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At least 289 records · Page 16

Mitigating Stranded Asset Risks to Utility Customers: an Exploration of Securitization and Retiring Coal Generation

Coal generation currently accounts for approximately 19.5 percent of electricity generated in the United States, down from 51.7 percent of the generation mix in 2000. In 2023, the EIA expects 8.9 gigawatts (GW) of planned retirements of coal-fired capacity. Many of the coal-fired power plant retirements that have already occurred or are planned for the next decade will be plants that have not yet reached the end of their useful life, and are therefore not fully depreciated. Ensuring that utility customers do not face an undue burden in paying for these stranded assets will become an increasingly important issue over the next few years for PUCs overseeing the safety, reliability, and affordability of investor-owned utility service. This report reviews the role that securitization can play in reducing the costs associated with stranded assets due to early coal plant retirements.

01 COAL, LIGNITE, AND PEAT↗

Electricity Cost for Electric Vehicle Fast Charging

As the adoption of plug-in electric vehicles (PEVs) continues to grow, so does the development of a network of fast-charging stations to support long-distance travel and provide alternatives to residential and workplace charging. Fast charging, however, could be significantly more expensive than residential/workplace charging, mainly due to high power consumption and low utilization. This poster highlights NREL's review of the current cost of electricity for PEV fast charging in the United States as well as its evaluation of alternative charting options to mitigate electricity costs for public fast-charging stations via on-site electricity generation (from photovoltaics) and storage.

25 ENERGY STORAGE↗

Projecting Future Energy Production from Operating Wind Farms in North America. Part II: Statistical Downscaling

Abstract Capacity factors (CFs) derived from daily expected power at 22 operating wind farms in different regions of North America are used as predictands to train statistical downscaling algorithms using output from ERA5. The statistical downscaling models are then used to make CF projections for a suite of CMIP6 Earth System Models (ESMs). Downscaling is performed using a hybrid statistical approach that employs synoptic types derived using k -means clustering applied to sea level pressure fields with variance corrections applied as a function of the pressure gradient intensity. ESMs exhibit marked variability in terms of the skill with which the frequency of synoptic types and pressure gradients are reproduced relative to ERA5, and that differential skill is used to infer differential credibility in the associated CF projections. Projections of median annual mean CF [P50(CF)] in each 20-yr period from 1980 to 2099 show evidence of declines at most wind farms except in parts of the southern Great Plains, although the magnitude of the changes is strongly dependent on the ESM. For example, P50(CF) in 2080–99 deviate from those in 1980–99 by from −3.1 to +0.2 percentage points in the Northeast. The largest-magnitude declines in P50(CF) ranging from −3.9 to −2 percentage points are projected for the southern West Coast. CF trends exhibit marked seasonality and are strongly linked to changes in the relative intensity of future synoptic patterns, with much less impact from shifts in the occurrence of synoptic types over time. Internal climate modes continue to play a significant role in inducing interannual variability in wind power production, even under high radiative forcing scenarios. Significance Statement We describe how future climate changes may affect wind resources and wind power generation. Near-term changes in projected wind power electricity generation potential at operating wind farms over North America are small, but by the end of the current century electricity production is projected to decrease in many areas but may increase in parts of the southern Great Plains. The amount of change in projected wind power production is a strong function of the Earth system model that is downscaled and also depends on the continued presence of internally forced climate variability. An additional dependence on the amount of greenhouse gas–induced global warming indicates the transition of the energy sector to low-carbon sources may assist in maintaining the abundant U.S. wind resource.

Meteorology & Atmospheric Sciences↗

Models and Strategies for Optimal Demand Side Management in the Chemical Industries

