WO2014022955A1 - Procédé pour gérer un rendement en énergie sous une charge périodique dans un bâtiment - Google Patents

Procédé pour gérer un rendement en énergie sous une charge périodique dans un bâtiment Download PDF

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Publication number
WO2014022955A1
WO2014022955A1 PCT/CN2012/079700 CN2012079700W WO2014022955A1 WO 2014022955 A1 WO2014022955 A1 WO 2014022955A1 CN 2012079700 W CN2012079700 W CN 2012079700W WO 2014022955 A1 WO2014022955 A1 WO 2014022955A1
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WO
WIPO (PCT)
Prior art keywords
data
energy consumption
energy
building
frequency domain
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PCT/CN2012/079700
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English (en)
Chinese (zh)
Inventor
刘岩
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珠海派诺科技股份有限公司
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Application filed by 珠海派诺科技股份有限公司 filed Critical 珠海派诺科技股份有限公司
Priority to CN201280013354.9A priority Critical patent/CN103890806B/zh
Priority to PCT/CN2012/079700 priority patent/WO2014022955A1/fr
Publication of WO2014022955A1 publication Critical patent/WO2014022955A1/fr

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
    • G16Z99/00—Subject matter not provided for in other main groups of this subclass

Definitions

  • the present invention relates to energy efficiency management, and more particularly to energy efficiency management in building energy use.
  • the total amount control method cannot consider the energy use characteristics and energy use characteristics of buildings.
  • the set energy management objectives are often changed due to the choice of samples, which is not conducive to the management of energy use in buildings.
  • Factors such as lighting, floors, walls, window sizes, curtain walls, etc. in different areas of the same building will have an impact on the regional energy use, and the actual energy efficiency level of the area cannot be well reflected by regional comparison.
  • the above method evaluates the energy use of buildings with the amount of energy used as the evaluation parameter, and does not fully analyze the information contained in the energy cycle of the building.
  • the invention proposes a building periodic load energy efficiency management method, and uses the Fourier transform to extract the periodic load data of the building, extracts the frequency information in the building energy consumption data, and analyzes the frequency i to find the building. Unreasonable, and then find the loopholes in energy waste during the use of the building.
  • the method mainly includes the following steps:
  • the energy of the device to be judged is collected, and the energy consumption data may be the power consumption of the device for a period of time, and the device may be a certain electrical device in the building, or For a certain type of electrical equipment in the building;
  • an appropriate judging period is selected, and the judging period may be days, weeks, months, years, etc., and the collected energy consumption data is divided into a plurality of data groups according to the judging period, and each data group includes the same judging period.
  • the third step is to define the attributes of each data group, such as working hours, non-working hours, special holidays, time, etc.
  • the Ken group with the same attribute is assumed to be N, and the N data groups are sorted in chronological order.
  • Each M consecutive data groups form a data group set, which constitutes N-M+1.
  • Data set collection for example, there are 10 data groups with the same property, namely ⁇ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ⁇ , and each 4 consecutive data groups form a data.
  • the N-M+1 ⁇ 3 ⁇ 4 data set is separately normalized; in the sixth step, the normalized N-M+1 data sets are respectively subjected to Fourier Transforming, transforming the time domain signal of the data into a frequency domain signal;
  • the corresponding amplitudes of the frequency domain signals of the N-M+1 energy groups of the Fourier transform are summed and averaged to obtain the mean value of the amplitude values of the frequency domain signals.
  • the amplitudes of the frequency domain signals of the N-M+1 capable groups are respectively compared with the corresponding mean values, and it is determined that the Kens data group of the same attribute is used in an unreasonable data group.
  • Figure 1 shows the data collected per unit area of the air conditioning unit
  • Figure 2 is a set of energy data sets of the same attribute after Fourier transform, all frequency pairs The distribution of the mean value of the magnitude of Fn[k].
  • This analysis uses the Discrete Fourier Transform (DFT) method to analyze the energy efficiency management of a building's periodic load for an air-conditioning electricity in a building.
