Multi-Unit HVAC Control Using Continuous ON/OFF Optimization
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Solution Overview
Problem
Existing HVAC systems face challenges in optimizing energy consumption across multiple units in a building, as current methods either focus on single units or restrict occupant control, leading to inefficiencies and computational difficulties in discrete optimization problems.
Innovation Solution
The method represents the operation of HVAC units using continuous functions subject to complementarity constraints, allowing for joint optimization of multiple units and reducing discrete decisions by modeling ON/OFF states, enabling efficient energy management through a processor-controlled system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If discrete models are used for HVAC unit operation optimization, then the ON/OFF states can be accurately represented, but the computational complexity increases significantly making the problem difficult to solve
Solution Approach 1:
The patent transforms the discrete binary variables (0 or 1) representing HVAC ON/OFF states into continuous variables that can take any value between 0 and 1. This parameter transformation allows the use of continuous optimization algorithms while still representing the discrete nature of HVAC operation through complementarity constraints, thereby reducing computational complexity while maintaining accuracy.
2Ease of operation
If multiple HVAC units are optimized independently, then each unit can be controlled简单地, but the overall energy consumption of the building cannot be minimized
Solution Approach 1:
The patent merges the control of multiple independent HVAC units into a unified joint optimization framework. By formulating a single optimization problem that simultaneously determines the ON/OFF states of all HVAC units based on building-wide temperature and energy constraints, the system achieves global energy minimization while maintaining coordinated control across all units.
3Loss of energy
If compressors are frequently turned OFF to save energy, then energy consumption decreases, but the number of discrete decisions increases making optimization more difficult
Solution Approach 1:
The patent applies parameter transformation specifically to compressor operation by introducing continuous variables to represent compressor ON/OFF decisions. The complementarity constraints ensure that these continuous variables correctly represent the discrete nature of compressor operation, allowing the optimizer to determine optimal switching times without the computational burden of traditional discrete optimization.
Data Source
AI summary
A method operates a set of heating, ventilation and air-conditioning (HVAC) units by optimizing jointly operations of the set of HVAC units subject to constraints to determine times of switching each HVAC unit ON and OFF and by controlling each HVAC unit according to the corresponding times of switching. The operation of each HVAC unit is represented by a continuous function. The constraints include a complementarity constraint for each HVAC unit, such that the complementarity constraint for the HVAC unit defines a discontinuity of the operation of the HVAC unit at corresponding times of switching.