Abstract

Due to the various uncertainties in multi-energy drying systems, traditional condition control struggles with the rational matching of multiple heat sources and precise temperature regulation. In order to automatically switch energy utilization modes based on current parameters to reduce energy consumption, this paper developed a fuzzy control system for a kelp multi-energy drying device. An automatic switching strategy between different operating modes and the action processes of various actuators were established for matching multiple energy sources. The system hardware and software were designed and installed, including a remote monitoring devices and human-machine interface. Drying experiments of kelp were conducted in solar, solar-heat pump, heat pump and Heat storage-heat pump mode using both the fuzzy control system and the original. The fuzzy control system showed a temperature overshoot of 2.57 %–3.95 %, temperature deviation within ±1.5 °C, which were superior to the original control system. The energy consumption in solar-heat pump mode was 0.398 kW h/kg, only 43 % of the original control system. BP neural networks prediction model of kelp moisture content under different drying modes was established to prevent over-drying. The model can accurately describe the pattern of moisture content variation with RMSE of 2.36–4.27.

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