Managing energy-water-carbon-food nexus for cleaner agricultural greenhouse production: A control system approach

被引:14
作者
Ren, Zhiling [1 ]
Dong, Yun [1 ]
Lin, Dong [1 ,2 ]
Zhang, Lijun [3 ]
Fan, Yuling [4 ]
Xia, Xiaohua [2 ]
机构
[1] Liaoning Tech Univ, Fac Elect & Control Engn, Huludao 125100, Peoples R China
[2] Univ Pretoria, Dept Elect Elect & Comp Engn, ZA-0002 Pretoria, South Africa
[3] Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Wuhan 430074, Peoples R China
[4] Huazhong Agr Univ, Coll Informat, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
Greenhouse; Energy-water-carbon-food nexus; Carbon emissions; Social cost of carbon; Sensitivity analysis; PREDICTIVE CONTROL; CLIMATE; COST; OPTIMIZATION; STRATEGIES; ENRICHMENT; DIOXIDE; MODEL;
D O I
10.1016/j.scitotenv.2022.157756
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Poverty, food insecurity and climate change arc global issues facing humanity, threatening social, economic and environmental sustainability. Greenhouse cultivation provides a potential solution to these challenges. l lowever, some greenhouses operate inefficiently and need to be optimized for more economical and cleaner crop production. In this paper, an economic model predictive control (EMPC) method for a greenhouse is proposed. The goal is to manage the energy-water-carbon-food nexus for cleaner production and sustainable development. First, an optimization model that minimizes the greenhouse's operating costs, including costs associated with greenhouse heating/cooling, ventilation, irrigation, carbon dioxide (CO2) supply and carbon emissions taking into account both the CO2 equivalent (CO2-eq) emissions caused by electrical energy consumption and the negative emissions caused by crop photosynthesis, is developed and solved. Then, a sensitivity analysis is carried out to study the impact of electricity price, supplied CO2 price and social cost of carbon (SCC) on the optimization results. Finally, a model predictive control (MPC) controller is designed to track the optimal temperature, relative humidity, CO2 concentration and incoming radiation power in presence of system disturbances. Simulation results show that the proposed approach increases the operating costs by R186 (R denotes the South African currency, Rand) but reduces the total cost by R827 and the carbon emissions by 1.16 tons when compared with a baseline method that minimizes operating costs only. The total cost is more sensitive to changes in SCC than that in electricity price and supplied CO2 price. The MPC controller has good tracking performance under different levels of system disturbances. Greenhouse environmental factors are kept within specified ranges suitable for crop growth, which increases crop yields. This study can provide effective guidance for growers' decision-making to achieve sustainable development goals.
引用
收藏
页数:12
相关论文
共 43 条
[1]   Technological progresses in modern sustainable greenhouses cultivation as the path towards precision agriculture [J].
Achour, Yasmine ;
Ouammi, Ahmed ;
Zejli, Driss .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2021, 147
[2]   Energy saving techniques for reducing the heating cost of conventional greenhouses [J].
Ahamed, Md Shamim ;
Guo, Huiqing ;
Tanino, Karen .
BIOSYSTEMS ENGINEERING, 2019, 178 :9-33
[3]  
[Anonymous], 2014, The Water-Energy-Food Nexus. A new approach in support of food security and sustainable agriculture (1)
[4]   Experimental study of an air conditioning system to control a greenhouse microclimate [J].
Attar, I. ;
Naili, N. ;
Khalifa, N. ;
Hazami, M. ;
Lazaar, M. ;
Farhat, A. .
ENERGY CONVERSION AND MANAGEMENT, 2014, 79 :543-553
[5]  
Bank W., 2022, AGR FOOD
[6]   Model-based predictive control of greenhouse climate for reducing energy and water consumption [J].
Blasco, X. ;
Martinez, M. ;
Herrero, J. M. ;
Ramos, C. ;
Sanchis, J. .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2007, 55 (01) :49-70
[7]   Optimal control strategies for carbon dioxide enrichment in greenhouse tomato crops - Part 1: Using pure carbon dioxide [J].
Chalabi, ZS ;
Biro, A ;
Bailey, BJ ;
Aikman, DP ;
Cockshull, KE .
BIOSYSTEMS ENGINEERING, 2002, 81 (04) :421-431
[8]   Greenhouse air temperature predictive control using the particle swarm optimisation algorithm [J].
Coelho, JP ;
Oliveira, PBD ;
Cunha, JB .
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2005, 49 (03) :330-344
[9]   CO2 utilisation in agricultural greenhouses: A novel 'plant to plant' approach driven by bioenergy with carbon capture systems within the energy, water and food Nexus [J].
Ghiat, Ikhlas ;
Mahmood, Farhat ;
Govindan, Rajesh ;
Al-Ansari, Tareq .
ENERGY CONVERSION AND MANAGEMENT, 2021, 228
[10]   A comparative study on the environmental impact of greenhouses: A probabilistic approach [J].
Golzar, Farzin ;
Heeren, Niko ;
Hellweg, Stefanie ;
Roshandel, Ramin .
SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 675 :560-569