WO2017052079A1 - Unmanned optimal control method for air conditioning system - Google Patents

Abstract

The present invention relates to an unmanned optimal control method for an air conditioning system, wherein: an automatic control apparatus previously predicts an outdoor air state and heating and cooling loads for each zone in a building, respectively, and then determines the amount of heat required by a device in a demand-side system and the operating schedule of the device for each zone so as to satisfy equations 8 and 9, on the basis of the predicted heating and cooling loads for each zone; the automatic control apparatus adds up the heating and cooling loads or amounts of heat for each zone, so as to predict the heating and cooling loads and amount of heat of the entire building, and determines the amount of heat supplied to a supply-side system and the operating schedule of the supply-side system so as to satisfy both an objective function represented by equation 10 and constraint conditions represented by equations 11 and 12, on the basis of the predicted heating and cooling loads of the entire building and in consideration of different energy rates according to hours and seasons and the performance and capacity of a supply-side device that vary according to operating conditions and outdoor air states; and each of the determined operating schedules of the demand-side and supply-side systems is automatically set and operated by a control program stored in the automatic control apparatus without the assistance of an operator.

Description

Unmanned Optimal Control Method of Air Conditioning System

The present invention relates to a method for optimal control of an air conditioning system, and more particularly, to predict an air-conditioning and heating load of a building in advance, and based on the predicted air-heating load, a device that varies by energy rate and heat source according to time and season. Considering the performance and the like, the present invention relates to an unmanned optimal control method of an air conditioning system that enables an unmanned operation of an air conditioning system without the need for an experienced operator most efficiently and economically.

Since much of Korea's total energy demand is used for the operation of the air conditioning system, in order to achieve energy saving, it is necessary to develop an economical and efficient operation method for the air conditioning system. Precise predictions of heating and cooling loads should be made first, and the various types of equipment constituting the air conditioning system should be operated in accordance with the predicted heating and cooling loads.

When the driver operates the air conditioning system in combination with the heating and cooling load, he / she operates based on the driver's manual or the driver's own knowledge or experience, because the driver's manual has limitations in describing all situations that may occur during the driving process. As a result, it is left to the driver's judgment, and sometimes the driver's judgment is wrong or unsatisfactory driving consumes unnecessary power or fails to meet the heating and cooling load, which may cause inconvenience to indoor residents.

On the other hand, in Korea, electricity and city gas are mainly used as energy sources of air-conditioning system. Especially, electricity is different depending on the time of day and usage. In particular, electricity charge is the most expensive during peak time in summer. If a certain amount of power is used during the time, the base rate of the power rate is calculated on the basis of the peak time rate, and excessive power charges may be charged.

Therefore, it is required to establish a strategy that can reduce the operation cost and operation cost of a more scientific and reasonable air conditioning system, away from the driving method based on the driver's judgment. Therefore, the applicant proposes an 'optimal operation method of the cooling system'. Has been registered (Patent No. 0949044), and this method predicts the cooling load per hour of the building in advance, and based on the estimated cooling load, the cooling device that varies with electricity and gas rates and heat sources according to time and season. The cooling system is operated in consideration of the performance of the cooling system, and thus the cooling system can be operated at the lowest cost while appropriately responding to the cooling load.

As shown in FIG. 1, an air conditioning system is generally installed in each zone and supplies air-conditioning energy according to air-conditioning energy demand of each zone, thereby directly cooling and heating the room to an AHU (Fan Coil Unit) and the like. It can be divided into a supply side system consisting of a plurality of sets of demand-side systems and a refrigerator, a boiler, etc. to supply and supply the total cooling and heating energy required by the plurality of sets of demand-side systems. It only shows the control method, not the control method of the demand side system.

However, in order to achieve efficient and optimal operation of the entire air conditioning system, the control of not only the supply side system but also the demand side system must be performed simultaneously. When only the supply side system is controlled as in the above patent, the heating and cooling load of the entire building is predicted. It is enough to do this, but in case of controlling the demand side system as well as the supply side system, since the demand side system is installed in each zone of the building, it is necessary to make predictions about the heating and cooling load for each zone to control the demand side system. Consideration should also be given to the heat requirements of the side systems and the operating characteristics of the equipment constituting the zones on the demand side by zone.

Moreover, the equipment used for both cooling and heating, such as absorption chiller and heat pump, heat pump, the performance is completely different when the air condition is different, like in winter and summer, so the cooling system control method of Patent No. 0949044 applies to the heating system. For this purpose, changes in the performance of the equipment due to external conditions should also be considered.