Deregulation and the increase of renewable electricity generation from wind and solar photovoltaics have transformed the U.S. electricity market. Economic and environmental benefits notwithstanding, the presence of renewables has increased variability and uncertainty on the supply side of the grid. Managing demand, rather than generation – a strategy referred to as “demand response (DR)” – is an attractive approach for mitigating this imbalance. DR efforts aim to reduce electricity usage during peak demand times, lessening stress on the grid. Industrial users are particularly attractive entities for DR participation since they present large, localized loads that can provide significant relief on grid demand and –unlike other large loads, such as buildings – are minimally dependent on human needs and preferences. In this project, we accomplished three main objectives. (1) We developed data-driven low-order DR scheduling-relevant dynamic models of chemical processes. Concurrently, we studied the formulation and solution of the associated optimal DR production scheduling problems. (a) A prototype air separation unit (ASU) model was used to generate simulated operating data for initial modeling efforts, which enabled the later use of industrial data for data-driven modeling. (b) We utilized Hammerstein-Wiener (HW) and Finite Step Response (FSR) models to represent nonlinear plant dynamics. (c) The HW models were linearized using exact linearization so they could potentially be embedded in power system models, which are formulated as mixed integer linear programs (MILPs). (d) We solved DR optimization problems under uncertainty and found that even naïve predictions of electricity price and product demand led to significant cost savings benefits. (2) Our DR scheduling optimization problem formulations are amenable to real-time solution. (a) We utilized Lagrangian Relaxation (LR) to efficiently solve the optimization problem by decoupling subproblems linked by complicating constraints. (b) We have achieved computation times for the 3-day DR scheduling problem of an ASU as low as 1.88 minutes. (3) Our representations of the DR behavior of chemical process as grid-level batteries were embedded in power system models. (a) For a small-scale grid, we found that incorporating the dynamics of the chemical plant in the optimal power flow calculations resulted in better resource management leading to up to 15% and 46% cost reduction for the grid and chemical plant operations, respectively, during periods of power line congestion. We have published several works dedicated to modeling and solving DR optimization problems from the user side. These were published in top peer-reviewed journals and are summarized in this report. The most recent work (and papers in preparation) considers DR scheduling from the grid side. Future efforts will consider networked plants (e.g., air separation units operating on a common pipeline) for DR participation, which is expected to amplify the capabilities of industrial DR participants to perform load-shifting. Our consideration of uncertainty in DR has inspired future directions in this area as well: we plan to develop multistage methods to fully account for the effects of uncertainty in DR scheduling.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Electrical control of coherent spin rotation of a single-spin qubit

Nitrogen vacancy (NV) centers, optically active atomic defects in diamond, have attracted tremendous interest for quantum sensing, network, and computing applications due to their excellent quantum coherence and remarkable versatility in a real, ambient environment. One of the critical challenges to develop NV-based quantum operation platforms results from the difficulty in locally addressing the quantum spin states of individual NV spins in a scalable, energy-efficient manner. Here, we report electrical control of the coherent spin rotation rate of a single-spin qubit in NV-magnet based hybrid quantum systems. By utilizing electrically generated spin currents, we are able to achieve efficient tuning of magnetic damping and the amplitude of the dipole fields generated by a micrometer-sized resonant magnet, enabling electrical control of the Rabi oscillation frequency of NV spins. Our results highlight the potential of NV centers in designing functional hybrid solid-state systems for next-generation quantum-information technologies. The demonstrated coupling between the NV centers and the propagating spin waves harbored by a magnetic insulator further points to the possibility to establish macroscale entanglement between distant spin qubits.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Validating and Comparing Energy Estimation Methods at Water Resource Recovery Facilities

Water resource recovery facilities play a crucial role in the water-energy nexus, consuming a substantial amount of energy in the United States. Growing treatment volumes and more stringent water quality standards are expected to increase the amount of energy needed to treat wastewater, but accurately estimating energy consumption and potential remains challenging due to variability in scale, treatment methods, and effluent treatment standards. In this study, we used publicly available data to evaluate the accuracy of methods for estimating energy consumption and generation, then quantified uncertainty based on key factors like flow rate, treatment level, and geographic location. To validate methods, we estimated energy consumption and generation at the facility-level, then compared estimates to self-reported data from utilities in major U.S. cities. We found that process models of treatment trains under best practice configurations were accurate relative to other methods for estimating electricity use, total energy use, and electricity generation from biogas utilization, and less complex methods based on effluent treatment level and prime movers also performed well for estimating electricity consumption and generation, respectively. Applying the evaluated methods to a national inventory of treatment facilities, we estimate that annual energy consumption ranged from 56.3 x 10^3 to 82.5 x 10^3 TJ in 2012 and 83.6 x 10^3 to 127 x 10^3 TJ in 2042. Our results indicate that not all estimation methods are suited for every use case, so we recommend that researchers and practitioners select an estimation method based on data availability and desired computational intensity.

