committed to a 100% clean-energy target by 2050 and deployment of solar and storage are expected to contribute significantly to reaching the goal. Deployment of customer-adopted solar, unlike utility-procured solar, is uncertain, but known to be spatially correlated with demographic factors and existing adoption. We develop a new method to adapt NREL's dGen model in order to represent building-level agents in adoption forecasts for the Orlando Utility Commission (OUC) service territory. Using the agent-based model we develop projections of solar adoption, subject to scenarios varying future solar costs and valuation, and aggregate adoption predictions by OUC distribution feeder. We find substantial spatial heterogeneity in the projected level of adoption by OUC distribution feeder. For instance, 25% of all projected adoption through 2050 would be concentrated on just 5% of feeders and 88% of projected adoption on 50% of feeders. Because of the uncertainty in adoption, bottoms-up solar adoption forecasting methods at the household-level are integral to long-term resource planning by anticipating system needs as customers increasingly adopt distributed solar, storage, electric vehicles, and other distributed energy resources.

14 SOLAR ENERGY↗
DOE OSTI2021

Storage Futures Study: Distributed Solar and Storage Outlook: Methodology and Scenarios

This report is one in a series of NREL’s Storage Futures Study (SFS) publications. The SFS is a multiyear research project that explores the role and impact of energy storage in the evolution and operation of the U.S. power sector. The SFS is designed to examine the potential impact of energy storage technology advancement on the deployment of utility-scale storage and the adoption of distributed storage, and the implications for future power system infrastructure investment and operations. The research findings and supporting data will be published as a series of reports, with each report being released on its completion. The table below lists the specific research topics planned for examination under the SFS and the associated publication formats. This report, the fourth in the SFS series, provides a set of scenarios for cost-effectiveness and customer adoption for a range of scenarios that include future technology costs and valuation of backup power. The SFS series provides data and analysis in support of the U.S. Department of Energy’s Energy Storage Grand Challenge, a comprehensive program to accelerate the development, commercialization, and utilization of next-generation energy storage technologies and sustain American global leadership in energy storage. The Energy Storage Grand Challenge employs a use case framework to ensure storage technologies can cost-effectively meet specific needs, and it incorporates a broad range of technologies in several categories: electrochemical, electromechanical, thermal, flexible generation, flexible buildings, and power electronics. More information, any supporting data associated with this report, links to other reports in the series, and other information about the broader study are available at https://www.nrel.gov/analysis/storage-futures.html.

25 ENERGY STORAGE↗
DOE OSTI2021

Stochastic Continuous-time Flexibility Scheduling and Pricing in Wholesale Electricity Markets

Large-scale integration of intermittent renewable energy sources (RES) is calling for additional flexibility resources as well as more advanced modeling and optimization techniques to account for the increasing uncertainty and variability in power systems operation. As the RES integration gains momentum, the magnitude and frequency of their variations increase, which may trigger ramping scarcity events in real-time power systems operation. This necessitates revisiting the present definition of power systems flexibility and reserve services to reflect their robustness and adequacy towards sub-interval variations of the load and RES, as well as adjusting the operation models to accommodate the new reserve services. This project took a fundamental approach and aimed at developing continuous-time scheduling and pricing model that accurately models the continuous-time variations of load and RES and efficiently deploys the ramping capability of flexible resources to compensate the sources of variability and uncertainty in the market. In this regard, this project pursued the following goals: Developing stochastic multi-fidelity continuous-time optimization models for scheduling of energy storage (ES) systems and flexible loads in wholesale energy markets; Developing the theory and practices of continuous-time locational marginal pricing for valuating energy storage systems and flexible loads in wholesale energy markets; Developing function space solution approach to convert the proposed stochastic multi-fidelity continuous-time optimization models into tractable mixed-integer linear optimization models; and Defining flexibility reserve as a new type of reserve in markets that would enable ultimate participation of energy storage devices in provision of services to compensate the variability and uncertainty of RES in electricity markets. This project successfully completed all five major tasks defined in the SOPO, and produced 8 high-impact journal papers, 6 conference papers, 3 published U.S. patents, and one web-based software for continuous-time operation optimization of power systems. The application of the proposed flexibility reserve and the stochastic multi-fidelity continuous-time operation scheduling models would modify the forward commitment and schedule of generating units, ES devices and flexible loads, and would line up the resources in such a way that the composition of available resources is better prepared to respond to the sub-hourly variations of the load and renewable resources in real-time operation. Therefore, this project paves the way to sustainable, reliable, and economic integration of renewable energy resources in power system, supporting the progress towards reaching the national targets on energy independence. Even if the proposed models offers a radically different point of view as compared to existing models, it does not alter fundamentally the architecture of power systems operations, nor the complexity of the scheduling problem, so the integration of this project in power systems is extremely practical.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Federal Resilience Resources for State Energy Offices