On the other hand, as described above, when a certain amount of power is used during the peak time, the power rate is calculated based on the rate during the peak time, so that the driver configures the supply side system and / or the demand side system at his / her own discretion. By forcibly shutting off some of the power, the power consumption is reduced during peak hours.In the case of the driver's judgment, it is possible to cut off the power of many devices more than necessary, which may cause inconvenience to the indoor residents, and the zone which must be cooled It may also cause the malfunction of the equipment installed in the zone by shutting off the power of the equipment. Therefore, if the power consumption during the peak time is expected to be higher than a certain amount, the reasonably planned operation procedure in advance without depending on the driver's arbitrary judgment (In scenario) Accordingly, the development of a control method that can automatically control the operation of the device is required.

The present invention has been made to improve the problems of the conventional control method of the air conditioning system as described above, the present invention is predicted in advance the overall heating and cooling load of the building based on the heating and cooling load for each zone, and the estimated heating and cooling load The purpose is to provide an unmanned optimal control method of the air conditioning system that enables the air conditioning system to operate unattended efficiently and economically without an experienced operator.

The object of the present invention as described above is to predict the air conditioning and the heating and cooling loads of each zone of the building in advance in the unmanned optimum control method of the air conditioning system, and then based on the estimated heating and cooling loads for each zone To satisfy Equation 8 and Equation 9 For each zone Determine the required heat and operation schedule of the demand-side system equipment, and estimate the heating and cooling load and the heat supply of the entire building by adding the heating and cooling load or the required heat for each zone in the automatic control device, and calculates the estimated heating and cooling load of the whole building Supply-side system to satisfy both the objective function of Equation 10 and the constraints of Equation 11 and Equation 12 in consideration of the performance and capacity of the supply-side device, which vary according to the energy rate, operation conditions, and outdoor conditions, which vary according to time and season. By determining the supply calories and the operation schedule of the supply-side system, and the determined operation schedule of the demand-side system and the supply-side system are respectively set and operated automatically by a control program stored in the automatic control unit without the help of the driver.

[Equation 8]

[Equation 9]

[Equation 10]

[Equation 11]

[Equation 12]

According to the present invention, when operating the supply side device and the demand side device according to the determined operation schedule of the supply side system and the demand side system, the power consumption of the machine in a certain time period is predicted in advance by the control program stored in the automatic control device according to Equation (13). When the estimated power consumption is more than the set allowable power, the supply side system is supplied by the required heat quantity of the demand side system which is cut off by automatically shutting off the power of the demand side system device according to the preset scenario without operating according to the operation schedule. It operates while reducing the heat, and when the estimated power consumption is lowered below the allowable power at a certain time, it is characterized by automatically supplying the power of the demanding system equipment in the reverse order of the power off sequence.

[Equation 13]

In another aspect, the present invention is characterized in that the operation schedule of the supply side system and the demand side system is adjusted in consideration of the pre-cooling / pre-heating time of the building, the remaining cooling / residual heat time of the system, the warm-up time of the equipment in the automatic control device.

In addition, according to the present invention, the performance of the device according to the operating conditions and the performance of the device according to the external conditions are respectively used as initial values, and the control program stored in the automatic control device based on the actual operation data of the device. It is another feature that is updated from time to time.

In the present invention, the solar load and the heat transfer load of the heating and cooling loads of each zone of the building are applied to the building load characteristic coefficients represented by the heat transfer characteristic coefficient and the solar radiation coefficient, respectively. Finding through is another feature.

[Equation 6]

[Equation 7]

In addition, the present invention, when predicting the heating and cooling load for each zone of the building, if the heat transfer coefficient and the solar radiation coefficient is not known, the representative values of the heat transfer coefficient and solar radiation coefficient, respectively, into the program stored in the automatic control device, and then based on the actual load Another feature is to predict the heating and cooling load by adjusting the representative value by the operation of the program stored in the automatic control device.

In addition, according to the present invention, the operating condition of the air conditioning system is fed back to the automatic control device in real time, and the actual heating and cooling load is calculated based on this, and the building load used for the prediction of the heating and cooling load. Another characteristic is that the characteristic coefficient is periodically adjusted based on past actual heating and cooling loads.

In the present invention, the predicted heating and cooling load is calculated again by applying the building load characteristic coefficient adjusted by the operation of the control program stored in the automatic control device, and the operating schedules of the demand-side system and the supply-side system are respectively calculated again. Another feature is that it is automatically modified by the control program stored in the automatic control device based on.

In another aspect, the present invention is characterized in that the building load characteristic coefficient used for the prediction of heating and cooling load is adjusted by a genetic algorithm.

In addition, the present invention includes the ice heat storage system in the supply-side system, the operation schedule of the ice heat storage system is set back and forth on the basis of the time predicted to be the lowest outside temperature of the midnight power time by the control program stored in the automatic control device. It is another feature.

