Systems and methods for agent based building simulation for optimal control
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Solution Overview
Problem
Building management systems (BMS) face challenges in integrating diverse systems and devices, leading to pre-programmed reactions that can cause unintended situations due to their scripted nature, limiting adaptability and optimization.
Innovation Solution
An agent-based simulation system that generates space, equipment, and control agents to communicate and optimize environmental conditions, allowing for dynamic control and integration of various building systems, enabling goal-oriented optimization and agile deployment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pre-programmed scripted reactions are used in BMS, then system reliability is improved, but adaptability deteriorates
Solution Approach 1:
The patent applies dynamics by transitioning from static pre-programmed reactions to dynamic agent-based decision-making. Agents continuously evaluate sensor data and autonomously determine control actions, allowing the system to adapt to changing conditions while maintaining reliability through structured agent behavior patterns.
Solution Approach 2:
The system segments building systems into independent agents (space agents, equipment agents, control agents) that can operate autonomously. This segmentation allows each agent to handle specific tasks with pre-programmed reliability while the collective agent network provides overall adaptability through decentralized decision-making.
2Adaptability or versatility
If multiple discrete systems are integrated in BMS, then system functionality is improved, but device complexity deteriorates
Solution Approach 1:
The patent implements universality by designing agents with multi-functional capabilities. A single agent architecture handles multiple tasks including environmental monitoring, equipment control, and optimization decision-making, reducing the need for separate discrete systems while maintaining comprehensive functionality.
Solution Approach 2:
Agents serve as intermediaries between different building systems and the central BMS. The agent layer abstracts complex system interactions, providing a simplified interface that reduces overall system complexity while enabling integrated functionality across diverse building subsystems.
3Ease of operation
If pre-programmed control actions are used, then ease of operation is improved, but optimization capability deteriorates
Solution Approach 1:
The system applies self-service by enabling agents to autonomously optimize building operations without requiring constant human intervention. Agents continuously analyze sensor data, evaluate optimization opportunities, and implement control actions independently, maintaining ease of operation while significantly improving optimization capability.
Solution Approach 2:
The patent implements feedback mechanisms where agents continuously monitor system performance and use this information to refine control decisions. Sensor data feeds back to agents, which adjust their behavior to optimize energy consumption and environmental conditions, enhancing productivity while maintaining operational simplicity.
Data Source
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.