1. Different control principles
General-purpose frequency converter control uses a general-purpose frequency converter to individually control the motors of pumps and fans. When the control system detects a controlled variable, it performs control based on a linear combination of proportional (P), integral (1), and derivative (D) functions, i.e., PID control, according to the error between this variable and the setpoint. This control method is only suitable for linear systems and for controlling a single object.
The dynamic variable flow energy-saving control system employs a control principle combining fuzzy control and variable frequency technology. While it does use a general-purpose variable frequency drive (VVVF), it does not use PID control but rather a fuzzy control method. This means that throughout the system control process, human knowledge is described in language and represented as fuzzy rules or relationships. Through reasoning and utilizing a knowledge base, certain knowledge is combined with the process state to achieve control behavior. It does not have a clear PID structure, but can be called a nonlinear PID controller. It determines the controller parameters based on the system's error signal and the derivative or difference of the error, making it particularly suitable for nonlinear and time-varying controlled objects.
2. Differences in control methods
The controlled parameters of a central air conditioning system are influenced by a combination of factors, including seasonal variations, environmental changes, usage time, and passenger flow. Therefore, it is a random variable, not a linear system, but rather a nonlinear system. Consequently, the demand for chilled (warm) water flow and temperature, as well as cooling water flow and temperature, is also a random variable.
The most important control parameters used in general-purpose frequency converters, such as the proportional coefficient K, integral time constant T1, and derivative time constant Td, are determined using empirical or experimental data and cannot be automatically adjusted once selected. Therefore, PID control systems are only suitable for linear systems and cannot achieve optimal control for nonlinear systems. That is, after selecting the proportional coefficient and time constant, using the same control method to deal with various different load conditions will obviously not yield ideal results.
Fuzzy control systems do not require accurate measurement of the controlled variable's value, but they take into account the various possibilities of the controlled variable, track changes in the controlled parameters, and always keep the controlled system in the optimal operating state. They can provide optimal decision-making for various nonlinear and time-varying systems.
3. Differences in control effect
When using PID control in general-purpose frequency converters to control nonlinear systems, it easily causes strong oscillations in the central air conditioning system, leading to wide fluctuations in the control range, increased energy consumption, and prolonged periods without reaching a stable setpoint. The control effect is unsatisfactory, resulting in energy savings of only 20%-30% for the chilled water pumps, cooling water pumps, and cooling tower fans配套的设备 (equipped with the main unit). Because measures are taken to ensure the chiller unit's operational status, fuel and main unit power savings are impossible. Furthermore, resource sharing and unattended operation are not feasible.
The dynamic variable flow energy-saving control system, due to its optimized fuzzy control model, provides sufficient estimates for potential problems in the central air conditioning system. Therefore, the overall decision table stored in the calculation provides the optimal control scheme, resulting in good system stability, minimal oscillations, and rapid steady-state operation. Energy savings can be achieved by correctly adjusting the flow rate, with uniform energy savings of 60%-80% for water pumps and cooling towers. Special measures ensure high conversion efficiency of the central air conditioning unit, keeping the unit's COP at its optimal value. Therefore, fuel savings of 20%-40% can be achieved for absorption lithium bromide units, and electricity savings of 10%-30% for electric chillers.
Dynamic variable flow control boasts powerful energy-saving capabilities. System integration is incorporated during the system design phase, enabling the linkage and interoperability of various subsystems and achieving resource sharing. Its robust automation features allow for unattended operation and networked management, saving manpower and resources. These are features that general-purpose variable frequency control systems cannot achieve.
