Forecasting Daily Primary Three-Hour Net Load Ramps in the CAISO System
This work provides a tool for system operators to better manage flexible capacity and maintain supply-demand balance in power systems with high variable energy resource penetration.
This paper addresses the challenge of forecasting daily primary three-hour net load ramps in the CAISO system, which are critical for system operators due to increasing variable energy resources. The authors developed a forecasting methodology using a long short-term memory model, demonstrating its effectiveness through comparative assessments on the CAISO system.
The deepening penetration of variable energy resources creates unprecedented challenges for system operators (SOs). An issue that merits special attention is the precipitous net load ramps, which require SOs to have flexible capacity at their disposal so as to maintain the supply-demand balance at all times. In the judicious procurement and deployment of flexible capacity, a tool that forecasts net load ramps may be of great assistance to SOs. To this end, we propose a methodology to forecast the magnitude and start time of daily primary three-hour net load ramps. We perform an extensive analysis so as to identify the factors that influence net load and draw on the identified factors to develop a forecasting methodology that harnesses the long short-term memory model. We demonstrate the effectiveness of the proposed methodology on the CAISO system using comparative assessments with selected benchmarks based on various evaluation metrics.