Central plant control system with setpoints modification based on physical constraints
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Solution Overview
Problem
Central plant HVAC systems face challenges in optimizing operating parameters to satisfy physical constraints and target thermal energy loads, which can lead to equipment damage and inefficient energy distribution.
Innovation Solution
A controller system that determines the ratio of flow rates between HVAC devices connected in parallel, generates candidate sets of operating parameters, predicts thermodynamic states, and adjusts to ensure compliance with physical constraints and target thermal energy loads, using a processing circuit to perform least squares optimization and adjust outlet temperatures and thermal energy loads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If operating parameters are optimized to meet target thermal energy loads, then energy distribution efficiency is improved, but physical constraints of HVAC devices may be violated causing equipment damage
Solution Approach 1:
The system performs preliminary prediction of thermodynamic states for candidate operating parameters before implementation. The controller predicts outlet temperatures and thermodynamic states in advance, checks them against physical constraints, and only selects parameters that satisfy both target loads and device constraints, preventing equipment damage before it occurs.
Solution Approach 2:
The system implements a feedback mechanism where the controller continuously monitors actual thermodynamic states and compares them with predicted states and constraint boundaries. Based on this feedback, the controller adjusts operating parameters to maintain both efficiency and equipment safety, creating a closed-loop control system.
2Reliability
If operating parameters are adjusted to satisfy physical constraints, then equipment safety is improved, but ability to meet target thermal energy loads may deteriorate
Solution Approach 1:
The system dynamically adjusts operating parameters by generating multiple candidate sets and selecting the optimal one that simultaneously satisfies both physical constraints and target thermal energy loads. The controller adapts parameter selection based on real-time conditions, maintaining a balance between safety and productivity through dynamic optimization.
Solution Approach 2:
The system changes operating parameters (such as flow rates, temperatures, and device capacities) to find the optimal operating point. By predicting thermodynamic states for different parameter sets and evaluating them against constraints and targets, the system identifies parameter changes that achieve both equipment safety and load satisfaction.
3Measurement precision
If candidate sets of operating parameters are generated and evaluated, then optimization accuracy is improved, but computational complexity increases
Solution Approach 1:
The system generates multiple candidate sets of operating parameters (excessive action) to ensure the optimal solution is found, but applies pruning by evaluating candidates against physical constraints and target loads, selecting only those that satisfy both criteria. This approach maintains high optimization accuracy while managing computational complexity through selective evaluation.
Data Source
AI summary
Disclosed herein are a system, method, and non-transitory computer readable medium for operating an energy plant. In one aspect, a system determines a ratio of flow rates between devices of the energy plant connected in parallel with each other in a branch. The system generates a candidate set of operating parameters of the devices according to the ratio of flow rates. The system predicts thermodynamic states of the devices operating according to the candidate set of operating parameters. The system determines whether the predicted thermodynamic states satisfy constraints of the devices. The system determines whether the predicted thermodynamic states satisfy a target thermal energy load of the branch based on the ratio of the flow rates. The system operates the energy plant according to the candidate set of operating parameters, in response to determining that the predicted thermodynamic states satisfy the constraints and the target thermal energy load.