  • the electricity consumption data of the air-conditioning distribution box is taken out from the database of the energy consumption monitoring system, and the hourly energy consumption data of the air-conditioning distribution box in April 2011 is retrieved.
  • the judging period is selected as one day, that is, starting from 1 o'clock on the day and 24 o'clock as the end point, dividing the air-conditioning distribution box data into energy consumption data groups, and each data group has 24 hour energy consumption data.
  • By querying the calendar in April 2011, April 2, 3, 9, 10, 16, 17, 23, 24, 24, 30 are non-working days, so the above dates correspond.
  • the attribute of the energy data group is a non-working day, and the attribute of the data group corresponding to the remaining date is a work ⁇ .
  • the data of each data group in each data set is normalized, that is, the energy consumption data of 24 hours per day is divided by the maximum value of the current energy consumption data to obtain 24 hours of normalized data.
  • the four energy consumption data sets normalized in one energy consumption data set are expressed as: ⁇ ml, m2, m3,..., m24 ⁇ ; ⁇ pl,p2,p3,...,p24 ⁇ ; ⁇ al,a2,a3,... ,a24 ⁇ ; ⁇ bl,b2,b3,b4,...,b24 ⁇ .
  • the 24 hours data normalized in each energy consumption data group is expanded to 32 data (filled with 0, supplemented by 8 0s), and the 4 energy consumption data groups become ⁇ ml, respectively.
  • the amplitude of the kth term that is, the modulus of x [ fc ], where En[0] is the DC component amplitude
  • Fourier transform is performed on the above 18 sets of energy consumption data sets, respectively, and 18 Fourier series can be obtained.
  • the amplitudes of the corresponding kth items in each expansion that is, the moduli of x [ fc ] are respectively summed and averaged to obtain 128 average values Fn[k].
  • Figure 2 shows the distribution of the energy value data set of the weekday attribute after the Fourier transform mean Fn[k]. Since the value of Fn[k] is extremely small as k increases, it is only shown in Figure 2. The data of Fn[0] to Fn[32].
  • the amplitude (hereinafter referred to as the target octave component amplitude) is used as a research object to judge the unreasonable energy consumption data in the energy consumption data group of the same attribute.
  • the maximum value of the mean values of the AC component amplitudes is Fn [5].
  • Criterion 1 If the DC component amplitude En[0] exceeds 1.1 times Fn[0], when the target multiplication component amplitude En[5] is equal to or greater than the mean Fn[5], then the energy consumption data set is No abnormal energy consumption occurred.
  • Criterion 2 If the DC component En[0] exceeds 1.1 times Fn[0], the target octave component amplitude En[5] is less than the mean Fn[5] and satisfies En[5] ⁇ 0.98*Fn[5]
  • the last energy consumption data group exhibits abnormal energy consumption, and the abnormal energy consumption performance is increased in the energy consumption period of the day. There are loads in the electrical equipment that should be turned off and not turned off.
  • Criterion 3 If the DC component En[0] exceeds 1.1 times Fn[0], the target octave component amplitude En[5] is less than the mean Fn[5] and satisfies En[5] ⁇ 0.96*Fn[5]
  • the fourth energy consumption data group included in the energy consumption data group set the last energy consumption data group exhibits abnormal energy consumption, and the abnormal energy consumption performance is that the energy consumption exceeds the standard during the valley period of the current energy consumption. There are a large number of electrical equipment that should be turned off without being turned off.
  • Criterion 4 If the DC component En[0] exceeds 1.1 times Fn[0], the target octave component amplitude En[5] is less than the mean Fn[5] and satisfies En[5] ⁇ 0.92*Fn[5]
  • the fourth energy consumption data group included in the energy consumption data group set the last energy consumption data group exhibits abnormal energy consumption, and the abnormal energy consumption performance is that the energy consumption in the valley period of the day energy consumption exceeds the standard, almost The load on all devices should be turned off and not turned off.
  • the above-mentioned judgment is respectively performed, and the unreasonable energy consumption in the energy consumption data of the non-working day attribute and the special holiday attribute can be judged.
  • the invention solves the previous influence on the energy consumption, is not affected by the change caused by the energy growth, fully exerts the periodicity of the energy fluctuation, and uses the mathematical transformation combined with the building energy characteristics to judge the rationality of the building energy.
  • This technology can effectively manage the cyclical load of the office building and prevent it.
  • the use of energy can be wasted.
  • the data of the same acquisition unit is analyzed to prevent interference with the judgment result due to changes in the environment, nature, and region of the analysis data.

