Central plant control system with dynamic computation reduction
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Solution Overview
Problem
Conventional methods for predicting thermodynamic states in central plant HVAC systems are inefficient in terms of computational resources, particularly when determining multiple sets of operating parameters, leading to excessive processor usage and memory consumption.
Innovation Solution
A central plant controller dynamically reduces computation by identifying schematic dependencies between HVAC devices using an incidence matrix, excluding inoperable devices and optimizing operating parameters based on changed conditions, thereby reducing the number of thermodynamic states to be predicted.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional non-linear solver is used to predict thermodynamic states for multiple candidate sets of operating parameters, then accurate power consumption predictions are obtained, but computational resources (processor usage and memory) are excessively consumed
Solution Approach 1:
The patent segments the HVAC system into independent subplants (e.g., chiller subplant, boiler subplant, cooling tower subplant). Each subplant is optimized separately by determining operating parameters for its constituent devices independently, rather than solving the entire system as one large non-linear problem. This segmentation reduces computational complexity while maintaining prediction accuracy.
Solution Approach 2:
The patent extracts and removes inoperable HVAC devices from the optimization calculation based on detected system conditions. By identifying devices that are offline or inoperable and excluding them from the candidate set of operating parameters, the computational burden is reduced without affecting the accuracy of power consumption predictions for the remaining operational devices.
2Reliability
If full thermodynamic states are computed for all HVAC devices in a complex arrangement, then complete system analysis is achieved, but computational efficiency deteriorates
Solution Approach 1:
The patent divides the complex HVAC system into multiple independent subplants, each containing specific types of devices (e.g., chillers, boilers, cooling towers). This segmentation allows the optimization algorithm to process each subplant separately, reducing the overall computational complexity while maintaining complete system analysis through aggregation of subplant results.
Solution Approach 2:
The patent computes thermodynamic states and optimizes operating parameters only for the subset of HVAC devices that are currently inoperable or require adjustment, rather than recalculating states for all devices in the system. This partial action approach maintains reliability by focusing computational resources on devices that actually need optimization.
3Ease of operation
If multiple candidate sets of operating parameters are evaluated to determine optimal power consumption, then optimal operating parameters are identified, but computation time increases
Solution Approach 1:
The patent evaluates candidate operating parameters for each subplant independently rather than generating and evaluating all possible combinations across the entire HVAC system. This segmentation of the parameter evaluation process significantly reduces computation time while still identifying optimal operating parameters through systematic comparison of candidate sets within each subplant.
Solution Approach 2:
The patent generates and evaluates a limited set of candidate operating parameters focused on the specific subplant and device conditions, rather than exhaustively evaluating all possible operating parameter combinations for the entire system. This approach achieves optimal parameter determination with reduced computation time by concentrating computational effort where it is most needed.
Data Source
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AI summary
A controller for a plurality of heating, ventilation, or air conditioning (HVAC) devices includes a processing circuit that includes one or more processors and memory. The controller detects a change in condition that affects an operating status of a first HVAC device of the plurality of HVAC devices. The controller uses schematic relationships between the plurality of HVAC devices to determine a reduced subset of the plurality of HVAC devices for which operating parameters are to be generated based on the operating status of the first HVAC device. The controller generates operating parameters for the reduced subset of the plurality of HVAC devices and operates the plurality of HVAC devices using the operating parameters.