Development and testing of a new day-ahead solar power forecasting system

Transcription

1 Development and testing of a new day-ahead solar power forecasting system Vincent E. Larson, Ryan P. Senkbeil, and Brandon J. Nielsen Aerisun LLC WREF 2012

2 Motivation Day-ahead forecasts of utility-scale solar photovoltaic power would benefit scheduling of electrical power generation.

3 Outline 1. Description of forecast algorithm 2. Examples of hindcasts at various sites 3. Understanding errors in solar forecasts

4 Forecasts of PV power have two main parts: 1. Forecasts of solar irradiance (GHI) 2. Calculation of power generated, given irradiance.

5 Part 1: Forecasts of solar irradiance. We start with existing numerical weather prediction models 1. North American Mesoscale (NAM) model 2. Global Forecast System (GFS) model These forecasts are freely available. Aerisun constructs a two-member ensemble forecast composed of NAM and GFS forecasts.

6 Part 2: Calculation of PV power generation We use the methodology of De Soto et al. (2006). It uses an equivalent circuit to model a solar cell.

7 Advantages of the De Soto 5- parameter model 1. It can model a wide variety of solar cell types, including monocrystalline silicon, polycrystalline silicon, and thin-film. 2. The needed parameters are usually publicly available from manufacturer's specifications. 3. It accounts for dependence of solar cell efficiency on temperature.

8 Outline 1. Description of forecast algorithm 2. Examples of hindcasts at various sites 3. Understanding errors in solar forecasts

9 Aerisun provides free beta forecasts for several utility-scale PV plants The specifications of the PV panels are based on publicly available information. The forecasts are run nightly at Three examples are now shown.

10 Silicon PV: Nellis Air Force Base Nellis Air Force Base in Nevada uses SunPower Si modules and SunPower T20 single-axis trackers. Its capacity is 14 MW.

11 Thin film PV: Copper Mountain This 48-MW solar plant is located in Nevada and owned by Sempra. It uses thin-film CdTe solar modules from First Solar.

12 Concentrating PV: University of Arizona s Science and Technology Park (UASTP) UASTP uses concentrating PV with dual-axis trackers from Amonix and has a capacity of 2 MW (AC).

13 How accurate are NAM and GFS forecasts of solar irradiance? SURFRAD irradiance obs from Boulder The observed irradiance (light blue) exhibits extreme intermittency.

14 Outline 1. Description of forecast algorithm 2. Examples of hindcasts at various sites 3. Understanding errors in solar forecasts

15 How can we improve the forecasts of irradiance? It is difficult to diagnose problems with the models without data on cloud-related variables. To obtain this information, we examine observations from the Atmospheric Radiation Measurement (ARM) site in Oklahoma.

16 Forecasts of irradiance (GHI) from NAM are scattered as compared to obs

17 Forecasts from GFS are scattered too

18 On clear days, GFS underpredicts irradiance (Obs) Thus, bias removal for the clear days may help.

19 On cloudy days, the errors in irradiance are large and of either sign (Obs) Simple bias removal is unlikely to help much on cloudy days if there are large errors of either sign.

20 On cloudy days, the errors in irradiance are related to errors in liquid water path (Obs) The errors are not simply errors in timing.

21 GFS and NAM errors show imperfect correlation on cloudy days The lack of correlation suggests that ensemble averaging may help.

22 Conclusions Aerisun has created an ensemble forecasting system for PV power. It runs every day for several sites. Hindcasts are freely available at GFS has biases for clear days; errors are large and of either sign for cloudy days. Diagnosing the source of model errors will require investigating fields other than irradiance.

23 Thanks for your time!

24 Extra slide

25 The equivalent circuit depends on five unknown parameters The unknowns are the light current I L, the diode reverse saturation current I O, the series resistance R S, the shunt resistance R SH, and a parameter a. These are solved using short circuit current, open-circuit voltage, the current and voltage at maximum power, and temperature coefficient of open-circuit voltage.