Adopting Dynamic VAR Compensators to Mitigate PV Impacts on Unbalanced Distribution Systems
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Results for “PV systems”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Development of Fixtures and Methods to Assess the Durability of Balance of Systems Components
The degradation of photovoltaic (PV) balance of systems (BoS) components is not well studied, but the consequences include offline modules, strings, and inverters; system shutdown; arc faults; and fires. A utility provider experienced a ~30% failure rate in their power transfer chain, originally attributed to branch connectors. Field-failed specimen assemblies were, therefore, examined, consisting of cable connector, branch connector, and discrete fuse components. In this study, unused field-vintage specimens are examined using a benchtop prototype fixture to identify the most influential environmental stressors on BoS components as well as the effect of external mechanical perturbation. The prototype fixture was used to develop a perturbation capability for future use in the combined-accelerated stress testing chamber. The benchtop experiments were also used to develop the in-situ data acquisition of specimen current, voltage, and temperature. A significant increase in operating temperature (~100 °C from ~40 °C) and a different failure mode (arcing at the metal pins rather than overheating of the fuse filament) were observed promptly once periodic mechanical perturbation was applied. The current at failure was decreased from 35 A (measured for static specimens, with failure occurring in the fuses) to 15 A (for tests with mechanical perturbation, with failure at the male/female metal pin connection). After initial examination using X-ray computed tomography, the external plastic was machined away from failed specimens to allow for failure analysis, including the extraction of the internal convolute springs for morphological examination (optical and electron microscopy). Chemical composition analysis included energy-dispersive X-ray spectroscopy, differential scanning calorimetry, and Fourier transform infrared spectroscopy.
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Aeroelastic Modeling and Full-Scale Loads Measurements for Investigation of Single-Axis PV Tracker Wind-Driven Dynamic Instabilities
While wind tunnel testing and proprietary industry modeling tools have been used for years to design and develop PV tracker systems, wind induced dynamic failures are becoming more prevalent and high visibility. Designers and manufactures have reacted by developing new systems or add-on products to improve system dynamics adding to overall system costs. To better understand the physics and aeroelastic behavior that leads to dynamic instabilities NREL researches have taken up a first of a kind study to both develop open source aeroelastic modeling tools and measure tracker loads on a single axis full-scale tracker system at a high wind site. These modeling tools can simulate the fluid-structure interaction driving torsional instabilities under a wide range of turbulent inflow conditions and stow angles. The results of these simulations reveal the flow features associated with panel rotation and the induced loads in the structure. The experimental load measurements can be used to validate models and provide a quantifiable understanding of tracker dynamics, critical loads paths, identify instability markers, inform resilient design, and suggest the most favorable stow approach.
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Duty-Cycle Predictive Control of Quasi-Z-Source Modular Cascaded Converter Based Photovoltaic Power System
A duty-cycle predictive control is proposed for dc grid integration of front-end isolated quasi-Z-source modular cascaded converter (qZS-MCC) photovoltaic (PV) power system. The post-stage qZS half-bridge dc-dc converter deals with PV maximum power point tracking, dc grid integration, and dc-link voltage balance; whereas, the front-end isolation converters operate at a constant duty cycle of 50%. Thus, it saves control hardware resources while overcoming challenges from PV-panel voltage variations and dc-bus voltage limit. The proposed control uses the derived circuit model to predict the global active-state duty cycle for grid-connected current control and predict the shoot-through duty cycles for dc-link voltage balance, achieving a fast and accurate tracking target. The proposed control method has advantages of: i) eliminating weighting factors that exist in conventional model predictive control (MPC), ii) no sophisticated loop parameters design that exists in proportional-integral (PI) control, iii) operating at constant switching frequency that is different from the conventional MPC with variable switching frequency. Simulation and experimental tests are carried out to verify the effectiveness of the proposed control method and compare with the PI-based control system.
42 ENGINEERING↗
PV Inverter Availability from the U.S. PV Fleet
In the PV Fleet Performance Data Initiative, we partner with photovoltaic (PV) fleet owners to collect time-series PV production data, and publish aggregated, anonymized results. An assessment of system availability is conducted on 1128 systems which passed our data quality checks, and include cumulative energy meter data. Overall inverter availability is low in the first 6 months of system performance before reaching steady-state by the end of the first year. System-level aggregated data shows a median (P50) system availability of 0.99, and a lower P90 value of 0.95. A dependence on system size is also identified, with better inverter availability results for smaller PV systems. Potential causes of this effect may include the selection of inverter itself: smaller inverters 6kW-250kW showed better average availability than inverters 300kW-5MW. The elimination of string combiner boxes and lower energy impact when one particular inverter goes off-line are potential benefits of a string inverter-based PV system architecture. DNV also analyzed availability data from over 1100 operating systems and found similar trends. DNV's P50 industry guidance on expected availability has been updated to reflect the data and the following observations: utility scale systems have lower availability than DG systems, availability is lower in first year compared to subsequent years, and that actual availability is lower than expected.