Hodson, Abigayle↗

Enabling Staged Pressurized Oxy-Combustion: Improving Flexibility and Performance at Reduced Cost

Introduction: The staged pressurized oxy-combustion (SPOC) process, developed by Washington University in St. Louis (WUSTL), is an oxy-combustion carbon capture technology that employs a steam power cycle to generate electricity. As with atmospheric-pressure oxy-combustion processes, carbon dioxide (CO 2 ) capture rates of 90% or higher can be achieved. The staged-combustion approach of the SPOC process, when operated at elevated gas pressure, allows for near elimination of flue gas recycle (FGR) and leads to significant improvements in efficiency and reduced costs. The primary goal of this project was to investigate the potential for SPOC for flexible operation beyond the capabilities of conventional coal-fired power plants, particularly those employing carbon capture and storage (CCS). Oxy-combustion differs from conventional coal combustion in that the combustion of coal is carried out using oxygen as opposed to air. The resultant flue gas is a mixture of primarily CO 2 and water, greatly simplifying CO 2 capture. As SPOC does the oxy-combustion process under pressure, it is higher efficiency and lower cost than atmospheric oxy-combustion. The project was led by the Electric Power Research Institute, Inc., with the assistance of WUSTL, Doosan Babcock (DBL – boiler plant original equipment manufacturer), and Air Liquide (AL – air separation experts). The specific objectives of the project were to: (1) Evaluate the SPOC concept and develop a risk-based approach to the heating surface layout ensuring that performance (gas and steam side), manufacturing, transportation, and plant erection considerations were fully accounted for in the system design. (2) Improve the technology to ensure its performance and cost potential are substantially better than today’s baseline pulverized coal power plant with post-combustion capture (PCC) or atmospheric oxy-combustion, and show progress toward performance commensurate with projected commercial operation, including 90% or more CO 2 capture. (3) Address critical technology gaps and improving overall system performance for the technology. (4) Perform combustion tests at scale under commensurate pressure to the commercial operating system validate combustor and advance the SPOC combustion modeling tools that will facilitate full-scale design. Combustion Testing: Testing was initially carried out at atmospheric pressure with methane to ensure that all systems were correctly operating. Following this, the testing then proceeded to moderate pressure operation at 4 bara, where different stoichiometric conditions were used across an extended heat input range, showing that a stable flame could be maintained. Testing then proceeded at 10 and 15 bara where it was shown that the ignition system needed to be replaced at these operating conditions. When testing recommenced, a similar stable flame shape was achieved, without any methane support, and the full 100 kWth coal oxy-combustion was demonstrated. Heat flux measurements showed 400 kW/m 2 (0.126 MMBtu/hr-ft 2 ) from the flame, within the 450 kW/m 2 (0.142 MMBtu/hr-ft 2 ) preferred limit defined by DBL for the full-scale design case. Carbon monoxide and carbon-in-ash measurements showed that complete combustion was possible with ultra-low excess oxygen at 1 vol % in the product flue gas. This allowed the full-scale models to be calculated based on this level of excess oxygen, improving the performance of the system as lower feed oxygen is produced in the air separation unit (ASU), saving auxiliary power. Full-Scale Design: The full-scale design is sized to deliver 550 MWe net electrical power output to allow direct comparison with the National Energy Technology Laboratory (NETL) baseline cases using the same Montana Powder River Basin (PRB) fuel. The cases used for direct comparison are: Case S12A (supercritical [SC] coal without CO 2 capture), Case S12B (SC coal with PCC at 90% CO 2 capture, and Case S12F (atmospheric oxy-combustion SC coal with 90% CO 2 capture). The SPOC stages were configured to be identical arrangements, allowing for a more straightforward design, construction, and control strategy. Each stage consists of two PVs, the first being the combustor PV module and the second being the convective PV module. The combustor module is the tallest vessel, with local coal feeding equipment and the burner FGR and oxygen plenums at the top and ash management at the bottom. The combustor module is effectively an open cross section with membrane tubes around the circumference – this unobstructed slender profile ensures that the relatively slower burnout mechanism needed for the low-speed turbulent mixing burner can proceed unimpeded and that molten ash will not attach to any surfaces at an angle to the predominant flue gas flow. The steam turbine used in the SPOC design is essentially the same unit utilized in the atmospheric oxy-combustion case except the degree of heat recovery possible allows the low-pressure (LP) feedwater heater train to be eliminated. This is a result of being able to capture the latent heat of evaporation of the moisture produced in the combustion (normally lost to the stack). The SPOC system outperforms the NETL atmospheric oxy-combustion baseline case by 3.3% points and the PCC case by 7.5% points. This performance increase is mainly a result of the improved heat recovery possible from the product flue gas and from the reduced auxiliary power consumption from the ASU and the CO 2 compression and purification unit over the atmospheric equivalent. The combined improvement in boiler efficiency and reduction in the steam turbine heat rate resulted in a net improvement in the overall plant efficiency by 0.61%, to 35.6% on a HHV basis. This relatively small improvement