Matthew Lave

A Wavelet-Based Variability Model (WVM) for Solar PV Power Plants

A wavelet variability model (WVM) for simulating solar photovoltaic (PV) power plant output given a single irradiance point sensor timeseries using spatio-temporal correlations is presented. The variability reduction (VR) that occurs in upscaling from the single point sensor to the entire PV plant at each timescale is simulated, then combined with the wavelet transform of the point sensor timeseries to produce a simulated power plant output. The WVM is validated against measurements at a 2-MW residential rooftop distributed PV power plant in Ota City, Japan and at a 48-MW utility-scale power plant in Copper Mountain, NV. The WVM simulation matches the actual power output well for all variability timescales, and the WVM compares well against other simulation methods.

Evaluation of Global Horizontal Irradiance to Plane-of-Array Irradiance Models at Locations Across the United States

We report an evaluation of the accuracy of combinations of models that estimate plane-of-array (POA) irradiance from measured global horizontal irradiance (GHI). This estimation involves two steps: 1) decomposition of GHI into direct and diffuse horizontal components and 2) transposition of direct and diffuse horizontal irradiance (DHI) to POA irradiance. Measured GHI and coincident measured POA irradiance from a variety of climates within the United States were used to evaluate combinations of decomposition and transposition models. A few locations also had DHI measurements, allowing for decoupled analysis of either the decomposition or the transposition models alone. Results suggest that decomposition models had mean bias differences (modeled versus measured) that vary with climate. Transposition model mean bias differences depended more on the model than the location. When only GHI measurements were available and combinations of decomposition and transposition models were considered, the smallest mean bias differences were typically found for combinations which included the Hay/Davies transposition model.

Testing a wavelet-based variability model (WVM) for solar PV power plants

A wavelet variability model (WVM) for simulating photovoltaic (PV) power plant output given a single irradiance point sensor as input is tested at the 48MW Copper Mountain solar PV plant. 4 days with different amounts of variability are chosen for validation of the model. Comparisons of wavelet fluctuation power index (fpi) and power output ramp rates (RRs) between the input point sensor, WVM simulated power output, and actual power output are presenwavelet fluctuation power indexted for the 4 test days. At all timescales, the WVM simulated power output is found to match the variability of the actual power output well, and to be a strong improvement over the input point sensor.

Ota City : characterizing output variability from 553 homes with residential PV systems on a distribution feeder.

This report describes in-depth analysis of photovoltaic (PV) output variability in a high-penetration residential PV installation in the Pal Town neighborhood of Ota City, Japan. Pal Town is a unique test bed of high-penetration PV deployment. A total of 553 homes (approximately 80% of the neighborhood) have grid-connected PV totaling over 2 MW, and all are on a common distribution line. Power output at each house and irradiance at several locations were measured once per second in 2006 and 2007. Analysis of the Ota City data allowed for detailed characterization of distributed PV output variability and a better understanding of how variability scales spatially and temporally. For a highly variable test day, extreme power ramp rates (defined as the 99th percentile) were found to initially decrease with an increase in the number of houses at all timescales, but the reduction became negligible after a certain number of houses. Wavelet analysis resolved the variability reduction due to geographic diversity at various timescales, and the effect of geographic smoothing was found to be much more significant at shorter timescales.

Simulated PV power plant variability: Impact of utility-imposed ramp limitations in Puerto Rico

The variability of solar PV power plants has led to some utilities imposing ramp limitations. For example, the Puerto Rico Electric Power Authority (PREPA) includes a 10% of capacity per minute limit on ramp rates produced by PV power plants in its minimum technical requirements for photovoltaic generation projects. However, it is difficult to determine storage requirements to comply with ramp limitations for plants in the planning or construction phase since the variability of the plant output is not known. In this paper, we use the wavelet variability model (WVM) to upscale irradiance measured in Mayaguez, PR to simulate various sizes of PV power plants. The results show that ramps will often exceed 10%, even for the largest plants (60MW) that benefit the most from in-plant spatial smoothing, meaning significant amounts of storage will be needed to meet the PREPA requirement. The results from Puerto Rico are compared to sites in San Diego and Oahu, Hawaii. Significant differences are seen in the ramp rate distributions of the three locations, demonstrating the importance of performing location-specific simulations.

