Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “marginal costs”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Liquid Salt Combined-Cycle Pilot Plant Design

The work described in this report is responsive to the Office of Fossil Energy program ‘Energy Storage for Fossil Power Generation.’ This Phase I report has been prepared by Pintail Power LLC, with support from Nexant ECA, Electric Power Research Institute (EPRI) and Southern Company Services as a deliverable for the U.S. Department of Energy for NETL Award DE-FE-00320016. The Liquid Salt Combined Cycle™ (LSCC™) technology provides large-scale energy storage integrated with Fossil Electric Generating Units (FEGUs) to meet critical needs in the energy transition by providing: • the lowest cost large-scale storage for time-shifting of renewable energy, • superior fuel efficiency to reduce GHGs from dispatchable resources, • flexible capacity and ramping to balance variability of wind and solar resources, • essential grid stability services to assure reliability of a low-carbon grid. The LSCC approach: • employs equipment that has already been proven in utility service, • uses safe, non-toxic, non-degrading, perpetual-life storage medium, • leverages and repurposes existing FEGU assets, • expands the value stack of energy storage to reduce market, financing, and commodity risks. Pintail Power has developed the LSCC technology to meet the need for reliable, efficient, and cost-effective integration of Variable Renewable Energy (VRE) into a low-carbon electric grid by coupling proven thermal energy storage with proven gas turbines, steam turbines, and heat transfer equipment. This novel approach is intended to address the key issues facing the grid and operators of renewable and fossil generating units including: • Overgeneration and curtailment of renewables, • Need for fast ramping dispatchable resources, • Improved efficiency and flexibility of fossil units, • Additional peaking capacity to support electrification of transportation and heating, • Provision of reliability services to support high penetration of VRE, especially synchronous inertia and fast frequency response. A Technology Readiness assessment by EPRI confirmed that LSCC technology consists of commercially proven hardware used in industrial and utility applications. Although the novel LSCC approach has not yet been demonstrated as a complete system, interfaces between major components have been conservatively specified. A Phase III pilot is planned to demonstrate equipment integration and operation. The patented innovation is removal of the evaporator section from the exhaust heat recovery system, with the evaporation performed by stored energy in a separate steam generator. This arrangement couples renewable and fossil power generation via long-duration energy storage to deliver cost, performance, and operational synergies, including superior charging and discharging flexibility, reduced fuel consumption and lower CO 2 emissions compared to conventional Combined Cycle Power Plants, and low-cost, large-scale energy storage. The LSCC technology is composed of proven equipment integrated with gas turbine exhaust heat in a novel system. During charging, electric heaters raise the salt temperature as it flows from the Cold Salt Tank to the Hot Salt Tank. During discharging, hot salt produces steam from feedwater that is heated with gas turbine exhaust, which also superheats steam to drive a steam turbine. LSCC technology can be added to any combustion-turbine to integrate renewable energy, provide needed grid services, and increase the value of fossil electric generating units based on the technology’s following attributes: • Long-duration storage enables time-shifting of VRE to avoid curtailment and impairment of renewable assets. • Long storage duration combined with fast-charging capability increases arbitrage opportunities by storing more energy when the price is low and discharging more hours when the price is high. • Long storage duration allows resource adequacy to be supplied across multiple days to increase reliability and reduce risk. • The stored energy reduces fuel heat rate and GHG emissions, and increases merit, so the LSCC dispatches earlier and longer to increase the plant’s capacity factor and asset value. • The stored energy enables pre-heating and startup of the steam cycle, without operating the gas turbine, to enable fast startup and ramping when dispatched for discharge. • The steam turbine can operate without the gas turbine so it can provide valuable synchronous inertia during charging without consuming fuel. • Fast frequency response and regulation services can be provided during charging using solid-state heater and pump controls to vary the charge power input in response