Design of digital low-carbon system for smart buildings based on PPO algorithm

Currently, the carbon emissions from buildings account for one-third of the total global carbon emissions. Therefore, how to control the carbon emissions of buildings becomes the main direction of current research. The study aims to address the issue of poor energy regulation and carbon emission control effectiveness in the current digital low-carbon system for smart buildings. A smart building digital low-carbon new system based on proximal policy optimization algorithm is proposed in the research. The new system uses a near-end strategy optimization algorithm to control the energy changes of buildings, and adds an actor-critic algorithm to enhance the evaluation and analysis ability of system strategies. The research results indicate that improving the near-end strategy optimization algorithm can reduce carbon emissions by 2354CO2e, while the lowest operating cost of the model is only 35,000 yuan. The new system can effectively control building costs, reducing commercial building thermal energy costs by 1.1w and industrial building electrical energy costs by 17,000 yuan. The highest reliability of the new system is 92.4%, the highest stability is 93.6%, and the shortest response time of the system is 768 ms. The results show that the new system is superior to the existing system in reducing carbon emissions, lowering operating costs, improving system reliability and stability, and shortening response time. This demonstrates the effectiveness and superiority of the new system in the digital low-carbon system of intelligent buildings. Using the novel system can effectively decline the carbon emissions of buildings and improve the control effect on building energy. This has good guiding significance for improving the low-carbon emission control effect of smart buildings.