The present invention minimizes the operating cost of the heating and cooling system while satisfying the given cooling and heating load conditions by operating unattended optimally without depending on the driver's experience and know-how, such as the combination method and operation schedule of the cooling and heating system, while providing a comfortable heating and cooling energy Power peaks can be reduced and efficient operation of the device can be achieved.

In addition, the present invention can calculate the heating and cooling load more accurately than the conventional by distinguishing the heat transfer and solar load characteristics of the windows and walls of the air conditioning target building and reflecting the solar radiation characteristics for each direction.

In addition, the present invention predicts the heating and cooling loads on the demand side system as well as the supply side system, and simultaneously controls the supply side system and the demand side system on the basis of this, and also configures the required calories of the demand side system and the demand side system for each zone. Since the air conditioning system is operated in consideration of the operating characteristics of the equipment and the performance change of the equipment according to the external air condition, a more comfortable and economical operation of the air conditioning system can be achieved.

In addition, the present invention predicts the power consumption in peak time in advance, and if the estimated power consumption is expected to be above the set allowable power, the inconvenience of the indoor residents by driving according to the planned driving scenario without depending on the driver's judgment And malfunction of the equipment can be minimized.

In addition, the present invention can minimize the energy cost for operating the ice storage system by determining that the operation is performed during the late night power time when the outside temperature is predicted to be the lowest when determining the operation schedule of the ice storage system.

Furthermore, the present invention introduces heat transfer adjustment coefficients and solar radiation adjustment coefficients into the heat transfer coefficients and the solar radiation coefficients of windows and walls, respectively, and adjusts them using genetic algorithms, thereby significantly reducing the inconsistency between the predicted load and the measured load.

1 is a configuration diagram showing an example of an air conditioning system composed of a supply side system and a demand side system.

Hereinafter, the configuration and operation of the present invention through the accompanying drawings showing a preferred embodiment in more detail.

The present invention is to provide an unmanned optimal control method of the air conditioning system to enable an unmanned operation of the air conditioning system effectively and economically without an experienced driver. Prediction of heating and cooling load should be preceded, and the air conditioning system should be operated by the control of the automatic control unit provided in the air conditioning system based on the predicted heating and cooling load.

The automatic control device for controlling the air conditioning system including the automatic control device of the present invention is generally installed in an integrated control room and has a control program (software) therein to provide integrated control of the air conditioning system. And a direct digital controller (DDC) connected to each control point, an NC (network controller) that is responsible for data exchange between the MMI and the DDC, a module for expanding the DDC, and the like. A method of unmanned optimal control of an air conditioning system using a device will be described.

In general, the air conditioning system is installed in each zone as described above, and is provided with a plurality of air handling units (AHUs) and fan coil units (FCUs) for directly heating and cooling the room by supplying heating and cooling energy according to the cooling and heating energy demand for each zone. It can be divided into a supply-side system composed of two demand-side systems and a refrigerator, a boiler, and the like for supplying heating and cooling energy to cover the entire cooling and heating energy supplied from the plurality of demand-side systems to the room.

In the present invention, when the heating and cooling load is predicted, the automatic control device first calculates and calculates the heating and cooling load for each zone of the building, that is, the heating and cooling energy (cooling and heating load) to be supplied by the devices constituting the plurality of demand side systems. The total heating and cooling loads to be supplied by the supply side system are calculated by summing the heating and cooling loads calculated for each zone.In this case, the automatic control device predicts and calculates the heating and cooling loads to be supplied by the devices constituting a plurality of demand side systems. The control program (software) for calculating the heating / cooling load or the like is stored so that the total heating / cooling load to be supplied is calculated.

When calculating and calculating the heating / cooling load for each zone in advance, the amount of solar radiation varies depending on the characteristics of the heating / cooling load of the room constituting each zone, that is, the direction of the room, and the amount of ventilation according to the number of people living in the room. Since the cooling and heating load should be calculated in consideration of these characteristics, the present invention calculates the heating and cooling load by the heating and cooling load prediction method of Patent No. 1506215 proposed by the applicant, but is calculated by dividing each zone, below The cooling and heating load calculation method proposed in the patent will be briefly described.

When predicting and calculating the heating and cooling loads of each zone of a building, the condition of the outside air has an absolute influence on the heating and cooling load, so the prediction of the outside air condition must be preceded. The prediction of the outside air condition is proposed by the applicant through Patent No. 1141027. Since many prediction methods are already known, including the hourly weather data prediction method, any one of these known outdoor condition prediction methods is selected to predict the outdoor condition.

After the outdoor air condition is predicted by the external air condition predicting method as described above, the cooling / heating load for each zone is calculated again.