to grid signals. • The LSCC system can be configured for resilience including black start, islanded/micro-grid operation, and even self-recharging of storage using either gas turbine power or gas turbine exhaust heat. The commercialization plan is to add LSCC technology to existing simple cycle gas turbine power plants with the 50MW GE LM6000 aero-derivative gas turbine as the reference design basis. A Techno-economic assessment of the reference design evaluated the benefits (Levelized Avoided Cost of Energy) and costs (Levelized Cost of Energy). The plant definition included all major systems and budgetary vendor quotes. Pintail Power and NexantECA developed the overall cost estimate for the LSCC plant up to the total plant cost level, following the DOE-NETL cost estimate guidelines at AACE Class 3 (-20%/+30%). This includes the equipment cost, bulk material, direct and indirect labor costs to arrive at the bare erected cost. Engineering costs are factored from the BEC and added to it to arrive at the EPC cost. Process and project contingencies were then factored from the EPC cost and rolled-up to yield the total plant cost of $\$$184 million for 1746 MWh of discharge electricity. • At $\$$105/kWh, the reference plant costs less than any of the Energy Storage Systems evaluated by PNNL in 2020 for the Energy Storage Grand Challenge. Operations and Maintenance cost estimates were scaled from combined cycle practice, assuming that the LSCC unit was co-located with and sharing some labor expense with other units, to arrive at $\$$2.2 million per year. Plant economics were evaluated using prices from the ERCOT Day-Ahead Market for calendar year 2019 (excluding the market disruptions from the COVID pandemic and the February 2020 deep freeze event). Assuming economic dispatch in the ERCOT Day-Ahead market, the reference plant capacity factor would have discharged for 2777 hours at 91.9 MW, a 31.66% capacity factor, with a marginal cost of $\$$25.59/MWh, and a LACE of $\$$82.41/MWh. Fixed charges were calculated according to EIA guidelines to arrive at an LCOE of $\$$83.48. The benefit-to-cost ratio of 0.99 suggests that the reference plant would have been cost-effective and competitive in the market. EPRI interviewed selected utilities to gauge the need for, applicability of and interest in the LSCC system. Several utilities are currently managing increased load growth along with the inclusion of increasing levels of renewable generation, putting pressure on conventional generation by requiring increased turndown requirements and ultimately lower capacity factors. All of the utilities interviewed have CO 2 reduction targets in the 2030-2050 timeframe that will severely limit the participation of fossil generation and require better utilization of carbon free generation. While there is limited opportunity for storage in the current markets, the utilities interviewed stated that there will be a substantial need for long duration energy storage in the future given the expected trends. Utilizing an energy storage system will generally be preferred over new gas capacity in some cases, with the capabilities of the LSCC system being a potential option for retrofit to existing simple cycle gas turbine units, allowing them to deliver greater participation in the market with lower carbon intensity. A technology gap assessment and technology maturation plan identified a pilot-scale demonstration as the final step before commercialization. Key gaps to be addressed during the Phase II FEED (Front-End Engineering Design) are component selection and design, commissioning procedures, and operational procedures and the control system for LSCC charging and discharging. The project team has been expanded to include Wood Group PLC as EPC. The proposed Phase II work leads to a pilot-scale engineering demonstration (TRL 6) to be conducted at Southern Company’s Plant Rowan, where the prototype system will perform “all the functions that will be required of the operational system.” The proposed pilot will facilitate commercialization (TRL-9) by scale-up to utility-scale systems integrated with peaking GTs or directly to facility scale systems using industrial GTs. The conceptual design for the pilot plant focuses on the novel integration aspects of LSCC technology. A slipstream of gas turbine exhaust will feed a waste heat recovery unit coupled to a molten salt steam generator heated by stored energy. The pilot is intended to demonstrate all key operating modes of the LSCC technology during charging, discharging and standby. The pilot equipment will be approximately one-seventh scale of the LM6000 commercial target and is expected to have commercial off-ramp potential for facility-scale applications.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

