Air Handling Unit Rule Flipping for Energy-Comfort Conflicts
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Solution Overview
Problem
Conventional Air Handling Units (AHUs) face challenges in optimizing performance parameters due to conflicting automation rules, leading to increased energy consumption and potential discomfort for occupants, as these rules are often heuristic and may violate constraints, causing frequent duty cycling of HVAC systems.
Innovation Solution
A processor-implemented method and system that utilize a test case generation framework to identify and rank rule sets with conflicting conditions, dynamically optimizing parameters such as energy consumption and discomfort level by selecting rule sets based on highest conflict frequency, and applying a rule flipping mechanism to balance energy and comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If heuristic automation rules are implemented in AHUs, then operational flexibility is improved, but energy consumption increases and system reliability deteriorates due to frequent duty cycling
Solution Approach 1:
The patent implements a feedback mechanism where the performance of automation rules is continuously monitored and evaluated. The system tracks metrics such as energy consumption, duty cycling frequency, and occupancy comfort levels. Based on this feedback, the rule engine dynamically adjusts or removes underperforming rules, creating a closed-loop system that optimizes energy usage while maintaining operational flexibility.
Solution Approach 2:
The system changes the parameters of automation rules based on performance evaluation. Rules are assigned priority values and performance scores that are dynamically adjusted. The rule engine modifies rule parameters such as activation thresholds, time periods, and priority levels to optimize system performance and reduce energy consumption while maintaining necessary operational flexibility.
2Adaptability or versatility
If multiple automation rules are implemented by different stakeholders, then system functionality is improved, but rule conflicts increase leading to system instability
Solution Approach 1:
The patent introduces an intermediary rule evaluation engine that acts as a mediator between multiple stakeholders' automation rules. This engine systematically evaluates all rules against defined performance criteria and conflict resolution mechanisms, ensuring that rules from different stakeholders are harmonized rather than conflicting. The intermediary layer prevents direct rule conflicts by orchestrating rule execution based on priority and performance metrics.
Solution Approach 2:
The system implements dynamic rule management where rule priorities and activation conditions are not fixed but adapt based on system state and performance evaluation. The rule engine dynamically adjusts rule behavior to prevent conflicts, allowing the system to maintain stability while accommodating multiple stakeholder requirements. Rules can be temporarily suspended or modified based on real-time system conditions.
3Loss of energy
If automation rules are frequently adjusted to optimize performance, then energy efficiency is improved, but device complexity and operational reliability worsen due to too-frequent duty cycling
Solution Approach 1:
The patent implements periodic evaluation of automation rules rather than continuous adjustment. The system assesses rule performance at defined intervals or based on trigger events, preventing excessive rule modifications. This periodic approach allows energy efficiency optimization while avoiding the operational instability caused by too-frequent adjustments. The rule engine reviews and adjusts rules based on accumulated performance data rather than real-time fluctuations.
Data Source
AI summary
Sub-systems of air handling units in infrastructures face unresolved problem of conflict in the rules that activate in a contradictory manner at the same time resulting in sub-optimal performance of the subsystems. The present disclosure provides a system and method for optimizing performance parameters of air handling units in infrastructures. Rule sets having conflicting conditions are identified after verification of rules which are specific to air handling units. Further, frequency of the rule sets having conflicting conditions is determined to generate a ranked list of the rule sets having conflicting conditions. Another ranking procedure is implemented for the rules comprised in the ranked list of the rule sets having conflicting conditions. The system dynamically optimizes one or more parameters specific to the performance criteria based on the ranking of rules.