Hybrid CEA Control Using Weather and Market-Responsive Energy Scheduling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Controlled environment agriculture (CEA) systems face high energy and capital costs due to the need for air conditioning, artificial lighting, and additional systems, with variable electricity demands and prices, necessitating optimized energy and resource management to balance costs and market demands.
Innovation Solution
A hybrid CEA system with a control unit that adjusts energy inputs, water usage, and land usage based on weather profiles and market conditions, incorporating thermal and electricity storage, and responsive load management to optimize energy use and reduce costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CEA facilities use air conditioning systems and artificial light sources to control environment, then plant growing conditions are improved, but energy consumption and capital costs increase dramatically
Solution Approach 1:
The system dynamically adjusts environmental controls based on real-time weather forecasts and actual conditions. The control unit modifies air conditioning and lighting operations according to predicted weather patterns, reducing energy consumption while maintaining acceptable growing conditions through adaptive rather than static control.
Solution Approach 2:
The system changes operational parameters of air conditioning and lighting systems based on weather forecasts. By adjusting temperature setpoints, lighting intensity, and operational timing according to predicted conditions, the system reduces energy consumption while maintaining plant growth requirements.
2Reliability
If CEA facilities operate with high energy consumption, then controlled environment is maintained, but operational costs increase
Solution Approach 1:
The system performs preliminary actions by forecasting weather conditions in advance and pre-adjusting environmental controls accordingly. By anticipating weather changes and preparing appropriate responses beforehand, the system avoids unnecessary energy consumption during actual weather events while maintaining environmental stability.
Solution Approach 2:
The system incorporates feedback loops that continuously monitor actual environmental conditions and compare them with forecasted conditions. This feedback mechanism allows the control unit to adjust operations in real-time, optimizing energy usage while maintaining required environmental parameters for plant growth.
3Productivity
If CEA facilities use multiple artificial light sources, then plant growth is supported, but capital investment and energy requirements increase
Solution Approach 1:
The system implements periodic lighting schedules based on weather forecasts and plant growth stages. By using lighting intermittently rather than continuously, and by adjusting intensity and timing according to predicted conditions, the system reduces the number and power of light sources needed while maintaining productivity.
4Productivity
If CEA facilities implement comprehensive environmental control systems, then growing conditions are optimized, but system complexity and capital costs increase
Solution Approach 1:
The control unit serves multiple functions by integrating weather forecasting, environmental monitoring, and control operations into a single system. This multi-functional approach reduces overall system complexity while maintaining optimized growing conditions through coordinated control of various environmental parameters.
Data Source
AI summary
An embodiment may respond to different weather profiles and market conditions within a controlled environment agricultural system, which may include one or more power consuming and environment controlling systems. Different market demands and prices may be used to influence which plants are grown and when they should be harvested. The growing process may be altered based on market demand, which may call for a varietal to be harvested at a delayed time or may require some other parameters to be optimized. A control unit may identify criticality of and power consumption by the systems and may compare those with the current cost of power. The control unit may analyze the cost of adjusting power to systems and the cost of powering those systems during a specified period of time. A weather profile may be forecasted which can be used to identify which systems to power or when to store energy.