AC Power Flow Based DLMP Calculation and Decomposition Method to Smooth Power Fluctuation of Distributed Renewable Energy Sources

As the penetration of renewable energy sources increases, the growing renewable power variability brings ramping issues to power systems. Meanwhile, the development of distributed energy resources (DERs) makes the distribution systems to provide both energy and ancillary services. To incentivise individual resources and customers to alleviate ramping issues on the demand side, a two-stage distribution locational marginal price (DLMP) calculation and decomposition method is developed to formulate the marginal power ramping price for DERs. In the first stage of the proposed method, a distribution system operator market scheduling model based on AC optimal power flow is designed to estimate the optimal operating point of the distribution system. Subsequently, the voltage and power flow constraints are linearised in stage two to calculate DLMP. Finally, based on the Lagrange function and sensitivity factors, DLMP is decomposed to the marginal costs for active/reactive power, voltage management, power loss and power variability. Case studies demonstrate that the proposed model can effectively smooth the power fluctuation and reduce the ramping flexibility requirements of distribution systems.

AC optimal power flow↗
DOE OSTI2023

Reserve and energy scarcity pricing in United States power markets: A comparative review of principles and practices

Here, errors in forecasting load and renewable-based generation in restructured power systems mean that independent system operators (ISOs) must procure sufficient operating reserves to keep the real-time operation of the system reliable and secure. But when procured reserves turn out to be insufficient in real-time due to the lack of resource capacity or ramp capability, operators often set higher prices for reserves and energy to encourage more supply, and to motivate consumers to decrease usage or shift it to other times. This procedure, which is called scarcity or shortage pricing, is a core feature of U.S. electricity markets. It is receiving increased attention from market designers and stakeholders because scarcity will become more important for spot price formation in the future with the increased penetration of zero-marginal cost renewables, and the shrinking role of fuel costs in setting prices. Scarcity pricing is implemented in various ways by different ISOs. These differences have practical implications for the level of prices and incentives for investment, operations, and demand modification. In this paper, general approaches and specific calculation procedures for reserve and energy scarcity pricing practices and calculations across the seven ISO-based U.S. power markets are reviewed and compared. A consistent terminology is used to facilitate the comparison. Current scarcity pricing practices are grouped into three approaches: (1) imposing an adder after the spot market is run; (2) including stepwise demand curves within market clearing procedures for non-contingency reserve products (e.g., the novel flexiramp product), which tends to yield longer right tails for energy scarcity premium curves; and (3) having stepwise demand curves for traditional contingency reserve products only, which results in shorter right tails in energy scarcity curves. A generic numerical example is presented to highlight the large practical differences among the reserve scarcity pricing approaches and specific implementations. To further investigate factors that contribute the most to demand curves differences among ISOs, a sensitivity analysis is performed. This analysis shows that the largest source of differences among the curves is the scarcity prices assumed in the case of severe scarcity, while the number of steps used and whether flexiramp is considered also yields important differences in scarcity prices. As renewable penetration increases, it will become increasingly crucial to employ administrative demand curves so that spot prices more effectively motivate supply and demand adjustments exactly when and where they are needed. This study shows that the different assumptions yield very different scarcity premiums for reserves and energy, and are likely to provide divergent incentives for resources to respond to shortages. It is concluded that to promote market efficiency, a reserve shortage demand curve should have at least three features: inclusion of the marginal value of reserve products at each shortage level, consideration of the magnitude and probability of supply contingencies, and avoidance of abrupt price discontinuities that can cause excessively volatile market outcomes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Chapter 9: Impact of Variable Renewable Energy Sources on Bulk Power System Planning and Operations

Wind and solar photovoltaics (PV) have experienced remarkable growth in recent years, with many consequent benefits within and outside of power systems. At the same time, wind and solar PV have unique characteristics relative to the historically dominant dispatchable technologies like coal, gas, and nuclear power plants that have required and will continue to require changes in power system planning and operations. This chapter discusses planning and operational challenges of integrating wind and solar PV into bulk power systems. We first present the key characteristics of wind and solar PV that differentiate it from conventional technologies, such as variable and uncertain electricity generation, asynchronous interconnection to the power system, and near-zero marginal costs. We then link these characteristics to power system planning and operational challenges at low through high wind and solar penetrations. Finally, we discuss near- and long-term solutions to those challenges, such as diversifying the generation mix and wind and solar fleets, improving system flexibility, diversifying ancillary service products, and integrating generation and transmission planning.

bulk power system↗
DOE OSTI2021

Plentiful electricity turns wholesale prices negative

In 2020, average wholesale electricity prices in the United States fell to $21/MWh, their lowest level since the beginning of the 21st century. Low natural gas prices and the proliferation of low marginal cost resources like wind and solar had already established a trend toward lower wholesale prices, and this trend was exacerbated by declining electricity demand due to the Covid-19 pandemic in 2020. Negative real-time hourly wholesale prices occurred in about 4% of all hours and wholesale market nodes across the United States, but these were not distributed evenly. Regional clusters emerged, for example, in the Permian Basin in western Texas, and in Kansas and western Oklahoma in the Southwest Power Pool (SPP), negative prices accounted for more than 25% of all hours. Negative electricity prices result either from local congestion of the transmission system leading supply to exceed demand locally or due to system-wide oversupply. Looking at the latter condition in SPP, we find that all major generator types contribute to this excess supply, because of limited ramping flexibility or self-scheduled out-of-market unit commitments. Additional monetary production incentives such as renewable energy credits or tax credits also enable negative bids; indeed, negative prices predominantly occur when demand levels are low and wind production levels are high. Frequent negative prices can inform the value of additional renewable energy investments at specific locations, the need for transmission and storage development, and opportunities load growth or adaptation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Carbon management technology pathways for reaching a U.S. Economy-Wide net-Zero emissions goal