fleet↗
Advanced Models and Fast Simulation Algorithms for MARS Plants
With the successful commercialization of modular multilevel converters (MMC) and rapid increase in photovoltaic (PV) penetration and energy storage systems (ESS), one of the research areas being explored dynamically is integration of PV systems and ESS systems to MMCs. On this front, an integrated development of PV plants, ESS, and alternating- and direct-current (ac/dc) systems through Multi-Port Autonomous Reconfigurable Solar (MARS) plant is proposed and being researched upon. However, simulation of MARS systems on traditional existing software takes very long time (order of days) due to the presence of a large number of states and non-linear devices. Therefore, development of fast high fidelity models is of paramount importance to test the hardware design, control design and planning of power system expansions. In this context, two research objectives are addressed in this paper: firstly, an ultra fast single- or multi- CPU simulation algorithm to simulate the MARS system based on state-space models, hybrid discretization algorithm with a relaxation technique that reduces the imposed computational burden and a multi-rate method is presented. Secondly, a reduced order model of MARS is also presented. Both the developed techniques are validated with respect to reference PSCAD/EMTDC model.
Marthi, Phani Ratna Vanamali↗
The Roles and Impacts of PV-Battery Hybrids in a Decarbonized U.S. Electricity Supply
In this paper, we explore the potential impacts of growing industry interest in hybrid systems comprising PV and battery technologies on the results and findings of the Solar Futures Study (DOE 2021). We employ similar scenario definitions in the same ReEDS capacity expansion model, but we perform two versions of each scenario: one in which PV and battery technologies must be deployed separately (No Hybrids), and one in which the model has the option of deploying them together as PVB hybrids (With Hybrids). By comparing the No Hybrids and With Hybrids versions of each scenario, we isolate the impacts of hybridization on the outcomes and findings of the Solar Futures Study. We find that PVB hybrid configurations capture a sizable share of PV deployment, and the highest-net-value PVB hybrid configuration depends strongly on policy conditions. A power sector decarbonization policy generally increases the value proposition of a more forward-looking PVB hybrid configuration that involves significant oversizing of the PV arrays, a larger battery (which facilitates greater recovery and utilization of otherwise clipped energy), and a higher capacity factor. The growing deployment of PVB hybrid configurations primarily displaces standalone PV capacity, such that total installed PV capacity is largely unaffected by the availability of PVB hybrid configurations. However, the higher capacity factors associated with PVB hybrid configurations drive a modest (1-2 percentage point) increase in PV's share of U.S. electricity supply in 2050. Finally, introducing the PVB hybrid configurations influences the future role and makeup of battery storage technologies, and it reduces the required transmission expansion, particularly under scenarios that involve a power sector decarbonization policy.
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Machine Learning-Based PV Reserve Determination Strategy for Frequency Control on the WECC System: Preprint
Frequency control from Photovoltaic (PV) plants has great potential to address the frequency response challenge of the power system with high renewable penetration. However, using model-based approaches to determine the optimal PV headroom reserve requires significant online computation and is intractable for an interconnection level system. This paper proposes a machine learning based strategy, that is suitable for real-time operation, to determine the optimal PV reserve for frequency control. The proposed machine learning algorithm is trained and tested on 1,987 offline simulations of a 60% renewable penetration Western Electricity Coordinating Council (WECC) system. Furthermore, the proposed reserve determination strategy is applied on a realistic one-day operation profile of the WECC system and demonstrates over 40% PV headroom saving compared to a conservative approach. It is evident that the proposed strategy can efficiently and effectively determine the optimal PV frequency control reserve for realistic interconnection systems.