in plant efficiency between sub-bituminous and bituminous coals shows the value of useful moisture latent heat recovery offered by the SPOC system when using low rank fuels. Flexibility and Turndown: The SPOC system has inherent high turndown capabilities because of a demonstrated high range of combustion stability and the ability to bypass stages, thereby reducing steam generation rates proportionally without altering firing rates in operating stages. ASU units do not generally offer significant turndown opportunities as they are limited by the performance of the compression plant. The baseline SPOC design has a 2-train ASU configuration, needed to be able to meet the 10,500 tonnes per day duty, that can deliver efficient turndown points between 85–100% load with both trains operating, and at 45–50% load with a single train operating. Outside these operating points, the flexibility and efficiency are limited and may be uncompetitive at loads below 45% as the ASU systems are unable to turndown beyond 85% for the base case and 70% for the flexible case. The ASU cold box for the flexible case was designed to operate at loads between 40-100%, below this operating range the purity of the produced oxygen cannot be guaranteed, resulting in additional load for the CPU equipment. The additional power consumption of these cases yields an uneconomic operating condition with poor efficiency when operating at low loads such as 25% and 12%. To address this flexibility constraint, AL evaluated how the ASU configuration could be altered to deliver efficient oxygen supply over the load range. This involved integrating the compressor duties across both ASU trains into a shared duty arrangement with multiple compressors, strategically sized to deliver the duty required across all load ranges between 40–100% by enabling different combinations of the main air compressors and the booster air compressors. The oxygen purity cannot be guaranteed below 40% load for each train – the power consumption at 25% and 12% loads were estimated based on the multi-compressor configuration at maximum turndown as these load cases were not considered in the flexible ASU design. With a different cold box configuration, i.e. number of trains, the entire load range could be delivered within oxygen purity specifications. Although there is a small efficiency reduction at full load, there are significant improvements in overall plant performance during low-load operation. The exact ASU configuration needed will therefore be dependent on the expected operating profile of the unit. Economic Analysis: Cost estimates for the baseline and the flexible cases were developed using NETL baseline case data for common BOP items and an Association for the Advancement of Cost Engineering International Class 5 (conceptual/screening study) assessment of key components unique to the SPOC system. The capital, operating, and maintenance costs were assessed along with the first-year power cost, levelized cost of electricity, and CO 2 captured and avoided cost for the SPOC cases were compared against the relevant NETL baseline cases in January 2019 dollars. Both SPOC cases achieve a lower cost that the alternative NETL baseline cases (with the flexible SPOC case being slightly higher than the baseline SPOC case due to the compounded impact of higher capital costs and lower efficiency at full load). The SPOC cases deliver a lower cost of CO 2 avoided than the NETL baseline cases due to greater efficiency in generating low-carbon power. However, the cost of CO 2 captured is higher because the higher efficiency of the SPOC process generates less CO 2 , hence less needs to be captured, resulting in a high capital cost being shared over a reduced CO 2 quantity. The flexible ASU adds 1.6% overall to the plant cost in comparison to the baseline case, but the efficiency improvements at loads below 50% are significant. Subsequently, depending on the plant load-profile expectation, the flexible ASU would be beneficial if the plant spends a significant portion of its operating life below 50% load. This kind of operating profile is likely to be required for all fossil plants when more renewable electricity generators are installed on the local grid, particularly solar power that can be predicted ahead of time, allowing for appropriate pricing signals to be incorporated into the diurnal cycle. R&D Recommendations: SPOC, while a promising technology, is a relatively recent concept and, as such, operability issues of combustor design and steam-side integration for such systems at a scale relevant to commercial deployment have not been evaluated. WUSTL has conducted extensive small pilot-scale (100 kWth) research to understand and advance pressurized oxy-combustion processes, including investigation of combustion and flame characteristics, radiative heat flux, burner operability, turn down, char burnout, ash characteristics, water-wash column operation, etc. for pressurized oxy-combustion systems. Nonetheless, at this stage in the development of the SPOC process, what is needed is a large-scale pilot plant that can serve to study pressurized oxy-combustion systems and components at a scale commensurate with the maturity of the technology. A scale of 10 MWth, which includes steam-side integration and two stages would yield essential information with respect to heat transfer characteristics both in the radiative and convective sections of the pressure vessels, and the ability to operate the fuel staging process. In addition, while modeling results indicate that combustion and flame characteristics improve with scale, direct studies of the combustor at this scale will ensure that the models can be relied upon for scale up to commercial scale. Furthermore, a detailed analysis must be performed to understand the scaling aspects of key components and systems.

