CN103530822A - Method for analyzing loss reduction potential of grids of Gansu Province - Google Patents

Method for analyzing loss reduction potential of grids of Gansu Province Download PDF

Info

Publication number
CN103530822A
CN103530822A CN201310505305.3A CN201310505305A CN103530822A CN 103530822 A CN103530822 A CN 103530822A CN 201310505305 A CN201310505305 A CN 201310505305A CN 103530822 A CN103530822 A CN 103530822A
Authority
CN
China
Prior art keywords
mrow
loss
msub
grids
msubsup
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201310505305.3A
Other languages
Chinese (zh)
Inventor
王维洲
李俊游
周喜超
梁才
郑晶晶
但扬清
卓建宗
蔡万通
王建波
刘聪
刘文颖
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
State Grid Corp of China SGCC
North China Electric Power University
State Grid Gansu Electric Power Co Ltd
Electric Power Research Institute of State Grid Gansu Electric Power Co Ltd
Original Assignee
State Grid Corp of China SGCC
North China Electric Power University
State Grid Gansu Electric Power Co Ltd
Electric Power Research Institute of State Grid Gansu Electric Power Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by State Grid Corp of China SGCC, North China Electric Power University, State Grid Gansu Electric Power Co Ltd, Electric Power Research Institute of State Grid Gansu Electric Power Co Ltd filed Critical State Grid Corp of China SGCC
Priority to CN201310505305.3A priority Critical patent/CN103530822A/en
Publication of CN103530822A publication Critical patent/CN103530822A/en
Pending legal-status Critical Current

Links

Images

Landscapes

  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The invention discloses a method for analyzing loss reduction potential of grids of Gansu Province. The method comprises the steps as follows: influence factors of loss of the grids of the Gansu Province are analyzed, and the loss reduction potential of a single influence factor in the influence factors of the loss of the grids of the Gansu Province is analyzed as well; on the basis of the analyzed loss value of the grids of the Gansu Province, the loss reduction rates of measures to single influence factors are calculated respectively; on the basis of the calculated loss reduction rates, the influence factors of the loss of the grids of the Gansu Province are analyzed with variable-weight grey relational analysis method, and the grey correlation degree of a single influence factor to the loss of the grids of the Gansu Province is determined; and according to the determined grey correlation degree, the weight is determined, a comprehensive loss reduction rate formula is acquired with a weighting method, and the loss reduction potential of the grids of the Gansu Province is obtained. According to the method for analyzing the loss reduction potential of the grids of the Gansu Province, defects of large loss of the transmission grid, poor economic benefits, high production cost and the like in the prior art can be overcome, so that the advantages of small loss of the transmission grid, good economic benefits and low production cost are realized.

