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Annual Technology Baseline: The 2020 Electricity Update

Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), the National Renewable Energy Laboratory annually provides an organized and centralized set of such cost and performance data. The ATB uses the best information from the Department of Energy national laboratories' renewable energy analysts. The ATB has been reviewed by experts and it includes the following electricity generation technologies: land-based wind, offshore wind, utility-scale solar photovoltaics (PV), commercial-scale solar PV, residential-scale solar PV, concentrating solar power, geothermal power, hydropower, utility-scale battery storage. EIA data for coal, natural gas, nuclear, and conventional biopower are included for reference. This webinar presentation introduces the 2020 update to the ATB Electricity data and documentation.

capacity factor↗

Annual Technology Baseline: The 2022 Electricity Update

Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), the National Renewable Energy Laboratory annually provides an organized and centralized set of such cost and performance data. The ATB uses the best information from the Department of Energy national laboratories' renewable energy analysts. The ATB has been reviewed by experts and it includes the following electricity generation and storage technologies: land-based wind, offshore wind, distributed wind, utility-scale solar photovoltaics (PV), commercial-scale solar PV, residential-scale solar PV, concentrating solar power, geothermal power, hydropower, utility-scale battery storage, commercial battery storage, residential battery storage, pumped storage hydropower, coal, and natural gas. EIA data for nuclear and conventional biopower are included for reference. This webinar presentation introduces the 2022 update to the ATB Electricity data and documentation.

capacity factor↗

Annual Technology Baseline: The 2024 Electricity Update

Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), the National Renewable Energy Laboratory annually provides an organized and centralized set of such cost and performance data. The ATB uses the best information from the Department of Energy national laboratories' energy analysts. The ATB has been reviewed by experts and it includes the following electricity generation and storage technologies: land-based wind, offshore wind, distributed wind, utility-scale solar photovoltaics (PV), commercial-scale solar PV, residential-scale solar PV, concentrating solar power, geothermal power, hydropower, utility-scale battery storage, commercial battery storage, residential battery storage, pumped storage hydropower, nuclear, coal, and natural gas. EIA data for conventional biopower are included for reference. This webinar presentation introduces the 2024 update to the ATB Electricity data and documentation.

battery storage↗

Annual Technology Baseline: The 2023 Electricity Update

Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), the National Renewable Energy Laboratory annually provides an organized and centralized set of such cost and performance data. The ATB uses the best information from the Department of Energy national laboratories' renewable energy analysts. The ATB has been reviewed by experts and it includes the following electricity generation and storage technologies: land-based wind, offshore wind, distributed wind, utility-scale solar photovoltaics (PV), commercial-scale solar PV, residential-scale solar PV, concentrating solar power, geothermal power, hydropower, utility-scale battery storage, commercial battery storage, residential battery storage, pumped storage hydropower, coal, and natural gas. EIA data for nuclear and conventional biopower are included for reference. This webinar presentation introduces the 2023 update to the ATB Electricity data and documentation.

capacity factor↗

Data-Driven Prediction and Optimization of Energy Use for Transit Fleets of Electric and ICE Vehicles

Due to the high upfront cost of electric vehicles, many public transit agencies can afford only mixed fleets of internal combustion and electric vehicles. Optimizing the operation of such mixed fleets is challenging because it requires accurate trip-level predictions of electricity and fuel use as well as efficient algorithms for assigning vehicles to transit routes. We present a novel framework for the data-driven prediction of trip-level energy use for mixed-vehicle transit fleets and for the optimization of vehicle assignments, which we evaluate using data collected from the bus fleet of CARTA, the public transit agency of Chattanooga, TN. We first introduce a data collection, storage, and processing framework for system-level and high-frequency vehicle-level transit data, including domain-specific data cleansing methods. We train and evaluate machine learning models for energy prediction, demonstrating that deep neural networks attain the highest accuracy. Based on these predictions, we formulate the problem of minimizing energy use through assigning vehicles to fixed-route transit trips. We propose an optimal integer program as well as efficient heuristic and meta-heuristic algorithms, demonstrating the scalability and performance of these algorithms numerically using the transit network of CARTA.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Optimal strategies for a cost-effective and reliable 100% renewable electric grid

