WO2017052079A1 - Procédé de commande optimal sans personnel pour climatiseur - Google Patents

Procédé de commande optimal sans personnel pour climatiseur Download PDF

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Publication number
WO2017052079A1
WO2017052079A1 PCT/KR2016/009211 KR2016009211W WO2017052079A1 WO 2017052079 A1 WO2017052079 A1 WO 2017052079A1 KR 2016009211 W KR2016009211 W KR 2016009211W WO 2017052079 A1 WO2017052079 A1 WO 2017052079A1
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Prior art keywords
heating
supply
side system
load
cooling
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Ceased
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PCT/KR2016/009211
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English (en)
Korean (ko)
Inventor
유성연
김태호
윤홍익
한규현
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Gagyotech Co Ltd
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Gagyotech Co Ltd
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Publication of WO2017052079A1 publication Critical patent/WO2017052079A1/fr
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F1/00—Room units for air-conditioning, e.g. separate or self-contained units or units receiving primary air from a central station
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
    • F24F11/00—Control or safety arrangements

Definitions

  • 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.
  • the driver 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the power consumption is reduced during peak hours.
  • 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.
  • 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
  • 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).
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • FIG. 1 is a configuration diagram showing an example of an air conditioning system composed of a supply side system and a demand side system.
  • 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.
  • DDC direct digital controller
  • NC network controller
  • 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.
  • AHUs air handling units
  • FCUs fan coil units
  • 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.
  • the automatic control device 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.
  • 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.
  • 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.
  • the cooling / heating load for each zone is calculated again.
  • Heating and cooling loads are generally equivalent to the solar load (1) ), Heat load ( ), Ventilation load ( ) And internal load (
  • 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 (
  • the building load characteristic coefficients heat transfer characteristic coefficient and insolation characteristic coefficient
  • 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.
  • 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.
  • 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).
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • Silver time Is the sum of the required calories of the demand-side system receiving cold or hot water from the supply-side system.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the type and setting of the operation scenario is through the program stored in the automatic control unit.
  • 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 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.
  • 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.

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  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Air Conditioning Control Device (AREA)

Abstract

La présente invention concerne un procédé de commande optimal sans personnel destiné à un climatiseur, dans lequel : un appareil de commande automatique prédit préalablement un état d'air extérieur et des charges de chauffage et de refroidissement pour chaque zone dans un bâtiment, respectivement, et détermine ensuite la quantité de chaleur requise par un dispositif dans un système côté demande et le programme de fonctionnement du dispositif pour chaque zone de manière à satisfaire aux équations 8 et 9, sur la base des charges de chauffage et de refroidissement prédites pour chaque zone; l'appareil de commande automatique additionne les charges de chauffage et de refroidissement ou les quantités de chaleur pour chaque zone, de manière à prédire les charges de chauffage et de refroidissement et la quantité de chaleur de l'ensemble du bâtiment, et détermine la quantité de chaleur fournie à un système côté alimentation et le programme de fonctionnement du système côté alimentation de sorte à satisfaire à la fois une fonction objectif représentée par l'équation 10 et des conditions de contrainte représentées par les équations 11 et 12, sur la base des charges de chauffage et de refroidissement prédites de l'ensemble du bâtiment et en tenant compte de différents débits d'énergie en fonction des heures et des saisons et de la performance et la capacité d'un dispositif côté alimentation qui varient en fonction des conditions de fonctionnement et d'états de l'air extérieur; et chacun des programmes de fonctionnement déterminés des systèmes côté demande et côté alimentation est automatiquement réglé et mis en œuvre par un programme de commande mémorisé dans l'appareil de commande automatique sans l'assistance d'un opérateur.
PCT/KR2016/009211 2015-09-21 2016-08-19 Procédé de commande optimal sans personnel pour climatiseur Ceased WO2017052079A1 (fr)

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KR1020150133426A KR101571806B1 (ko) 2015-09-21 2015-09-21 공기조화시스템의 무인 최적제어 방법
KR10-2015-0133426 2015-09-21

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11168916B2 (en) 2018-06-11 2021-11-09 Broan-Nutone Llc Ventilation system with automatic flow balancing derived from a neural network and methods of use

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KR102379638B1 (ko) * 2017-09-27 2022-03-29 삼성전자주식회사 공기조화장치 및 그의 제어 방법
KR102032810B1 (ko) * 2018-11-19 2019-10-17 뉴브로드테크놀러지(주) Hvac 시스템 연동 기반 에어컨 자동제어 장치
CN113837665B (zh) * 2021-11-04 2024-04-19 华北电力大学 一种基于智能体建模的区域电供暖负荷预测方法
CN115978720B (zh) * 2022-12-30 2023-07-04 北京创今智能科技有限公司 一种空气源热泵机组非等量分组方法

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2000146257A (ja) * 1998-09-04 2000-05-26 Atr Adaptive Communications Res Lab 建物エネルギ―システムの制御方法及び装置並びに制御処理プログラムを記録した記録媒体
JP2003120982A (ja) * 2001-10-16 2003-04-23 Hitachi Ltd 空調設備運用システム及び空調設備設計支援システム
JP2008025951A (ja) * 2006-07-25 2008-02-07 Jfe Techno Research Corp 空調設備の運転制御方法および装置
KR100949044B1 (ko) * 2009-08-07 2010-03-24 충남대학교산학협력단 냉방시스템의 최적 운전방법
KR101506215B1 (ko) * 2015-01-16 2015-03-26 (주)가교테크 예측 일사량을 이용한 냉난방부하 예측방법

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2000146257A (ja) * 1998-09-04 2000-05-26 Atr Adaptive Communications Res Lab 建物エネルギ―システムの制御方法及び装置並びに制御処理プログラムを記録した記録媒体
JP2003120982A (ja) * 2001-10-16 2003-04-23 Hitachi Ltd 空調設備運用システム及び空調設備設計支援システム
JP2008025951A (ja) * 2006-07-25 2008-02-07 Jfe Techno Research Corp 空調設備の運転制御方法および装置
KR100949044B1 (ko) * 2009-08-07 2010-03-24 충남대학교산학협력단 냉방시스템의 최적 운전방법
KR101506215B1 (ko) * 2015-01-16 2015-03-26 (주)가교테크 예측 일사량을 이용한 냉난방부하 예측방법

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11168916B2 (en) 2018-06-11 2021-11-09 Broan-Nutone Llc Ventilation system with automatic flow balancing derived from a neural network and methods of use

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