), 전열부하(

), 환기부하(

) 및 내부부하(

)로 구분하여 계산하는데, 본 발명에서는 환기부하(

) 및 내부부하(

)는 종래와 같은 방법으로 구하고, 일사부하(

), 전열부하(

)는 각각 환기부하(

) 및 내부부하(

)에 비해 냉난방 부하에 상대적으로 큰 영향을 미치기 때문에 이를 고려하여, 창호와 벽체를 구분하면서 방위별로 다른 건물부하특성계수(전열특성계수와 일사특성계수)를 적용하여 아래의 수학식 2 및 수학식 3에 의해 구한다.Heating and cooling loads are generally equivalent to the solar load (1)

), Heat load (

), Ventilation load (

) And internal load (

In the present invention, the ventilation load (

) And internal load (

) Is calculated in the same manner as before, and the solar load (

), Heat load (

) Is the ventilation load (

) And internal load (

In consideration of this, the building load characteristic coefficients (heat transfer characteristic coefficient and insolation characteristic coefficient) are applied to each bearing while distinguishing windows and walls. Obtained by 3.

[Equation 1]

는 냉난방부하,

는 현열부하,

는 잠열부하를 나타내고,

은 일사부하,

는 전열부하,

는 환기부하,

는 내부부하를 나타낸다.here,

Is the heating and cooling load,

Is the sensible heat load,

Represents latent heat load,

Silver solar load,

Is the heat load,

Ventilation load,

Represents the internal load.

[Equation 2]

과

은 각각 창호와 벽체의 전열특성계수,

과

은 각각 창호와 벽체의 면적이고,

는 건물 냉난방 공간을 둘러싸고 있는 6개면의 방위를 나타내고,

는 건물의 한 방위면을 구성하는 벽체 또는 창호 종류의 수를 나타낸다.

는 매 시간의 예측 외기온도,

는 냉난방 공간의 실내온도이다.here,

and

Are the heat transfer coefficients of windows and walls,

and

Are the areas of windows and walls, respectively,

Represents the orientation of the six sides surrounding the building's heating and cooling space,

Represents the number of wall or window types that constitute one azimuth of the building.

Is the forecast outside temperature for each hour,

Is the room temperature of the heating and cooling space.

[Equation 3]

과

은 각각 창호와 벽체의 일사특성계수이고,

은 방위별 매 시간의 예측 일사량으로서 공지의 방법에 의해 구한다.here,

and

Are the solar radiation coefficients of windows and walls, respectively.

Is a predicted insolation amount of time for each direction, and is obtained by a known method.

)는 수학식 4, 벽체의 전열특성계수(

)는 수학식 5, 창호의 일사특성계수(

)는 수학식 6, 벽체의 일사특성계수(

)는 수학식 7에 의해 각각 구한다.Since the building load characteristic coefficient cannot be obtained from the load statement as in the prior art, in the present invention, the building energy simulation program based on the energy balance method, for example, EnergyPlus, is used for the heat transfer characteristic coefficient of the windows.

) Is the equation 4, the heat transfer coefficient of the wall (

) Is Equation 5, solar radiation coefficient of window (

) Is the equation 6, the solar radiation coefficient (

Are each obtained by the equation (7).

[Equation 4]

는 창호의 총합열전달계수로서 건물설계서 등에 이미 기재되어 있거나 또는 창호의 종류를 알면 계산에 의해 쉽게 산출할 수 있으며, 상수

,

는 건물에너지 시뮬레이션 프로그램을 사용하여 구할 수 있고,

는 건물 냉난방 공간을 둘러싸고 있는 6개면의 방위를 나타내며,

는 건물의 한 방위면을 구성하는 창호 종류의 수를 나타낸다.here,

Is the total heat transfer coefficient of the windows, which is already listed in the building design, etc., or can be easily calculated by calculation if the type of windows is known.

,

Can be obtained using a building energy simulation program,

Represents the six sides of the orientation surrounding the building's heating and cooling space,

Represents the number of windows and doors that constitute one azimuth of the building.

[Equation 5]

는 벽체의 총합열전달계수로서 건물설계서 등에 이미 기재되어 있거나 또는 벽체의 구조를 알면 계산에 의해 산출할 수 있으며, 상수

,

도 건물에너지 시뮬레이션 프로그램을 사용하여 구할 수 있다.here,

Is the total heat transfer coefficient of the wall, which is already described in the building design, or can be calculated by calculation if the structure of the wall is known.

,

It can also be obtained using a building energy simulation program.

)를 구할 때에는 EnergyPlus에서 제공하는 여러 종류의 창호에 대해 일사획득계수(

)와 일사특성계수(

) 사이의 관계를 그래프화한 다음 커브피팅하면 창호에 대한 일사특성계수(

)는 수학식 6에서와 같이 일사획득계수(

)의 2차식으로 표현되며, 따라서 실제 설치된 창호에 대한 일사획득계수(

)를 수학식 6에 대입하면 창호의 일사특성계수(

)를 구할 수 있다.Insolation Characteristics Coefficient of Windows

), The solar energy acquisition coefficient (for the different types of windows provided by EnergyPlus)

) And solar radiation coefficient (

Graphing the relationship between the curves and then curve fitting,

) Is the same as in Equation 6

It is expressed as a quadratic equation, and thus the solar gain coefficient for the actual installed windows (

) Into Equation 6, the solar characteristic coefficient (

) Can be obtained.

[Equation 6]

,

및

는 각각 건물에너지 시뮬레이션 프로그램을 사용하여 구할 수 있고,

는 창호에 설치된 외부 차양장치의 일사차폐계수로서 차양의 기하학적 형상과 방위를 고려하여 계산되며 차양이 없는 경우에는 1이 된다.Where constant

,

And

Can be found using a building energy simulation program,

Is the solar radiation coefficient of the external awning installed on the windows and is calculated in consideration of the geometry and orientation of the awning and is 1 if there is no awning.

[Equation 7]

는 벽체의 태양흡수율이고,

는 벽체의 총합열전달계수로서 이들 값은 건물설계서 등에 이미 기재되어 있거나 또는 벽체의 구조를 알면 계산에 의해 쉽게 산출할 수 있으며, 계수

,

과 지수

,

는 건물에너지 시뮬레이션 프로그램을 사용하여 구할 수 있고,

는 벽체에 설치된 외부 차양장치의 일사차폐계수로서 차양의 기하학적 형상과 방위를 고려하여 계산된다.here,

Is the solar absorption rate of the wall,

Is the total heat transfer coefficient of the wall. These values are already described in the building design, or can be easily calculated by calculation if the structure of the wall is known.

,

And exponent

,

Can be obtained using a building energy simulation program,

Is the solar radiation coefficient of the external awning installed on the wall and is calculated by considering the geometry and orientation of the awning.

The present invention can predict the cold half load of each zone by using the building load characteristic coefficient as described above, but the building load characteristic coefficient, that is, the heat transfer coefficient and the solar radiation coefficient cannot be obtained due to the loss of design data of the building. In this case, by inputting the representative value of the building load characteristic coefficient into the control program stored in the automatic control device, and then adjusting the building load characteristic coefficient based on the actual load, it is possible to predict the heating and cooling load for each zone. The operational status of the demand side system equipment is fed back to the automatic control device in real time, and based on this, the actual cooling and heating load is calculated by the automatic control device.

And the building load characteristic coefficients used in estimating the heating and cooling load are periodically adjusted based on the actual heating and cooling load by the operation of the control program stored in the automatic control device.

,

)에 전열조정계수(

,

)를 각각 곱하고, 창호와 벽체의 일사특성계수(

,

)에 일사조정계수(

,

)를 각각 곱한 다음, 유전자 알고리즘을 사용하여 창호와 벽체의 전열조정계수(

,

)와 일사조정계수(

,

)를 각각 조정함으로써 보정하며, 이에 의해 건물의 예측부하와 실측부하 간의 오차를 최소로 줄일 수 있고, 이러한 일련의 과정은 자동제어장치에 저장된 제어 프로그램에 의해 수행된다.Zone heating and cooling loads predicted by the above process may be different from the actual load (actual load), therefore, in the present invention, the heat transfer coefficients of windows and walls (

,

Heat transfer coefficient ()

,

) And multiply solar radiation coefficients of windows and walls by

,

), Solar radiation adjustment coefficient (

,

), Then multiply each by using a genetic algorithm to determine the heat transfer coefficients for windows and walls (

,

) And solar radiation adjustment coefficient (

,

), Which can be reduced by minimizing the error between the predicted and actual loads of the building, and this series of processes is performed by a control program stored in the automatic control unit.

,

)를 조정하는 절차는 이미 잘 알려져 있으므로 이에 대한 상세한 설명은 생략한다.Then, using genetic algorithm, variables (insolation adjustment coefficients)

,

The procedure for adjusting) is already well known, so a detailed description thereof will be omitted.

After the prediction cooling load for each zone in the automatic control apparatus is calculated by the above process, an operation plan for the equipment constituting the demand side system installed in each zone must be established based on the calculated prediction cooling load for each zone. In the present invention, to satisfy the following equation (8) and equation (9) For each zone The required heat quantity of the demand side system and the operation schedule of the device are determined, and the operation schedule is determined by the automatic control device, where the devices installed for each zone of the demand side system, that is, AHU, FCU and other devices (EHP), respectively. The amount of heating / heating energy (or ratio) that is in charge of the supply is set in advance and inputted to the MMI, and the supply-side system supplies cooling / heating energy according to the amount of cooling / heating energy for each device of the demand-side system set by the automatic controller in advance. do.