This paper explores cost-optimal pathways to 100% renewable power systems for the U.S. building stock. We show that long-duration misalignments of supply and demand, spanning from multi-day to seasonal timescales, present a dominant challenge that must be addressed to meet real-time 100% renewable targets. While long-duration misalignments can be addressed through energy storage, we show that alternative and readily available solutions that are more cost-effective should be considered first. Through a techno-economic analysis, we identify cost-optimal, region-dependent, supply-side, and demand-side strategies that reduce, and in some U.S. regions eliminate, the otherwise substantial capacities and associated costs of long-duration energy storage. Investigated supply-side strategies include optimal mixes of renewable portfolios and oversized generation capacities. Considered demand-side strategies include building load flexibility and building energy efficiency investments. Our results reveal that building energy efficiency measures can reduce long-duration storage requirements at minimum total investment costs. In addition, oversizing and diversifying renewable generation can play a critical role in reducing storage requirements, remaining cost effective even when accounting for curtailed generation. We identify regionally dependent storage cost targets and show that for emerging long-duration energy storage innovations to achieve broad adoption, their costs will need to compete with the decreasing cost of renewables. The findings of this research are particularly important given that most long-duration storage technologies are currently either uneconomical, geologically constrained, or still underdeveloped.

100% renewable↗

Federal Workplace Charging Program Guide

The 2015 Fixing America's Surface Transportation (FAST) Act authorizes the installation, operation, and maintenance of electric vehicle supply equipment (EVSE) for the purpose of recharging employees' privately owned vehicles (POVs) under the custody or control of the General Services Administration (GSA) or a Federal agency. It requires the collection of fees to recover the costs of installing, operating, and maintaining this equipment and imposes reporting requirements. This program guide reviews those requirements, excerpts the relevant language in Appendix A, and describes when and how fees may be required to cover costs of electricity, network costs, EVSE units, and installations in various scenarios. This program guide is designed to support Federal agencies developing and refining workplace charging programs for employee POVs. While it provides guidance and best practices, it does not replace agencywide policies or agency-specific legal counsel. It contains a roadmap for agency workplace charging programs and defines roles and responsibilities. This guide explains how to determine the number of POVs likely to charge at a given site and contains a sample employee survey in Appendix B. It reviews EVSE planning, including unit selection and acquisition, charger location(s), accounting for available power capacity, using existing infrastructure, and funding an incentive program. It also discusses the costs associated with EVSE acquisition, installation, and network management. These costs inform the subsequently provided information, which describes how to amortize costs to determine appropriate fees for each charging session. The final two sections of this guide address aspects of ongoing program management that the facility coordinator should consider and the reporting requirements associated with the FAST Act. The insights in this guide are applicable to all agency-owned and GSA-leased buildings or facilities offering the use of EVSE or a 120-volt receptacle for the purpose of recharging an employee's POV. However, the FAST Act requirements typically do not apply to any building or facility operated and maintained by a third-party vendor offering the use of EVSE as part of a commercial building lease unless the agency is managing the station and/or energy on behalf of the building and collecting POV fees.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Climate-Induced Tradeoffs in Planning and Operating Costs of a Regional Electricity System

Electricity grid planners design the system in order to supply electricity to end users reliably and affordably. Climate change threatens both objectives through potentially compounding supply- and demand-side climate-induced impacts. Uncertainty surrounds each of these future potential impacts. Given long planning horizons, system planners must weigh investment costs against operational costs under this uncertainty. Here, we developed a comprehensive and coherent integrated modeling framework combining physically-based models with cost-minimizing optimization models in the power system. We applied this modeling framework to analyze potential tradeoffs in planning and operating costs in the power grid due to climate change in the Southeast U.S. in 2050. We find that planning decisions that do not account for climate-induced impacts would result in a substantial increase in social costs associated with loss of load. These social costs are a result of under-investment in new capacity and capacity deratings of thermal generators when we included climate change impacts in the operation stage. Finally, these results highlight the importance of including climate change effects in the planning process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Design and Techno-Economic Analysis of a 150-MW Hybrid CSP-PV Plant

