With the rapid development of economy and society, many problems such as environmental pollution and shortage of fossil energy have become increasingly prominent. It is urgent to develop and vigorously utilize renewable and clean energy such as solar energy. The purpose of this work is to study the system integration and biomass thermochemistry based on neural network algorithm. The proposed methanol and electricity cogeneration system is used to complete the step-by-step and orderly conversion of fuel chemical energy, and analyze the thermal characteristics of the cogeneration. Analysis and discussion are made for the academic characteristics and economic performance under different operating modes. The performance evaluation results of the solar-biomass gasification polygeneration system show that the thermal energy loss or exergy loss of the system is 63885kW and 15187.9kW respectively, of which the solar heat collection part has the largest loss, accounting for 43.2% of the total heat loss of the system and 43.2%. The total exergy loss accounts for 48.6%. Based on this, the collaborative optimization of the operating parameters of these devices will greatly promote the effective utilization of system energy.

Natalia Markova. System Integration and Method for High-efficiency Utilization of Solar Energy and Biomass Energy Thermochemically Based on Neural Network Algorithm. Academic Journal of Energy (2022), Vol. 3, Issue 4: 42-50. https://doi.org/10.38007/RE.2022.030405.

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