Description

Loss reduction potential analysis method for Gansu power grid
Technical Field
The invention relates to the technical field of energy conservation of power systems, in particular to a loss reduction potential analysis method for a Gansu power grid.
Background
The Gansu power grid is located in the center of the northwest power grid, the extended region is narrow and long, and the distance from the northwest to the southeast of the province power grid exceeds 1300 kilometers. Due to the special geographical position of the grids in Gansu province, frequent large-scale power exchange must be carried out through the grids in Gansu province, and extra transmission loss is caused to the grids in Gansu province. And the grids in Gansu province have large-scale wind power access, and these wind power are far away from the load center, can't be absorbed on the spot, need long distance outgoing, and this has also increased the active loss on the transmission line. In addition, in some areas of the grids in Gansu province, electromagnetic looped networks composed of 750kV and 330kV voltage levels can be generated, and active power can be circulated, so that active loss is increased.
Considering that the grid loss problem of the grids of Gansu province is very outstanding, the potential of loss reduction is very large, and on the basis of researching the generation mechanism of the grid loss of the grids of Gansu province in different dispatching operation modes, reasonable loss reduction measures need to be taken, so that the grid loss of the grids of Gansu province is effectively reduced, unnecessary loss in the power transmission process is reduced, the economic benefit of the grids of Gansu province is improved, and the production cost of grid enterprises is reduced.
At present, loss reduction analysis of each part in the grids in Gansu province has already been studied to a certain extent and is partially applied, but the research aims are mainly focused on the loss reduction analysis aiming at single factors, such as improving the transmission voltage grade to reduce the active loss of a transmission line, adopting an on-load tap changer to reduce the active loss of the transformer, optimizing the grid structure of the grids to reduce the loss caused by power circulation and the like, and the research is lacked in the aspect of a loss reduction potential analysis method aiming at the whole grids in Gansu province.
In the process of implementing the invention, the inventor finds that the prior art at least has the defects of large transmission network loss, poor economic benefit, high production cost and the like.
Disclosure of Invention
The invention aims to provide a loss reduction potential analysis method for a Gansu power grid to solve the problems so as to achieve the advantages of small transmission grid loss, good economic benefit and low production cost.
In order to achieve the purpose, the invention adopts the technical scheme that: a loss reduction potential analysis method for a Gansu power grid comprises the following steps:
a. analyzing influence factors of the grid loss of the Gansu power grid, and analyzing the loss reduction potential of a single influence factor in the influence factors of the grid loss of the Gansu power grid;
b. based on the mean loss value of the grids of Gansu province obtained by analyzing the step a, the loss reduction rate delta aiming at a single influence factor is respectively calculated and adoptedi
c. B, calculating the loss reduction rate delta based on the step biAnalyzing the influence factors of the grid loss of the Gansu power grid by using a variable-weight grey correlation analysis method, and determining the grey correlation degree omega of the influence of a single influence factor on the grid loss of the Gansu power gridi
d. The grey correlation degree omega determined according to the step ciDetermining the weight, obtaining a comprehensive loss reduction rate formula by using a weighting method to obtain the Gansu powerLoss reduction potential of the network.
Further, in step a, the influence factors of the grid loss of the grids of the Gansu province at least include the influence of the voltage level on the grid loss, the influence of the light load/heavy load of the line on the grid loss, the influence of the reactive compensation configuration on the grid loss, and the influence of the wind power output power on the grid loss.
Further, in step a, the operation of analyzing the loss reduction potential of the single factor includes:
analyzing the influence of the voltage grade on the network loss, and adopting a formula:
<math> <mrow> <mi>&Delta;</mi> <mrow> <mo>(</mo> <mi>&Delta;P</mi> <mo>)</mo> </mrow> <mo>=</mo> <mi>&Delta;P</mi> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <mfrac> <msubsup> <mi>U</mi> <mn>1</mn> <mn>2</mn> </msubsup> <msubsup> <mi>U</mi> <mn>2</mn> <mn>2</mn> </msubsup> </mfrac> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow> </math>
wherein, Delta P is the active loss value before voltage boosting, U1For pre-boost voltage class, U, of the grid2Boosting the voltage grade of the power grid; mainly analyzes the voltage class of 330kV and the voltage class of 750 kV.
Further, in step a, the operation of analyzing the loss reduction potential of the single factor further includes:
analyzing the influence of reactive compensation configuration on network loss, and adopting a formula:
Figure BDA0000400808880000022
wherein,
Figure BDA0000400808880000023
the power factor of the power supply is the original power factor,
Figure BDA0000400808880000024
to improve the power factor.
Further, in step a, the operation of analyzing the loss reduction potential of the single factor further includes:
