Multi-environment perception driven crop power utilization coordinated regulation and control system under photovoltaic panel

The photovoltaic power supply and crop power consumption coordination control system driven by multi-environment perception utilizes a dual-modal algorithm of improved DDPG and lightweight CNN to solve the problem that existing technologies cannot adapt to different scenarios and emergency responses, and achieves precise matching of photovoltaic power supply and crop power consumption and system stability.

CN122052183APending Publication Date: 2026-05-15JINJIANG ENERGY DEVELOPMENT (YONGREN) CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
JINJIANG ENERGY DEVELOPMENT (YONGREN) CO LTD
Filing Date
2026-02-05
Publication Date
2026-05-15

AI Technical Summary

Technical Problem

Existing photovoltaic power generation control technology for crops cannot adapt to different scenarios under normal conditions, cannot respond to photovoltaic array failures in a timely manner, and lacks an algorithm parameter calibration mechanism for equipment operation feedback, resulting in decreased control accuracy and poor supply and demand balance.

Method used

A photovoltaic power supply coordination and control system for crops under photovoltaic panels, driven by multi-environmental perception, collects data in real time through multiple environmental perception units. It combines an improved deep deterministic strategy gradient (DDPG) and a lightweight convolutional neural network (CNN) dual-modal control algorithm to dynamically adjust weight coefficients and photovoltaic array parameters. In emergency control, the lightweight CNN is invoked to generate partition control instructions, and the algorithm parameters are calibrated in real time by receiving feedback data from the equipment.

Benefits of technology

It enables precise adaptation to the power demand of crops at different growth stages and under diffused light conditions under normal conditions, timely response to photovoltaic array failures, avoids the problem of indiscriminate regulation between faulty and non-faulty areas, and ensures the long-term stability and regulation accuracy of the system.

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Abstract

The invention relates to the technical field of photovoltaic agriculture, in particular to a multi-environment perception driven crop power utilization coordinated regulation and control system under a photovoltaic panel. Comprising a multi-environment sensing unit; a crop electricity demand association unit; and the power utilization regulation and control execution unit adopts a dual-mode regulation and control algorithm of an improved depth deterministic strategy gradient DDPG + a lightweight convolutional neural network CNN. Through a bimodal regulation and control algorithm, in a normal state, a photosynthetic efficiency weight is adjusted according to a crop growth stage, the weight is additionally adjusted and increased after a scattered light scene is judged in combination with photovoltaic array parameters, and the power utilization requirements of different crop growth stages and the scattered light scene are met; the light adaptation critical value is adjusted according to the current difference of the photovoltaic string in emergency, and when the illumination change exceeds the critical value, the lightweight CNN is called to fuse the fault position and the crop partition to generate a partition instruction, the light supplementing intensity of the fault area is improved, the irrigation delay is compressed, the fault and the illumination sudden change are responded in time, and accurate matching of photovoltaic power supply and crop power utilization is achieved.
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