20 FOSSIL-FUELED POWER PLANTS↗

Nonlinear Model Predictive Control Based on Real-Time Iteration Scheme for Wave Energy Converters Using WEC-Sim

One of several challenges that wave energy technologies face is their inability to generate electricity cost-competitively with other grid-scale energy generation sources. Several studies have identified two approaches to lower the levelised cost of electricity: reduce the cost over the device's lifetime or increase its overall electrical energy production. Several advanced control strategies have been developed to address the latter. However, only a few take into account the overall efficiency of the power take-off (PTO) system, and none of them solve the optimisation problem that arises at each sampling time on real-time. In this paper, a detailed Nonlinear model predictive control (NMPC) approach based on the real-time iteration (RTI) scheme is presented, and the controller performance is evaluated using a time-domain hydrodynamics model (WEC-Sim). The proposed control law incorporates the PTO system's efficiency in a control law to maximise the energy extracted. The study also revealed that RTI-NMPC clearly outperforms a simple resistive controller.

model predictive control↗

Nonlinear Model Predictive Control Based on Real-Time Iteration Scheme for Wave Energy Converters Using WEC-Sim: Preprint

One of several challenges that wave energy technologies face is their inability to generate electricity cost-competitively with other grid-scale energy generation sources. Several studies have identified two approaches to lower the levelised cost of electricity: reduce the cost over the device's lifetime or increase its overall electrical energy production. Several advanced control strategies have been developed to address the latter. However, only a few take into account the overall efficiency of the power take-off (PTO) system, and none of them solve the optimisation problem that arises at each sampling time on real-time. In this paper, a detailed Nonlinear model predictive control (NMPC) approach based on the real-time iteration (RTI) scheme is presented, and the controller performance is evaluated using a time-domain hydrodynamics model (WEC-Sim). The proposed control law incorporates the PTO system's efficiency in a control law to maximise the energy extracted. The study also revealed that RTI-NMPC clearly outperforms a simple resistive controller.

model predictive control↗

Cost and Performance Estimates for State-of-the-Art and Advanced 1×1 H-Class Natural Gas-Fired Power Plants

As an extension of NETL's Fossil Energy Baseline for Electricity Generating Units Volume 1: Coal and Natural Gas to Electricity (FEB Rev 4a, this study develops cost and performance estimates for analogous NGCC cases using a state-of-the-art 2023 vintage H-Class CT in a 1×1 configuration, where a single combustion turbine and heat recovery steam generator are coupled to a single steam turbine on a common shaft. These 1×1 H-Class cases are used to develop cost and performance estimates of X-Class 1×1 NGCC cases with advanced performance characteristics, analogous to NETL’s cost and performance projections report.