41 EE - Solar Energy Technologies Office (EE-4S)↗
Segmented Energy Routing for a Modular AC/DC Hybrid System
This article presents a modular ac/dc system with both distributed and centralized power ports for energy router (ER) applications. In each module of the described system, photovoltaic (PV) power generation units, battery-type energy storage (ES) units, and critical loads are connected to the cascaded H-bridge (CHB)-organized medium-voltage (MV) dc links, with fully distributed low-voltage (LV) dc power ports. Copies of modules share the centralized load bus and interact with an MV ac grid in parallel. Hybrid power port (HPO) assigns flexibility to the system but makes energy routings a necessity for stable operation. In this article, a segmented energy management strategy for the HPO-ER is proposed. In terms of the grid-side power transferring, the system ratings are intentionally designed to match significant power imbalance. Focally, a segmented energy management strategy is proposed to realize fully autonomous energy routing involving MV ac grid, distributed PV generations, distributed battery storages, and LV load. The system is proven to be stable using the derived impedance-based model considering the interaction between power blocks. The feasibility of the topology and control strategy is also verified through software simulation, laboratorial hardware prototype experiment, and hardware-in-the-loop (HIL) emulation.
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Effect of Torque-Tube Parameters on Rear-Irradiance and Rear-Shading Loss for Bifacial PV Performance on Single-Axis Tracking Systems
The emergence of cost-competitive bifacial PV modules has raised the question of the additional value of bifacial 1-axis tracking arrays, in particular when considering rear-irradiance losses from the tracker system itself. In this work, the effect of different geometries and materials of torque tubes is evaluated through ray-trace simulations and found to cause rear irradiance shading factors between 2% to 8% for systems without gap between the modules in 2-UP configuration. Inclusion of a gap between the modules can offset the shading factor. Electrical mismatch is also evaluated for the various configurations, and a methodology to apply shading factor and electrical mismatch loss to rear irradiance from the calculated loss in DC power, which averages 1% for the systems explored here, is proposed.
41 EE - Solar Energy Technologies Office (EE-4S)↗
PV Fleet Performance Data Initiative Final Technical Report (FTR)
Improved analysis and reporting of photovoltaic (PV) field performance increases the certainty of owners and financiers that systems will perform as expected. Advanced module technologies (e.g., PERC, HJT, and bifacial) introduce new degradation mechanisms and performance characteristics. This project will leverage data from the ever-increasing PV fleet to develop models and understanding of the field performance of existing and new technologies. Please see our list of public reports at https://www.nrel.gov/pv/fleet-performance-data-initiative.html. Objective 1: Support the global PV industry with scalable, robust data analysis tools that reduce the uncertainty of PV system performance and loss calculation. Objective 2: Reduce perceived risk arising from degradation rate, soiling loss, and system availability by publishing detailed statistics on U.S. fleet performance. Objective 3: Highlight factors leading to system underperformance including module type, climate, mounting configuration, etc. Objective 4: Enable continued high system performance in modern PV systems, as turnover and advances in technology bring new suppliers and high-efficiency modules into the market.
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Recent Improvements in PV+Battery Modeling in NREL's System Advisor Model
This poster covers recent updates to the NREL System Advisor Model's battery model that can be coupled to the PV model to add value to both front of meter and behind the meter systems. Topics include new dispatch algorithms focusing on smoothing the output of a PV plant to meet ramp rate requirements and responding to price signals to maximize system revenue, validated battery lifetime models, grid outage simulations and resiliency metrics, and the new levelized cost of storage (LCOS) metric. We will also share preliminary results from NREL analysis projects using these features.
battery↗
Getting brighter: Impacts of improved day-ahead solar forecasts in high-solar, high-storage electricity systems
This paper analyzes the impacts of improved day-ahead solar forecasts on costs and dispatch in the solar-rich Southeast U.S. It uses an optimized high-solar, high-storage resource portfolio in which solar generation capacity accounts for 45 % of total installed capacity (34 %–36 % of generation) and energy storage capacity (43 GW) is equivalent to 33 % of peak demand. In a base scenario, improved day-ahead solar forecasts reduce production costs by $\$87$ million per year ($\$0.13$ per MWh load, $2023$$). This level of savings is within the range or lower than earlier studies of solar forecast improvements at lower levels of solar generation (<25 % of total generation). In this study, solar expansion was accompanied by two important sources of flexibility for managing solar forecast error: energy storage and day-ahead solar curtailment. Furthermore, the analysis finds that regional coordination complements day-ahead solar forecast improvements while natural gas commitment flexibility is a substitute for forecast improvements, as the improved solar forecast leads to sub-optimal commitment of thermal units. Day-ahead solar forecast improvements reduce reserves required to manage forecast error by 30 %. Fewer reserves to manage large, infrequent solar forecast errors could be an important benefit of improved solar forecasts.
