Hydronic Network Balancing Using Centralized Pressure-Flow Modeling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing hydronic heating and cooling systems face challenges in balancing distributed networks, leading to inefficiencies such as increased energy consumption, overheating, and instability due to decentralized, iterative methods that require manual adjustments and specialized equipment.
Innovation Solution
A centralized, non-iterative model-based multivariable balancing approach using global differential pressure/flow rate information, where a simplified mathematical model of the hydronic system is created, and balancing valve settings are calculated to minimize pressure drops across selected valves, implemented as a computer program to support application engineers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If decentralized iterative methods are used for balancing, then each balancing valve can be controlled independently, but the system requires special equipment on each valve and multiple iterations which decreases economic performance and increases time consumption
Solution Approach 1:
The patent merges all balancing valve controls into a centralized system where a single controller manages all valves through a unified interface. This eliminates the need for special equipment on each individual valve while maintaining independent control capability through software-based management of all balancing operations.
Solution Approach 2:
The centralized controller serves multiple functions: it controls all balancing valves, processes measurements from the entire network, performs calculations for optimal settings, and provides a user interface. This multi-functional approach replaces the need for specialized single-purpose equipment at each valve location.
2Ease of operation
If decentralized iterative methods are used for balancing, then each balancing valve can be adjusted locally, but a number of iterations are required which is time consuming
Solution Approach 1:
The system performs preliminary measurements of the entire hydronic network before calculating balancing valve settings. By collecting all necessary data upfront and performing comprehensive calculations in advance, the system determines optimal settings in a single pass rather than requiring multiple iterative adjustments, significantly reducing time consumption.
Solution Approach 2:
The system implements a feedback mechanism where measurements from pressure sensors and flow meters are continuously monitored. The controller uses this feedback to verify balancing results and make minimal adjustments if needed, rather than requiring multiple full iterations. The feedback confirms when optimal settings are achieved.
3Ease of operation
If manual balancing adjustments are made, then operators can control each valve, but energy consumption increases due to increased pump head and hot water supply temperatures
Solution Approach 1:
The system enables self-service balancing where the automated controller determines and implements optimal valve settings without requiring manual operator intervention. The controller autonomously adjusts all balancing valves based on measured network conditions, eliminating the need for operators to increase pump head or water temperatures to compensate for poor balancing, thereby reducing energy consumption.
4Ease of operation
If decentralized balancing control is used, then individual valves can be adjusted independently, but the approach decreases economic performance of the overall system
Solution Approach 1:
The patent consolidates all control functions into a single centralized controller, eliminating the need for expensive specialized equipment at each balancing valve location. This merging approach maintains independent control capability through software while significantly reducing hardware costs and improving overall economic performance of the system.
Data Source
AI summary
A method and system for optimal model-based multivariable balancing for distributed hydronic networks based on global differential pressure/flow rate information. A simplified mathematical model of a hydronic system can be determined utilizing an analogy between hydronic systems and electrical circuits. Thereafter, unknown parameters can be identified utilizing the simplified mathematical model and a set of available measurements. Next, balancing valve settings can be calculated by reformulating the simplified mathematical model based on the parameterized model. The sum of pressure drops across selected balancing valves can be then minimized to achieve optimal economic performances of the system. The data can be collected and transferred to a central unit either by wireless communication or manually by reading the local measurement devices. Such a multivariable balancing approach provides a fast and accurate balancing of distributed hydronic heating systems based on a centralized and non-iterative approach.