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  • Remote Monitoring And Control Of Power-Distribution Networks (AREA)

Abstract

L'invention vise, par l'analyse de l'utilisation d'énergie d'un dispositif consommant de l'énergie de façon périodique dans un bâtiment, à déterminer les caractéristiques de consommation d'énergie du dispositif périodique, et à décrire la consommation d'énergie du dispositif périodique dans le bâtiment sous la forme d'une série de Fourier. A cet effet,selon l'invention, par l'analyse du coefficient d'une expansion de séries, la solution évalue l'utilisation d'énergie du dispositif, trouve rapidement si l'utilisation d'énergie du dispositif est anormale ou déraisonnable, et peut en même temps identifier si la raison pour la fluctuation de charge périodique appartient ou non à une utilisation d'énergie normale.
PCT/CN2012/079700 2012-08-05 2012-08-05 Procédé pour gérer un rendement en énergie sous une charge périodique dans un bâtiment WO2014022955A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201280013354.9A CN103890806B (zh) 2012-08-05 2012-08-05 一种建筑周期性负荷能效管理方法
PCT/CN2012/079700 WO2014022955A1 (fr) 2012-08-05 2012-08-05 Procédé pour gérer un rendement en énergie sous une charge périodique dans un bâtiment

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Application Number Priority Date Filing Date Title
PCT/CN2012/079700 WO2014022955A1 (fr) 2012-08-05 2012-08-05 Procédé pour gérer un rendement en énergie sous une charge périodique dans un bâtiment

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WO2014022955A1 true WO2014022955A1 (fr) 2014-02-13

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CN (1) CN103890806B (fr)
WO (1) WO2014022955A1 (fr)

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CN101833310A (zh) * 2009-03-09 2010-09-15 纵横网路资讯股份有限公司 用电量管控系统及方法
CN102289585A (zh) * 2011-08-15 2011-12-21 重庆大学 基于数据挖掘的公共建筑能耗实时监测方法

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JP2000121126A (ja) * 1998-10-21 2000-04-28 Toshiba Corp ビル監視制御装置
CN101572638A (zh) * 2008-04-30 2009-11-04 当代天启技术（北京）有限公司 一种楼宇能耗分项计量的方法和系统
GB2481579B (en) * 2010-06-25 2014-11-26 Enmodus Ltd Monitoring of power-consumption
JP5283678B2 (ja) * 2010-10-25 2013-09-04 株式会社日立ビルシステム エネルギー管理システム
CN102034143A (zh) * 2010-10-26 2011-04-27 中华电信股份有限公司 节费式节能管理系统及其方法

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CN101833310A (zh) * 2009-03-09 2010-09-15 纵横网路资讯股份有限公司 用电量管控系统及方法
CN102289585A (zh) * 2011-08-15 2011-12-21 重庆大学 基于数据挖掘的公共建筑能耗实时监测方法

Non-Patent Citations (2)

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LIU, DANDAN: "Method for Detecting Abnormal Building Energy Consumption", JOURNAL OF SHANGHAI UNIVERSITY OF ELECTRIC POWER, vol. 27, no. 2, April 2011 (2011-04-01), pages 149 - 152 and 159, ISSN: 1006-4729 *
T.A. REDDY ET AL.: "Using synthetic data to evaluate multiple regression and principal component analyses for statistical modeling of daily building energy consumption", ENERGY AND BUILDINGS, vol. 21, no. 1, December 1994 (1994-12-01), pages 35 - 44 *

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CN103890806B (zh) 2016-06-15
CN103890806A (zh) 2014-06-25

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