The Weatherization and Intergovernmental Programs Office, through the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy, has compiled federally funded and publicly available qualitative and quantitative resources that support energy resilience and disaster mitigation planning. This handout is accompanied by the downloadable Resilience Valuation Tools Table that offers more detailed specifications on each quantitative tool.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Comprehensive Assessment of On-And Off-Board Vehicle-To-Grid Technology Performance and Impacts on Battery and the Grid

This project defined, developed, and tested the open standards-based requirements, engineering design and system integration of on and off-vehicle Vehicle-to-Grid technologies both on the grid and on the PEV, to assess their effectiveness in implementing the use cases that create value for the grid, which in turn, can be passed on to the ratepayers and the PEV owners. The project comprised of three key categories of work and four key sub-areas of work. The three key categories were: On-Vehicle V2G, Off-Vehicle V2G, and impact of V2G operation on the battery capacity degradation. The four key sub-areas of work under each of these categories were: defining requirements, implementing the technology, performing system integration testing, and estimating the value of each of the grid services under specific assumptions, on a per-vehicle and on an aggregated basis. The technical implementation demonstrated the validity of standards-based approach to grid integration that led to interoperability, in addition to assessing the operational details with grid constraints imposed at the transformer level. The technology implementation also identified the subtle gaps in the standards definition to close the feedback loop on the accuracy of the standards as written, which are being implemented as revisions to the appropriate protocols. The battery impacts assessment developed a test cycle that the batteries from a real PHEV were subjected to for both the mobility-only and mobility with V2G specific energy cycling. While the battery impact results show a clear incremental degradation in response to additional throughput for V2G application purposes, the amount of additional kWh that can be made available without exceeding the end-of-life capacity definition of the battery at its 10-year warranty period was found to be significant. Given that the PEV battery being exercised during testing was a PHEV battery (smaller energy capacity), and 44% of its usable energy (i.e., SOC) was utilized daily for V2G applications, the EVs with much larger batteries will fare much better, either in terms of extracting more value in terms of incremental kWh for V2G, or in terms of relative incremental degradation of the capacity through the battery lifespan. Further, this battery was the second-generation Lithium-Ion chemistry circa 2015, which is at least two generations ago. Continual improvements in electrochemistry and manufacturing techniques as well as on-board capacity will enable the future batteries to provide even more energy for non-mobility-related services. Finally, the valuation of V2G energy services at the premise, distribution, and the ISO/market level was carried out for both the on-vehicle and off-vehicle cases, to understand both the GHG mitigation and operational efficiency improvements in quantitative terms. The analysis indicates that between $\$400$ and $\$1400$ per year of total value to the grid can be realized. When netted of costs to implement V2G either on or off-vehicle, the net value is available to be shared between the ratepayers and the EV owners. Over the life of the EV, therefore, this value becomes significant and can easily provide both ratepayer and EV owner benefits more than the cost of the equipment, either on or off-board, in addition to providing GHG mitigation benefits both on the grid and on the mobility sides. For these benefits to accrue, the key learnings from both the on- and off-vehicle V2G parts of the project indicate the need for at-scale demonstrations through involvement of real EV owners to validate both the technical feasibility, interoperability, as well as real grid benefits by performing extensive data collection and analysis. This will help inform the grid planners, the program designs, and tariff designers, as well as automotive and equipment manufacturers how best to create their products to maximize grid, ratepayer, and EV owner value.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

