Smart Building Manager With Demand Response and Fault Diagnostics
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Solution Overview
Problem
Current building management systems lack integration with smart grid components, limiting their ability to optimize energy use and efficiency, and fail to effectively manage energy demand in response to real-time pricing and availability.
Innovation Solution
A building manager system that includes a communications interface with the smart grid, an integrated control layer, fault detection and diagnostics, and a demand response layer, which processes information from the smart grid to adjust control algorithms, curtail energy use, and utilize local or remote energy sources, enabling seamless integration with disparate building subsystems and optimizing energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If building management systems integrate with smart grid components and implement demand response layers, then energy efficiency and cost optimization improve, but system complexity increases
Solution Approach 1:
The building management system is divided into distinct functional layers: integrated control layer for subsystem management, fault detection and diagnostics layer for monitoring, and demand response layer for energy optimization. This segmentation allows each layer to operate independently while contributing to overall energy efficiency, resolving the contradiction between improved energy loss and increased system complexity.
Solution Approach 2:
The demand response layer acts as an intermediary between the smart grid and building subsystems, processing pricing information and coordinating control algorithm adjustments. This intermediary structure enables energy optimization without requiring direct complex integration between all grid components and building subsystems, thereby improving energy efficiency while managing system complexity.
2Productivity
If real-time control algorithm adjustments are implemented based on pricing information, then energy cost optimization improves, but processing requirements and system complexity increase
Solution Approach 1:
The system pre-processes pricing information and prepares control algorithm adjustments in advance of peak pricing periods. The demand response layer receives and analyzes pricing data, then proactively adjusts control algorithms before high-cost energy usage occurs, optimizing energy costs while reducing the need for complex real-time processing during critical periods.
Solution Approach 2:
The integrated control layer continuously monitors building subsystem performance and feeds this information back to the demand response layer. This feedback loop enables the system to automatically adjust control algorithms based on both pricing information and actual system performance, achieving cost optimization through iterative refinement rather than complex centralized processing.
3Reliability
If fault detection and diagnostics layers are added to monitor building subsystems, then system reliability improves, but computational requirements increase
Solution Approach 1:
The fault detection and diagnostics layer implements self-service monitoring by having building subsystems report their own operational status and performance data. This distributed self-diagnosis approach improves system reliability through continuous monitoring while minimizing computational requirements by avoiding centralized analysis of all subsystem data.
Solution Approach 2:
Fault detection is implemented at the local subsystem level rather than through centralized monitoring. Each building subsystem incorporates its own diagnostic capabilities to detect and report faults locally, improving overall system reliability while reducing the computational burden on the central building management system by processing data at the source.
Data Source
AI summary
A building manager includes a communications interface configured to receive information from a smart energy grid. The building manager further includes an integrated control layer configured to receive inputs from and to provide outputs to a plurality of building subsystems. The integrated control layer includes a plurality of control algorithm modules configured to process the inputs and to determine the outputs. The building manager further includes a fault detection and diagnostics layer configured to use statistical analysis on the inputs received from the integrated control layer to detect and diagnose faults. The building manager yet further includes a demand response layer configured to process the information received from the smart energy grid to determine adjustments to the plurality of control algorithms of the integrated control layer.