The interest in concentrated solar power (CSP) has increased significantly over the years since it is dispatchable and requires thermal storage instead of electric storage. When compared to photovoltaics (PV), CSP has a higher Levelized Cost of Electricity (LCOE). In this paper, we present the design of a hybrid power plant using CSP and PV technologies. The hybrid system offers a lower LCOE than CSP but will still have dispatchability. The 150-MW hybrid system consists of 100-MW CSP and 50-MW PV capacity. Furthermore, the CSP system (central receiver system) has a molten salt-based thermal storage of 12 hours. The geographical focus of this study is Pakistan, which is a developing country struggling with energy crises, but which has high solar potential. The hybrid system is modeled using the System Advisor Model (SAM). The results show that by hybridizing CSP with PV, the LCOE can be reduced by 18.5%.

concentrated solar power↗

Development of a Geothermal Module in reV: Quantifying the Geothermal Potential while Accounting for the Geospatial Intersection of the Grid Infrastructure and Land Use Characteristics

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. This paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results should be considered with care due to the highly uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for five scenarios: four hydrothermal (3.5km depth) and one EGS (4.5km depth). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

exclusions↗

Development of a Geothermal Module in reV: Quantifying the Geothermal Potential While Accounting for the Geospatial Intersection of the Grid Infrastructure and Land Use Characteristics: Preprint

The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. This paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results should be considered with care due to the highly uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for five scenarios: four hydrothermal (3.5km depth) and one EGS (4.5km depth). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.

exclusions↗

Rewarding Grid-Friendly Behavior: Estimating the Potential Bill Reduction and Load Shifting Benefits of Dynamic Prices

Shifting electric load from times of peak demand can be a key strategy to slow price growth as reducing peak demand avoids the cost of upgrading generation, transmission and distribution infrastructure. Utilities are releasing time-varying prices, such as time of use rates or dynamic prices, to incentivize grid-friendly load shifting. New dynamic price programs provide insight into the true cost of operating electricity grids and the potential economic benefits of load shifting. Program developers and device manufacturers need to understand the economic opportunities in terms of 1) the variation in prices across hours, days, and seasons; 2) the change in utility bills for customers who don’t shift load; and 3) the potential load shifted and economic value of different technologies if manufacturers or aggregators deploy price-responsive controls. This paper estimates possible impacts of dynamic price adoption and load shifting controls if customers paid the dynamic rate from one pilot program. Statistical analysis of historical prices identified annual and seasonal metrics as well as representative price curves for each circuit in the pilot. Simulations for residential technologies with price-responsive controls including unitary heat pump water heaters, central multifamily heat pump water heaters, heating & cooling + storage systems, and pool pumps estimated the potential impacts of highly dynamic prices both with and without load shifting controls. Results showed the potential to reduce electricity costs on representative days by 42-94% and reduce consumption during times of high electricity prices by 63-100% compared to baseline operation for those flex-friendly devices.

Grant, Peter↗

Doping CdSexTe1-x/CdTe Graded Absorber Films with Arsenic for Thin-Film Photovoltaics

CdTe thin-film photovoltaics have demonstrated some of the lowest costs of electricity generation owing to its low material cost and ease of manufacturing. However, the full potential of polycrystalline CdTe photovoltaics can only be realized if the open-circuit voltage can be increased beyond 1 V Open-circuit voltage ~850-900 mV has been consistently observed for state-of-the-art polycrystalline CdTe solar cells. Open-circuit voltage of over 1V has been demonstrated for single crystal CdTe devices by doping with Group V elements. Therefore, this study is aimed at understanding behavior of polycrystalline CdTe devices with arsenic doping, its activation and process and performance optimization in order to overcome current voltage limitations in CdTe solar cells.

