Undisturbed air conditioner energy-saving system control method

Abstract

The invention discloses an undisturbed air conditioner energy-saving system control method. An upper computer optimization platform and a lower computer self-control platform are included. When the upper computer optimization platform controls the cold source system, the cold source system is firstly controlled to enter a cold state first refrigeration mode, and then the cold source system is controlled by calling the optimization period dynamic change module; when the lower computer self-control platform controls the cold source system, the cold source system is controlled to enter a self-control cold mode; and when the upper computer optimization platform and the lower computer self-control platform are switched, the cold source system is controlled to firstly enter a hot-state first-time refrigeration mode, and then the cold source system is controlled by calling the optimization period dynamic change module. According to the invention, the cold source system can be efficiently controlled without disturbance.

Description

Technical Field

[0001] The invention relates to a control method for an air conditioning cold source system, in particular to a control method for a non-disturbance air conditioning energy-saving system. Background Art

[0002] As the energy shortage problem becomes increasingly prominent, building energy conservation has become a focus of attention. In building energy consumption, central air conditioning system energy consumption accounts for a large proportion, of which refrigeration units account for 50%. Therefore, it is very important to optimize and control the central air conditioning cold source system. The current air conditioning energy conservation solutions mainly include the following:

[0003] 1. By developing a group control system in the controller, interlocking control of equipment such as chillers, refrigeration pumps, cooling pumps, cooling towers, valves, etc. is achieved, and automation and energy saving are achieved through reasonable scheduling and frequency conversion technology.

[0004] 2. By developing a big data energy-saving platform, a large amount of on-site equipment operation data, environmental data, etc. is collected. Through intelligent means such as AI, corresponding control strategies are given according to the predicted cooling load demand, and the on-site equipment is directly controlled by the big data energy-saving platform.

[0005] 3. Integrate solutions 1 and 2, with the controller performing basic group control and the energy-saving platform providing an optimized control solution to jointly complete energy-saving optimization control.

[0006] Although the above methods can achieve automation and energy saving, they also have some defects:

[0007] In the first method, although the controller has the advantages of stability and reliability, its storage capacity and computing power are relatively weak, so it cannot be endowed with AI attributes to achieve intelligent control. It mainly aims at automation and only achieves energy saving through water pump frequency conversion.

[0008] The second method is to utilize the powerful storage capacity, computing power and scalability of the host computer to fully tap the value of the operating data of the cold source system equipment and realize intelligent control through various big data deep learning algorithms. A single host computer often causes system instability due to network problems, which in turn affects the stable operation of the cold source system.

[0009] The third method was originally designed to give full play to the intelligence of the upper computer and the stability of the lower computer to build an energy-saving solution that integrates the upper and lower computers. However, due to communication problems between the upper and lower computers, consistency problems of control strategies, stability problems of platform switching, etc., the final effect is not ideal and it cannot operate stably for a long time.

[0010] Therefore, although the current cold source group control system has increasingly reflected intelligence in practical applications, there are still some problems when the AI ​​platform and the controller jointly complete the energy-saving control of the on-site cold source, such as the switching of the upper and lower control platforms is prone to instability, the conflict of the upper and lower computer optimization strategies leads to frequent start and stop of equipment, and the fixed optimization cycle leads to the untimely issuance of optimization strategies. It is urgent to design a disturbance-free air-conditioning energy-saving system optimization method. Summary of the invention

[0011] The object of the present invention is to provide a disturbance-free air conditioning energy-saving system control method. The present invention can control the cold source system without disturbance and efficiently.

[0012] The technical solution of the present invention is as follows: a disturbance-free air conditioning energy-saving system control method, comprising an upper computer optimization platform and a lower computer automatic control platform; when the upper computer optimization platform controls the cold source system, the cold source system is first controlled to enter a cold state first cooling mode, and then the cold source system is controlled by calling an optimization cycle dynamic change module; when the lower computer automatic control platform controls the cold source system, the cold source system is controlled to enter an automatic control cooling mode; when switching between the upper computer optimization platform and the lower computer automatic control platform, the cold source system is controlled to enter a hot state first cooling mode, and then the cold source system is controlled by calling an optimization cycle dynamic change module.

[0013] In the aforementioned disturbance-free air-conditioning energy-saving system control method, the optimization cycle dynamic change strategy of the optimization cycle dynamic change module is: set the initial optimization cycle, and re-search the optimization control strategy every optimization cycle. If no new optimization control strategy is generated after an optimization cycle, the optimization cycle will be shortened to 1 / 3 of the original one, until it is shortened to 20 seconds per cycle; after a new optimization control strategy is generated, it will be restored to the initial optimization cycle.

[0014] In the aforementioned disturbance-free air conditioning energy-saving system control method, the initial optimization cycle is 30 minutes.

[0015] In the aforementioned disturbance-free air conditioning energy-saving system control method, the cold state first cooling mode is: the cold source system is turned on for the first time under the control of the upper computer optimization platform, and maintains an initial optimization cycle.

[0016] In the aforementioned disturbance-free air conditioning energy-saving system control method, the hot first cooling mode means that when the upper computer optimization platform and the lower computer automatic control platform are switched, the cold source system is already in operation, and is in the hot first cooling mode during the optimization cycle; the cold source system runs an initial optimization cycle in the hot first cooling mode.

[0017] In the aforementioned disturbance-free air conditioning energy-saving system control method, the automatic cooling mode refers to controlling the cold source system through the lower computer automatic control platform.

[0018] In the aforementioned disturbance-free air conditioning energy-saving system control method, optimizing the cooling mode refers to controlling the cold source system through the upper computer optimization platform, and the cold source system is in a non-cold cooling mode and a hot first cooling mode.

[0019] Compared with the prior art, the present invention defines two sets of platforms (host computer optimization platform and slave computer automatic control platform), and accordingly sets four refrigeration modes (cold state first refrigeration mode, hot state first refrigeration mode, self-control refrigeration mode, optimization refrigeration mode), when the host computer optimization platform controls the cold source system, first controls the cold source system to enter the cold state first refrigeration mode, and then controls the cold source system by calling the optimization cycle dynamic change module; when the slave computer automatic control platform controls the cold source system, controls the cold source system to enter the self-control refrigeration mode; meanwhile, when switching between the host computer optimization platform and the slave computer automatic control platform, controls the cold source system to enter the hot state first refrigeration mode first, and then controls the cold source system by calling the optimization cycle dynamic change module. The present application effectively avoids the two control brains of the upper and lower computers through multiple refrigeration modes of the upper and lower computers, and issues instructions at the same time, causing the unstable operation of the cold source system. The present application not only avoids the optimization in an unstable state by setting a dynamic periodic scheduling optimization module, but also improves the optimization sensitivity by dynamically shortening the optimization cycle, and solves the problem of being able to quickly respond to optimization needs when there is no new control strategy for a long time. In summary, the present invention can control the cold source system without disturbance and efficiently. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 is a control flow chart of the present invention;

[0021] Figure 2 It is the control flow chart of the dynamic change module of the optimization cycle. DETAILED DESCRIPTION

[0022] The present invention is further described below in conjunction with the accompanying drawings and embodiments, but they are not intended to limit the present invention.

[0023] Embodiment. A disturbance-free air conditioning energy-saving system control method, comprising: Figure 1 As shown, it includes an upper computer optimization platform and a lower computer automatic control platform;

[0024] When the upper computer optimization platform controls the cold source system, it first controls the cold source system to enter the cold state first cooling mode, and then controls the cold source system by calling the optimization cycle dynamic change module;

[0025] When the lower computer automatic control platform controls the cold source system, the cold source system is controlled to enter the automatic control cooling mode;

[0026] When switching between the upper computer optimization platform and the lower computer automatic control platform, the cold source system is controlled to enter the hot first cooling mode first, and then the cold source system is controlled by calling the optimization cycle dynamic change module.

[0027] The optimization cycle dynamic change strategy of the optimization cycle dynamic change module is: set the initial optimization cycle, and re-search the optimization control strategy every optimization cycle. If no new optimization control strategy is generated after an optimization cycle, the optimization cycle will be shortened to 1 / 3 of the original one, until it is shortened to 20 seconds per cycle; after a new optimization control strategy is generated, it will be restored to the initial optimization cycle.

[0028] The initial optimization cycle is 30 minutes.

[0029] The first cooling mode in cold state is: the cooling source system is turned on for the first time under the control of the upper computer optimization platform, and an initial optimization cycle is run to avoid optimization just after the system is turned on and not yet completely stable, which may cause the optimization results to deviate from the actual situation.

