Building automation system with hybrid disaster recovery
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Solution Overview
Problem
Existing HVAC system control algorithms require iterative rebuilds and deployments, leading to inefficiencies in algorithm development and testing.
Innovation Solution
A method for parallel computation and hybrid cluster optimization in building management systems, utilizing a processing circuit to generate and execute computing threads based on property models, and a dynamic cloud-based control framework for managing failures and optimizing resource allocation across on-premises and off-premises nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If iterative rebuild and deployment of control algorithms is performed, then algorithm development and testing can be done, but efficiency is reduced due to repeated rebuilds
Solution Approach 1:
The system segments the control algorithm deployment process into separate development environment and runtime environment. The runtime engine executes algorithms without requiring full rebuilds, allowing incremental changes and faster iteration. This separation enables the development team to work on algorithm improvements while the runtime system continues operating with existing algorithms.
Solution Approach 2:
The runtime engine performs preliminary compilation and validation of control algorithms before deployment to the building management system. By pre-processing algorithms in the development environment and validating them against the runtime schema, the system eliminates the need for repeated full rebuilds during iterative development, significantly reducing deployment time.
2Adaptability or versatility
If control algorithms are rebuilt iteratively, then changes can be made and tested, but the process becomes inefficient
Solution Approach 1:
The system implements dynamic algorithm loading where the runtime engine can load, unload, and update control algorithms without stopping the building management system. This dynamic approach allows developers to modify algorithms and immediately test changes in a controlled manner, maintaining adaptability while improving deployment efficiency through selective updates rather than full rebuilds.
3Reliability
If a robust method for developing algorithms is implemented, then reliability of the system is improved, but complexity of the development process increases
Solution Approach 1:
The runtime engine acts as an intermediary between the development environment and the building management system. It provides a standardized interface for algorithm execution, validation, and deployment, ensuring that algorithms meet reliability requirements without requiring complex manual verification processes. The runtime schema validation serves as an automated intermediary check that ensures algorithm correctness.
Data Source
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AI summary
A method for executing computations in parallel for a building management system of a building includes receiving a computing job request to determine values for one or more particular properties, receiving a property model indicating dependencies between a plurality of properties, the plurality of properties including the one or more particular properties, wherein the plurality of properties include building data for the building, and generating one or more computing threads based on the property model, wherein each computing thread includes a sequence of computations for determining values for the plurality of properties. The method further includes executing the computing threads in parallel to determine the values for the particular properties.