Method for detecting a storm and for avoiding storm-induced deactivations in networked heating systems
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Solution Overview
Problem
Modulating fuel-operated heating systems, particularly gas condensing boilers, face issues with device shutdowns and reduced operational reliability due to wind-induced pressure fluctuations during storms, leading to unstable combustion and decreased heating comfort.
Innovation Solution
A networked method where a central data acquisition system collects storm warnings and error messages from individual heating systems, adjusting the modulation range of connected heating systems to maintain stable combustion by increasing minimum fan speeds or restricting modulation ranges during storm conditions, and reverting changes once the storm phase ends.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the blower speed is reduced to achieve high modulation capability and energy efficiency, then energy consumption is reduced and modulation range is improved, but combustion stability deteriorates due to increased sensitivity to pressure fluctuations from wind gusts
Solution Approach 1:
The system performs preliminary detection of storm conditions through weather services or preliminary error message collection from heating systems before combustion instability occurs. When storm conditions are detected or preliminary errors are accumulated, the control raises the minimum load of the modulation range in advance, increasing the blower speed before the storm fully impacts the system. This preliminary action prevents flame tear-off and flashback by ensuring sufficient pressure differential exists before wind gusts arrive.
Solution Approach 2:
The system dynamically adjusts the modulation range based on detected storm conditions. The minimum load is raised from its normal low value to a higher value during storm conditions, and this adjustment is temporary and reversible. When storm conditions cease, the system automatically lowers the minimum load back to its original value. This dynamic adaptation allows the system to maintain combustion stability during storms while preserving energy efficiency during normal operation.
2Reliability
If the minimum load is raised to improve combustion stability during storms, then operational reliability is improved, but energy consumption increases and modulation flexibility is reduced
Solution Approach 1:
The system dynamically adjusts the modulation range based on detected storm conditions. The minimum load is raised from its normal low value to a higher value during storm conditions, and this adjustment is temporary and reversible. When storm conditions cease, the system automatically lowers the minimum load back to its original value. This dynamic adaptation allows the system to maintain combustion stability during storms while preserving energy efficiency during normal operation.
Solution Approach 2:
The system continuously monitors storm conditions through weather services or collects feedback from preliminary error messages indicating flame failures. Based on this feedback, the control adjusts the minimum load accordingly. When feedback indicates storm conditions are present, the minimum load is raised. When feedback indicates storm conditions have ceased or a specified time has passed, the minimum load is lowered. This feedback mechanism ensures energy is consumed only when necessary for stability.
3Reliability
If real-time storm detection and network communication are implemented to maintain stable combustion, then operational reliability is improved, but device complexity increases
Solution Approach 1:
The system uses a weather service or network communication system as an intermediary to detect storm conditions. Rather than requiring complex local sensing equipment, the heating system receives storm warning information from external weather services through network connections. This intermediary approach provides reliable storm detection while keeping the local system complexity relatively low, as the heavy lifting of weather data collection and processing is performed by the external service.
Solution Approach 2:
The system enables heating systems to send preliminary error messages automatically when flame failures occur, and the central server collects and analyzes these messages. This self-service mechanism allows the network to autonomously detect storm patterns without requiring constant external monitoring. The system uses its own operational data (error messages) to trigger the modulation range adjustment, reducing the need for complex external detection infrastructure.
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
Ensures trouble-free operation of fuel-operated heating systems by stabilizing combustion and maintaining heating comfort and operational reliability during storms by dynamically adjusting the modulation range based on real-time data and weather information.
Implementation Method 1
the pressure difference in the air/exhaust gas system generated by the blower
Implementation Method 2
the amount of fuel gas and air conveyed into the combustion chamber
Data Source
AI summary
A method for operating modulating, fuel-fired heating systems with a network connection involves increasing the maximum output of a modulation range as needed. Individual heating systems, if they shut down without prior fuel shut-off, send an initial notification to a central data acquisition point in the network. If several faults occur in a specific area within a certain period, the minimum load of the heating systems in that area is increased. This information can also originate from a weather service.