HVAC Operating State Prediction for Temperature-Cost Control
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Solution Overview
Problem
HVAC systems consume a significant amount of energy, with operating costs often overlooked and difficult to estimate, particularly due to factors like operating temperature and external conditions, necessitating methods that consider and reduce these costs.
Innovation Solution
A method for operating HVAC systems that includes models for indoor temperature and operating cost, combined with predicted future outdoor temperatures, to calculate and optimize future operating states, thereby minimizing energy consumption and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If HVAC systems operate to maintain a specific building temperature, then comfort and protection of temperature sensitive contents is improved, but energy consumption increases
Solution Approach 1:
The system performs preliminary actions by predicting future outdoor temperatures and calculating future operating states in advance. The optimization algorithm determines ahead of time when and how to adjust HVAC operation based on forecasted conditions, allowing the system to pre-condition spaces or adjust operations to minimize energy consumption while maintaining temperature requirements.
Solution Approach 2:
The system changes operational parameters dynamically by adjusting the building temperature setpoint based on predicted future conditions. Instead of maintaining a fixed temperature, the system varies temperature parameters over time based on optimization calculations that consider future outdoor temperatures, thereby reducing energy consumption while still meeting comfort and protection requirements.
2Reliability
If HVAC systems are set to maintain a specific operating temperature, then building comfort is improved, but operating costs increase and become difficult to estimate
Solution Approach 1:
The system implements feedback by providing users with estimated operating costs associated with different temperature settings. The optimization algorithm calculates and communicates cost information back to users, enabling them to make informed decisions about temperature preferences. This feedback loop transforms the black-box operation into a transparent system where users understand the cost implications of their temperature choices.
Solution Approach 2:
The system introduces an intermediary layer between the user and the HVAC system operation. This intermediary is the optimization algorithm that translates user temperature preferences into cost estimates and recommends operating states. It mediates the relationship between user comfort preferences and actual operating costs, making the system easier to operate by providing guidance and information.
3Stability of the object's composition
If HVAC systems operate continuously to maintain temperature, then temperature stability is improved, but energy expenditure increases
Solution Approach 1:
The system transitions from continuous operation to periodic action by determining optimized operating states at discrete time intervals. Instead of running continuously, the HVAC system adjusts operations periodically based on predicted future conditions and optimization calculations, maintaining temperature stability only when necessary while reducing unnecessary energy expenditure during periods when temperature adjustment is not required.
Solution Approach 2:
The system introduces dynamics by making temperature setpoints and operating states variable rather than fixed. The optimization algorithm dynamically adjusts operating parameters based on changing predicted conditions, allowing the system to adapt between maintaining stability and reducing energy use depending on future forecasts, thereby breaking the trade-off between stability and energy consumption.
Data Source
AI summary
A method for operating an HVAC system of a building is provided. The method includes providing a model for an indoor temperature of the building, a model for an operating cost of the HVAC system, and predicted future outdoor temperatures. Utilizing at least the models for the indoor temperature and the operating cost of the HVAC system and the predicted future outdoor temperatures, future operating states of the HVAC system can be calculated.