CAISO Issue Paper

Integration of Solar Energy into the Participating Intermittent Resource Program (PIRP)

DRAFT August 10th 2007

Revised February 8, 2008

Revised April 17, 2008

Prepared by

Jim Blatchford

Sr. Policy Representative

CAISO

John Zack

AWS True Wind, LLC.

Integration of Solar Into the PIRP

ISSUE PAPER, Revision 1, February 6, 2008

Introduction

The California ISO (CAISO) established the Participating Intermittent Resource Program (PIRP) to ensure the successful integration of Intermittent Resources into the market and operations of the California grid. The CAISO tariff's original focus was on wind resources but also took into account other intermittent resources including solar energy production. The CAISO tariff states:

Eligible Intermittent Resources other than wind projects that wish to become Participating Intermittent Resources will be required to provide data of comparable relevance to estimating Energy generation. Standards will be developed as such projects are identified and will be posted on the ISO Home Page.[1]

Solar energy production is more predictable than wind energy production, but it does have distinct components of intermittency. For instance, energy production is obviously non-existent during the twilight to dark periods, but it will also be reduced due to cloud cover, dust storms or even high winds that may affect the focus of the solar beam into thermal troughs. Because of its intermittency, solar energy production is included in the California Renewable Portfolio Standard (RPS) and the PIRP.

The purpose of this paper is to establish guidelines for the integration of solar energy production (concentrated and photovoltaic) into the PIRP.

Eligibility

In order for a solar power producer to participate in the solar component of PIRP, they must meet ALL criteria set forth in the Appendix Q EIRP of the CAISO Conformed Simplified and Reorganized Tariff dated Apr 6, 2007, except for those paragraphs directly related to wind production. To participate in the PIRP, solar energy production cannot be augmented by fossil fuel generation devices. Although the California Renewable Portfolio Standard[2]allows for a de minimis amount of fossil fuels to augment the production, because augmentation of the hourly energy production for a solar Participating Intermittent Resource (PIR) could unfairly advantage the other PIRs[3][4].

Physical Site Data

A solar farm must provide the CAISO with an accurate footprint of the site before a forecast can be produced. The footprint must include (1) the location (latitude and longitude coordinates), and elevation of meteorological collection devices, (2) the location, elevation and orientation angles of arrays or concentrators, (3) the generation capacity of the facility and (4) the type of solar generation technology employed at the facility. For redundancy purpose, each solar farm must provide a minimum of 2 meteorological stations with an independent power source.

Meteorological and Production Data

As outlined in the PIRP, meteorological data must be provided to the CAISO via the Data Processing Gateway (DPG) for accurate power generation forecasting. Global irradiance (GHI) is composed of direct and diffuse components. For most flat plate energy collection via PV, much of the output variability can be explained by global irradiance alone (>90% in the case of fixed collector and >80% for trackers). For solar thermal collection involving concentration and tracking, the direct component must be known and global alone may not be enough to explain the variability.

Fortunately there are techniques and models to generate direct irradiance from global using the time series of the latter. In fact, the recently released high-resolution satellite-derived direct normal irradiance (DNI) data from NREL’s National Solar Resource Data Base was generated using such a technique (George et al. 2007[5]; Perez et al. 2002[6]; Perez et al. 1992[7]). Therefore, on site GHI measurements could be used to extrapolate DNI with an acceptable degree of accuracy. In addition, having tilted irradiance measurements available could be used as needed as a fine-tuning step for DNI estimation using an anisotropic diffuse model such as described by Perez et al. 1990[8].

The second most important factor in the performance of the solar array is the temperature. For a photovoltaic (PV) array, it is the back panel temperature that is particularly important. In general, temperature accounts for slightly less than 10% of the variability of output of the solar array. For crystalline silicon that constitute the majority of PV installations, for every 20 C ° change in temperature the power output changes by approximately 10% [9] (the higher the temperature the lower power output). The exact sensitivity to temperature is dependent on the type of solar technology. In general, thin film technologies are less sensitive to operating temperature.

The third most important factor is the wind, but it accounts for less than 1% of the variability of output from a solar array. The primary impact of the wind is the ventilation factor of removing heat away from the array.

