Building equipment with predictive control and allocation of energy from multiple energy sources
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Solution Overview
Problem
HVAC systems, such as air handling units (AHUs) and rooftop units (RTUs), face challenges in minimizing power consumption, leading to high energy costs and carbon emissions, as they rely on grid electricity without efficient energy management strategies.
Innovation Solution
A predictive controller is implemented to optimize the use of electric energy by determining the optimal amount of energy to purchase from the grid and store or discharge from a battery or renewable energy sources, considering costs, carbon emissions, and occupant comfort, using a predictive cost function that accounts for time-varying energy prices and demand charges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If building equipment operates using grid electricity, then the equipment can function reliably, but energy costs and carbon emissions increase
Solution Approach 1:
The battery stores electric energy in advance during periods when grid electricity is cheaper or renewable energy is available, so that the stored energy can be used during periods when grid electricity is expensive, thereby reducing overall energy costs while ensuring equipment operation reliability
Solution Approach 2:
The predictive controller changes the timing parameter of energy consumption by shifting load operation to periods when renewable energy is available or when electricity rates are lower, thereby reducing energy costs without compromising equipment reliability
2Duration of action of stationary object
If building equipment operates using grid electricity, then the equipment can function continuously, but carbon emissions increase
Solution Approach 1:
The battery accumulates electric energy from renewable sources in advance, enabling the equipment to operate for extended periods using clean energy, thereby reducing carbon emissions while maintaining continuous operation capability
Solution Approach 2:
The battery acts as an intermediary energy storage device between renewable energy sources and the building equipment, decoupling the equipment operation from direct grid electricity consumption and reducing carbon emissions
3Use of energy by stationary object
If the predictive controller optimizes energy usage, then energy costs decrease, but system complexity increases
Solution Approach 1:
The predictive controller uses feedback from energy pricing signals, battery state of charge, and equipment operational requirements to dynamically optimize energy usage, reducing energy costs while managing system complexity through adaptive control
Solution Approach 2:
The system performs self-optimization by automatically adjusting energy consumption patterns based on predictive algorithms that consider future energy prices and renewable energy availability, reducing the need for complex manual control while lowering energy costs
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The predictive controller reduces energy costs and carbon footprint by optimizing energy usage, shifting peak demand, and integrating renewable energy sources, thereby enhancing the efficiency and sustainability of HVAC systems.
Implementation Method 1
the second energy source includes at least one of a battery configured to store and discharge the second amount of the electric energy for use by the building equipment
Implementation Method 2
renewable energy generation equipment configured to generate the second amount of the electric energy from a renewable energy source
Data Source
AI summary
A predictive controller for building equipment associated with a building includes one or more processing circuits configured to control electric energy used by the building equipment. The building equipment includes an electric energy using component. The one or more processing circuits are configured to utilize a predictive cost function to determine a first amount of the electric energy supplied from an energy grid source and a second amount of the electric energy supplied from a second energy source to the electric energy using component.