The Carbon Management Study Group of the 37 th Energy Modeling Forum (EMF 37) designed seven scenarios to explore the role of three potentially key technology suites – point source carbon dioxide capture and storage (PSCCS), direct air capture of carbon dioxide (DACCS), and hydrogen systems (H 2 ) – in shaping the broader technology pathways to reaching net-zero carbon dioxide (CO 2 ) emissions in United States by 2050. Each scenario was run by up to 13 models participating in the EMF 37 study. Results show that carbon dioxide removal technologies were consistently a major part of successful pathways to net-zero U.S. CO 2 emissions in 2050. Achieving this net-zero CO 2 goal without any form of carbon dioxide capture and storage was found to be impossible for most models; some models also found it impossible to reach net-zero without DACCS. The marginal cost of achieving net-zero CO 2 emissions in 2050 was between two and 10 times higher without PSCCS and/or DACCS available. The carbon price at which DACCS was deployed as a backstop technology depended upon the assumed cost at which DACCS was available at scale. Carbon prices were between $\$$250 and $\$$500 per ton CO 2 when DACCS deployed as a backstop. The average CO 2 capture rate across all models in 2050 in the central net-zero scenario was 1.3 GtCO 2 /year, which implies a substantial upscaling of capacity to move and store CO 2 . Finally, hydrogen sensitivity scenarios showed that H 2 typically constituted a relatively small share of the overall U.S. energy system; however, H 2 deployed in applications that are considered hard to decarbonize, facilitating transition towards net-zero emissions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Price formation in zero-carbon electricity markets - fundamentals, challenges, and research needs

Future power systems dominated by zero-carbon generation resources may require significant revisions to electricity market designs to ensure capacity adequacy and market efficiency. Here, in this paper, we first conceptually outline key fundamentals underlying electricity market design and price formation in U.S. electricity markets. We then discuss a set of potential market design challenges related to price formation in a grid dominated by zero-carbon resources with marginal cost profiles that differ compared to traditional thermal resources. Next, we review electricity market design solutions that have been proposed in the literature to ensure market efficiency in zero-carbon systems, and the associated implications for price formation. We conclude by summarizing key observations and establishing a set of research questions that should be addressed to improve our understanding of market design, price formation, and market efficiency in zero-carbon power systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

A review of Geological Thermal Energy Storage for seasonal, grid-scale dispatching

Energy storage is essential for the decarbonization of the U.S. energy grid, especially with the increasing deployment of variable renewable energy sources like solar and wind. Geological thermal energy storage (GeoTES) has emerged as a promising long duration, grid scale solution, providing stability and security through flexible operations and valuable grid services. GeoTES utilizes subsurface reservoirs to store thermal energy for power generation and direct-use heating and cooling. This approach significantly enhances the use of low-temperature reservoirs, which would otherwise be unsuitable for geothermal power plants. It also aligns well with depleted oil and gas reservoirs, concentrating solar power, non-flexible renewables (photovoltaic and wind), and geothermal-related power cycles. Given the favorable marginal costs of GeoTES as storage duration increases, it becomes particularly competitive for seasonal, grid-scale dispatch, where few technologies are viable. This paper provides a comprehensive review of GeoTES systems and the research underpinning itsr development. This analysis begins by defining and categorizing the unique characteristics of thermal energy storage techniques, setting GeoTES apart from other technologies. The various components, configurations, subsurface characteristics, and modeling efforts that guide GeoTES development are then explored. Finally, challenges in GeoTES research, development, and deployment are discussed, along with mitigation strategies and lessons from related technologies. Beyond their economic benefits, GeoTES systems support grid resilience and decarbonize industrial processes. Their scalability, broad distribution, seasonal storage potential, and flexible dispatch capacity make GeoTES a valuable tool for expanding renewable energy deployment and addressing climate change.