analyzing the influence of the wind power output power on the grid loss, and adopting a formula for a power transmission system with n nodes:
<math> <mrow> <mi>&Delta;P</mi> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <mo>[</mo> <msup> <mrow> <mo>(</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mi>i</mi> <mo>+</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mfrac> <msub> <mi>P</mi> <mi>j</mi> </msub> <msub> <mi>V</mi> <mi>j</mi> </msub> </mfrac> <mo>-</mo> <mfrac> <msub> <mi>P</mi> <mi>WF</mi> </msub> <msub> <mi>V</mi> <mi>n</mi> </msub> </mfrac> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>+</mo> <msup> <mrow> <mo>(</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mi>i</mi> <mo>+</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mfrac> <msub> <mi>Q</mi> <mi>j</mi> </msub> <msub> <mi>V</mi> <mi>j</mi> </msub> </mfrac> <mo>+</mo> <mfrac> <msub> <mi>Q</mi> <mi>WF</mi> </msub> <msub> <mi>V</mi> <mi>n</mi> </msub> </mfrac> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>]</mo> <msub> <mi>R</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>i</mi> <mo>+</mo> <mn>1</mn> </mrow> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow> </math>
wherein, the active and reactive power of the wind power plant are respectively PWF、QWFThe power consumption of each node of the system is Pj、QjThe voltage of each node of the system is Vj,j∈[1,n]。
Further, in step a, the operation of analyzing the loss reduction potential of the single factor further includes:
and analyzing the influence of light/heavy load of the line on the network loss, performing curve analysis, and making a curve of the current magnitude of the head end of the line on the network loss by using a simulation result to obtain the influence trend of the transmission power of the line on the network loss.
Further, in step b, the calculation assumes a loss reduction rate δ for a single influencing factoriComprising:
the loss reduction rate is calculated by adopting a formula:
<math> <mrow> <msub> <mi>&delta;</mi> <mi>i</mi> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>&Delta;P</mi> <mn>0</mn> </msub> <mo>-</mo> <msub> <mi>&Delta;P</mi> <mn>1</mn> </msub> </mrow> <mi>P</mi> </mfrac> <mo>*</mo> <mn>100</mn> <mo>%</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>4</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow> </math>
wherein, Δ P0Representing the grid loss, Δ P, before taking action1And (4) representing the grid loss value after a certain measure is taken, wherein P is the total active power generation amount.
Further, in step c, the operation of analyzing the influence factors of the grid loss of the grids of the Gansu province by using the variable-weight grey correlation analysis method specifically includes:
the grey correlation analysis method for calculating the variable weight adopts a formula
Figure BDA0000400808880000032
Determining gray correlation degree of certain network loss influence factor after the weight is considered;
wherein, ω isijGray relevance without considering weight; wiAssociation weight for factor i:wherein
Figure BDA0000400808880000034
uikDetermining elements in the evaluation factor set U according to the change order relation and the additional influence of each network loss factor on the line loss; any factor XiAnd Y0The gray correlation coefficient of (a) is:
<math> <mrow> <msub> <mi>&omega;</mi> <mi>ij</mi> </msub> <mo>=</mo> <mfrac> <mrow> <mo>(</mo> <munder> <mi>min</mi> <mi>i</mi> </munder> <munder> <mi>min</mi> <mi>j</mi> </munder> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>+</mo> <mi>&zeta;</mi> <mi>max</mi> <mi>max</mi> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>)</mo> </mrow> <mrow> <mo>(</mo> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mi>&zeta;</mi> <mi>max</mi> <mi>max</mi> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>)</mo> </mrow> </mfrac> <mo>.</mo> </mrow> </math>
further, in step d, calculating the loss reduction potential of the grids of Gansu province by using a weighting method, and adopting a formula:
<math> <mrow> <mi>&delta;</mi> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>&alpha;</mi> <mi>j</mi> </msub> <msub> <mi>&delta;</mi> <mi>j</mi> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>6</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow> </math>
wherein alpha isjThe gray correlation equivalent weight coefficient influenced by a certain network loss,
Figure BDA0000400808880000042
and delta is the loss reduction potential of the grids in Gansu province, and the loss reduction potential delta of the grids in Gansu province can be obtained through the obtained actual value of the loss reduction rate of a certain factor and the weight of the factor.
The analytical method for loss reduction potential of the grids in Gansu province of the embodiments of the invention comprises the following steps: analyzing influence factors of the grid loss of the Gansu power grid, and analyzing the loss reduction potential of a single influence factor in the influence factors of the grid loss of the Gansu power grid; based on the analyzed mean loss value of the grids in Gansu province, the loss reduction rate delta aiming at a single influence factor is respectively calculated and adoptedi(ii) a Loss reduction rate delta obtained based on calculationiGrey correlation analysis using variable weightsThe method comprises the steps of analyzing influence factors of the grid loss of the Gansu power grid, and determining the grey relevance degree omega of the influence of a single influence factor on the grid loss of the Gansu power gridi(ii) a According to the determined grey correlation degree omegaiDetermining the weight, and obtaining a comprehensive loss reduction rate formula by using a weighting method to obtain the loss reduction potential of the Gansu power grid; the system can ensure that the Gansu power grid can operate under the most economic condition on the basis of ensuring safety and stability, and improves the transmission efficiency of the power grid; therefore, the defects of large transmission network loss, poor economic benefit and high production cost in the prior art can be overcome, and the advantages of small transmission network loss, good economic benefit and low production cost are realized.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic flow chart of the loss reduction potential analysis method for the grids of the Gansu province of the invention;
