Building Energy Analytics With Preprocessed Timeseries Retrieval
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Solution Overview
Problem
Building management systems (BMS) face delays in data presentation due to the need for raw timeseries data to be retrieved and processed in response to requests, which can hinder real-time monitoring and control of building energy management.
Innovation Solution
A building energy management system that includes a data collector, analytics service, and timeseries database, which processes and stores data to generate optimized timeseries data, allowing for immediate retrieval and analysis, including weather normalization, energy benchmarking, and load ratio comparisons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If raw timeseries data is stored in a relational database without significant organization or processing at the time of data collection, then data storage simplicity is improved, but data presentation speed deteriorates due to processing delays at query time
Solution Approach 1:
The patent applies preliminary action by pre-processing and organizing timeseries data into optimized structures (such as time-series databases or data warehouses) at the time of data collection rather than leaving it raw. This preliminary organization enables immediate retrieval and analysis without processing delays at query time, directly resolving the contradiction between storage simplicity and presentation speed.
2Adaptability or versatility
If applications retrieve and process raw timeseries data in response to requests, then data processing flexibility is improved, but real-time monitoring capability deteriorates due to significant delays
Solution Approach 1:
The system performs preliminary processing of timeseries data into optimized formats and pre-calculates various views and aggregations before they are requested. This allows applications to immediately retrieve pre-processed data for real-time monitoring while maintaining the flexibility to request different types of processed data as needed.
Solution Approach 2:
The patent implements dynamic data processing by maintaining multiple pre-processed views of the timeseries data in different formats and levels of aggregation. This dynamic structure allows the system to adapt to different application needs in real-time without reprocessing the entire dataset, thus maintaining both flexibility and speed.
3Measurement precision
If weather normalization analytics are performed on timeseries data, then energy management accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent introduces an intermediary analytics service layer that handles weather normalization processing. This intermediary service receives raw timeseries data, performs weather normalization by comparing actual energy consumption with expected consumption based on weather conditions, and returns normalized results. This approach improves energy management accuracy while containing processing complexity within a dedicated service rather than throughout the entire system.
Data Source
AI summary
A building energy management system includes building equipment, a data collector, an analytics service, a timeseries database, and an energy management application. The building equipment monitor and control one or more variables in the building energy management system and provide data samples of the one or more variables. The data collector collects the data samples from the building equipment and generates a data timeseries including a plurality of the data samples. The analytics service performs one or more analytics using the data timeseries and generates a results timeseries including a plurality of result samples indicating results of the analytics. The timeseries database stores the data timeseries and the results timeseries. The energy management application retrieves the data timeseries and the results timeseries from the timeseries database in response to a request for timeseries data associated with the one or more variables.