Considering the elements and factors that influence the performance of the array, the required data from the production site should include:

  • Real Time MW production
  • Global horizontal irradiance in watts/ m2, which accounts for ~90% of variability of flat plate systems variability. But global horizontal irradiance typically only accounts for 40-50% of a concentrating system's variability unless the global horizontal irradiance is converted into direct normal irradiance through a model that accounts for the strong non-linear relationship between the two. If such a model is used the direct normal irradiance can account for 90% of the system's performance variability.[10]
  • Plane of array irradiance recommended for flat plat technologies
  • Direct normal and diffuse irradiance measurements should not be NOT REQUIREDfor flat-plate PV plants
  • Direct irradiance accounts for >95% of concentrating system’s variability.
  • Diffuse irradiance, the difference between the two above components, is often used for quality control purposes when both quantities are measured.[11]
  • Ambient temperature at the array height in ◦C accounts for slightly less than 10% of the variability – ambient temperature is used to estimate panel temperature, unless this is directly measured on the back of the panel
  • Wind speed and direction at the array height in m/s and degrees accounts for less than 1% of the variability

Direct and diffuse irradiance can be modeled from global irradiance with a degree of accuracy that is sufficient for non-concentrating applications. The plane of array irradiance recommended for flat plat technologies can be obtained by the use of a calibrated reference cell or a pyranometer. For concentrating solar technologies, it is necessary to measure direct irradiance, either directly with a pyrheliometer, or indirectly using a rotating shadowband pyranometer. For all above measurements, calibration accuracy is an important concern.

The ambient and back panel temperature will require two separate temperature probes. In addition the ambient temperature probe will require a probe shield to protect it from the direct solar radiation. The wind speed and direction requires a mounting mast and standard cup anemometer and wind vane device.

There will be other miscellaneous pieces of equipment required such as masts mounting hardware and surge protectors. Table 1 gives the devices needed along with the units and costs associated with the installation of the equipment for the flat plate technologies. Table 2 gives the devices, units and costs associated with the installation of the equipment for the concentrating technologies.

It should be noted that all cost estimates are based on prices that are current as of the date of this paper but are, of course, subject to change and the cost of communication equipment is not included in these estimates.

Table 1. Equipment needed and typical associated costs to make required measurements for Flat Plate Technologies.

Element / Device (s)
Needed / Units / Var / Equip Cost / Install
Costs
Plane-of-ArrayIrradiance / Calibrated Reference cell orPyranometer / W/m 2 / ~90% / $300 -1,000 / $300-1,500
Global HorizontalIrradiance / Pyranometer / W/m 2 / ~90% / $300 -1,000 / $300-1,500
Ambient temperature at the array height / Temperature probe & shield for ambient temp. / ◦C / ~10% / $225 - $300 / $100 - $150
Back panel temperature for PV type arrays / Temperature probe for back panel temperature / ◦C / ~1% / $90- $120 / $100 - $150
Wind speed and direction at the array height / Cup anemometer, wind vane and wind mast / m/s deg / ~1% / $460 - $500 / $460 - $500
Other Miscellaneous Equipment / Masts, mounting hardware, surge protectors etc. / N/A / N/A / $1050 - $1200 / $1000 - $1100

Table 2. Equipment needed and typical associated costs to make required measurements for Concentrating Technologies.

Element / Device (s)
Needed / Units / Var / Equip Cost / Install
Costs
Option 1: Direct and global horizontal irradiance / Full station with a Normal Incidence Pryheliometer(NIP) for direct irradianceand tracking disk for global and diffuse. . / W/m 2 / ~90% / $26-30,000 / *$14-16,000
Option 2: Direct and global horizontal irradiance / Rotating shadow band and pyranometer / W/m 2 / ~90% / $11-13,000 / *$5 - 7,000
Ambient temperature at the array height / temperature probe and shield for ambient temperature / ◦C / ~10% / $225 - $300 / $100 - $150
Back panel temperature for PV type arrays / temperature probe for back panel temperature / ◦C / ~1% / $90- $120 / $100 - $150
Wind speed and direction at the array height / Cup anemometer, wind vane and wind mast / m/s deg / ~1% / $460 - $500 / $460 - $500
Other Miscellaneous Equipment / Masts, mounting hardware, surge protectors etc. / N/A / N/A / $1050 - $1200 / $1000 - $1100

* Option 1 and Option 2 include initial 6 months costs.