The Distribution System Operator with Transactive (DSO+T) Study

The Distribution System Operator with Transactive (DSO+T) study investigates the engineering and economic performance of a transactive energy retail market coordinating a high penetration of customer-side flexible energy assets. The study seeks to answer whether such an implementation is cost effective for customers, recovers sufficient revenue for DSOs, and is equally applicable and beneficial to a range of flexible asset types, renewable generation scenarios, and market assumptions. Using a highly interdisciplinary co-simulation and valuation framework, this assessment encompasses the entire electrical delivery system from bulk system generation and transmission, through the distribution system, to the modeling of individual customer buildings and flexible assets (including heating, ventilation, and air conditioning [HVAC] units, water heaters, batteries, and electric vehicles). The study exercises a transactive energy retail market coordination scheme designed to integrate with an existing day-ahead and real-time competitive wholesale electricity market. Software decision-making agents are designed for the retail market operator as well as various price-responsive flexible assets. The engineering and economic performance of the transactive energy scheme is studied for two separate flexible asset deployments: flexible loads (HVAC units and residential water heaters) and behind-the-meter batteries. The results of each transactive case are compared to a business-as-usual case. These cases are subject to two different renewable generation scenarios, a moderate renewable generation scenario, representative of current levels of renewable generation deployment, and a future high renewables scenario, including the increased deployment of rooftop solar photovoltaic and electric vehicles. The transactive coordination scheme is shown to produce effective and stable control and decrease peak loads 9–15%. The resulting annual demand flexibility provides net economic savings of $3.3–5.0B per year for a region the size of Texas. Detailed analysis shows that net benefits were seen for a range of distribution system operator, customer, and flexible asset types. Both participating customer (with transactive flexible assets) and nonparticipating customers (with nonflexible assets) see reductions in annual utility bills and net annual energy expenses in the range of 10–16%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Distribution System Operator with Transactive (DSO+T) Study: Volume 1 (Main Report)

The Distribution System Operator with Transactive (DSO+T) study investigates the engineering and economic performance of a transactive energy retail market coordinating a high penetration of customer-side flexible energy assets. The study seeks to answer whether such an implementation is cost effective for customers, recovers sufficient revenue for DSOs, and is equally applicable and beneficial to a range of flexible asset types, renewable generation scenarios, and market assumptions. Using a highly interdisciplinary co-simulation and valuation framework, this assessment encompasses the entire electrical delivery system from bulk system generation and transmission, through the distribution system, to the modeling of individual customer buildings and flexible assets (including heating, ventilation, and air conditioning [HVAC] units, water heaters, batteries, and electric vehicles). The study exercises a transactive energy retail market coordination scheme designed to integrate with an existing day-ahead and real-time competitive wholesale electricity market. Software decision-making agents are designed for the retail market operator as well as various price-responsive flexible assets. The engineering and economic performance of the transactive energy scheme is studied for two separate flexible asset deployments: flexible loads (HVAC units and residential water heaters) and behind-the-meter batteries. The results of each transactive case are compared to a business-as-usual case. These cases are subject to two different renewable generation scenarios, a moderate renewable generation scenario, representative of current levels of renewable generation deployment, and a future high renewables scenario, including the increased deployment of rooftop solar photovoltaic and electric vehicles. The transactive coordination scheme is shown to produce effective and stable control and decrease peak loads 9–15%. The resulting annual demand flexibility provides net economic savings of $3.3–5.0B per year for a region the size of Texas. Detailed analysis shows that net benefits were seen for a range of distribution system operator, customer, and flexible asset types. Both participating customer (with transactive flexible assets) and nonparticipating customers (with nonflexible assets) see reductions in annual utility bills and net annual energy expenses in the range of 10–16%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

GIS-Based Graphical User Interface Tools for Analyzing Solar Thermal Desalination Systems & High-Potential Implementation

This project developed a user-friendly, open-source, software that enables a comparative evaluation of solar thermal desalination technology options and employs geospatial data layers to identify regions of high-potential for solar thermal desalination. This was accomplished by integrating solar models with desalination models and enhancing their utility by providing GIS-based data inputs. The developed Solar Energy Desalination Analysis Tool (SEDAT) enables techno-economical evaluation of desalination technologies and selection of regions with the highest potential for using solar energy to power desalination plants. It simplifies the planning, design, and valuation of solar thermal and solar hybrid desalination systems in the U.S. and worldwide. SEDAT uses Dash for integrating various layers of large volumes of GIS data with Python-based models of solar energy generation and desalination technologies. It derives time-series of energy generation and water production, with details of plant performance and suggestions for improving the solar-desalination coupling. It is a one of-a-kind tool of analysis representing a definitive advancement in the state-of-the-art. Of solar desalination modeling This report summarizes the various phases of the tool’s development, and presents examples of the results.