20 FOSSIL-FUELED POWER PLANTS↗

Solar and Wind Forecast Error Reserve Sharing in a Multi-Utility Region

As electricity systems transition to higher levels of solar and wind generation, electric system operators will likely need to hold additional reserves to manage solar and wind forecast error. Because solar and wind forecast errors tend to be weakly correlated across space, system operators can reduce their reserve requirements by sharing reserves. This paper examines the benefits of forecast error reserve sharing among balancing areas in the Southeastern United States, in scenarios in which solar and wind generation ranges from 34% to 65% of total generation. It finds that day-ahead forecast error reserve requirements increase linearly with growth in solar and wind generation capacity (6%-10% of total capacity), but that reserve sharing can significantly reduce these requirements (by 6%-29%). It finds that, in economic terms, the value of forecast error reserve sharing ($\$$0.09-$\$$1.24 billion per year, $\$$0.12-$\$$1.68/MWh of load across scenarios) tends to decline with higher levels of solar and wind generation, due to lower reserve and energy prices. Even with declines in reserve prices, forecast error reserve sharing can still provide substantial value, though with higher levels of solar, wind, and electricity storage this value is increasingly tied to avoiding scarcity prices.

14 SOLAR ENERGY↗

The Role of Energy Storage in the Uptake of Renewable Energy: A Model Comparison Approach

The power sector needs to ensure a rapid transition towards a low-carbon energy system to avoid the dangerous consequences of greenhouse gas emissions. Storage technologies are a promising option to provide the power system with the flexibility required when intermittent renewables are present in the electricity generation mix. This paper focuses on the role of electricity storage in energy systems with high shares of renewable sources. The study encompasses a model comparison approach where four models (GENeSYS-MOD, MUSE, NATEM, and urbs - MX) are used to analyse the storage uptake in North America. The analysis addresses the conditions affecting storage uptake in each country and its dependence on resource availability, technology costs, and public policies. Results show that storage may promote emissions reduction at lower costs when renewable mandates are in place whereas in presence of carbon taxes, renewables may compete with other low-carbon options. The study also highlights the main modelling approach shortcomings in the modelling of electricity storage in integrated assessment models.

electricity storage↗

Evaluation of Energy Storage Potential of Unconventional Shale Reservoirs Using Numerical Simulation of Cyclic Gas Injection

Compressed air energy storage (CAES) stores energy as compressed air in underground formations, typically salt dome caverns. When electricity demand grows, the compressed air is released through a turbine to produce electricity. CAES in the US is limited to one plant built in 1991, due in part to the inherent risk and uncertainty of developing subsurface storage reservoirs. As an alternative to CAES, we propose using some of the hundreds of thousands of hydraulically fractured horizontal wells to store energy as compressed natural gas in unconventional shale reservoirs. To store energy, produced or “sales” natural gas is injected back into the formation using excess electricity and is later produced through an expander to generate electricity. To evaluate this concept, we performed numerical simulations of cyclic natural gas injection into unconventional shale reservoirs using cmg-gem commercial reservoir modeling software. We tested short-term (diurnal) and long-term (seasonal) energy storage potential by modeling well injection and production gas flowrates as a function of bottom-hole pressure. First, we developed a conceptual model of a single fracture stage in an unconventional shale reservoir to characterize reservoir behavior during cyclic injection and production. Next, we modeled cyclic injection in the Marcellus shale gas play using published data. Results indicate that Marcellus unconventional shale reservoirs could support both short- and long-term energy storage at capacities of 100–1000 kWe per well. The results indicate that energy storage in unconventional shale gas wells may be feasible and warrants further investigation.

25 ENERGY STORAGE↗

Transitioning to Hybrid Power Plants

Hybrid power plants are power generation systems that combine two or more types of electricity generation or storage, creating systems where the optimal dispatch provides more benefits that the sum of the individual components can. These plants exemplify the interconnected challenges of grid modernization. On one hand, rapid increase in deployment and enhanced controllability of renewable energy assets is needed to meet clean energy targets, but on the other, increasing electrification makes it more difficult to manage load and growth in the number of endpoints and stakeholders involved with hybrid plants complicates asset management and cybersecurity. This talk will cover trends in hybrid power plant technologies and deployments, identify future prospects for hybrid systems, and discuss the challenges and research opportunities that exist to transition from the traditional power grids of today to smart, distributed, hybrid power grids we may see in the next few decades.

