KR101855680B1 - System and method for saving fan power of air conditioner and energy using multiple regression analysis and time series estimation of filter change point - Google Patents

Abstract

The present invention relates to a system and a method for saving energy using fan power of an air conditioner according to the optimum filter replacement point presented utilizing the multiple regression analysis and the time series estimation. The energy saving system comprises: a filter information input unit receiving basic information of a filter; an air conditioner state analyzing unit for creating state information of the air conditioner; a filter differential pressure analyzing unit for creating filter differential pressure analysis information by receiving a filter differential pressure change according to an accumulated air volume of the air conditioner and an air volume change according to an open rate and an accumulation amount of an external damper of the air conditioner; an indoor differential pressure deducting unit for creating indoor and outdoor differential pressure change information; and a replacement time deducting unit for creating filter replacement time information according to a fan motor power change rate by filter differential pressure. The energy saving system and method can enhance life cycle costs of a building by deducting a duct static pressure change dependent on a differential pressure increase of the air conditioner filter and deducting the optimum replacement time of the filter through time-series analysis of a change in energy of a blowing power device due to filter plugging of the air conditioner.

Description

FIELD OF THE INVENTION The present invention relates to a system and method for energy reduction using an air conditioner fan power according to the presentation of a filter optimum replacement point by using multiple regression analysis and time series evaluation, CHANGE POINT}

The present invention relates to a system and method for reducing energy using an air conditioner fan power according to multiple filter regression and time series evaluation, and more particularly, to a system and method for reducing energy using an air conditioner fan power when an air conditioner filter is clogged. In order to solve the problem that the air flow supplied is reduced, the power load increases according to the operation of heating and cooling for maintaining a constant temperature inside the building, and the lifetime cost of the building increases as the cooling / heating ratio increases, The present invention relates to a technique for improving the life-time cost of a building by deriving an optimal replacement point of the filter by analyzing the energy change of the apparatus in a time-wise manner.

The application of air conditioning equipment in buildings is essential, and the ratio of energy required for air conditioning equipment among the annual energy consumption of office buildings is about 47.3%, and the energy of air conditioning fan power equipment It accounts for about 9.5% of total energy. In addition, it is shown that the ratio of the cost of the LCC of the building to the maintenance stage after the completion of the building is high. Therefore, in order to reduce the cost, development of the energy management technology, Do.

In other words, in order to reduce the energy in the air-conditioning system, it is necessary to establish an operation method for maximizing the efficiency of the entire system while improving the efficiency of the individual devices.

The filter installed inside the building air conditioner functions as an air purifier to maintain the cleanliness of the room through purifying the air to be taken in. It is used for indoor hygiene environment and product productivity improvement according to the purpose of use . However, when this filter is blocked, the air flow can not be smoothly communicated, which affects the indoor air environment as well as the energy efficiency of the system, raising the blowing power electrical energy.

In order to prevent this, in the automatic control (BA) of the facility, the pressure difference before and after the filter is monitored in real time to prevent the filter from clogging, but the quantitative reduction effect of the blowing power that can be achieved through this is not yet reported.

In addition, although the filter management cycle of the air conditioner in the current building differs depending on the inside / outside environment of the building, most of them are processed simply by a regular periodical operation by the experience of the filter maker and the manager, There is a need for an effective filter management standard that can improve the working environment and reduce the cost because labor and material costs are introduced and the blowing power is increased due to clogging of the filter.

Korean Registration Practice No. 20-0164637

It is an object of the present invention to provide a method and a device for deriving the change in the duct static pressure due to an increase in the pressure difference of the air conditioner filter and to obtain an optimum replacement point of the filter by analyzing the energy change of the wind power device according to the clogging of the air conditioner, And to provide an air conditioner filter management system and a method thereof that improve cost.