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Optimal Distribution System Voltage Regulation using State Estimation and DER Grid-Support Functions
Increasing solar energy penetrations may create challenges for distribution system operations because production variability can lead to large voltage deviations or protection system miscoordination. Instituting advanced management systems on distribution systems is one promising method for combating these challenges by intelligently controlling distribution assets to regulate voltage and ensure protection safety margins. While it is generally not the case today, greater deployment of power system sensors and interoperable distributed energy resources (DER)e.g., photovoltaic (PV) inverters, energy storage systems (ESS), electric vehicles (EVs)will enable situational awareness, control, and optimization of distribution systems. In this work, a control system was created which measures power system parameters to estimate the status of a feeder, forecasts the distribution state over a short-term horizon, and issues optimal set point commands to distribution-connected equipment to regulate voltage and protect the system. This two-year project integrated multiple research innovations into a management system designed to safely allow PV penetrations of 50% or greater. The integrated software was demonstrated through extensive real-time (RT) and power hardware-in-the-loop studies and a field demonstration on a live power system with a 684 kVA PV system.
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Battery Energy Storage System Evaluation Method
This report describes development of an effort to assess Battery Energy Storage System (BESS) performance that the US DOE Federal Energy Management Program (FEMP) and others can employ to evaluate performance of deployed BESS or solar photovoltaic (PV) +BESS systems. The proposed method is based on actual battery charge and discharge metered data to be collected from BESS systems provided by federal agencies participating in the FEMP's performance assessment initiatives. Long-term (e.g., at least one year) time series (e.g., hourly) charge and discharge data are analyzed to provide approximate estimates of key performance indicators (KPIs).
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Impact of Thermal Plant Operational Flexibility on VRE Curtailment: The Curtailment Paradox
This presentation provides an overview of a previously published paper in Joule "The curtailment paradox in the transition to high solar power systems." The adoption of PV and battery storage has accelerated globally in recent years, driven by rapid cost declines. A corresponding increase in curtailment is anticipated as PV growth continues. This study explores the effect of system flexibility options on curtailment across increasing PV penetration levels. Results highlight a paradox where thermal generator flexibility matters most only at mid-PV penetration levels (25%-40%), and a misalignment exists where PV provides system value by providing operating reserves without sufficient opportunity for monetary compensation.
capacity expansion modeling↗
Smart Phone Application to Compute Annual Solar Production of One Panel of a Plug-and-Play Solar Appliance (Cooperative Research and Development Final Report, CRADA Number CRD-19-00832)
The primary goal of the project is to develop a smart phone application (App) that will be available in both the Apple App Store and the Android store that displays results from the NREL's photovoltaic application, PVWatts Calculator, an application that estimates the energy production and cost of energy of grid-connected PV energy systems, and that will provide quick-response changes based on the orientation of the smart phone by the end user.
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Managing Solar Photovoltaic Integration in the Western United States: Resource Adequacy Considerations
This study examines the impact of reserve margin-based reliability assessment, as commonly used in capacity expansion models, on planning resource-adequate power systems under high penetrations of solar photovoltaics (PV). As a generation resource, PV is operationally different from the conventional dispatchable resources for which most capacity expansion models were designed. The question this study attempts to answer is whether large amounts of PV on a system (in this case, the Western Interconnection of North America) would bias the results of conventional reserve margin-based capacity expansion modeling towards an over- or under-provisioning of resource adequacy. This analysis used NREL’s Resource Planning Model (RPM) for capacity expansion modeling and NREL’s Probabilistic Resource Adequacy Suite (PRAS) for resource adequacy assessment. RPM uses a reserve margin requirement to enforce resource adequacy. PRAS, a collection of tools for studying the resource adequacy of power systems and the adequacy contributions of individual resources on a probabilistic basis, was used to compute multiple resource adequacy metrics across a number of simulated scenarios and system representations with differing regional detail. In all cases, including high PV penetrations (up to 33% annual generation from PV, interconnection-wide), RPM was able to produce resource-adequate systems as measured by normalized expected unserved energy and loss-of-load expectation results from PRAS. The accuracy of reserve margin approaches depends heavily on the underlying assumptions informing the capacity credit assigned to variable and energy-limited resources, particularly when such resources are abundant in the modeled system. RPM’s standard methodology for estimating variable and flexible resources’ capacity contributions, which is based on the top 100 hours of net load, did not appear to systematically undervalue or overvalue variable generation relative to a more rigorous equivalent firm capacity assessment using PRAS, although both over- and under-valuations were observed in specific scenarios. In the worst cases, the top 100 hour method underestimated the equivalent firm capacity of PV by two percentage points, and overestimated the equivalent firm capacity of PV by five percentage points. Calculating capacity contributions based on the top 10 hours of net load systematically underestimated equivalent firm capacities at more modest PV penetrations, but was often a better approximation of equivalent firm capacity than the existing 100-hour approach in scenarios with higher PV penetrations.
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