14 SOLAR ENERGY↗

An Adaptive Dynamic Agrivoltaic Production Tool

In the pursuit of sustainable and land-use-efficient solutions to mitigate climate change, the concept of agrivoltaic systems, which integrate renewable solar energy into conventional agriculture, has emerged. By deploying solar arrays above the crop field, these systems are designed to maximize the land use efficiency or, in other words, the value of generated electricity and crop yield per unit area. While power generation has been extensively studied and modeled, research gaps persist in simulating crop performance [1], [2]. Early studies utilized generalized relationships between photosynthetically active radiation (PAR) and crop production. However, significant variations in crop performance due to other factors, such as weather and soil, can compromise the reliability of the results [2]. Current studies focus on comprehensive process-based crop models, such as DSSAT [3] and STICS [4]. Nevertheless, the validation status varies greatly across different species, and the validation process requires well-designed experiments to adjust specific processes. For less common shade-tolerant crops with limited validation, such as cabbage, physiological behaviors can be difficult to predict [5]. This study investigates an adaptive dynamic agrivoltaic production tool (ADAPT) with few data requirements and minimal on-site calibration that can be easily applied in real applications.

Long, Qirui↗

An Advanced Cooling Device for Concentrated Photovoltaic Systems

Concentrated photovoltaics (CPV) have the potential to significantly enhance the energy conversion utilization of solar panels and reduce solar generation costs, making them a crucial area of advancement in solar power generation technology. However, the concentration of sunlight can lead to overheating of solar panels, resulting in a notable reduction in both the efficiency of solar power generation and the lifespan of the panels. This challenge remains the predominant technical hurdle that hinders the application of concentrated photovoltaic power generation technology. In this study, we propose a new cooling method for concentrated photovoltaic power generation systems via an integrated approach of incorporating Phase-Change Thermal Storage (PCTS) and Thermoelectric Generator (TEG) technology. This new method not only enhances the overall system's electricity generation efficiency but also effectively resolves the technical challenge of concentrated photovoltaic panel overheating issues, ensuring the continuity of concentrated photovoltaic power generation and extending the lifespan of solar panels and their components. In order to make full use of the wasted heat generated by photovoltaic power generation and effectively improve the power generation efficiency of the system, this work developed a phase change heat storage device based on a phase change material. This device uses the temperature difference between day and night to recover wasted heat from photovoltaic power generation. Through integration with the thermoelectric power generation system, thermal energy can be converted into electrical energy. In addition, the Peltier effect of thermoelectric materials is used to construct a photovoltaic panel overheating protection system, which significantly improves the reliability and service life of the system.

14 SOLAR ENERGY↗

Solar and Wind Forecast Error Reserve Sharing in a Multi-Utility Region

As electricity systems transition to higher levels of solar and wind generation, electric system operators will likely need to hold additional reserves to manage the forecast error associated with these resources. Because wind and solar forecast errors tend to be poorly correlated across space, system operators can reduce their reserve requirements by sharing reserves. This paper examines the value of forecast error reserve sharing among balancing areas in the Southeast United States. It finds that forecast error reserve requirements increase linearly with growth in solar and wind generation capacity but that reserve sharing can significantly reduce physical (MW) reserve requirements (from 25%-26% to 18%-19% of average load in high solar scenarios). It finds that the value of forecast error reserve sharing declines with higher levels of solar and wind generation, due to lower wholesale energy and reserve prices. Even with declines in wholesale prices, forecast error reserve sharing can still provide substantial value (as much as $\$$400 million per year in a high solar scenario), though with higher levels of solar, wind, and electricity storage, this value is increasingly tied to avoiding scarcity prices. The results suggest the importance of coordinated capacity expansion planning for forecast error reserve sharing.

14 SOLAR ENERGY↗