15 - GEOTHERMAL ENERGY↗
DOE OSTI2020

Too Much of a Good Thing? Global Trends in the Curtailment of Solar PV

Solar photovoltaic (PV) systems generate electricity with no marginal costs or emissions. As a result, PV output is almost always prioritized over other fuel sources and delivered to the electric grid. However, PV curtailment is increasing as PV composes greater shares of grid capacity. In this paper, we present a novel synthesis of curtailment in four key countries: Chile, China, Germany, and the United States. We find that about 6.5 million MWh of PV output was curtailed in these countries in 2018. We find that: Policy and grid planning practices influence where, when, and how much PV is curtailed; Some PV curtailment is attributable to limited transmission capacity connecting remote solar resources to load centers; PV curtailment peaks in the spring and fall, when PV output is relatively high but electricity demand is relatively low. We discuss available measures to reduce PV curtailment as well as increasing PV curtailment in the contexts of evolving grids and energy technologies.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2020

Convergence acceleration of Monte Carlo many-body perturbation methods by using many control variates

Herein, the use of many control variates is proposed as a method to accelerate the second- and third-order Monte Carlo (MC) many-body perturbation (MC-MP2 and MC-MP3) calculations. A control variate is an exactly integrable function that is strongly correlated or anti-correlated with the target function to be integrated by the MC method. Evaluating both integrals as well as their covariances in the same MC run, one can effect a mutual cancellation of the statistical uncertainties and biases in the MC integrations, thereby accelerating its convergence considerably. Six and thirty-six control variates, whose integrals are known a priori, are generated for MC-MP2 and MC-MP3, respectively, by systematically replacing one or more two-electron-integral vertexes of certain configurations by zero-valued overlap-integral vertexes in their Goldstone diagrams. The variances and co- variances of these control variates are computed at a marginal cost, enhancing the overall efficiency of the MC-MP2 and MC-MP3 calculations by a factor of up to 14 and 20, respectively.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Real-Time Regional PV Spinning Reserve Estimator with AGC Look-Ahead Windows

Curtailed PV generation is a zero-marginal cost spinning reserve that can be used for a number of active power control services. However, unlike the traditional spinning reserve providers, i.e., fossil-fueled generators, who have well-defined operating characteristics, e.g., available headroom or potential high limit (PHL), PV plants have by nature variable and uncertain operating characteristics. To ensure the effective coordination between PV plants and the system operator during an active power control event, accurate forecasts of the PV PHL are essential. A novel reference-control grouping based scaling method has been proposed by NREL to estimate the PV PHL in real-time. This work further enhances the methodology by: 1) improving the model accuracy through machine learning; 2) considering look-ahead windows introduced by the computation and communication latencies; 3) applying the method to regional spinning reserve estimation. A significant performance improvement, over 99% of estimation error reduction, has been observed based on real-world data collected by CAISO and PV plant operators.

potential high limit↗
DOE OSTI2024

A CHIL Validation of Machine Learning-Assisted Methods for Real-Time Controls of Solar PV for Grid Services

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been proposed; however, these technologies lack comprehensive validation under real-world application scenarios. This paper addresses this gap by designing and developing a controller-hardware-in-the-loop framework to evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. Simulation results indicate the superior performance of an ML-based approach compared to the conventional reference-control grouping-based approach, showcasing its potential to support grid stability and operational efficiency.

closed-loop validation↗
DOE OSTI2024

Market Implications of Alternative Operating Reserve Modeling in Wholesale Electricity Markets

Pricing and settlement mechanisms are crucial for efficient resource allocation, investment incentives, market competition, and regulatory oversight. In the United States, Regional Transmission Operators (RTOs) adopts a uniform pricing scheme that hinges on the marginal costs of supplying additional electricity. This study investigates the pricing and settlement impacts of alternative reserve constraint modeling, highlighting how even slight variations in the modeling of constraints can drastically alter market clearing prices, reserve quantities, and revenue outcomes. Focusing on the diverse market designs and assumptions in ancillary services by U.S. RTOs, particularly in relation to capacity sharing and reserve substitutions, the research examines four distinct models that combine these elements based on a large-scale synthetic power system test data. Our study provides a critical insight into the economic implications and the underlying factors of these alternative reserve constraints through market simulations and data analysis.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

An improved representation of the relationship between photosynthesis and stomatal conductance leads to more stable estimation of conductance parameters and improves the goodness-of-fit across diverse data sets

