Modeling Energy LED Light Consumption Based on an Artificial Intelligent Method Applied to Closed Plant Production System

Ernesto Olvera-Gonzalez,Martín Montes Rivera,Eduardo Flores-Gallegos,Nivia Escalante-Garcia

doi:10.3390/app11062735

Abstract

Artificial lighting is a key factor in Closed Production Plant Systems (CPPS). A significant light-emitting diode (LED) technology attribute is the emission of different wavelengths, called light recipes. Light recipes are typically configured in continuous mode, but can also be configured in pulsed mode to save energy. We propose two nonlinear models, i.e., genetic programing (GP) and feedforward artificial neural networks (FNNs) to predict energy consumption in CPPS. The generated models use the following input variables: intensity, red light component, blue light component, green light component, and white light component; and the following operation modes: continuous and pulsed light including pulsed frequency, and duty cycle as well energy consumption as output. A Spearman’s correlation was applied to generate a model with only representative inputs. Two datasets were applied. The first (Test 1), with 5700 samples with similar input ranges, was used to train and evaluate, while the second (Test 2), included 160 total datapoints in different input ranges. The metrics that allowed a quantitative evaluation of the model’s performance were MAPE, MSE, MAE, and SEE. Our implemented models achieved an accuracy of 96.1% for the GP model and 98.99% for the FNNs model. The models used in this proposal can be applied or programmed as part of the monitoring system for CPPS which prioritize energy efficiency. The nonlinear models provide a further analysis for energy savings due to the light recipe and operation light mode, i.e., pulsed and continuous on artificial LED lighting systems.

Highlights

Introduction iationsClosed Plant Production Systems (CPPS) consist of a wide variety of growing methods, like vertical farms, plant factories, greenhouses, growth chambers, tissue culture rooms, phytotrons, and high tunnels, among others [1,2,3,4,5,6,7,8,9]
Energy consumption, we propose two nonlinear models based on artificial intelligence that support modeling of the energy requirements of the light-emitting diode (LED) lighting
The irradiation is emitted by ultrabright LEDs, with features for control parameters such as different wavelengths in continuous and pulsed light, frequency and duty cycles

Summary

Introduction

Introduction iationsClosed Plant Production Systems (CPPS) consist of a wide variety of growing methods, like vertical farms, plant factories, greenhouses, growth chambers, tissue culture rooms, phytotrons, and high tunnels, among others [1,2,3,4,5,6,7,8,9]. The controlled agricultural environments approach allows producers to establish ideal conditions for given crops (e.g., in terms of the quantity and quality of light, humidity, temperature, carbon dioxide, among others). Such an approach yields higher crop production and quality, and means that any variety of plant can be planted at any time of the year. The literature has shown that light-emitting diodes (LEDs) are an energy efficient substitute for other types of lamps (filament lamps and gas discharge lamps with mercury and sodium), and enhance plant growth. The radiation emitted by LEDs has various advantages like rapid response time, longer lifetime, controllability, Licensee MDPI, Basel, Switzerland

Methods

Results

Conclusion