Chapter 7 – Quantifying and Simulating Solar-Plant Variability Using Irradiance Data

This chapter presents metrics for characterizing and simulating the variability of solar-power plant output. Especially important is the variability reduction, VR, which describes the geographic diversity and is defined as the ratio of variability at a point to the variability of an entire power plant. VR is a function of the size of the plant, the timescale of interest (ramp duration), and meteorological conditions. The wavelet variability model (WVM) was developed to simulate the variability of a solar-power plant using irradiance measurements at a point sensor as input and estimating the VR at each timescale. The WVM is described and validated at the Sempra U.S. Gas & Power Copper Mountain 48 MW photovoltaic plant. As an example application, the WVM is used to simulate the numbers of ramps larger than 10% of capacity per minute at various sizes of PV plants in Puerto Rico. These results are compared to WVM-simulated PV plants in San Diego, California, and Oahu, Hawaii, to show the effect of local climate on ramp rates. The WVM is an ideal tool to create virtual time series of power-plant output in the planning stage that can be used in the design phase to simulate the sizes and operation of ramp-rate mitigation tools such as solar forecasting and energy storage.

High temporal resolution load variability compared to PV variability

While solar variability has often been quantified and its impact to distribution grids simulated, load variability, especially high-frequency (e.g., 1-second) load variability, has been given less attention. The assumption has often been made that high-frequency load variability is much smaller than PV variability, but with little evidence. Here, we compare load and PV variability using 1-second measurements of each. The impact on voltage regulator tap change operations of using low-resolution (e.g., 15- or 30-minute) interpolated load profiles instead of 1- second is quantified. Our results generally support the assumption that distribution feeder aggregate PV variability is much greater than aggregate load variability.

Advanced inverter controls to dispatch distributed PV systems

The research presented in this paper compares five real-time control strategies for the power output of a large number of distributed PV systems in a large distribution feeder circuit. Both real and reactive power controls are considered with the goal of minimizing network over-voltage violations caused by high penetrations of PV generation. The control parameters are adjusted to maximize the effectiveness of each control. The controls are then compared based on their ability to achieve multiple objectives. These objectives include minimizing the total number of voltage violations, minimizing the total amount of PV energy curtailed or reactive power generated, and maximizing the fairness of any control action among all PV systems. The controls are simulated on the OpenDSS platform using time series load and spatially-distributed irradiance data.

PV ramp rate smoothing using energy storage to mitigate increased voltage regulator tapping

A control algorithm is designed to smooth the variability of PV power output using distributed batteries. The tradeoff between smoothing and battery size is shown. It is also demonstrated that large numbers of highly distributed current, voltage, and irradiance sensors can be utilized to control the distributed storage in a more optimal manner. It is also demonstrated that centralized energy storage control for PV ramp rate smoothing requires very fast communication, typically less than a 15-second update rate. Finally, advanced inverter dynamic reactive current is shown to provide voltage variability smoothing, hence reducing the number of voltage regulator tap changes without energy storage.

Multi-Objective Advanced Inverter Controls to Dispatch the Real and Reactive Power of Many Distributed PV Systems.

The research presented in this report compares several real - time control strategies for the power output of a large number of PV distributed throughout a large distribution feeder circuit. Both real and reactive power controls are considered with the goal of minimizing network over - voltage violations caused by large amounts of PV generation. Several control strategies are considered under various assumptions regarding the existence and latency of a communication network. The control parameters are adjusted to maximize the effectiveness of each control. The controls are then compared based on their ability to achieve multiple objectiv es. These objectives include minimizing the total number of voltage violations , minimizing the total amount of PV energy curtailed or reactive power generated, and maximizing the fairness of any control action among all PV systems . The controls are simulat ed on the OpenDSS platform using time series load and spatially - distributed irradiance data.