Production and meteorological data will be collected for a minimum of 60 days before the farm is considered in the PIRP. This data needs to be collected in advance in order to train the forecast models (e.g. artificial neural networks) responsible for producing the power production (MW) forecast for each site. The forecast service provider requires high quality, continuously streaming data to provide an accurate forecast.

Anticipated Forecast Error

Studies have shown that the accuracy of a solar power prediction system is highly depended on the types of local weather conditions and the time of day . [12] In general such solar irradiance prediction systems are quite accurate with an MAE of 3- 4 % of the solar irradiance for clear sky or consistent cloud cover that persist for more than an hour. However, the MAE increases to as high as 15% of actual irradiance for situations when small scale convective cloud elements develop that have life cycles on the order of 15 - 20 minutes. This type of condition is most likely to occur during mid to late afternoon during the warm season.

Outage Data

If the solar farm is reducing its production from its stated maximum production value (pMax), it is the responsibility of the solar farm (or its Scheduling Coordinator) to provide the CAISO with plant outage information via the CAISOs Scheduling Logging for the ISO of California (SLIC) reporting system. This data is needed to ensure the MW forecast does not exceed the plants derated capability.

Explanation of Terms

Global solar irradiance isa measure of the rate of total incoming solar energy (both direct and diffuse) on a horizontal plane at the Earth's surface.

Direct (normal) solar irradiance is a measure of the rate of solar energy arriving at the Earth's surface from the Sun's direct beam, on a plane perpendicular to the beam.

Diffuse solar irradiance is a measure of the rate of solar energy arriving at the Earth's surface that is the result of scattering of the Sun's beam due to the various atmospheric constituents.

Satellite-derived measurements of solar irradiance (both global and direct solar irradiance) are possible through the use of computer models. A model of solar irradiance uses radiation measurements from the visible-radiation channel and visible cloud imagery from geostationary meteorological satellites to estimate ground level global and direct irradiation. Diffuse irradiance can be calculated by using the relationship: diffuse = global – direct. For the current generation of geostationary meteorological satellites, the ground resolution is about one kilometer for the visible-radiation sensors. Studies have concluded that satellite-derived measurements of solar irradiance are more accurate to use than ground based observation if the ground based observing site is more than 25 km away from the site of interest.

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[1]Conformed Simplified and Reorganized Tariff as of April 6, 2007 Appendix Q

[2]Ca RPS defines de minimus as 2% for new facilities and 5% for existing facilities measured on an annual basis of electricity production.

[3] “SCE would support the incorporation of solar into PIRP as long as the CEC
requirements were enforced.”

[4] “While there may be reasons for the development of augmented solar facilitates, PG&E does not support the extension of the PIRP benefits to these facilities during periods of augmentation.”

[5] George R., S. Wilcox, M. Anderberg and R. Perez, (2007): National Solar Radiation Database (NSRDB) - 10 Km Gridded Hourly Solar Database. Proc. ASES National Conference, Cleveland, OH

[6] Perez R., P. Ineichen, K. Moore, M. Kmiecik, C. Chain, R. George and F. Vignola, (2002): A New Operational Satellite-to-Irradiance Model. Solar Energy 73, 5, pp. 307-317

[7] Perez, R., P. Ineichen, E. Maxwell, R. Seals and A. Zelenka, (1992): Dynamic Global-to-Direct Irradiance Conversion Models. ASHRAE Transactions-Research Series, pp. 354-369

[8] Perez, R., P. Ineichen, R. Seals, J. Michalsky and R. Stewart, (1990): Modeling Daylight Availability and Irradiance Components from Direct and Global Irradiance. Solar Energy Vol. 44, pp. 271-289

[9] E.g., Menicucci D.F., and J.P. Fernandez, (1988): User's Manual for PVFORM. Report # SAND85-0376-UC-276, Sandia Natl. Labs, Albuquerque, NM

[10]

[11]

[12]