Energy-water management system based on robust predictive control for open-field cultivation

Area of Science:

• Agricultural Science
• Environmental Engineering
• Sustainable Resource Management

Background:

• Global events threaten food availability, increasing demand on agriculture, water, and energy resources.
• Increased agricultural activity leads to groundwater over-extraction and greenhouse gas emissions.
• Balancing water, energy, and food resources is critical for global sustainability.

Purpose of the Study:

• To design a sustainable energy-water management system using the water-energy-food nexus.
• To develop a robust predictive control system for optimizing resource allocation.
• To address global challenges of food security, water availability, and energy access.

Main Methods:

• Implemented a robust predictive control system for an energy-water management system.
• Utilized fuzzy prediction intervals to estimate worst-case climate scenarios (solar radiation, temperature, precipitation, etc.).
• Scheduled irrigation and groundwater extraction based on predicted climate and available solar energy.

Main Results:

• The robust approach ensured maximum crop development and minimized water consumption.
• The system successfully avoided groundwater over-extraction.
• Renewable energy sources were prioritized, minimizing operating costs and environmental impact.

Conclusions:

• The proposed energy-water management system is sustainable and effective.
• The water-energy-food nexus approach successfully tackles global resource challenges.
• This system promotes food security, water availability, and energy access through optimized resource management.