Stomata play a central role in surface-atmosphere exchange by controlling the flux of water and CO 2 between the leaf and the atmosphere. Representation of stomatal conductance (g sw ) is therefore an essential component of models that seek to simulate water and CO 2 exchange in plants and ecosystems. For given environmental conditions at the leaf surface (CO 2 concentration and vapor pressure deficit or relative humidity), models typically assume a linear relationship between g sw and photosynthetic CO 2 assimilation (A). However, measurement of leaf-level g sw response curves to changes in A are rare, particularly in the tropics, resulting in only limited data to evaluate this key assumption. Here, we measured the response of g sw and A to irradiance in six tropical species at different leaf phenological stages. We showed that the relationship between g sw and A was not linear, challenging the key assumption upon which optimality theory is based-that the marginal cost of water gain is constant. Our data showed that increasing A resulted in a small increase in g sw at low irradiance, but a much larger increase at high irradiance. We reformulated the popular Unified Stomatal Optimization (USO) model to account for this phenomenon and to enable consistent estimation of the key conductance parameters g 0 and g 1 . Our modification of the USO model improved the goodness-of-fit and reduced bias, enabling robust estimation of conductance parameters at any irradiance. In addition, our modification revealed previously undetectable relationships between the stomatal slope parameter g 1 and other leaf traits. We also observed nonlinear behavior between A and g sw in independent datasets that included data collected from attached and detached leaves, and from plants grown at elevated CO 2 concentration. We propose that this empirical modification of the USO model can improve the measurement of g sw parameters and the estimation of plant and ecosystem-scale water and CO 2 fluxes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Modeling and Optimizing Pumped Storage in a Multi-stage Large Scale Electricity Market under Portfolio Evolution

To leverage the fast-ramping capability of resources to provide great value to the grid, electricity system operators such as the Midcontinent Independent System Operator (MISO) continue to evolve their approaches for integrating energy storage resources, including pumpedstorage hydro (PSH), into the electricity markets. However, new challenges arise in modeling and optimizing these energy-limited resources across multiple market clearing processes and planning studies with uncertainties and imperfect information. For instance, current market practices of PSH owners specifying pumping/generating hours can result in sub-optimal generation dispatch. Letting grid operators optimize PSH with the consideration of multiple operating modes and energy limitation constraints can potentially bring economic benefits to both the system and the PSH owners. However, in multi-stage clearing process of electricity markets, utilizing the PSH flexibility to deal with realized uncertainties can cause deviation in the multi-stage scheduling processes. The resulting financial risks from the schedule deviation may not be acceptable to PSH owners. In addition, to effectively utilize this energy limited resource, the state of charge (SOC) constraints of PSH needs to be continuously optimized and the marginal cost of deviation need to reflect the expected cost to purchase or sell energy at future times to compensate for deviations. This project aims to develop a prototype enhanced PSH model and improved price signals in the multi-stage market clearing process with proper consideration of the unique characteristics of PSH, in order to better align underlying PSH capabilities with evolving grid needs, particularly including the needs for more frequent and larger cycling to manage variability and uncertainty from renewables.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Capacity Markets for Transactive Energy Systems

Capacity markets provide important incentives for resource adequacy in electricity markets and may become more important for providing sufficient revenue and generation capacity with changes to energy market prices driven by increasing levels of zero marginal cost resources. However, current capacity market designs also have important shortfalls that may limit the benefits they can provide to the future grid. Current capacity markets are primarily designed for participation from conventional thermal generators, but markets are evolving with increasing levels of variable renewable energy resources. However, further reforms may be necessary to enable more participation from DERs and demand-side resources. To understand the benefits and shortfalls of current capacity market design, we review the historical reasons electricity markets have needed capacity markets or capacity payments for resource adequacy, and how current capacity market designs may create challenges for incorporating increasing levels of DERs and demand-side resources. We then consider how transactive systems, which allow the coordination of bids and offers for DERs and demand-side resources through a market interaction approach, administered by a Distribution System Operator (DSO), can address traditional resource adequacy problems due to inelastic consumer demand. We also consider the need for a DSO-level capacity market in helping to meet resource adequacy, reliability, and other electricity market objectives. We find that because the missing money in electricity markets is largely driven by incentives to meet resource adequacy goals, and the bulk grid would always supply power to the DSO, that resource adequacy is unlikely to be a determining factor in the need for a DSO-level capacity market. Many current reliability problems could also be addressed by the incorporation of more flexible demand enabled with transactive energy systems. However, other DSO objectives, including resilience, reactive power, voltage control, environmental policies, and energy equity could lead to specific challenges that could be aided by a DSO-level capacity market. We consider the possibility of a DSO-level capacity market in addressing these challenges as well as its potential role in coordinating with the Independent System Operator (ISO) who operates the wholesale market. We conclude with suggestions for future research, including the need to develop analytical models of DSO-level capacity market designs to address these potential objectives and examine their implications for DSOs and consumers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Regional Real-Time PV Spinning Reserve Estimator

