Agent-Based Building Simulation for Adaptive Environmental Control
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Solution Overview
Problem
Building management systems (BMS) face challenges in optimizing environmental control due to preprogrammed reactions that can lead to unwanted situations, as they often rely on scripted responses rather than adaptive or optimized control strategies.
Innovation Solution
The implementation of an agent-based building simulation system that generates space, equipment, and control agents to communicate and optimize environmental conditions, such as temperature, through dynamic channel communications and machine learning, allowing for adaptive and goal-oriented optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If preprogrammed scripted reactions are used in BMS, then system reliability is improved through predictable responses, but adaptability deteriorates causing unwanted situations
Solution Approach 1:
The patent transforms the static, preprogrammed BMS into a dynamic system using multi-agent simulation where agents continuously adapt their behaviors based on changing building conditions, occupancy patterns, and environmental factors, resolving the contradiction between reliability and adaptability
Solution Approach 2:
The simulation system enables self-service by allowing the BMS to automatically evaluate its own performance and optimize control strategies through agent-based modeling, eliminating the need for manual reprogramming while maintaining adaptability
2Adaptability or versatility
If agent-based simulation is implemented, then adaptability is improved through dynamic optimization, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the building into multiple autonomous agents (space agents, equipment agents, occupancy agents) that each manage specific functions independently, reducing overall system complexity while maintaining high adaptability
Solution Approach 2:
The simulation platform serves multiple functions including performance evaluation, optimization, prediction, and control strategy development, reducing the need for separate systems and thereby managing complexity
3Device complexity
If traditional BMS control strategies are used, then device complexity is reduced through simple scripting, but productivity deteriorates due to suboptimal environmental control
Solution Approach 1:
The system performs preliminary simulation and optimization before actual control implementation, allowing the BMS to pre-determine optimal control strategies based on predicted conditions, thereby improving productivity without requiring complex real-time control systems
Data Source
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AI summary
A system for a building management system simulation includes one or more processors and memory. The memory includes instructions stored thereon, that when executed by the one or more processors, cause the one or more processors to generate a space agent representing a space in a building, the space agent to maintain an environmental condition of the space based on an optimization state of the space, generate an equipment agent representing a device that serves the space, and register the space agent and the equipment agent to a space communication channel associated with the space. The space agent communicates with the equipment agent over the space communication channel.