Next Article in Journal
Hourly Solar Radiation Forecasting Using a Volterra-Least Squares Support Vector Machine Model Combined with Signal Decomposition
Previous Article in Journal
ACT-R Cognitive Model Based Trajectory Planning Method Study for Electric Vehicle’s Active Obstacle Avoidance System
Open AccessArticle

Energy Consumption Prediction of a Greenhouse and Optimization of Daily Average Temperature

by Yongtao Shen, Ruihua Wei and Lihong Xu *
College of Electronics and Information Engineering, Tongji University, Shanghai 201804, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work and should be considered co-first authors.
Energies 2018, 11(1), 65; https://doi.org/10.3390/en11010065
Received: 4 December 2017 / Revised: 21 December 2017 / Accepted: 22 December 2017 / Published: 1 January 2018
Greenhouses are high energy-consuming and anti-seasonal production facilities. In some cases, energy consumption in greenhouses accounts for 50% of the cost of greenhouse production. The high energy consumption has become a major factor hindering the development of greenhouses. In order to improve the energy efficiency of the greenhouse, it is important to predict its energy consumption. In this study, the energy consumption mathematical model of a Venlo greenhouse is established based on the principle of energy conservation. Three optimization algorithms are used to identify the parameters which are difficult to determine in the energy consumption model. In order to examine the accuracy of the model, some verifications are made. The goal of achieving high yield, high quality and high efficiency production is a problem in the study of greenhouse environment control. Combining the prediction model of greenhouse energy consumption with the relatively accurate weather forecast data for the next week, the energy consumption of greenhouse under different weather conditions is predicted. Taking the minimum energy consumption as the objective function, the indoor daily average temperatures of 7 days are optimized to provide the theoretical reference for the decision-making of heating in the greenhouse. The results show that the optimized average daily temperatures save 9% of the energy cost during a cold wave. View Full-Text
Keywords: greenhouse; energy; model; prediction; optimization algorithms; optimizing average temperature greenhouse; energy; model; prediction; optimization algorithms; optimizing average temperature
Show Figures

Figure 1

MDPI and ACS Style

Shen, Y.; Wei, R.; Xu, L. Energy Consumption Prediction of a Greenhouse and Optimization of Daily Average Temperature. Energies 2018, 11, 65.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop