Building Energy Simulation Splitting on HVAC Nonoperating Days
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Simulating energy consumption in a building before construction is computationally intensive and prone to errors when parallel simulations are performed without adequate initialization of thermal environment states.
Innovation Solution
A simulation device that splits the simulation period into nonoperating days of the air conditioning system to minimize initialization errors by using holiday conditions, allowing parallel simulations with reduced thermal environment influence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If simulations are done in parallel for respective split periods, then calculation time is reduced, but errors occur in simulations due to inadequate initialization of thermal environment states
Solution Approach 1:
The simulation period is divided into multiple split periods that can be processed in parallel. Each split period is assigned to different calculation units, enabling concurrent execution while maintaining temporal segmentation of the simulation timeline.
Solution Approach 2:
The planning unit pre-processes the simulation period to identify appropriate starting days for each split period. By selecting starting days when thermal environment states are likely to be stable (e.g., non-operating days of air conditioning systems), the system preliminarily establishes conditions that minimize initialization errors before parallel simulation execution begins.
2Productivity
If simulation period is split into multiple periods for parallel processing, then productivity increases, but manufacturing precision decreases due to initialization errors
Solution Approach 1:
The system incorporates feedback mechanisms where the planning unit monitors thermal environment conditions and adjusts the selection of starting days for split periods accordingly. This feedback loop ensures that parallel simulations begin at optimal points in the thermal cycle, maintaining precision while enabling high-speed parallel processing.
Solution Approach 2:
The system dynamically changes the parameter of starting day selection based on thermal environment conditions. By adjusting which days serve as starting points for parallel simulations (e.g., selecting non-operating days when air conditioning systems are off), the system optimizes both processing speed and accuracy through parameter adaptation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Reduces simulation errors by ensuring thermal environment states asymptotically approach steady states during nonoperating days, enabling faster and more accurate energy consumption simulations.
Implementation Method 1
the quantities of state concerning the thermal environment inside the building asymptotically approach a steady state of the nonoperating days
Data Source
AI summary
An acquisition unit (21) acquires a simulation period indicating an object period for which simulations of amounts of energy consumption in a building are to be done, a parallel number indicating the number of the simulations that are to be performed in parallel, and a holiday condition indicating nonoperating days of an air conditioning system installed in the building. A planning unit (22) splits the simulation period into the parallel number to generate split periods. The planning unit (22) splits the simulation period into the parallel number so that starting days of the split periods other than an initial split period may be the nonoperating days indicated by the holiday condition. A simulation unit (23) does the simulations of the amounts of energy consumption in the building in parallel, for the split periods.