14 SOLAR ENERGY↗

Techno-economic Analysis of the Cryogenic Flux Capacitor Compared to Other forms of Hydrogen Production and Storage

The Cryogenic Flux Capacitor (CFC) is a cold, dense energy storage core that is being studied in the cryo-compressed, about 300 bar and 80K, region of gaseous hydrogen (GH2) storage and liquid hydrogen (LH2) region near the normal boiling point. The hydrogens storage is improved by physically bonding the molecules within the nanoscale pores of the aerogel composite blanket material. The process of bonding or debonding is governed by principles of physical adsorption (physisorption) and thermodynamics. The large surface area afforded by the nanoporous aerogel (~1,000 m2/g) allows its storage performance to easily exceed capacities of high-pressure GH2 storage for an equivalent volume. With the integrated aerogel, subscale tests have shown that storage is increased by about 49% over a simple tank filled with GH2 at the same operating temperature and pressure. For LH2 conditions, the CFC is shown to operate at equivalent densities. For the techno-economic analysis (TEA), the source of hydrogen is compared between onsite steam methane reforming (SMR) and onsite solar photovoltaic (PV) panels providing power to electrolyzers to produce GH2. The TEA compares pure hydrogen burning in a combined cycle gas turbine (CCGT) to hydrogen fuel cells with an overall net power output of 650 MW. The SMR system uses natural gas as an input and includes a carbon capture and storage (CCS) system. The levelized cost of electricity is developed based on the capital cost and operating cost of the systems. Sensitivities are discussed around the cost of natural gas, ranging from 1.93 USD per MMBTU to 6.75 USD per MMBTU, and carbon dioxide disposal, ranging from 7 USD per tonne to 10 USD per tonne. For comparison to the conventional CCGT baseline, a baseload scenario is adopted with 85% capacity factor. The results of the study show that onsite hydrogen generation from SMR is about 1 to 3 USD per kg over the life of the plant and the PV hydrogen production produces at 4 to 5 USD per kg. The cost of storage for CFC is compared to other systems, including high-pressure GH2 and atmospheric LH2. The system is shown to provide the lowest costs for all these options at the grid scale, due to its higher capacity than high-pressure GH2 and ability to operate at 80K, receiving refrigeration from liquid nitrogen systems reducing capital and operating costs when compared LH2 storage systems. SMR is competitive with CCGT at the gas prices, both of which have lower LCOE than the PV system. When accounting for variability in gas prices, the PV and electrolyzer system is less sensitive to these changes and provides the lowest LCOE across the whole range.

08 HYDROGEN↗

FINAL TECHNICAL AND ECONOMIC FEASIBILITY STUDY ON THE APPLICATION OF A HEAT INTEGRATED POST-COMBUSTION CO2 CAPTURE SYSTEM WITH HITACHI ADVANCED SOLVENT INTO EXISTING COAL-FIRED POWER PLANT