[Equation 8]

는 시간

에서의 존별, 시간별 수요측 기기의 예측 냉난방부하이고,

은 해당 존에 냉난방 에너지를 공급하는 수요측 시스템 기기의 운전허용 최소열량이며,

은 냉방

과 난방

을 구분하는 색인(index)값이다.here,

Time

Forecast heating and cooling loads of demand-side devices by zone and time in,

Is the minimum allowable heat capacity of the demand side system equipment that supplies heating and cooling energy to the zone,

Silver air conditioning

And heating

Index value that distinguishes.

[Equation 9]

는 시간

에서의 임의의 수요측 시스템 기기(

)의 요구열량이고,

은 수요측 시스템 기기(

)의 공칭열량이며,

은 냉방

과 난방

을 구분하는 색인값이다.here,

Time

Any demand-side system appliance in

Required calories,

Is the demand side system appliance (

Is the nominal calorific value of

Silver air conditioning

And heating

Index value to distinguish between.

Next, after the heating and cooling loads or the required calories for each zone are calculated by the above process, all the heating and cooling loads or the required calories are summed up to calculate the heating and cooling loads and the calorific values of the entire building to be supplied by the supply system. Is done at the automatic control unit.

On the other hand, as described above, since electric energy charges vary by hour and season, and the equipment performance of the supply side system varies according to the outside air condition, this point should be considered in order to achieve economical operation and efficient operation of the air conditioning system. .

Accordingly, in the present invention, the objective function and equation of Equation 10 below are considered in consideration of the operating performance and capacity of the supply-side system device which varies according to the operating conditions and the external air condition based on the cooling and heating load of the whole building calculated by the above process. The supply calories and the operation schedule of the apparatus constituting the supply side system are determined so that all of the constraints of Equations 11 and 12 are satisfied, and the operation schedule is determined by the automatic control apparatus by the operation of the stored control program.

[Equation 10]

는 공급측 시스템의 하루 동안의 예상 총에너지 비용을 나타내고,

는 시간

에서의 공급측 시스템을 구성하는 기기(

)가 감당하게 될 열량이고,

는 요구열량을 공급하는데 필요한 각 기기의 에너지 비용이며,

는 운전조건에 따른 기기의 성능을 나타내고,

는 외기상태에 따른 기기의 성능을 나타내며,

은 냉방

과 난방

을 구분하는 색인값이고,

는 에너지 비용 계산을 수행하는 시간 간격이다.here,

Represents the estimated total energy costs for the day on the supply side system,

Time

Configuring the supply-side system in

) Is the amount of calories

Is the energy cost of each device needed to supply the required calories,

Indicates the performance of the device according to the operating conditions,

Indicates the performance of the device according to the outside air condition,

Silver air conditioning

And heating

Index value that distinguishes between

Is the time interval for performing the energy cost calculation.

[Equation 11]

은 시간

에서의 공급측 시스템으로부터 냉수 또는 온수를 공급받는 수요측 시스템의 요구열량의 합이다. here

Silver time

Is the sum of the required calories of the demand-side system receiving cold or hot water from the supply-side system.

[Equation 12]

은 공급측 시스템 기기(

)가 냉방 또는 난방 시 공급하여야 하는 열량이고,

은 공급측 시스템 기기(

)의 공칭용량이며,

은 공급측 시스템 기기(

)의 최소 용량이다.here

Supply-side system appliances (

) Is the amount of heat to be supplied when cooling or heating,

Supply-side system appliances (

) Is the nominal capacity of

Supply-side system appliances (

) Is the minimum dose.

)의 성능(

)과 외기상태에 따른 기기(

)의 성능(

)을 각각 결정할 때에는 초기값으로 기기의 운전매뉴얼에서 제시하는 표준값을 사용하고, 이후 기기(

)의 실제 운전 데이터에 기초하여 주기적으로 업데이트되며, 이를 위해 공급측 시스템을 구성하는 각 기기(

)의 실제 운전 데이터는 통신망을 통해 자동제어장치에 실시간으로 입력되고, 이 데이터에 기초하여 자동제어장치에 저장된 제어 프로그램의 동작에 의해 운전조건에 따른 기기(

)의 성능(

)과 외기상태에 따른 기기(

)의 성능(

)이 주기적으로 업데이트된다.Device according to the operating conditions in the above equation (10)

) Performance

) And equipment according to the air condition (

) 'S performance (

) Are used as initial values, and the standard values given in the operating manual of the device are used.