fig. 2 is a power grid wiring diagram of an embodiment of the loss reduction potential analysis method for the grids of the Gansu province of the invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
According to the embodiment of the invention, as shown in fig. 1 and fig. 2, a method for analyzing the loss reduction potential of the grids of the Gansu province is provided, and the method is used for analyzing how much loss reduction space the measures are taken to realize loss reduction during operation of the grids of the Gansu province.
The analytical method for loss reduction potential of the grids in Gansu province of the embodiment comprises the following steps:
step 1: analyzing the influence factors of the grid loss of the Gansu power grid, and analyzing the loss reduction potential of a single factor (namely the influence factors of the grid loss of the Gansu power grid);
in the step 1, influence factors of grid loss of the grids of the Gansu province specifically include influence of voltage levels on grid loss, influence of light/heavy load of a line on grid loss, influence of reactive compensation configuration on grid loss, influence of wind power output power on grid loss and the like;
in step 1, the operation of analyzing the loss reduction potential of a single factor comprises:
analyzing the influence of the voltage grade on the network loss, and adopting a formula:
<math> <mrow> <mi>&Delta;</mi> <mrow> <mo>(</mo> <mi>&Delta;P</mi> <mo>)</mo> </mrow> <mo>=</mo> <mi>&Delta;P</mi> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <mfrac> <msubsup> <mi>U</mi> <mn>1</mn> <mn>2</mn> </msubsup> <msubsup> <mi>U</mi> <mn>2</mn> <mn>2</mn> </msubsup> </mfrac> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow> </math>
wherein, Delta P is the active loss value before voltage boosting, U1For pre-boost voltage class, U, of the grid2Boosting the voltage grade of the power grid; mainly for 330kVAnalyzing the voltage grade and the 750kV voltage grade;
in step 1, the operation of analyzing the loss reduction potential of the single factor further comprises:
analyzing the influence of reactive compensation configuration on network loss, and adopting a formula:
wherein,
Figure BDA0000400808880000053
the power factor of the power supply is the original power factor,
Figure BDA0000400808880000054
to an improved power factor;
in step 1, the operation of analyzing the loss reduction potential of the single factor further comprises:
analyzing the influence of the wind power output power on the grid loss, and adopting a formula for a power transmission system with n nodes:
<math> <mrow> <mi>&Delta;P</mi> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <mo>[</mo> <msup> <mrow> <mo>(</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mi>i</mi> <mo>+</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mfrac> <msub> <mi>P</mi> <mi>j</mi> </msub> <msub> <mi>V</mi> <mi>j</mi> </msub> </mfrac> <mo>-</mo> <mfrac> <msub> <mi>P</mi> <mi>WF</mi> </msub> <msub> <mi>V</mi> <mi>n</mi> </msub> </mfrac> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>+</mo> <msup> <mrow> <mo>(</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mi>i</mi> <mo>+</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mfrac> <msub> <mi>Q</mi> <mi>j</mi> </msub> <msub> <mi>V</mi> <mi>j</mi> </msub> </mfrac> <mo>+</mo> <mfrac> <msub> <mi>Q</mi> <mi>WF</mi> </msub> <msub> <mi>V</mi> <mi>n</mi> </msub> </mfrac> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>]</mo> <msub> <mi>R</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>i</mi> <mo>+</mo> <mn>1</mn> </mrow> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow> </math>
wherein, the active and reactive power of the wind power plant are respectively PWF、QWFThe power consumption of each node of the system is Pj、QjThe voltage of each node of the system is Vj,j∈[1,n];
The corresponding change value of the network loss when the factors change can be obtained by performing offline load flow calculation by a power system analysis integration program (PSASP); in addition, for the influence of light/heavy load of the line on the network loss, curve analysis can be adopted, and a curve of the current magnitude at the head end of the line on the network loss is made by using a simulation result, so that the influence trend of the transmission power of the line on the network loss is obtained;
step 2: separate calculation of the loss reduction rate delta for a single influencing factori
In step 2, the calculation takes the loss reduction rate δ for a single influencing factoriComprising:
the loss reduction rate is calculated by adopting a formula:
<math> <mrow> <msub> <mi>&delta;</mi> <mi>i</mi> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>&Delta;P</mi> <mn>0</mn> </msub> <mo>-</mo> <msub> <mi>&Delta;P</mi> <mn>1</mn> </msub> </mrow> <mi>P</mi> </mfrac> <mo>*</mo> <mn>100</mn> <mo>%</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>4</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow> </math>
