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ARS Home » Plains Area » Bushland, Texas » Conservation and Production Research Laboratory » Livestock Nutrient Management Research » Research » Publications at this Location » Publication #287453

Title: Adding concentrated solar power plants to wind farms to achieve a good utility electrical load match

Author
item Vick, Brian
item MOSS, TIM - Sandia National Laboratory

Submitted to: Solar Energy
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/20/2012
Publication Date: 6/1/2013
Citation: Vick, B.D., Moss, T.A. 2013. Adding concentrated solar power plants to wind farms to achieve a good utility electrical load match. Solar Energy. 92:298-312.

Interpretive Summary: Texas is the number one state in the United States in wind generated electricity. The wind farms in the Texas Panhandle sell their electricity to the utilities for only 2.5 to 3.5 cents per kilowatt-hour. The main reason for the low price of this wind generated electricity is due to installing the wind turbines on towers 200 to 300 ft tall. At these heights the wind turbine blade rotors are exposed to much higher wind speeds than at heights below 80 feet. Above 200 ft the highest wind speeds occur mainly in the early hours of the morning and the lowest wind speeds occur in the afternoon. This trend in wind speed above 200 feet is opposite that of the wind speed trend below 80 ft. Due to taller tower heights the wind farm generated electricity is greatest in the early morning hours and least in the afternoon. This means the wind farm generated electricity is almost the exact opposite of the utility electrical load. However, the wind generated electricity is a good match to the utility electrical load in the evening. Scientists at USDA-ARS-CPRL (Bushland, TX) and (SNL) Sandia National Laboratory, Albuquerque, NM) analyzed the addition of a solar power plant to a wind farm in the Texas Panhandle. The objective of this study was to determine if the renewable energy match to the utility electrical load could be improved. A computer program was written which used wind speed and atmospheric data in the Texas Panhandle and a power curve of a 1 MW wind turbine to simulate the wind farm output. The solar power plant output was simulated using solar radiation and atmospheric data in the Texas Panhandle as input data to two models (DIRINT and SAM). The DIRINT model was used to predict solar direct normal irradiance (DNI). SAM used DNI and air temperature to simulate a concentrating solar power (CSP) plant with and without 6 hours of thermal storage. Storing thermal energy with the CSP plant helped if the solar or wind energy decreased during the day. It was found that adding a CSP plant (with thermal storage) at half the wind farm rating resulted in a good annual match to the utility electrical load. It was also found that on hot days in the summer (highest utility electrical load) the CSP plant with storage operated at about100% of rated from 8 AM to 11 PM. Except for the evening, the wind farm electrical output on these hot days during this time period was usually low. The cost of energy (COE) of the CSP plant is currently about 3 times greater than the COE of the wind farm. Therefore, it is more economical if the CSP plant has a lower rating than the wind farm. Although the COE of the hybrid wind farm/CSP plant is greater than the wind farm only COE, the electricity generated is more valuable to the utility. Also, the COE of a CSP plant with storage is actually less than that of a CSP plant without storage. This analysis showed that the problem of the mismatch of the wind farm generated electricity with the utility electrical loading could be solved by adding a CSP plant with storage. Replacing finite fossil fuels with renewable energy will help conserve our natural gas and coal reserves, and also decrease the emissions from burning less fossil fuel.

Technical Abstract: Texas has the greatest installed wind turbine capacity of any state in the United States, the percentage of wind capacity approaches 10% of the utilities capacity (in 2010 the total wind generated capacity in Texas was 8%). It is becomimg increasingly difficult for the utility to balance the electrical load, due to the mismatch between the wind farm generated electricity and the utility electrical loading. Wind farm output was shown to be diurnally and seasonally mismatched with the utility electrical loading in the Texas Panhandle (e.g. Texas Panhandle has the highest wind energy resource in Texas). In addition, the wind farm output in the Texas Panhandle does not normally contribute significantly at the peak hourly electrical load, and the peak hourly electrical load is a major deciding factor for a utility to add new power plants. Various ratios of wind farm output to concentrating solar power (CSP) parabolic trough plant output (with and without 6 hours of solar thermal storage) were calculated for the Texas Panhandle. This information was compared to the utility electrical loading on an annual, monthly, and hourly basis (each renewable energy system was analyzed at a 100 MW rating). On an annual basis, a 67 MW wind farm, combined with a 33 MW CSP plant with 6 hours of solar thermal storage, was approximately the best match to the utility electrical loading. Typically for each month, the wind farm did not match the utility electrical loading except in the evening while the CSP plant (without storage) matched the utility electrical loading with the exception of in the evening. For the peak utility electrical loading months (July and August), and the days with the peak electrical loadings during those months, the 100 MW CSP plant with 6 hours storage performed best in terms of supporting the utility electrical load (e.g. no wind farm). For the Texas Panhandle the cost of a hybrid wind farm/CSP plant is higher than a wind farm only system, but the benefits of adding solar may justify the additional cost. Although the Texas Panhandle was the only location analyzed for combining CSP plants with wind farms, the analysis described in this paper can be used for other regions, states, or countries.