Solar Energy, Vol.140, 93-108, 2016
Evaluating the benefits of using short-term direct normal irradiance forecasts to operate a concentrated solar thermal plant
Past studies about using direct normal irradiance (DNI) forecasts to operate a concentrated solar thermal (CST) plant have not considered intra-day forecasts. This is a critical research gap because short-term forecasts are recommended for managing variable output from renewable energy generators, including CST plants. This study evaluates the benefits of using 1-h forecasts to decide updated bids for a CST plant after making initial bids from 48-h forecasts. The benefits are represented by the financial value calculated from revenue and reserve generation (RG) payments, and the reliability calculated from the equivalent forced outage rate (EFOR). Simulating a CST plant operating in the Australian National Electricity Market for one year showed that using 1-h forecasts increases financial value by $1.04-1.13 million and reduces EFOR by 20-21% points for a 50 Megawatt (MW). CST plant with 7.5 h of storage, and increases financial value by $0.7-$0.9 million and reduces EFOR by 20-23% points for a 50 MW CST plant without storage. Reduced RG costs contributed towards 76-98% of the financial value increase for both CST plants. A CST plant without storage that uses 1-h forecasts achieves an EFOR of 10-11%, whereas a CST plant with storage that does not use 1h forecasts achieves an EFOR of 21-22%, so using 1-h forecasts may improve reliability more than adding storage to a CST plant without storage. Using 1-h forecasts does not achieve the same total net value as a perfect 48-h forecast, but it achieves close to maximum value per unit electricity generated. Overall, CST plants should use short-term forecasts if permitted under local electricity market regulations because they can achieve higher financial value and reliability. Future studies should use short-term forecasts when allowed by the local electricity market to more accurately demonstrate the value of CST plants. (C) 2016 Elsevier Ltd. All rights reserved.