Generator Run Time Prediction via Load Profiling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Facilities face challenges in accurately predicting the available running time of generators, which is crucial for managing power distribution and fuel consumption, especially during backup operations.
Innovation Solution
A power monitoring system that includes monitors to track power usage from generators, processors to generate load profiles based on various parameters, and calculates predicted available run time by considering critical and non-critical loads, fuel consumption rates, and remaining fuel levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system monitors individual component loads and generates detailed load profiles, then prediction accuracy is improved, but device complexity increases
Solution Approach 1:
The system segments the facility loads into multiple individual component loads, creating separate load profiles for each component. This segmentation allows the system to monitor and predict power consumption at a granular level, improving overall prediction accuracy while managing complexity through modular organization of monitoring data.
Solution Approach 2:
The system performs preliminary actions by monitoring and storing load profile data for each component before generating predictions. Historical load profiles are collected and analyzed in advance, enabling the system to predict future power consumption patterns without requiring complex real-time calculations during prediction events.
2Productivity
If the system categorizes loads into critical and non-critical groups, then productivity is improved, but device complexity increases
Solution Approach 1:
The system applies local quality by assigning different characteristics to different load groups. Critical loads are identified and separated from non-critical loads, allowing the system to apply different prediction and management strategies to each group. This differentiation improves power management efficiency by prioritizing essential loads while simplifying handling of non-essential loads.
Data Source
AI summary
At least one aspect of the invention is directed to a power monitoring system including a generator coupled to a fuel tank, a plurality of monitors, and a processor configured to monitor one or more loads drawing power from the generator; monitor one or more parameters that affect the amount of power drawn by the one or more loads; monitor a fuel consumption rate of the generator; generate one or more load profiles for each of the one or more loads; receive a set of the one or more loads for which a predicted time is to be generated; receive values for the one or more parameters; generate a predicted load profile for the set of the one or more loads and the values of the one or more parameters; receive information indicating an amount of remaining fuel; and calculate a predicted available run time.