According to an aspect of the present invention, there is provided an energy reduction system using an air conditioner fan power according to a filter optimal replacement point by using a multiple regression analysis and a time series evaluation, ; An air conditioner status analyzing unit for generating air conditioner status information including air supply and ventilation for the air conditioner, change in ambient temperature and outdoor air damper opening, CO2 concentration and outdoor air damper opening rate, indoor and outdoor differential pressure, fan inverter, outdoor damper opening rate, ; A filter differential pressure analyzer for generating filter differential pressure analysis information by analyzing a change in the filter differential pressure according to the cumulative air flow rate of the air conditioner and a change in the air flow rate according to the opening rate and accumulation amount of the air conditioner ambient air damper and analyzing an influence of the opening rate of the outside air damper on the filter differential pressure; The basic information is applied to measure the filter differential pressure of the inverter fan size of the supply fan, the regular air flow rate of the air conditioner, and the variable air flow rate to determine the inverter change rate of the fan according to the air flow rate change and filter clogging, An indoor differential pressure deriving unit for generating differential pressure change information; And a replacement timing derivation unit for synthesizing the basic information, the air conditioner state information, the filter differential pressure analysis information, and the indoor / outdoor differential pressure change information to generate filter replacement time information according to the fan motor power change rate by the filter differential pressure .

Preferably, the basic information includes at least one of a filter type (prefilter and medium filter), price unit price, replacement cost, rated capacity for the air conditioner and motor, season / hour power unit price And a cumulative increase amount.

The filter differential pressure analyzing unit receives the basic information including the rated capacity for the air conditioner and the motor from the filter information input unit for generating the filter differential pressure analysis information and is configured to receive the CO2 concentration and the outdoor air damper opening rate from the air conditioner condition analyzing unit And an air flow rate measuring sensor for deriving the filter differential pressure in proportion to the air flow rate of the air conditioner.

The constant air flow rate is measured by varying the blowing temperature while keeping the air flow rate constant, and the variable air flow rate is measured by changing the blowing amount according to the variation of the room load with a single duct configuration and keeping the blowing temperature constant.

The filter replacement point-in-time information includes at least one of a filter element including an air conditioner filter type, a management method, a management cost, an air conditioning method and management cycle data, an electric element including an air conditioner operation time, an electric power increase amount, The cost of the filter, the cost of the fan power, and the cost of the fan power.

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According to the present invention as described above, the change in the duct static pressure due to the increase in the pressure difference of the air conditioner filter is derived, and the optimum change point of the filter is derived by analyzing the energy change of the air- Management has the effect of improving the life cost of the building.

FIG. 1 is a block diagram illustrating an energy reduction system using an air conditioner fan power according to an embodiment of a multi-regression analysis and time series evaluation according to an embodiment of the present invention.
FIG. 2 is a flowchart illustrating an overall process of an energy reduction system using an air conditioner fan power according to a filter optimal replacement point presentation using a multiple regression analysis and a time series evaluation according to an embodiment of the present invention.
3 is a graph showing a result of a constant air flow test of an energy reduction system using an air conditioner fan power according to a filter optimal replacement point presentation using a multiple regression analysis and a time series evaluation according to an embodiment of the present invention.
FIG. 4A is a graph showing the relationship between the inverter ratio of the air supply fan and the fan power value in the variable airflow condition of the energy reduction system using the fan power of the air conditioner according to the filter optimal replacement point presentation using the multiple regression analysis and the time series evaluation according to the embodiment of the present invention Fig.
FIG. 4B is a graph showing the relationship between the filter clogging point and the filter clogging point from the filter replacement start point under the varying air flow conditions of the energy reduction system using the air conditioner fan power according to the filter optimal replacement point presentation using the multiple regression analysis and the time series evaluation according to the embodiment of the present invention The analysis of elapsed time until reaching.
FIG. 4c is a graph showing the relationship between the period from the starting point to the clogging point after the filter replacement under the variable airflow condition of the energy reduction system using the fan power of the air conditioner according to the filter optimal replacement point presentation using the multiple regression analysis and the time series evaluation according to the embodiment of the present invention. Lt; RTI ID = 0.0 > a < / RTI >
FIG. 5 is a graph showing an example of a filter clogging alarm according to inverter size of an air supply fan under an ambient air flow condition of an energy reduction system using an air conditioner fan power according to an embodiment of a multiple regression analysis and a time series evaluation according to an embodiment of the present invention. Fig.
6 is a diagram illustrating a filter optimum replacement cost model of an energy reduction system using an air conditioner fan power according to a filter optimal replacement point presentation using a multiple regression analysis and a time series evaluation according to an embodiment of the present invention.
FIG. 7 is a diagram illustrating a filter optimum replacement point of an energy reduction system using an air conditioner fan power according to a filter optimal replacement point presentation using a multiple regression analysis and a time series evaluation according to an embodiment of the present invention; FIG.
FIG. 8 is a diagram showing a filter differential pressure analysis result in a short term of an energy reduction system using an air conditioner fan power according to a filter optimal replacement point presentation using a multiple regression analysis and a time series evaluation according to an embodiment of the present invention. FIG.
9 is a graph showing a result of a filter differential pressure analysis in a long-term aspect of an energy reduction system using an air conditioner fan power according to a filter optimal replacement point presentation using a multiple regression analysis and a time series evaluation according to an embodiment of the present invention.
FIG. 10 is a flowchart illustrating an energy reduction method using an air conditioner fan power according to a filter optimal replacement point presentation using a multiple regression analysis and a time series evaluation according to an embodiment of the present invention. FIG.
FIG. 11 is a flowchart illustrating a detailed procedure of a step S10 of an energy reduction method using an air conditioner fan power according to a filter optimal replacement point presentation using a multiple regression analysis and a time series evaluation according to an embodiment of the present invention.
FIG. 12 is a flowchart illustrating a detailed procedure of an energy reduction method using an air conditioner fan power according to an exemplary embodiment of the present invention using a multiple regression analysis and a time series evaluation. FIG.
FIG. 13 is a flowchart illustrating a detailed procedure of step S30 of the energy reduction method using the fan power of the air conditioner according to the filter optimal replacement point presentation using the multiple regression analysis and the time series evaluation according to an embodiment of the present invention.
FIG. 14 is a flowchart illustrating a detailed procedure of step S40 of the energy reduction method using the fan power of the air conditioner according to the filter optimal replacement point presentation using the multiple regression analysis and the time series evaluation according to an embodiment of the present invention.

Specific features and advantages of the present invention will become more apparent from the following detailed description based on the accompanying drawings. Prior to this, terms and words used in the present specification and claims are to be interpreted in accordance with the technical idea of the present invention based on the principle that the inventor can properly define the concept of the term in order to explain his invention in the best way. It should be interpreted in terms of meaning and concept. It is to be noted that the detailed description of known functions and constructions related to the present invention is omitted when it is determined that the gist of the present invention may be unnecessarily blurred.

FIG. 1 is a configuration diagram showing an energy reduction system (S) using an air conditioner fan power according to an embodiment of a multiple regression analysis and time series evaluation according to an embodiment of the present invention, (S) using an air conditioner fan power according to a filter optimal replacement point presentation using a multiple regression analysis and a time series evaluation according to an embodiment of the present invention.

As shown in FIGS. 1 and 2, an embodiment of the present invention derives an optimal replacement point of a filter by deriving a duct static pressure change due to an increase in filter pressure differential based on basic information of a filter for an air conditioner operation, An air conditioner state analyzer 20, a filter differential pressure analyzer 30, an indoor differential pressure deriving unit 40 and a replacement timing deriving unit 50.

Specifically, the filter information input unit 10 receives the basic information of the filter for operating the air conditioner. At this time, the basic information includes the filter type (prefilter and medium filter), price unit price, replacement cost, rated capacity for the air conditioner and motor, seasonal / hourly power unit price .

)은 '[공조기 모터의 필터막힘동력 1인증가량 X 일 전력보급단가(원/Kw) X 가동일(

)]'에 따라 도출된다.At this time, among the filter types included in the basic information, the medium filter is classified according to the size (W * H * D), the capacity (CFM), the initial resistance (Inch WC), and the clogging resistance (Inch WC) It differs according to 'summer, spring ㅇ autumn, winter, time (light load, intermediate load, maximum load)', and cumulative increase in fan power of air conditioner

) 'Is the filter clogging power of the air conditioner motor 1 certification X days Power supply unit price (won / Kw) X operation day (

)] '.

The air conditioner condition analyzing unit 20 analyzes the condition of the air conditioner including the air supply and ventilation to the air conditioner, the change of the outside air temperature and the change of the outside air damper opening, the CO concentration and the opening ratio of the outside air damper, the indoor and outdoor differential pressure, Information.

The filter differential pressure analyzing unit 30 receives the change in the filter differential pressure according to the cumulative air flow rate of the air conditioner and the change in the air flow rate according to the opening rate and the accumulation amount of the air conditioner outside air damper and analyzes the influence of the opening rate of the outside air damper on the filter differential pressure. . At this time, the filter differential pressure analysis information can be generated by multiple regression analysis based on the three factors, air volume, outdoor air damper opening rate, and CO2, which are considered to affect filter differential pressure in the air conditioner system.

Specifically, the filter differential pressure analyzer 30 uses the Stepwise option to select the most relevant variable among the various independent variables and to derive a plurality of predictive expressions in order of importance during the multiple regression analysis. In the embodiment of the present invention, The filter pressure differential according to the multiple regression analysis is derived from the equation (1), and the filter differential pressure according to the multiple regression analysis is derived from the equation (1) ] Is the filter differential pressure according to the multiple regression analysis.

Here, DDP is the filter differential pressure [inch wc], Dp is the open air damper opening ratio [%], Fl is the air flow rate [CMH], and CO ₂ is CO ₂ [ppm].

The filter differential pressure analyzing unit 30 receives the basic information including the rated capacity for the air conditioner and the motor from the filter information input unit 10 to generate filter differential pressure analysis information, And an air flow rate measuring sensor configured to receive the rate of opening of the outside air damper and derive the filter differential pressure in proportion to the air flow rate of the air conditioner.

The indoor differential pressure deriving unit 40 receives the basic information and measures the filter differential pressure for each inverter size of the air supply fan, the regular air flow rate and the ambient air flow rate of the air conditioner, calculates the inverter change rate of the fan, And the indoor / outdoor inter-vehicle pressure change information due to the operation / stop of the inverter. In this case, it is preferable to understand that the constant air flow rate is measured by keeping the air flow rate constant by changing the blowing temperature, and the variable air flow rate is measured by changing the blowing amount according to the indoor load variation with a single duct configuration and keeping the blowing temperature constant.

3 to 5, experimental results on the constant air flow rate measurement, the variable air flow rate measurement, and the rate of change of the filter differential pressure alarm point by air flow rate are as follows.

First, the constant air flow rate was measured by fixing the fan inverter at 100% and opening the VAV damper of the indoor side 100%. In the air conditioner operated at the constant air flow rate under the same air volume condition, The process of change.

Fig. 3 shows changes in the filter differential pressure and changes in the indoor static pressure according to the nonwoven fabric installation. When 3 nonwovens were installed, 1 inch w.c. (The filter replacement time in this air conditioner), it is necessary to replace the filter. Also, it can be seen that the static pressure on the indoor side drops from 15 mmAq to 12.3 mmAq as the filter is clogged. It can be seen that the filter differential pressure increases with the clogging of the filter, and the static pressure of the fan decreases and the air amount decreases.

On the other hand, in order to arbitrarily increase the filter differential pressure, the variable air flow rate measurement was performed by attaching three nonwoven fabrics to the front surface of the filter as in the case of the constant air flow measurement.

As shown in FIG. 4A, as the differential pressure due to the clogging of the filter is increased in the variable air flow condition, the inverter ratio of the air supply fan is increased to maintain the constant static pressure in the duct, and the fan power value is also increased .

FIG. 4B is an analysis of the elapsed time from the start point of the filter replacement to the point when the filter clogging point is reached because the differential pressure due to clogging of the filter increases when the air flow rate is large. In this case, the average replacement period of the air conditioner filter in the experiment was calculated as 124 days as the average value of the air conditioner filter history data was 124 days, and the elapsed time from the starting point to the clogging point after the filter replacement was calculated as 124 days. inch wc and the increase of the inverter value is about 13%. If it is converted to the value for 1 day, the increase value of the filter differential pressure is 0.0039 inch wc and the inverter increase value can be converted to 0.081%.

FIG. 4C is a graph showing an increase in the filter differential pressure during the period from the starting point to the clogging point after the filter replacement. In the case of the fan having the fan motor capacity of 11 kW, the increase amount of the motor power is 2.5 kW, % Of the power increase, which is converted to a value for one day, the filter differential pressure increase value is 0.0039 inch wc and the daily power increase value can be converted to 0.0202 kW.

5 shows changes in the filter clogging alarm point according to the inverter size of the air supply fan. In the case of a variable air volume air conditioner, the filter clogging alarm point must change according to the magnitude of the air volume as the range of the filter clogging alarm point changes to the magnitude of the air volume as shown in FIG. 4A. However, it is considered that it is desirable to change the filter clogging alarm point according to the inverter ratio of the air supply fan as shown in Fig. 5, since no air flow sensor is installed in the air conditioner to be tested.

The replacing time derivation unit 50 calculates the replacing time based on the basic information received from the filter information input unit 10, the air conditioner state information received from the air conditioner condition analyzing unit 20, the filter differential pressure analyzing information And the indoor / outdoor pressure difference change information received from the indoor differential pressure deriving unit 40 to generate filter replacement time information according to the fan motor power change rate due to the filter differential pressure. At this time, the filter replacement time information includes filter elements including filter type, management method, management cost, air conditioning method and management cycle data, electric elements including air conditioner operation time, power increase amount and electric power cost, It is desirable to understand that it is information for calculating an economical filter replacement period on the basis of the filter cost and the fan power cost.

In addition, the filter management system S for preventing fan power reduction of the air conditioner through the filter clogging time series evaluation using the multiple regression analysis according to an embodiment of the present invention can be realized by a server or an administrator terminal connected through an information communication network, Information of the air conditioner, state of the air conditioner, information on the differential pressure of the filter, information on the change in the indoor / outdoor pressure difference, and information on the time of the filter replacement are transmitted to enable the building manager to monitor the operation state of the air conditioner, whether the filter is blocked, and the optimum replacement time of the filter in real time.

FIG. 6 is a diagram illustrating a filter optimum replacement cost model of an energy reduction system (S) using an air conditioner fan power according to a filter optimal replacement point presentation using a multiple regression analysis and a time series evaluation according to an embodiment of the present invention. FIG. 7 is a view showing a filter optimum replacement point, FIG. 8 is a diagram showing a filter differential pressure analysis result in a short term aspect, and FIG. 9 is a diagram showing a filter differential pressure analysis result in a long term aspect.

Specifically, detailed considerations in generating filter replacement point information of the replacement timing derivation unit 50 according to the embodiment of the present invention (the cost required for replacing the filter, the one-day operation period of the air conditioner, the motor capacity of the air conditioner, Power cost, and daily power increase due to filter clogging).

1) Cost of replacing filter

The total cost for replacing the filter is divided into material cost, labor cost, and waste material cost, and the details are as follows.

A) Material cost

- Filter dimensions: 24 "x 24"

- Material cost: Free filter 9,500 원 × 6 ea./set = 57,000 won / set

            Medium filter 90,000 Won x 6 ea./set = 540,000 won / set

B) For personnel expenses (self-management)

- 1 Month Replacement Management Number of Jobs: Average 23 times / month

- Worker 2 popularity

- Worker wage: 180,000 won

→ For one time replacement, labor cost: 180,000 won / 23 times = 7,800 won / set

C) Waste materials cost

- Waste collection outside work

- One month outside collection fee: 400,000 won

→ In case of 1 replacement, waste materials cost: 400,000 won / 23 times = 17,000 won / set

D) Total filter replacement cost (based on prefilter)

57,000 won / set + 7,800 won / set + 17,000 won / set = 81,800 won / set

2) Air conditioner 1 day operation period

- Weekdays uptime: 13 hours (06:30 - 19:30)

- Saturdays uptime: 8.5 hours (06:30 - 15:00)

3) Air conditioner motor capacity

- Rated capacity: 11 kW

4) Power cost

- Electricity charge: When the contracted electric power is 3,842 kWh, the electric energy charge is calculated as follows, and the electric energy calculation standard is set as shown in [Table 2] and [Table 3].

5) Calculate electricity price per day

A) Weekday

- Time zone: 06:30 - 19:30 (13 hours)

B) Summer

- Calculate the electricity cost per day for summer on weekdays as follows.

- Calculation process: Light load time × Summer light load time Power unit price + Intermediate load time × Summer interim load time Power unit price + Maximum load time × Summer maximum load time Power unit price

- Result: 1357.55 won / kW ← Light load 1.5 hours × 38.60 won / kWh + Medium load 6.5 hours × 85.10 won / kWh + Maximum load 5 hours × 149.30 won / kWh

C) spring and fall

- In the spring and autumn, the daily electricity price for weekdays is calculated as follows.

- Calculation process: Light load time × Spring Fall time Light load time Power unit cost + Mid load time × Spring Autumn middle load time Power unit price + Max load time × Spring fall Max load time Power unit price

- Result: 888.35 won / kW ← Light load 1.5 hours × 38.6 won / kWh + Medium load 6.5 hours × 62.30 won / kWh + Maximum load 5 hours × 85.10 won / kWh

D) Winter

- Calculate the electricity cost per day for the weekday in winter, as follows.

- Calculation process: Light load time × Winter light load time Power unit price + Mid load time × Winter load middle load time Power unit price + Max load time × Winter time Max load time Power unit price

- Result: 983.85 won / kW ← Light load 1.5 hours × 38.60 won / kWh + Medium load 8 hours × 71.60 won / kWh + Maximum load 3.5 hours × 100.90 won / kWh

6) Estimated daily power increase due to filter clogging

- Calculation process: Fan power 1 day Increase power amount × 1 day Power unit price

Here, the power increase amount of the fan power per day is calculated considering that the power is increased by 23% during the average replacement cycle 124 days obtained through the actual survey, and this value is increased by 0.0202 kW per day.

A) Summer = 0.0202 kW / day x 1357.55 yuan / kW

B) spring and autumn = 0.0202 kW / day × 888.35 won / kW

C) Winter = 0.0202 kW / day x 983.85 yuan / kW

The replacement timing deriving unit 50 of the energy reduction system S using the air conditioner fan power according to the filter optimal replacement point presentation using the multiple regression analysis and the time series evaluation according to an embodiment of the present invention as described above, The filter clogging point is considered as a filter optimum replacement cost model depending on whether the filter clogging point occurs earlier or later than the filter economy point determined by the power cost and the filter cost.

In this case, the classification of CASE I and CASE II is based on whether the filter clogging point occurs earlier or later than the filter economy point determined by the power cost and the filter cost.

In addition, the replacement timing deriving unit 50 of the energy reduction system S using the air conditioner fan power according to the filter optimal replacement point presentation using the multiple regression analysis and the time series evaluation according to an embodiment of the present invention, The point at which the air conditioner fan power increase cost accumulation becomes equal to the filter replacement cost is derived as the filter optimum replacement point.

First, the cumulative increase cost of the fan power of the air conditioner is calculated as Σ [the amount of increase in the filter clogging power of the air conditioner motor by one day × the daily power rate unit price (won / kW) × operation day (X)] as shown in the following equation (2).

The filter optimum replacement point is calculated as shown in Equation (3) below.

The derivation value of Equation (3) is a value based on a five-day operation of the week, 76.5 when converted into actual calendar date, 76.5 corresponds to 15 weeks, and a calendar date of 15 weeks is expressed by Equation same.

That is, as shown in FIG. 4, the filter clogging point is 124 days, and the filter optimal replacement point, which is determined by the power cost and filter replacement cost, is derived to be 105 days.

In addition, the replacement timing derivation unit 50 of the energy reduction system S using the air conditioner fan power according to the filter optimal replacement point presentation using the multiple regression analysis and the time series evaluation according to the embodiment of the present invention, As a result, the filter differential pressure analysis results in the short term are derived.

That is, FIG. 8 compares the economic cost model and the filter clogging model in terms of the one-time filter replacement cost. Since the filter clogging point occurs later than the filter economy point determined by the power cost and the filter cost, It has been analyzed that the replacement is favorable, and it is desirable to replace it at the filter economy point in consideration of the short-term power cost due to the one-time filter replacement.

Finally, the replacement timing deriving unit 50 of the energy reduction system S using the fan power of the air conditioner according to the filter optimal replacement point presentation using the multiple regression analysis and the time series evaluation according to the temporary example of the present invention, As shown in the figure, the filter differential pressure analysis results in the long term are derived.

That is, FIG. 9 compares the economic cost model with the filter clogging model in terms of the one-year cost, and the analysis of the cost profile at the time of replacing the filter economy point and the cost profile at the time of replacing the filter clogging point , The filter replacement period (point A in Fig. 6) of the filter clogging point becomes longer than the replacement period (point B in Fig. 6) at the filter economy point only considering the power cost and the filter replacement cost, It can be seen that replacement at the filter clogging point is more economical.

Therefore, it can be seen that the management of the filter clogging can realize the economical building management in consideration of the long term management. Also, it can be seen that this value is more economical than the cost due to empirical management (point C in FIG. 6).

Hereinafter, a method of energy reduction using the fan power of the air conditioner according to the filter optimal switching point using the multiple regression analysis and the time series evaluation according to an embodiment of the present invention based on the system described above with reference to FIG. 10 will be described. same.

First, the filter information input unit receives the basic information of the filter for operating the air conditioner (S10).

The air conditioner status analyzer then generates the air conditioner status information including the air supply, the ventilation, the outside air temperature, the change for the outside air damper opening, the CO2 concentration and the outside air damper opening rate, the indoor and outdoor differential pressure, the fan inverter, the outdoor damper opening rate and the fan inverter change S20).