14 SOLAR ENERGY↗
DOE OSTI2022

Distributed Wind Energy Futures Study

To better understand distributed wind opportunities in the United States, researchers at the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory explored cost, performance, and valuation benchmarks necessary for distributed wind to achieve widespread commercial viability in the United States by 2035. Building on DOE's prior benchmark report "Assessing the Future of Distributed Wind: Opportunities for Behind-the-Meter Projects", the new Distributed Wind Futures Study employs higher-resolution data and new modeling techniques to highlight geographic trends in technical and economic potential and to compare the cost and performance of distribution-connected, megawatt-scale wind applications (referred to as "front-of-the-meter" applications) and behind-the-meter systems, thereby informing the case for investment. The report identifies the best locations and sectors for behind-the-meter and front-of-the-meter applications and provides data to inform the trade-offs consumers face when deciding between distributed wind and solar photovoltaic (PV).

17 WIND ENERGY↗
DOE OSTI2022

Valuing Residential Energy Efficiency: Analysis for a Prototypical Southeastern Utility [Slides]

The increasing amount of variable renewable energy resources and shifts towards more end-use and vehicle electrification suggests profound changes to power system planning and operation. Specifically, renewable energy is expected to shift net peak demand from late afternoon to early evening and end-use electrification may significantly increase winter peak demand. Residential energy efficiency is likely to align well with these shifts as it tends to produce savings in the early evening (e.g., from lighting measures) and coincident with heating loads (e.g., from envelope and space conditioning measures). Despite the opportunity to decrease system costs and emissions, residential energy efficiency is often limited by static valuation methods and its economic potential is considerably less than its technical potential. Using hourly residential energy efficiency characterizations, utility program cost data, and a capacity expansion model, we estimate the benefits of residential energy efficiency for a prototypical, summer-peaking utility in the Southeastern region. We first establish the cost-effective residential energy efficiency portfolio through “competition” with supply-side resources in a forward-looking capacity expansion model. Importantly, we then evaluate several scenarios intended to drive an increasing amount of cost-effective residential energy efficiency through measure cost reductions, increased customer adoption, policy goals (e.g., carbon price), and delivery of an integrated package of measures. The results quantify total system cost and emissions reductions, fossil-fuel plant retirements, and peak demand reductions. Results suggest the design and prioritization of policies and programs to access the untapped amount of cost-effective residential energy efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Distributed Wind Energy Futures Study [Slides]

To better understand distributed wind opportunities in the United States, researchers at the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory explored cost, performance, and valuation benchmarks necessary for distributed wind to achieve widespread commercial viability in the United States by 2035. Building on DOE's prior benchmark report "Assessing the Future of Distributed Wind: Opportunities for Behind-the-Meter Projects", the new Distributed Wind Futures Study employs higher-resolution data and new modeling techniques to highlight geographic trends in technical and economic potential and to compare the cost and performance of distribution-connected, megawatt-scale wind applications (referred to as "front-of-the-meter" applications) and behind-the-meter systems, thereby informing the case for investment. The report identifies the best locations and sectors for behind-the-meter and front-of-the-meter applications and provides data to inform the trade-offs consumers face when deciding between distributed wind and solar photovoltaic (PV).

