A Methodology for Quantifying Reliability Benefits From Improved Solar Power Forecasting in Multi-Timescale Power System Operations

Solar power forecasting improvements are mainly 1 evaluated by statistical and economic metrics, and the practi2 cal reliability benefits of these forecasting enhancements have 3 not yet been well quantified. This paper aims to quantify relia4 bility benefits from solar power forecasting improvements. To 5 systematically analyze the relationship between solar power 6 forecasting improvements and reliability performance in power 7 system operations, an expected synthetic reliability (ESR) metric 8 is proposed to integrate state-of-the-art independent reliability 9 metrics. The absolute value and standard deviation of area con10 trol errors (ACEs), and the North American Electric Reliability 11 Corporation Control Performance Standard 2 (CPS2) score are 12 calculated through the multi-timescale scheduling simulation, 13 including the day-ahead unit commitment, real-time unit commit14 ment, real-time economic dispatch, automatic generation control 15 sub-models. The absolute ACE in energy, CPS2 violations, CPS2 16 score, and standard deviation of the raw ACE are all calculated 17 and combined as the ESR metric. Numerical simulations show 18 that the reliability benefits of multi-timescale power system oper19 ations are significantly increased due to the improved solar power 20 forecasts. 21