The invention discloses a solar low-heat-value heat storage
heating system. According to the invention, through the AI prediction sub-module of the intelligent
heat energy allocation module, the matching precision of
energy supply and demand is significantly improved. The
system can collect various data such as meteorological parameters, historical loads and heat storage states in real time,
heat supply requirements, solar input fluctuation and heat
storage efficiency are accurately pre-judged through
feature extraction and multi-
model prediction, and prediction results are continuously corrected through error calibration. The
system can know how much heat is needed and how much
solar energy can be provided in advance, so that energy flow in heat collection, heat storage and
heat supply links is more reasonably allocated, the situation of heat waste or insufficient supply is reduced, the self-
adaptive learning sub-module effectively strengthens the long-term operation capacity of the
system, the system achieves self-learning, and the energy
utilization rate of the system is improved. The operation stability is kept, the energy efficiency can be continuously optimized along with the external environment, more energy is saved after long-term use, and more convenience and rapidness are achieved.