This report contains the results of a techno-economic assessment (TEA) conducted of a heat integrated post-combustion CO2 capture process with Hitachi advanced solvent for retrofit into an existing coal-fired power plant (but treated as greenfield plant on cost analysis). The process has been developed by the University of Kentucky Center for Applied Energy (UK CAER). EPRI was chiefly responsible for this analysis, with significant input from WorleyParsons, Hitachi Power Systems America (Hitachi) and UK CAER. The project also involves the design, fabrication, installation, testing, and analyses of a slipstream facility located at L&GE-KU’s E.W. Brown Generating Station to demonstrate the UK CAER carbon capture system that could utilize heat integration with the main power plant. The design, start-up, and baseline of the pilot system was performed with a generic 30 wt% MEA solvent to obtain data for direct comparison with the DOE/NETL Reference Case followed by testing Hitachi’s proprietary solvent H3-1. In this techno-economic analysis, two cases utilizing the UK CAER process are compared, using different approach temperatures and solvent, against the DOE/NETL Reference Case (Case 10). The results are shown comparing the energy demand for post-combustion CO2 capture and the net higher heating value (HHV) efficiency of the power plant integrated with the post-combustion capture (PCC) plant. A levelized cost of electricity (LCOE) assessment was performed showing the costs of the options presented in the study. The key factors contributing to the reduction of LCOE were identified as CO2 partial pressure increase at the flue gas inlet, thermal integration of the process, and performance of the Hitachi H3-1 solvent. Recent UK CAER process pilot-scale testing data and process simualtion data showed that the packing heights of absorber and stripper columns were significantly oversized in the prelimanary TEA (Task 2 of this project) and thus updated in this final TEA for the H3-1 case only. In addition, the solvent make-up cost for H3-1 was updated based on lattest test results. Finally, a heat integration with the main power plant was applied in this final TEA to increase overall energy effciency for both the MEA and H3-1 cases. Additonal reductions in capital and operational costs are expected but not taken into account here. Shorter columns result in reduced pressure drops, smaller blower head and pump hydraulic head requirements. An increase in overall energy efficiency resuls in a decreased size of the power plant, the CCS and a reduced parasitic steam requirement to the CCS. The net efficiency of the UK CAER integrated PC power plant with CO2 capture changes from 26.2% for the Reference Case 10 plant in 2010 revised DOE/NETL baseline report to 27.6% for the MEA options considered, and 29.1% for the options utilizing the Hitachi advanced solvent. The UK CAER Process + Hitachi case also produces an extra 30.9 MW of generation compared to the UK CAER Process + MEA case and total 60.9 MW more than DOE Case 10. LCOE ($/MWh) values are $172.08/MWh for the MEA option and $157.65/MWh for the Hitachi H3-1 solvent cases considered in comparison to $189.59/MWh in January 2012 dollar for the Reference Case 10. The UK CAER CCS process with MEA case lowers energy consumption for CO2 capture to 1340 Btu/lb-CO2 captured as compared to 1540 Btu/lb-CO2 in the Reference Case 10. The UK CAER CCS process with H3-1 case further lowers energy consumption for CO2 capture to 973 Btu/lb-CO2 captured, for an advantage of 36.8% less energy consumption than Case 10. The study also shows 38.1% less heat rejection associated with the carbon capture system from 3398 MBtu/hr (Case 10) to 2104 MBtu/hr for the UK CAER + MEA system. Heat rejection is reduced to 2464 MBtu/hr in the UK CAER + H3-1 case, for a 27.5 % decrease compared to Case 10. Modeling outputs show that in the UK CAER process, the cooling water that is 2-5°C cooler than conventional cooling tower water can be achieved for ambient conditions common to the midwest and other regions. The results from the techno-economic assessment show that the proposed technology can be investigated further as a viable alternative to conventional CO2 capture technology. The evaluation also shows the effect of the critical parameters on the LCOE, with the main variables being the approach temperature and CO2 partial pressure increase at the flue gas inlet. A summary of the key advantages of the UK CAER Process + H3-1 case for LCOE and other economic factors compared to the DOE Case 10 is as follows: • A lower variable operating cost by $1.56/MWh ($1.08MWh less than the UK CAER Process + MEA Case), a 11.7% reduction compared to the DOE Case 10 • A lower COE by $25.32MWh ($13.94/MWh lower than the UK CAER Process + MEA Case), a 16.9% reduction compared to the DOE Case 10 • A lower LCOE by $31.94/MWh ($17.51/MWh lower than the UK CAER Process + MEA Case), a 16.9% reduction compared to the DOE Case 10 • A lower cost of CO2 captured by $18.65/tonne CO2 ($9.44/tonne CO2 lower than the UK CAER Process + MEA Case), a 30.4% reduction compared to the DOE Case 10 • A lower cost of CO2 avoided by $34.95/tonne CO2 ($18.53 tonne CO2 lower than the UK CAER Process + MEA Case), a 38.7% reduction compared to the DOE Case 10

Bhown, Abhoyjit S.↗

Integration and Optimization of a Waste Heat Driven Organic Rankine Cycle for Power Generation in Wastewater Treatment Plants

The study focuses on achieving energy self-sufficiency in Wastewater Treatment Plants by proposing a comprehensive model for integrating, sizing, and optimizing an Organic Rankine Cycle system. The Organic Rankine Cycle system is designed to utilize waste heat from the gensets at As Samra Wastewater Treatment Plant in Jordan, where it will contribute to the overall electrical energy supply of the plant. Real data from As Samra Wastewater Treatment Plant is used to model and calculate the available waste heat using TRNSYS® software. The Organic Rankine Cycle model is then developed using ASPEN PLUS® software to explore the impact of operational parameters and determine their optimal values for maximizing the plant's energy profile. An economic analysis is conducted to assess the feasibility of the proposed model, considering system components, installation, operation, and maintenance costs. To optimize the Organic Rankine Cycle system, the study employs the Multi-Output Support Vector Regression technique to capture nonlinear relationships between independent variables (fluid type, turbine inlet pressure, turbine inlet temperature, turbine outlet pressure, and mass flow rate) and dependent variables (pump power input, waste heat input, and turbine specific work). The Osprey optimization algorithm is used to address the multi-objective optimization problem, with the proposed Pareto-based Osprey Optimization Algorithm and the Multi-Objective Particle Swarm Optimization technique being employed to evaluate critical performance and economic parameters such as system thermal efficiency, net power output, and the levelized cost of electricity. The results of the optimization strategies indicate that the M-SVR model's prediction accuracy is significantly improved after parameter optimization, with the model returning high R 2 and low Mean Square Error values of 0.991 and 0.00216, respectively. The Pareto-Based Osprey Optimization Algorithm optimizer identifies the best working fluid as Isobutane/Isopentane in a ratio of 66:34, with optimal turbine inlet pressure and temperature of 15 bars and 218 °C, respectively. In conclusion, the Organic Rankine Cycle model at these optimal conditions achieves a cycle efficiency of 19.93% and an Levelized Cost of Electricity value of 0.0353 USD/kWh.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Timed to save: the added value of accounting for hourly incidence of electricity savings from residential space-conditioning measures

Abstract Previous research has recognized that the value of measures that reduce electricity usage depends upon the timing of the savings generated, but the lack of hourly savings shapes has limited the demonstration of this concept. We develop empirical hourly savings shapes for residential space-conditioning measures from nearly 18,000 efficiency projects in California and show how they combine with the diurnal and seasonal variation in electricity system costs. We find that these measures (cooling replacements; windows, doors, and skylights; and other envelope measures) tend to save electricity when system costs are highest and that the hourly savings account for 1.4–1.5 times as much value as non-time-sensitive estimates of efficiency would predict. We present these impact multipliers for each measure to quantify the additional value revealed by the time-sensitive approach. We show that this additional value is similar in an evolving electricity grid with storage, rather than natural gas generation, as the marginal resource.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Wind plant wake losses: Disconnect between turbine actuation and control of plant wakes with engineering wake models

Wake losses from neighboring plants may become a major factor in wind plant design and control as additional plants are constructed in areas with high wind resource availability. Because plant wakes span a large range of physical scales, from turbine rotor diameter to tens of kilometers, it is unclear whether conventional wake models or turbine control strategies are effective at the plant scale. Wake steering and axial induction control are evaluated in the current work as means of reducing the impact of neighboring wind plants on power and levelized cost of electricity. FLOw Redirection and Induction in Steady State (FLORIS) simulations were performed with the Gauss–Curl Hybrid and TurbOPark wake models as well as two operation and maintenance models to investigate control setpoint sensitivity to wake representation and economic factors. Both wake models estimate losses across a range of atmospheric conditions, although the wake loss magnitude is dependent on the wake model. Annual energy production and levelized cost of electricity are driven by wind direction frequency, with frequently aligned plants experiencing the greatest losses. However, both wake steering and axial induction are unable to mitigate the impact of upstream plants. Wake steering is constrained by plant geometry, since wake displacement is much less than the plant wake width, while axial induction requires curtailing the majority of turbines in upstream plants. Individual turbine strategies are limited by their effective scale and model representation. New wake models that include plant-scale physics are needed to facilitate the design of effective plant wake control strategies.

Scott, Ryan (ORCID:0000000328107574)↗