A Regional Power Grid Cooling Load Power Prediction Method Based on Improved Gated Cycle Units

The demand for efficient cooling in regional power grids is ever-increasing, necessitating accurate cooling load power predictions for optimal grid management. This paper presents a novel approach to address this challenge by incorporating an adaptive plant cell swarm algorithm to optimize the parameters of an improved gated loop unit model. Our research introduces an enhanced gated cycle unit model that considers the adaptive plant cell swarm algorithm's output as an integral component. This model seamlessly integrates meteorological variables, historical cooling load data, and real-time gated cycle unit data, offering improved accuracy and reliability in cooling load power predictions.