Next, the filter differential pressure analyzing unit receives the change in the filter differential pressure according to the cumulative air volume of the air conditioner and the change in air volume according to the opening rate and the accumulation amount of the air conditioner outside air damper, and generates filter differential pressure analysis information analyzing the influence of the opening rate of the outside air damper on the filter differential pressure. (S30).

Next, the indoor differential pressure deriving part measures the filter differential pressure of the inverter fan size of the air supply fan, the air flow rate of the air conditioner, and the air flow rate of the air supply fan, And generates period pressure change information (S40).

Then, the replacement timing derivation unit generates filter replacement time information according to the fan motor power change rate due to the filter differential pressure based on the air conditioner state information, the filter differential pressure analysis information, and the indoor / outdoor differential pressure change information (S50).

Hereinafter, with reference to FIG. 11, a detailed procedure of the step S10 of the energy reduction method using the fan power of the air conditioner according to the filter optimal replacement point presentation using the multiple regression analysis and the time series evaluation according to the embodiment of the present invention will be described. same.

First, the filter information input unit receives a price unit price and a replacement cost for a pre-filter or a medium filter installed in the air conditioner (S11).

Then, the filter information input unit receives the rated capacity for the air conditioner and the motor (S12).

Subsequently, the filter information input unit receives the power unit price for the pre-filter or the medium filter (S13).

Then, the filter information input unit receives the cumulative fan power increase amount of the air conditioner (S14). At this time, the cumulative increase amount of the fan power of the air conditioner is derived from the calculation of the filter clogging power of the air conditioner motor 1 authentication amount X days power supply unit price (KRW / Kw) X operation day.

Hereinafter, with reference to FIG. 12, a detailed procedure of step S20 of the energy reduction method using the fan power of the air conditioner according to the filter optimal replacement point presentation using the multiple regression analysis and the time series evaluation according to an embodiment of the present invention will be described. same.

After step S10, the air conditioner condition analyzing unit derives a change for air supply, ventilation, outdoor temperature, and open air damper opening for the air conditioner (S21).

Subsequently, the air conditioner condition analyzing unit derives the CO 2 concentration and the outdoor air damper opening rate for the air conditioner (S 22).

Subsequently, a comparison value is calculated for the indoor / outdoor differential pressure, the fan inverter, and the outdoor air damper opening rate for the air conditioner condition analyzing unit (S23).

Subsequently, the fan inverter change value is derived according to the indoor / outdoor differential pressure and the outdoor air damper opening rate for the air conditioner state analyzing unit (S24).

Then, the air conditioner status analyzing unit generates the air conditioner status information based on the rate of change of the air supply fan inverter value to the air conditioner (S25).

Hereinafter, with reference to FIG. 13, the details of the step S30 of the energy reduction method using the fan power of the air conditioner according to the filter optimal replacement point presentation using the multiple regression analysis and the time series evaluation according to the embodiment of the present invention will be described. same.

After step S20, the filter differential pressure analyzing unit derives a filter differential pressure change according to the cumulative air flow rate of the air conditioner (S31).

Then, the filter differential pressure analyzing unit receives the CO 2 concentration and the opening ratio of the outdoor air damper from the air conditioner state analyzing unit and derives the air volume change according to the opening rate and accumulation amount of the air conditioner outdoor air damper (S32).

Next, the filter differential pressure analyzing unit receives the rated capacity and air flow rate for the air conditioner and the motor, the opening rate of the outside air damper, and factors for CO2 from the filter information input unit (S33).

Then, the filter differential pressure analyzing unit derives the filter differential pressure change amount with respect to the opening rate of the outside-air damper (S34).

Hereinafter, with reference to FIG. 14, the details of step S40 of the energy reduction method using the fan power of the air conditioner according to the filter optimal replacement point presentation using the multiple regression analysis and the time series evaluation according to the embodiment of the present invention will be described. same.

After step S30, the indoor differential pressure derivation unit receives the basic information including the price unit price for the filter, the replacement cost, and the rated capacity of the air conditioner and the motor from the filter information input unit (S41)

Then, the indoor differential pressure deriving part derives the filter differential pressure change rate for each inverter size of the supply fan (S42).

