Building Control System Load Curtailment Optimization
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Solution Overview
Problem
Central plants face challenges in optimally distributing energy loads across subplants during curtailment periods, leading to uncomfortable building conditions due to insufficient load management.
Innovation Solution
A controller with a processing circuit that performs optimizations of an objective function subject to constraints, modifying constraint variables based on gradients to reduce resource requirements and costs, and operates equipment accordingly, recommending changes to users and modifying constraints to achieve optimal energy distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If load profile is used to control central plant, then energy distribution is simplified, but building comfort deteriorates during curtailment periods
Solution Approach 1:
The control system dynamically adjusts operational parameters of subplants based on real-time conditions and curtailment requirements. The asset allocator modifies setpoints and operational modes adaptively, allowing the system to respond flexibly to changing load conditions while maintaining comfort within acceptable ranges.
Solution Approach 2:
The system changes operational parameters such as temperature setpoints, flow rates, and equipment modulation levels to optimize performance during curtailment. By adjusting these parameters within acceptable ranges, the system reduces energy consumption while preventing building conditions from deteriorating below comfort thresholds.
2Productivity
If existing building equipment is used to meet large building load, then equipment capacity is充分利用, but load must be curtailed causing uncomfortable conditions
Solution Approach 1:
The system performs preliminary optimization calculations to determine the maximum achievable load satisfaction before actual curtailment occurs. The asset allocator pre-calculates optimal distribution strategies and prepares adjustment plans that maximize equipment utilization while identifying the point where comfort thresholds would be violated.
Solution Approach 2:
The control system continuously monitors building conditions, equipment performance, and load requirements. This feedback loop allows the system to adjust operational parameters in real-time, ensuring that equipment is utilized to its fullest capacity without pushing building conditions beyond acceptable comfort ranges.
3Device complexity
If optimization is performed without modifying constraint variables, then computational simplicity is maintained, but cost reduction is limited
Solution Approach 1:
The system performs partial optimization by focusing computational efforts on the most critical constraint variables that have the greatest impact on energy costs. Rather than exhaustively optimizing all parameters, the asset allocator identifies and adjusts key variables such as subplant prioritization and load distribution ratios, achieving significant cost reductions with moderate computational complexity.
Data Source
AI summary
A system controlling equipment to serve energy loads of a building includes a cost function generator configured to obtain a cost function of decision variables representing an amount of resources consumed or produced by the equipment, an optimizer configured to perform a first optimization of the cost function subject to a first set of constraints defining first values of constraint variables to generate a first result defining first values of decision variables, a constraint modifier configured determine a cost gradient, recommend changes to constraint variables, and modify constraint variables to modified values in response to changes. The optimizer is configured to perform an optimization of the cost function subject to a second set of constraints to generate a second optimization result defining second values of the decision variables. The system includes a controller that operates equipment to consume or produce resources defined by second values of the decision variables.