Intelligent Dispatching of Electricity Consumption Information Collection in the Electricity Market Environment

Factors affecting data collection are varied, with the continuous innovation of technology, management measures continue to improve, electric power data collection is reliably guaranteed, the success rate of data collection will play a water to the effectiveness of the improvement. This article studies how to optimize the collection of electricity consumption information through intelligent scheduling systems in the electricity market environment. A collection and scheduling algorithm based on Deep Reinforcement Learning (DRL) is proposed to improve the overall efficiency and reliability of the power system by analyzing the demand and supply fluctuations in the electricity market. In the experiment, a comprehensive evaluation of the intelligent power collection and scheduling system based on DRL was conducted through three experiments, and the accuracy of the collection method based on DRL algorithm was 0.84. In the real-time response speed evaluation experiment, the average response time of the scheduling system based on DRL algorithm was 0.83 seconds. In the final experiment, the intelligent power collection system based on DRL algorithm achieved a power resource utilization efficiency of 0.87. In the above data conclusions, the intelligent power collection system based on DRL algorithm has significant advantages in accuracy, real-time performance, and efficiency improvement.