Subsequently, the indoor differential pressure deriving unit receives the air flow rate change value according to the opening ratio and the accumulation amount of the air conditioner outdoor damper from the filter differential pressure analyzing unit, and derives the inverter change rate of the fan according to the filter clogging when the air flow rate and the variable air flow rate of the air conditioner change (S43) .

Next, the indoor differential pressure deriving unit derives the indoor / outdoor differential pressure change amount due to the operation / stop of the air supply fan and the exhaust fan of the air conditioner (S44).

Then, the indoor differential pressure deriving section generates the indoor / outdoor air pressure variation information based on the indoor differential pressure variation with the air supply fan inverter and the exhaust fan inverter of the air conditioner (S45).

While the present invention has been particularly shown and described with reference to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. It will be appreciated by those skilled in the art that numerous changes and modifications may be made without departing from the invention. And all such modifications and changes as fall within the scope of the present invention are therefore to be regarded as being within the scope of the present invention.

S: Energy reduction system using fan power of air conditioner according to filter optimal replacement point by using multiple regression analysis and time series evaluation
10: Filter information input section
20: A /
30: filter differential pressure analyzing section
40: Indoor pressure difference deriving part
50: replacement timing deriving unit

Claims (10)

An air conditioner filter management system comprising:
A filter information input unit for receiving basic information of a filter for operating an air conditioner;
The condition of the air conditioner that generates the air conditioner status information including the air supply, ventilation, outside temperature and air conditioner damper opening change, CO2 concentration and outside air damper opening rate, indoor / outdoor differential pressure, fan inverter, outdoor damper opening rate and fan inverter change for the air conditioner part;
Wherein the filter differential pressure analysis information is generated by analyzing a change in the filter differential pressure according to the cumulative air flow rate of the air conditioner and a change in the air flow rate according to the opening rate and accumulation amount of the air conditioner outside air damper and analyzing an influence of the opening rate of the outside air damper on the filter differential pressure, Wherein the controller is configured to receive basic information including a rated capacity for an air conditioner and a motor from the filter information input unit for generating analysis information and receive a CO2 concentration and an outdoor air damper opening rate from the air conditioner condition analyzer, A filter differential pressure analyzing unit including an air flow rate measuring sensor for deriving a filter differential pressure in proportion to an amount of air flowing into the filter;
By receiving the above basic information, the filter differential pressure of the inverter fan size of the air supply fan, the normal air flow rate and the air flow rate of the air conditioner are measured, and the inverter change rate of the fan according to the airflow change and the filter clogging, An internal differential pressure derivation unit for generating differential pressure variation information; And
A replacement timing derivation unit for synthesizing the basic information, the air conditioner state information, the filter differential pressure analysis information, and the indoor / outdoor differential pressure change information to generate filter replacement time information according to the fan motor power change rate by the filter differential pressure,
The air conditioner operating state, the filter clogging state, and the optimum replacement timing of the filter are monitored in real time by receiving the basic information, the air conditioner state information, the filter differential pressure analysis information, the indoor / outdoor differential pressure change information, A server or an administrator terminal,
The filter replacement point-
A filter element including the filter type, the management method, the management cost, the air conditioning method and the management period data of the air conditioner, the electric element including the air conditioner operation time, the power increase amount and the electric power cost price, , And the cost of the fan power, and calculates an economical filter replacement period,
The filter differential pressure is derived by Equation 1, the Equation 1 of the DDP The filter differential pressure [inch wc], Dp is the outside-air damper opening rate [%], Fl is the air volume [CMH], CO ₂ is CO ₂ [ppm]. The energy reduction system using the fan power control of the air conditioner according to the optimum filter replacement point by using the time series evaluation and multiple regression analysis.
[Equation 1]

The method according to claim 1,
The basic information includes:
The air conditioner includes a filter type (prefilter and medium filter), price unit price, replacement cost, rated capacity for the air conditioner and the motor, season / hour power unit price (light / medium / full load) Energy Reduction System Using Fan Power of Air Conditioner by Using Multiple Regression Analysis and Time Series Evaluation. delete The method according to claim 1,
The air flow rate is measured by varying a blowing temperature while maintaining a blowing rate constant,
Wherein the variable air flow rate is a single duct configuration and the air flow rate is changed according to the variation of the indoor load and the blowing temperature is maintained at a constant value to measure the fan power of the air conditioner according to the filter optimal replacement point by using the multiple regression analysis and the time series evaluation Used energy reduction system. delete delete delete delete delete delete

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