Building Energy Scorecard with Multi-Dimensional Consumption Widgets
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Solution Overview
Problem
Building management systems (BMS) lack effective tools for comprehensive energy monitoring and reporting, particularly in visualizing key performance indicators across various building systems, leading to inefficiencies in energy consumption and equipment performance analysis.
Innovation Solution
A BMS that includes a metric generation system and a visualization engine to create scorecards displaying total consumption, consumption by space, and consumption by commodity, using widgets such as energy density by space, consumption by load type, and consumption by peak demand, along with an interface generator for user-selectable data views.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If building management systems use traditional monitoring methods, then system simplicity is maintained, but energy monitoring comprehensiveness and visualization capability are insufficient
Solution Approach 1:
The system segments energy consumption data into multiple dimensions including total consumption, consumption by space, consumption by commodity, energy density by space, consumption by load type, and consumption by peak demand. Each dimension is visualized through dedicated widgets that break down complex energy data into manageable, actionable insights without overwhelming the user.
Solution Approach 2:
The system transforms traditional one-dimensional energy monitoring into multi-dimensional analysis by introducing spatial dimensions (by space, by commodity, by load type) and temporal dimensions (peak demand, energy density per day). This dimensional expansion enables comprehensive energy monitoring while maintaining clarity through structured visualization.
2Productivity
If detailed energy data is collected and analyzed, then energy management effectiveness is improved, but data processing complexity increases
Solution Approach 1:
The metric generation system automatically collects raw energy data from building equipment, processes it through defined calculations, and generates key performance indicators without requiring manual intervention. The system self-manages the complex data processing pipeline, transforming raw data into actionable metrics that improve energy management efficiency.
Solution Approach 2:
The system establishes feedback loops where energy consumption data is continuously collected, analyzed, and presented through visualizations that enable informed decision-making. This feedback mechanism allows building operators to monitor energy performance in real-time and implement corrective actions, thereby improving overall energy management effectiveness.
3Loss of information
If comprehensive key performance indicators are displayed, then energy performance visibility is enhanced, but user interface complexity increases
Solution Approach 1:
The user interface is segmented into distinct functional widgets, each dedicated to a specific energy metric (total consumption, consumption by space, consumption by commodity, energy density by space, consumption by load type, consumption by peak demand). This segmentation allows comprehensive information display while maintaining interface simplicity through organized, modular presentation.
Solution Approach 2:
Each widget is designed with specific visual characteristics optimized for its data type, such as thermal maps for spatial consumption patterns, ring charts for load type distribution, and gauges for peak demand metrics. This localized optimization enhances information visibility while maintaining overall interface consistency and ease of use.
Data Source
AI summary
A building management system includes building equipment, a metric generation system, and a visualization engine. The building equipment is configured to generate data samples. The metric generation system is configured to collect the data samples and generate key performance indicators. The visualization engine is configured to create a scorecard that displays the key performance indicators. The scorecard comprises a building energy overview widget that displays total consumption of a building, a consumption by space widget that displays consumption of a plurality of subspaces of the building, and a consumption by commodity widget that displays consumption of the building categorized by commodity. In some embodiments, the scorecard also includes an energy density by space widget that displays consumption per unit area per day for the subspaces of the building.