Central Cooling Control for Chiller Load and Pump Speed Optimization
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Solution Overview
Problem
Existing HVAC systems lack sophisticated energy management, focusing primarily on user-selected cooling performance without optimizing for energy efficiency, leading to suboptimal energy consumption.
Innovation Solution
A central cooling and circulation energy management control system, including an energy management controller device with processors, memory elements, and sensors, that determines operational control signals based on equipment data, configuration tables, and operational efficiency matrices to optimize energy efficiency in HVAC operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If conventional HVAC control systems are used, then user-selected cooling performance is achieved, but energy consumption is suboptimal
Solution Approach 1:
The control system continuously monitors operational parameters (temperatures, pressures, flow rates) from sensors and uses this feedback to dynamically adjust chiller loading, pump speeds, and valve positions. This closed-loop feedback mechanism enables real-time optimization of energy consumption while maintaining cooling performance, resolving the contradiction between energy efficiency and system complexity.
Solution Approach 2:
The system transitions from static, fixed-setpoint control to dynamic control that continuously adapts to changing operational conditions. By dynamically adjusting chiller loading ratios, variable speed pump operations, and cooling tower fan speeds based on real-time measurements, the system optimizes energy consumption without requiring overly complex infrastructure.
2Use of energy by moving object
If chiller loading is optimized for energy efficiency, then energy consumption per unit cooling load decreases, but system operational complexity increases
Solution Approach 1:
The control system performs self-optimization by automatically calculating optimal chiller loading ratios and adjusting operational parameters without requiring manual intervention. The processor autonomously analyzes sensor data, applies optimization algorithms, and executes control adjustments, making the system self-managing and reducing operational complexity despite advanced energy optimization capabilities.
Solution Approach 2:
The system optimizes energy consumption by dynamically changing operational parameters such as chiller loading ratios, pump speeds, and valve positions. These parameter adjustments are automatically managed by the control processor, which translates complex optimization requirements into simple executable control actions, maintaining ease of operation while achieving energy efficiency.
3Loss of energy
If multiple control parameters are adjusted for optimization, then energy efficiency improves, but control system complexity increases
Solution Approach 1:
The control processor serves multiple functions simultaneously: it monitors sensor inputs, calculates optimal operating points, adjusts chiller loading ratios, controls pump speeds, and logs operational data. This multi-functional integration consolidates what would otherwise require separate control systems into a single universal controller, improving energy efficiency without proportionally increasing overall system complexity.
Data Source
AI summary
A novel central cooling and circulation energy management control system is provided, including an energy management controller device, a central cooling system, and associated methods, according to various embodiments. In one illustrative embodiment, a central cooling energy management controller device includes one or more signal connections, one or more electronic memory elements, and one or more processors. The controller device has access to resources that are either stored on the electronic memory elements or are accessible via the signal connections. The resources include an equipment data table, an equipment and operational configuration table, an operational efficiency matrix, and executable instructions. The processor determines operational control signals for energy-efficient operation of a central cooling system, based on sensor input from the central cooling system, and on data from the equipment data table, the equipment and operational configuration table, and the operational efficiency matrix; and provides the operational control signals via the signal connections.