Energy Consumption Estimating System for Building Devices
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Solution Overview
Problem
Current building monitoring systems cannot estimate the energy-saving and emission-reduction benefits of replacing existing energy-consumption devices with new ones, limiting their ability to help users achieve the goal of zero emissions.
Innovation Solution
An estimating system and method that includes an IO module connected to energy-consumption devices to collect operating parameters, a server that analyzes these parameters, and a simulating module to calculate the energy-consumption and carbon-emission results of new devices, allowing for a replacement-benefit estimation based on historical data and performance coefficients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If building monitoring systems only analyze current-existing devices, then the system complexity remains low, but the ability to estimate energy-saving benefits of new devices is lost
Solution Approach 1:
The system performs preliminary actions by collecting and storing operating parameters and energy-consumption data from current devices before replacement. This historical data is preserved and used later for simulation purposes, enabling benefit estimation without requiring actual new devices to be installed for testing.
Solution Approach 2:
The system creates a virtual copy of the current device's operating characteristics through simulation. By replicating the device model with simulated parameters based on historical data, the system can evaluate new devices virtually without physical installation, thus avoiding increased system complexity while gaining estimation capability.
2Reliability
If no simulation of new devices is performed, then the system operation is simple, but users cannot make informed decisions about device replacement
Solution Approach 1:
The system introduces a simulation module as an intermediary between historical data and decision-making. This module acts as a mediator that translates past operating parameters into predictive information about new device performance, providing reliable basis for decisions without direct complex interaction between data storage and decision processes.
Solution Approach 2:
The simulation performs preliminary evaluation of new devices before actual replacement decisions are made. By pre-calculating energy-saving benefits and performance metrics through simulation, the system ensures reliable decision-making foundation is established in advance, reducing the need for complex post-installation adjustments.
3Measurement precision
If detailed operating parameters are collected and simulated, then the energy-saving estimation precision is improved, but the data processing complexity increases
Solution Approach 1:
The system extracts only the essential operating parameters that significantly impact energy consumption from the complete set of collected data. By identifying and isolating key parameters such as operating hours, load factors, and environmental conditions, the system achieves precise estimation without processing all available data, thus reducing complexity while maintaining accuracy.
Solution Approach 2:
The system transforms detailed operating parameters into simplified simulation inputs through parameter aggregation and normalization. By converting raw data into meaningful performance indicators and using parameter scaling techniques, the system maintains estimation precision while reducing the computational complexity of data processing.
Data Source
AI summary
An estimating system for energy-saving and emission-reduction is provided and includes an energy-consumption device operating in the environment based on multiple operating parameters to generate an energy-consumption and carbon-emission result and a server for receiving and storing corresponding values of each operating parameter of the energy-consumption device. The server includes an energy-consumption factor analyzing module for selecting multiple energy-consumption factors relevant to power-consumed amount and carbon-emitted amount from the multiple operating parameters, a new-device-parameter importing module for importing multiple performance coefficients of multiple new devices, and a simulating module for performing a simulation and calculating an energy-consumption simulated result of each new device as if each new device were operated under same environment within a specific historical time-period. The server performs a replacement-benefit estimating procedure for each new device based on the energy-consumption and carbon-emission result of the energy-consumption device and the energy-consumption simulated results of each new device.