Research on the Optimization of Chemical Waste Heat Recovery Device Operation Based on GA-BP Neural Network

Utilizing industrial waste heat as a heat source for centralized heating is a viable measure for energy saving and carbon reduction, which is of great significance for enhancing the social reputation and market competitiveness of enterprises. This paper proposes a study on the operation optimization of chemical waste heat recovery devices based on GA (genetic algorithm)-BP (back propagation) neural network technology: firstly, a heat load forecasting model is established utilizing the BP neural network, which is subsequently optimized through the application of a genetic algorithm; subsequently, the model's accuracy is thoroughly assessed using a meticulously prepared test set of data; finally, an optimization operation plan supported by quantitative data is generated in combination with chemical engineering calculations. The findings of this paper can guide production personnel to make precise adjustments and anticipatory regulation of water supply temperature and flow, provide clean and reliable heating services for the city, improve user experience, reduce carbon emissions, and enhance the market competitiveness of enterprises.

I. Introduction

Global warming is a significant challenge that humanity will face in the future. The latest research results from the IPCC (Intergovernmental Panel on Climate Change) indicate that the Earth's surface temperature is anticipated to escalate by 1.5°C over the course of the next 20 years. (around 2040). To attain the objective of limiting the global temperature rise to no more than 1.5°C above pre-industrial levels by the conclusion of the 21st century, it is necessary to significantly reduce CO2 emissions globally in the next decade ^[1]. China is actively implementing a national strategy to mitigate climate change, setting a goal to "endeavor to attain a peak in carbon emissions by 2030 and accomplish carbon neutrality by 2060." According to calculations by relevant authorities, the thermal power industry must reach its peak in carbon emissions no later than 2034 ^[2]. The thermal power sector is one out of a multitude significant areas of CO2 emissions. For a long time, China's heating energy structure has been dominated by coal-fired boilers, but with the in-depth advancement of energy transformation in recent years, it has also shown a trend of diversified development.