Integrated Intelligent Energy ›› 2023, Vol. 45 ›› Issue (12): 29-35.doi: 10.3969/j.issn.2097-0706.2023.12.004

• Intelligent & Clean Heating • Previous Articles     Next Articles

Intelligent scheduling and control of a geothermal-gas complementary heating system based on model prediction

ZHONG Wei1,2(), BO Qiming1, CAI Chenyu1, LU Shimeng1, LI Manjie2,3   

  1. 1. College of Energy Engineering, Zhejiang University,Hangzhou 310058,China
    2. Shanghai Institute for Advanced Study of Zhejiang University,Shanghai 200135,China
    3. Changzhou Engipower Technology Company Limited, Changzhou 213022,China
  • Received:2023-04-14 Revised:2023-05-24 Online:2023-06-12 Published:2023-06-12
  • Supported by:
    National Key R&D Program of China(2019YFE0126000)

Abstract:

In recent years, geothermal heating technology has been doing applied to large-scale central heating for cities in northern China. However, due to the uncertainty and volatility of geothermal heating technology, coordinating and optimizing the outputs of the geothermal heat sources and fossil energy sources is the key to the safe, reliable, efficient and low-carbon operation of the whole heating system. In view of complexity of the heating system for Xiong'an New District geothermal-gas complementary heating system, an intelligent scheduling and control method based on model prediction for this heating system is proposed. Prediction on heat load is made based on the multi-layer perceptron (MLP), and geothermal heating capacity prediction model is established, in order to provide complementary scheduling and control strategy for a geothermal-gas heating system in different heating stages. The trial operation of the system shows that the scheduling and control method can effectively guarantee the stable operation of the complex heating system with a users' heating load fluctuation under 15%. The strategy realizes the efficient complementary operation between geothermal sources and gas-fired boilers, and improves the flexibility and economy of the heating system.

Key words: geothermal heating, geothermal-gas complementarity, low-carbon heating, multi-layer perceptron, load forecasting, intelligent heating, "dual carbon" target

CLC Number: