KR20230067966A - Air compressor control method for predicting operation pattern and work load - Google Patents

Abstract

According to the present invention, an air compressor control method for analyzing and predicting an operation pattern and a load comprises: a step of being connected between a corresponding air compressor and a reserve tank temporarily storing air, and monitoring and collecting operation time, flow, consumption wattage, the discharge pressure of the compressor, and the storage pressure of the reserve tank in real time; a step of calculating individual SER values (wattage consumed in production of air of 1m^3) and individual efficiency values of a plurality of air compressors based on the collected data, and comparing the individual efficiency values and the individual SER values with a standard efficiency value (air compressor manufacturer efficiency value) and a standard SER value; and a step of comparing the flow, the individual efficiency values, the individual SER values, and the discharge pressure, and the storage pressure with a specific operation pattern in a database during the corresponding operation time to output comparison results. According to the present invention, the air compressor control method for analyzing and predicting an operation pattern and a load can individually control a plurality of air compressors based on a real power consumption pattern such as the usage, operation trend, and workload of a corresponding air compressor to greatly reduce energy in a FEMS environment in units of medium and small factories.

Description

Air compressor control method to analyze and predict operation trend and load {AIR COMPRESSOR CONTROL METHOD FOR PREDICTING OPERATION PATTERN AND WORK LOAD}

The present invention relates to an air compressor control method for analyzing and predicting operation trends and loads, and more particularly, operation that can save energy by comparing not only power consumption but also operation trends and load changes to databased operation patterns. It relates to an air compressor control method that analyzes and predicts trends and loads.

In recent years, the government has focused on allocating government budgets to smart factory construction and advancement projects, and projects related to smart factory solutions and facilities linked to smart factory solutions and facilities, and energy saving related projects are being carried out.

Unlike general factories, smart factories can be applied to all fields of industry, such as various sensors optimized for factory operation and control, robotics control systems, artificial intelligence, data collection, analysis, and algorithms of patterns.

As part of this, a variety of products and services are provided under the FEMS (Factory Energy Management System) environment for the recently expanded, real-time expansion of consumer energy centered on flexible energy demand management for improved efficiency in power supply and demand and energy efficiency analysis through consumer energy analysis. It is becoming.

However, most of these measures are merely managing the maximum power of power facilities based on real-time monitoring at the factory level, and there are multiple air compressor control devices based on this, and the amount of use, operation trend, and workload of the corresponding air compressor Establishment of an efficient control method based on the actual power consumption pattern of the etc. is far away.

The present invention has been proposed to solve the above problems, and it is possible to individually control a plurality of air compressors based on actual power consumption patterns such as usage, operation trend, and workload of the corresponding air compressor, thereby enabling FEMS of small and medium-sized factories. Provides an air compressor control method that analyzes and predicts operation trends and loads that can save energy in the environment.

The present invention has been proposed to solve the above problems, and is connected between a corresponding air compressor and a reserve tank for temporarily storing air, operating time, flow rate, power consumption, discharge pressure of the compressor, and storage of the reserve tank. monitoring and collecting pressure in real time; Based on the collected data, the individual efficiency values and individual SER values (the amount of power consumed in the production of 1㎥ air) of the plurality of air compressors are calculated, and the individual efficiency values and the individual SER values are calculated as standard efficiency values (air compressor manufacturer efficiency value) and standard SER values, respectively; and comparing the flow rate, the individual efficiency value, the individual SER value, the discharge pressure, and the storage pressure with a specific operation pattern on a database and outputting them during the corresponding operation time.

The method may further include controlling an operating time of the corresponding air compressor according to the matched operating pattern.

The controlling of the operation time may be triggered when one of the individual efficiency value and the individual SER value is relatively lower than the standard efficiency value (air compressor manufacturer efficiency value) and the standard SER value in a specific driving pattern on the database. can

The controlling of the operation time may be triggered according to a relative ratio of the discharge pressure to the storage pressure.

In the controlling of the operation time, the flow rate collected per unit time may be activated according to a relative ratio of the maximum flow rate and the manufacturer standard.

The specific driving pattern may be classified according to the driving time of the collected data, and the classified data may be stored using a data mining technique.

An air compressor control method for analyzing and predicting operation trends and loads according to the present invention can individually control a plurality of air compressors based on actual power consumption patterns such as usage, operation trends, and workloads of the corresponding air compressors. Energy savings can be excellent in a factory-level FEMS environment.

1 is a schematic configuration diagram of an air compressor for analyzing and predicting operating trends and loads according to an embodiment of the present invention.
2 is a flow chart of an air compressor control method for analyzing and predicting operating trends and loads according to an embodiment of the present invention.
Figure 3 is a graph for explaining the change in efficiency of the air compressor during operation of the air compressor system.

Hereinafter, an embodiment of an air compressor control method for analyzing and predicting an operation trend and a load according to the present invention will be described in detail with reference to the accompanying drawings.

1 is a schematic configuration diagram of an air compressor for analyzing and predicting operating trends and loads according to an embodiment of the present invention.

2 is a flow chart of an air compressor control method for analyzing and predicting operating trends and loads according to an embodiment of the present invention.

Figure 3 is a graph for explaining the change in efficiency of the air compressor during operation of the air compressor system.

In the air compressor system for analyzing and predicting operation trends and loads according to an embodiment of the present invention, as shown in FIG. 1, a plurality of air compressors 110, 120, and 130 may be connected in parallel. The plurality of air compressors 110, 120, and 130 may be connected to one or more pipelines to provide compressed air adjusted to a specific pressure.

And, the reserve tank 100 may be connected on this pipeline. The reserve tank 100 stores or temporarily stores compressed air, and can supply compressed air to the output side as needed. For example, the compressed air stored in the reserve tank 100 may be compressed air produced and supplied by the air compressors 110 120 and 130 .

Various sensors, that is, a discharge pressure meter 211, a flow meter 212, and a power meter 213 may be connected between the corresponding air compressors 110, 120, and 130 and the reservoir tank 100 for storing air. The discharge pressure meter 211, the flow meter 212, and the power meter 213 are provided for each air compressor, and can sense whether or not the air compressor is operating.

The discharge pressure meter 211, the flow meter 212, and the power meter 213 may be connected to the control unit 300 through a network.

The control unit 300 may control the pressure and flow rate of compressed air supplied through the pipeline. To this end, the controller 300 may include a data collection unit 310, an analysis unit 320, and an output unit 330.

Through the control unit 300, compressed air of constant pressure is provided by selective control of the air compressor according to operating time, pressure, and flow rate.

Referring to FIG. 2, the air compressor control method for analyzing and predicting the operating trend and load by the air compressor system having this configuration is connected between the corresponding air compressor and the reserve tank 100 for temporarily storing air, and operating time Monitoring and collecting the flow rate, the amount of power consumption, the discharge pressure of the compressors 110, 120 and 130, and the storage pressure of the reserve tank 100 in real time (S100); Based on the collected data, the individual efficiency values and individual SER values (the amount of power consumed in producing 1㎥ air) of the plurality of air compressors (110, 120, 130) are calculated, and the individual efficiency values and the individual SER values are standardized Comparing the efficiency value (air compressor manufacturer's efficiency value) with the standard SER value (S200); and comparing the flow rate, the individual efficiency value, the individual SER value, the discharge pressure, and the storage pressure with a specific operation pattern on a database and outputting them at the corresponding operating time (S300); and controlling the operation time of the corresponding air compressor (110, 120, 130) according to the matching operation pattern (S700).

The step of monitoring and collecting in real time (S100) is the pressure measured by installing a discharge pressure gauge 211, a flowmeter 212, and a power meter 213 on the output side of the individual air compressors constituting the plurality of air compressors, per unit time. Operation information such as flow rate and electric power is collected and stored in the data collection unit.

The step of comparing (S200) calculates the individual efficiency values and individual SER values (the amount of power consumed in producing 1 m3 air) of the plurality of air compressors (110, 120, 130) based on the collected data, and the individual efficiency values and the individual SER values may be compared with standard efficiency values (air compressor manufacturer efficiency values) and standard SER values, respectively.

That is, individual efficiency values and individual SER values of the air compressors 110, 120, and 130 are calculated.

[Equation 1]

Efficiency value [ℓ/s/kW] = flow rate [ℓ/s] ㆇ power consumption [kW]

In addition, the individual SER values use Equation 2 below.

[Equation 2]

SER value (kWh/㎥) = power consumption [kWh] ㆇ production flow rate [㎥/min] ㆇ 60 (minutes)

In addition, the standard efficiency value (air compressor manufacturer's efficiency value) and standard SER value (air compressor manufacturer's SER value) may be determined by specifications.

Next, in the step of outputting (S300), the flow rate, the individual efficiency value, the individual SER value, the discharge pressure, and the storage pressure, at the corresponding operation time, can be compared with a specific operation pattern on the database and output. That is, it can be made into a database.

Here, database creation may be preceded in advance and driving patterns may be stored. Each driving pattern is largely classified according to driving time, and then various sensing values may be listed and stored.

Next, controlling the operation time of the corresponding air compressor (110, 120, 130) according to the matching operation pattern (S700) may be performed.

In the step of controlling the operating time (S700), any one of the individual efficiency value and individual SER value is relatively higher than the standard efficiency value (air compressor manufacturer efficiency value) and standard SER value in a specific operating pattern on the database. In this case, it may be triggered (S400).

In this case, the individual efficiency value of each air compressor (110, 120, 130) constituting the plurality of air compressors (110, 120, 130) is compared with the individual standard value indicated on the nameplate, and the air compressor with low efficiency is checked. Determine

Next, a cross-check is performed based on the relative ratio of the discharge pressure to the storage pressure (S500).

Next, the flow rate collected per unit time may be activated according to the relative ratio with the manufacturer standard maximum flow rate (S600).

When all of the above conditions are satisfied, a step of controlling the operating time of the corresponding air compressor (110, 120, 130) is performed. Alternatively, a method of setting the driving time at intervals or turning off the power may be devised.

For example, when the individual efficiency values of the air compressors (110, 120, 130) are higher than the standard value and the individual SER values are less than the average SER value, that is, when both the individual efficiency values and the SER values are operating within the normal range, operation Continuous monitoring while collecting information.

Next, when the efficiency value of the corresponding air compressor (110, 120, 130) or the SER value of the corresponding air compressor is high, the next step is performed.

Cross-check with the relative ratio of the discharge pressure to the storage pressure of the corresponding air compressor (110, 120, 130), and if it is within the preset ratio, the flow rate collected per unit time of the corresponding air compressor is relative to the maximum flow rate based on the manufacturer After determining whether the ratio is within a preset ratio, when all of the above conditions are met, the power of the corresponding air compressor (110, 120, 130) is controlled.

Accordingly, variability within a certain range as shown in (a) to (b) of FIG. 3 is maintained, and power efficiency of, for example, 74% or more can be achieved.

The specific driving pattern may be classified according to the driving time of the collected data, and the classified data may be stored using a data mining technique. A specific pattern is classified by corresponding time, and an index can be provided.

Through this step configuration, it is possible to individually control a plurality of air compressors (110, 120, 130) based on actual power consumption patterns such as usage or operation trends of the corresponding air compressors (110, 120, 130), so small and medium-sized factories. Energy savings can be excellent in the FEMS environment of

In the above, the present invention has been described in detail using preferred embodiments, but the scope of the present invention is not limited to specific embodiments, and should be interpreted according to the appended claims. In addition, those skilled in the art should understand that many modifications and variations are possible without departing from the scope of the present invention.

100: reserve tank 110, 120, 130: air compressor
201: storage pressure gauge 211: discharge pressure gauge
212: flow meter 213: power meter
300: control unit 310: data collection unit
320: analysis unit 330: output unit

Claims (6)

Connected between the air compressor and a reserve tank for temporarily storing air, monitoring and collecting operating time, flow rate, power consumption, discharge pressure of the compressor, and storage pressure of the reserve tank in real time;
Based on the collected data, the individual efficiency values and individual SER values (the amount of power consumed in the production of 1㎥ air) of the plurality of air compressors are calculated, and the individual efficiency values and the individual SER values are calculated as standard efficiency values (air compressor manufacturer efficiency value) and standard SER values, respectively;
Analyzing and predicting the operation trend and load, including the step of comparing the flow rate, the individual efficiency value, the individual SER value, and the discharge pressure and storage pressure with a specific operation pattern on the database at the corresponding operation time and outputting Air compressor control method. According to claim 1,
The air compressor control method of claim 1, further comprising controlling an operation time of the corresponding air compressor according to the matched operation pattern. According to claim 2,
In the step of controlling the operation time, if any one of the individual efficiency value and individual SER value is relatively lower than the standard efficiency value (air compressor manufacturer efficiency value) and standard SER value in a specific driving pattern on the database, An air compressor control method for analyzing and predicting operating trends and loads, characterized in that. According to claim 3,
The step of controlling the operation time is an air compressor control method for analyzing and predicting an operation trend and a load, characterized in that activated according to the relative ratio of the discharge pressure to the storage pressure. According to claim 4,
In the step of controlling the operating time, the air compressor control method for analyzing and predicting the operating trend and load, characterized in that the flow rate collected per unit time is activated according to the relative ratio of the maximum flow rate based on the manufacturer. According to claim 5,
The specific operating pattern is an air compressor control method for analyzing and predicting operating trends and loads, characterized in that the collected data is classified by operating time and the classified data is stored by data mining technique.

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