[0030] The hot first cooling mode means that when the upper computer optimization platform and the lower computer automatic control platform are switched, the cold source system is already in operation, and it is the hot first cooling mode during the optimization cycle; the cold source system runs an initial optimization cycle in the hot first cooling mode. Avoid different control strategies on different platforms, which may cause system instability.

[0031] The automatic cooling mode refers to controlling the cooling source system through the lower computer automatic control platform.

[0032] The optimized cooling mode refers to the control of the cold source system through the upper computer optimization platform, and the cold source system is in the non-cold cooling mode and the hot first cooling mode.

[0033] The upper computer optimization platform calls the optimization cycle dynamic change module's optimization cycle dynamic change strategy (such as Figure 2 The upper computer optimization platform can set the initial optimization cycle (the default is 30 minutes), and the optimization control strategy will be searched again every other optimization cycle ( Figure 2 ), the optimization frequency should not be too fast. The cold source system is a large lag system. If the optimization frequency is too fast, it will lead to. If no new control strategy is generated after an optimization cycle, the optimization cycle will be shortened to 1 / 3 of the original, until a cycle of 20 seconds. After a new control strategy is generated, it will be restored to the default optimization cycle (default 30 minutes). The optimization formula algorithm is as follows:

[0034] The initial value T0=30, Flag is a mark indicating whether a new strategy appears. When the value is 1, it means that a new strategy is searched.

[0035] The present invention constructs a stable and efficient control method for central air conditioning cold source group control, which is applied to the cold source group control system developed in the edge controller. The present invention avoids the optimization in an unstable state through dynamic periodic scheduling, and improves the optimization sensitivity by dynamically shortening the optimization cycle, so as to quickly respond to optimization needs when there is no new control strategy for a long time.

[0036] Through the design of multiple cooling modes for the upper and lower computers, the situation where the two control brains of the upper and lower computers issue commands at the same time, causing unstable operation of the cold source system, is effectively avoided.

Claims

1. A disturbance-free air conditioning energy-saving system control method, characterized in that: Including upper computer optimization platform and lower computer automatic control platform; When the upper computer optimization platform controls the cold source system, it first controls the cold source system to enter the cold state first cooling mode, and then controls the cold source system by calling the optimization cycle dynamic change module; When the lower computer automatic control platform controls the cold source system, the cold source system is controlled to enter the automatic control cooling mode; When switching between the upper computer optimization platform and the lower computer automatic control platform, the cold source system is controlled to enter the hot first cooling mode first, and then the cold source system is controlled by calling the optimization cycle dynamic change module.

2. The non-disturbance air conditioning energy-saving system control method according to claim 1, characterized in that: The optimization cycle dynamic change strategy of the optimization cycle dynamic change module is: set the initial optimization cycle, and re-search the optimization control strategy every optimization cycle. If no new optimization control strategy is generated after an optimization cycle, the optimization cycle will be shortened to 1 / 3 of the original one, until it is shortened to 20 seconds per cycle; after a new optimization control strategy is generated, it will be restored to the initial optimization cycle.

3. The non-disturbance air conditioning energy-saving system control method according to claim 1, characterized in that: The initial optimization cycle is 30 minutes.

4. The non-disturbance air conditioning energy-saving system control method according to claim 1, characterized in that: The cold first cooling mode is: the cold source system is turned on for the first time under the control of the upper computer optimization platform and runs an initial optimization cycle.

5. The non-disturbance air conditioning energy-saving system control method according to claim 1, characterized in that: The hot first cooling mode means that when the upper computer optimization platform and the lower computer automatic control platform are switched, the cold source system is already in operation, and it is the hot first cooling mode during the optimization cycle; The cold source system runs an initial optimization cycle in the hot first cooling mode.

6. The non-disturbance air conditioning energy-saving system control method according to claim 1, characterized in that: The automatic cooling mode refers to controlling the cooling source system through the lower computer automatic control platform.

7. The non-disturbance air conditioning energy-saving system control method according to claim 1, characterized in that: The optimized cooling mode refers to the control of the cold source system through the upper computer optimization platform, and the cold source system is in the non-cold cooling mode and the hot first cooling mode.

Images