Is periodically updated based on the actual operating data of the

The actual operation data of) is input to the automatic control device in real time through the communication network, and the device (according to the operation condition)

) 'S performance (

) And equipment according to the air condition (

) 'S performance (

) Is updated periodically.

In addition, the warm-up time is required to operate each device constituting the supply-side system and the demand-side system, and the operation of these devices must consider the preheating / preheating time of the building and the remaining cooling / heating time of the system. The operation schedule of each device constituting the supply side system and the demand side system is set to be adjusted in consideration of the preheating / preheating time of the building, the residual cooling / residual heat time of the system, and the warming up time of the device through the control program stored in the control device.

After the operation schedule of each device constituting the demand-side system and the supply-side system is determined by the above process, the operation schedule is input to and stored in the automatic control device that controls the entire air conditioning system. The operation of each device constituting the demand-side system and the supply-side system is controlled through a communication network according to the input and stored operation schedule, whereby the air conditioning system is optimally operated unattended without the help of a driver.

When operating the supply side system device according to the determined operation schedule, the power consumption is predicted in advance in a specific time zone, for example, during a peak time in summer, by Equation 13 below, wherein the estimated power consumption is expected to be higher than the set allowable power. In this case, the operation of the demand-side system is blocked by setting the operation of the device constituting the demand-side system according to a preset operation scenario, by sequentially shutting down the power of the device constituting the demand-side system from the low-priority device according to a preset operation scenario. The operating load of the supply-side system equipment is reduced by the amount of heat, and if the estimated power consumption is lowered below the allowable power in a specific time period, the power supply of the demand-side system equipment is reversed from the power-off order in order from the most important devices. With automatic power supply Is set to resume, the type and setting of the operation scenario is through the program stored in the automatic control unit.

[Equation 13]

는 임의 시간(

)에서의 공급측 시스템의 전체 전기에너지 사용량을 나타내고,

는 임의 시간(

)에서 공급측 시스템 기기(

)가 감당하게 될 열량이며,

는 요구열량을 공급하는데 사용되는 각 기기의 전기에너지 사용량이고,

는 운전조건에 따른 기기의 성능을 나타내며,

는 외기상태에 따른 기기의 성능을 나타내고,

은 냉방

과 난방

을 구분하는 색인값이다.here,

Is a random time (

Represents the total electrical energy usage of the supply-side system in

Is a random time (

On the supply side system appliance (

) Is the amount of calories

Is the electrical energy consumption of each device used to supply the required calories,

Indicates the performance of the device according to the operating conditions,

Indicates the performance of the device according to the outside air condition,

Silver air conditioning

And heating

Index value to distinguish between.

On the other hand, in order to save the building's cooling energy, the ice storage system is often included in the supply-side system, and such ice storage system is mainly operated so that ice storage occurs during the late night power time when the electric energy charge is low, even when the outside temperature is low. Compared to the case where the outside air temperature is high, more electrical energy should be input. Therefore, in the present invention, when the operation schedule of the ice storage system is determined, the ice storage operation is performed during the late night power time. The operation is performed at the time before and after the estimated time.

As described above, the present invention predicts the air-conditioning and heating load of the building in advance, and operates the air conditioning system in consideration of the performance of the device that varies according to the energy bill and the heat source according to the time and season based on the estimated heating and cooling load. The most economical operation is possible, and since this operation is automatically performed by a control program stored in the automatic controller, an effective unmanned operation is achieved without an experienced driver.

Claims (10)

In a control method for unattended operation of the air conditioning system consisting of the supply-side system and the supply-side system using an automatic control device for controlling the air conditioning system by storing a control program therein, In the automatic control apparatus, the air conditioner and the air-conditioning load for each zone of the building are predicted in advance, and then the equations 8 and 9 are satisfied based on the predicted air-conditioning load for each zone. For each zone Determine the required heat quantity and operation schedule of the demand side system equipment, The automatic control device estimates the heating and cooling load and the heat supply of the entire building by adding the heating and cooling load or the required heat amount for each zone, and based on the estimated heating and cooling load of the entire building, different energy rates, operating conditions and In consideration of the performance and capacity of the supply-side equipment according to the external air condition, the supply calories and the operation schedule of the supply-side system are determined to satisfy both the objective function of Equation 10 and the constraints of Equation 11 and Equation 12, The determined operation schedules of the demand-side system and the supply-side system are automatically set and operated by a control program stored in the automatic control apparatus without the help of a driver, respectively. [Equation 8]

here,

Time

Demand-side devices by zone and hour in

) Is the estimated heating and cooling load,

Is a demand-side system device that supplies heating and cooling

) Is the minimum allowed heat of driving,

Silver air conditioning

And heating

Index value to distinguish between. [Equation 9]

here,

Time

Any demand-side system appliance in

Required calories,

Is the demand side system appliance (

Nominal calories. [Equation 10]

here,

Represents the estimated total energy costs for the day on the supply side system,

