Hierarchical Building Control for Multi-Zone Energy Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing building management systems (BMS) face challenges in efficiently controlling and optimizing energy usage across multiple zones and systems due to proprietary programming languages and manual sequencing of operations.
Innovation Solution
A hierarchical resource analysis system that utilizes multiple processors to implement causal agents and a causal coordinator. This system monitors and adjusts resource operations across zones to maintain optimal environmental conditions, using machine learning algorithms to predict energy consumption and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual programming of sequences of operation is used in each controller, then the system can be controlled using proprietary programming languages, but the system complexity increases and energy optimization capability deteriorates
Solution Approach 1:
The patent introduces a centralized energy management system that acts as an intermediary between individual building controllers and the central management platform. This intermediary layer translates proprietary controller commands into standardized energy optimization algorithms, reducing system complexity while maintaining ease of programming for individual components.
Solution Approach 2:
The patent implements a universal energy management platform that can interface with multiple types of building equipment (HVAC, lighting, security) using a single standardized protocol. This multi-functional approach eliminates the need for separate proprietary programming for each device type, reducing overall system complexity.
2Ease of operation
If manual sequencing of operations is implemented in each controller, then device control is simplified, but energy consumption optimization deteriorates
Solution Approach 1:
The patent implements continuous feedback loops where the central energy management system monitors real-time energy consumption data from all building systems, analyzes performance against optimization targets, and automatically adjusts operational sequences. This feedback mechanism maintains simple device control while achieving energy optimization through centralized intelligence.
Solution Approach 2:
The patent uses predictive algorithms that analyze historical energy consumption patterns and environmental conditions to pre-calculate optimal sequencing of operations before peak energy demand periods. This preliminary action allows simple device controllers to execute pre-optimized sequences without requiring complex real-time decision-making capability.
3Reliability
If proprietary programming languages are used for each device, then manufacturer-specific control requirements are met, but system-wide energy optimization capability deteriorates
Solution Approach 1:
The patent introduces a translation layer that acts as an intermediary between proprietary device protocols and the centralized energy optimization engine. This intermediary maintains reliable device-specific control by preserving original communication protocols while enabling system-wide energy optimization through standardized data exchange formats and unified optimization algorithms.
Data Source
AI summary
A hierarchical resource analysis system, for a building that has a plurality of zones each with a corresponding resource arranged to alter an environment of the zone, includes one or more processors that implement a plurality of causal agents and a causal coordinator. Each of the causal agents reports to the causal coordinator parameter values describing a state of the environment of one of the zones and parameter values describing a state of the corresponding resource for the zone. The causal coordinator, responsive to indication that at least one of the parameter values describing a state of the environment of one of the zones is outside a predefined zone range and all of the parameter values describing the states of the corresponding resources for the zones being within corresponding predefined resource ranges, commands at least one of the causal agents to operate the corresponding resource within an altered span.