Curtailed photovoltaic (PV) generation is a zero-marginal-cost spinning reserve that can be used for a number of active power control services. Unlike traditional spinning reserve providers, however, i.e., fossil-fueled generators, which have well-defined operating characteristics, e.g., available headroom or potential high limit (PHL), PV plants have by nature variable and uncertain operating characteristics. To ensure the effective coordination between PV plants and the system operator during an active power control event, accurate knowledge of the PV PHL is essential. It ensures that enough headroom is reserved by the PV plants to deliver the award services in real time and informs feasible dispatch decisions made by the market operator. To tackle this challenge, a novel reference-control grouping-based PV plant reserve estimation method has been proposed by the National Renewable Energy Laboratory under past projects funded by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Solar Energy Technologies Office. The estimation method separates inverters within a plant into two groups: a control group and a reference group. While the reference group is reserved to operate at its PHL, the control group can be curtailed to provide the grid services. Real-time outputs from the reference inverters are used to estimate the PHL for the whole plant based on the ratio between capacities of the reference group and of the plant. This work further enhances the methodology by (1) improving the model accuracy through machine learning; (2) automating the reference inverter selection through correlation analysis; (3) considering estimation look-ahead windows; and (4) applying to regional spinning reserve estimation. Significant performance improvement has been observed based on real-world data collected by CAISO, Southern Company, and Terabase Energy. Compared with the original scaling method, the newly proposed machine learning-based approach reduces the estimation errors by 30% and 13% at the plant level and region level, respectively. Results obtained from this project are intended to be used by grid operators, market operators, balancing authorities, and PV plant owners and operators to facilitate PV participation in ancillary service markets. Regulators, policymakers, and system planners can also consider the results of this work in their decision-making processes. In addition to the performance improvement on the existing reference-control based grouping method, we also investigated how the variability of PV generation from a single PV inverter can be used to represent the variability of PV generation at the plant level.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Integrate Latimer Controls' Solution into RTAC (CRADA Final Report, CRD-23-24672)

Latimer Controls, Inc. was awarded two vouchers under the Department of Energy's American-Made Solar Prize Round 6 to conduct collaborative research at a national laboratory. The National Renewable Energy Laboratory (NREL) was selected as a partner to assist Latimer Controls in the performance evaluation of its photovoltaic (PV) control software. This collaboration focuses on developing a hardware-in-the-loop (HIL) testbed at NREL, which will be used to test and validate the Latimer PV control technology in a realistic yet de-risked environment. Both Latimer and NREL teams will work together to analyze the collected test data, derive insights, and disseminate the scientific findings. Recent studies underscore the potential of solar energy as a zero-marginal-cost and zero-emission flexibility resource within the bulk power system, particularly when integrated with advanced control systems. To enhance the performance of such systems, Latimer Controls has developed leading-edge technologies, including machine learning (ML) algorithms and hierarchical inverter set-point allocation methods. These innovations are designed to estimate the operational headroom of large PV plants for grid integration and control. However, comprehensive validation under real-world conditions remains necessary. To address this gap, the concurrent CRADA project proposes the real-world application and validation of the Latimer Control solution within a HIL environment. Initially, the Latimer algorithm was developed and tested within MATLAB Simulink, a platform suitable for research-level simulations and iterative development. However, transitioning this technology to a real solar site as an industry-ready solution necessitates implementation in a format compatible with widely used solar power plant controllers. In this additional CRADA work, the MATLAB Simulink-based logic will be translated into Structured Text, a programming language compliant with IEC 61131 standards, which is commonly used for custom logic implementations in industry-leading programmable logic controllers (PLCs), such as the Schweitzer SEL real-time automation controller (RTAC). This transition will facilitate the deployment of the Latimer Control solution in real-world solar power plants, thereby advancing the technology towards commercialization.

14 SOLAR ENERGY↗