Time

Configuring the supply-side system in

) Is the amount of calories

Is the energy cost of each device needed to supply the required calories,

Indicates the performance of the device according to the operating conditions,

Indicates the performance of the device according to the outside air condition,

Silver air conditioning

And heating

Index value that distinguishes between

Is the time interval for performing the energy cost calculation. [Equation 11]

here

Silver time

Is the sum of the required calories of the demand-side system receiving cold or hot water from the supply-side system. [Equation 12]

here

Supply-side system appliances (

) Is the amount of heat to be supplied when cooling or heating,

Supply-side system appliances (

) Is the nominal capacity of

Supply-side system appliances (

) Is the minimum dose. The method according to claim 1, When the supply side device and the demand side device are operated in accordance with the determined operation schedule of the supply side system and the demand side system, the power consumption of the device in a specific time period is previously determined by a control program stored in the automatic control apparatus according to Equation (13). If the predicted power usage is more than the set allowable power, the power of the demand-side system device is automatically cut off according to a preset scenario without driving according to the driving schedule, and the power of the demand-side system is blocked. It operates while reducing the supply heat of the supply-side system, and if the estimated power consumption is lowered below the allowable power again in the specific time period, the power supply of the demand-side system equipment is automatically supplied in the reverse order of the power off sequence. Air tank Unmanned optimal control method of the system. [Equation 13]

here,

Is a random time (

Represents the total electrical energy usage of the supply-side system in

Is a random time (

On the supply side system appliance (

) Is the amount of calories

Is the electrical energy consumption of each device used to supply the required calories,

Indicates the performance of the device according to the operating conditions,

Indicates the performance of the device according to the outside air condition,

Silver air conditioning

And heating

Index value to distinguish between. The method according to claim 1, The operation schedules of the supply side system and the demand side system are each adjusted in consideration of the pre-cooling / preheating time of the building, the remaining cooling / heating time of the system, and the warm-up time of the equipment. Control method. The method according to claim 1, Performance of the device according to the operating conditions (

) And the performance of the device according to the air condition (

) Is used as an initial value of the standard value presented in the operation manual, and is updated at any time by a control program stored in the automatic control device based on the actual operation data of the device. The method according to claim 1, Of the heating and heating loads of each zone of the building, the solar load and the heat transfer load are respectively applied to the building load characteristic coefficients expressed by the heat transfer characteristic coefficient and the solar radiation coefficient by the control program stored in the automatic control apparatus. Unattended optimal control method of the air conditioning system, characterized in that obtained through. [Equation 6]

here,

and

Are the heat transfer coefficients of windows and walls,

and

Are the areas of windows and walls, respectively,

Represents the orientation of the six sides surrounding the building's heating and cooling space,

Represents the number of wall or window types that constitute one azimuth of the building.

Is the forecast outside temperature for each hour,

Is the room temperature of the heating and cooling space. [Equation 7]

here,

and

Are the solar radiation coefficients of windows and walls,

Is the forecasted solar radiation at each hour of the bearing. The method according to claim 5, When predicting the heating and cooling load for each zone of the building, if the heat transfer coefficient and the solar radiation coefficient are not known, the representative values of the heat transfer coefficient and the solar radiation coefficient are respectively input to the control program stored in the automatic control device, and then the actual load is input. Unattended optimal control method of the air conditioning system, characterized in that for predicting the heating and cooling load by adjusting the representative value based on the operation of the control program stored in the automatic control device. The method according to claim 5, The operation condition of the air conditioning system is that the operating condition of the demand-side system device is fed back to the automatic control device in real time so that the actual heating and cooling load is calculated, and the building load characteristic coefficient used for the prediction of the cooling and heating load. Unattended optimal control method of the air conditioning system, characterized in that periodically adjusted based on the actual heating and cooling load of the past. The method according to claim 7, The estimated heating and cooling load is recalculated by applying the building load characteristic coefficient adjusted by the operation of the control program stored in the automatic control device, and the operation schedules of the demand-side system and the supply-side system respectively calculate the re-calculated heating and cooling load. Unattended optimal control method of the air conditioning system, characterized in that automatically modified on the basis. The method according to claim 6 or 7, The building load characteristic coefficient used for the prediction of the heating and cooling load is controlled by a genetic algorithm. The method according to claim 1, The supply-side system includes an ice storage system, and the operation schedule of the ice storage system is set back and forth on the basis of the time when the outside air temperature is predicted to be the lowest of the midnight power time by the control program stored in the automatic controller. Unmanned optimal control method of air conditioning system.

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