17 WIND ENERGY↗
DOE OSTI2022

Marine Renewable Energy Applications for Restorative Ocean Farming: Kelp

Kelp farming and kelp forest restoration have both been proposed as a solution to locally decrease the impacts of ocean acidification and eutrophication, often with co-benefits to other forms of aquaculture and mariculture. Compared to global markets, the kelp industry in the United States is still in its early phases, with the first commercial kelp farm founded in Casco Bay, Maine in 2010. Since then, interest and effort in kelp production has been increasing, with farms now present in Maine, New Hampshire, Connecticut, Rhode Island, Massachusetts, New York, Washington, and Alaska. Many research projects are underway in the United States to explore benefits of 3D ocean farming, tackle logistical problems of working in the ocean, autonomous farming, and explore viable end uses for kelp products. In seaweed farming, to remove the stored carbon or excess nutrients from the system, the biomass needs to be harvested at the optimal time to avoid the release of CO 2 that comes with decomposition. Timing of the harvest is also important for maximum crop yield, which can vary based on the final product. Additional monitoring needs can include a variety of water quality metrics, growth measurements, and visuals to ensure the health of the farm, comply with permits, support operations and maintenance functions. The variables measured may vary by desired end use of the product, location of farm, and operational design. Monitoring all of these parameters requires specialized devices that can be costly and challenging to maintain. Monitoring devices often face power and logistical constraints that could prevent kelp farmers from adopting these technologies or receiving accurate, efficient monitoring to assess ecosystem benefits and valuation. Marine energy has been identified as a possible power source for these devices. This project investigates the power needs for conducting kelp farm environmental monitoring compared with the available marine energy resource to evaluate if locally generated ocean energy could provide a solution to these monitoring challenges and benefit kelp farmers. This process was structured as follows: 1. Define what data is needed for farmers and their communities through desk research and interviews with end users. 2. Identify sensors and power requirements currently in use or available for commercial purchase. 3. Analyze current kelp and other mariculture farm locations for the potential marine energy resource. 4. Analyze farm designs and associated structures to make recommendations for marine energy design. 5. Quantify value that investment in sensors could provide in terms of carbon credit possibilities.

09 BIOMASS FUELS↗
DOE OSTI2020

Energy Storage Grand Challenge: Energy Storage Market Report

As part of the Department of Energy's (DOE) Energy Storage Grand Challenge (ESGC), DOE intends to synthesize and disseminate best available energy storage data, information, and analysis to inform decision-making and accelerate technology adoption. The ESGC Roadmap provides options for addressing technology development, commercialization, manufacturing, valuation, and workforce challenges to position the United States for global leadership in the energy storage technologies of the future. This report provides a baseline understanding of the numerous, dynamic energy storage markets that fall within the scope of the ESGC via an integrated presentation of deployment, investment, and manufacturing data from the best, publicly-available sources. This report covers the following energy storage technologies: lithium ion batteries, lead acid batteries, pumped storage hydropower, comrpessed air energy storage, redox flow batteries, hydrogen, building thermal energy storage, and select long duration energy storage technologies. Not all energy storage technologies and markets could be addressed in this report. Due to the wide array of energy technologies, market niches, and data availability issues, this market report only included a select group of technologies. For example, thermal energy storage technologies are very broadly defined and cover a wide range of potential markets, technology readiness levels, and primary energy sources. In other areas, data scarcity necessitates a greater understanding of future applications and emerging science. Future efforts will update data presented in this report and be expanded to include other energy storage technologies. This data-driven assessment of the current status of energy storage markets is essential to track progress toward the goals described in the Energy Storage Grand Challenge and inform the decision-making of a broad range of stakeholders. At the same time, gaps identified through the development of this report can point to areas where further data collection and analysis could provide an even greater level of understanding of the full range of markets and technologies. Finally, numerous complementary analyses are planned, underway, or completed that will provide a deeper understanding of the specific technologies and markets covered at a high-level in this report.

25 ENERGY STORAGE↗
DOE OSTI2022

Modeling Value Flows in Utility Rate Structures

As the increased adoption of distributed energy resources continues to challenge flat utility rate structures, time-varying rates and more dynamic mechanisms like transactive energy systems can better leverage customer-sited distributed energy resources to provide grid services. However, adopting new utility policies can be a timely process and requires a high level of transparency into the energy system. A wide range of stakeholders must understand who may be affected by policy changes and how. This work employs the valuation methodology developed under Pacific Northwest National Laboratory’s Transactive Systems Program to outline the functional differences in value flow under a series of conventional rate structures and a transactive energy system. The resulting value model illustrates the nuances that arise and highlights future avenues of work that will be necessary as utilities across the country continue to develop new rate structures and market mechanisms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