wherein, Δ P0Representing the grid loss, Δ P, before taking action1The grid loss value after a certain measure is taken is shown, and P is the total active power generation amount; the network loss values required by calculating the loss reduction rate are obtained by offline calculation of a power system analysis integration program (PSASP) in the step 1;
and step 3: the influence factors of the grid loss of the Gansu power grid are analyzed by applying the variable-weight grey correlation analysis method, and the grey correlation degree omega of the influence of a single influence factor (namely the influence factor of the grid loss of the Gansu power grid) on the grid loss of the Gansu power grid is determinedi
In step 3, the gray correlation method for calculating the variable weight adopts a formula
Figure BDA0000400808880000062
Determining certain network loss influence factor after considering weightThe gray correlation degree of (a);
wherein, ω isijGray relevance without considering weight; wiAssociation weight for factor i:
Figure BDA0000400808880000063
wherein
Figure BDA0000400808880000064
uikDetermining elements in the evaluation factor set U according to the change order relation and the additional influence of each network loss factor on the line loss; any factor XiAnd Y0The gray correlation coefficient of (a) is:
<math> <mrow> <msub> <mi>&omega;</mi> <mi>ij</mi> </msub> <mo>=</mo> <mfrac> <mrow> <mo>(</mo> <munder> <mi>min</mi> <mi>i</mi> </munder> <munder> <mi>min</mi> <mi>j</mi> </munder> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>+</mo> <mi>&zeta;</mi> <mi>max</mi> <mi>max</mi> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>)</mo> </mrow> <mrow> <mo>(</mo> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mi>&zeta;</mi> <mi>max</mi> <mi>max</mi> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>)</mo> </mrow> </mfrac> <mo>;</mo> </mrow> </math>
specifically, in step 3, the operation of calculating the gray association method of the variable weight further includes:
gray correlation method, taking historical statistics of network loss rate to form target sequence Y0Taking corresponding factor indexes to form factor sequence XiEstablishing a corresponding matrix <math> <mrow> <mfenced open='[' close=']'> <mtable> <mtr> <mtd> <msub> <mi>Y</mi> <mn>0</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>X</mi> <mn>1</mn> </msub> </mtd> </mtr> <mtr> <mtd> <mo>&CenterDot;</mo> </mtd> </mtr> <mtr> <mtd> <mo>&CenterDot;</mo> </mtd> </mtr> <mtr> <mtd> <mo>&CenterDot;</mo> </mtd> </mtr> <mtr> <mtd> <msub> <mi>X</mi> <mi>i</mi> </msub> </mtd> </mtr> </mtable> </mfenced> <mfenced open='' close=''> <mrow> <mo>=</mo> <mfenced open='[' close=']'> <mtable> <mtr> <mtd> <msub> <mi>Y</mi> <mn>0</mn> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mtd> <mtd> <msub> <mi>Y</mi> <mn>0</mn> </msub> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mtd> <mtd> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> </mtd> <mtd> <msub> <mi>Y</mi> <mn>0</mn> </msub> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <msub> <mi>X</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mtd> <mtd> <msub> <mi>X</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mtd> <mtd> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> </mtd> <mtd> <msub> <mi>X</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <mo>&CenterDot;</mo> </mtd> <mtd> <mo>&CenterDot;</mo> </mtd> <mtd> <mo>&CenterDot;</mo> </mtd> <mtd> <mo>&CenterDot;</mo> </mtd> </mtr> <mtr> <mtd> <mo>&CenterDot;</mo> </mtd> <mtd> <mo>&CenterDot;</mo> </mtd> <mtd> <mo>&CenterDot;</mo> </mtd> <mtd> <mo>&CenterDot;</mo> </mtd> </mtr> <mtr> <mtd> <mo>&CenterDot;</mo> </mtd> <mtd> <mo>&CenterDot;</mo> </mtd> <mtd> <mo>&CenterDot;</mo> </mtd> <mtd> <mo>&CenterDot;</mo> </mtd> </mtr> <mtr> <mtd> <msub> <mi>X</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mtd> <mtd> <msub> <mi>X</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mtd> <mtd> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> </mtd> <mtd> <msub> <mi>X</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> </mtd> </mtr> </mtable> </mfenced> </mrow> </mfenced> <mo>,</mo> </mrow> </math> The grey correlation coefficient is obtained by adopting a formula:
<math> <mrow> <msub> <mi>&omega;</mi> <mi>ij</mi> </msub> <mo>=</mo> <mfrac> <mrow> <mo>(</mo> <munder> <mi>min</mi> <mi>i</mi> </munder> <munder> <mi>min</mi> <mi>j</mi> </munder> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>+</mo> <mi>&zeta;</mi> <mi>max</mi> <mi>max</mi> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>)</mo> </mrow> <mrow> <mo>(</mo> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mi>&zeta;</mi> <mi>max</mi> <mi>max</mi> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>)</mo> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow> </math>
wherein any factor X is calculatediAnd Y0Zeta is 0.5;
<math> <mrow> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mo>=</mo> <mo>{</mo> <mn>1</mn> <mo>,</mo> <mfrac> <mrow> <msub> <mi>Y</mi> <mn>0</mn> </msub> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow> <mrow> <msub> <mi>Y</mi> <mn>0</mn> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>,</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>,</mo> <mfrac> <mrow> <msub> <mi>Y</mi> <mn>0</mn> </msub> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> </mrow> <mrow> <msub> <mi>Y</mi> <mn>0</mn> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>}</mo> </mrow> </math>
<math> <mrow> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mo>=</mo> <mo>{</mo> <mn>1</mn> <mo>,</mo> <mfrac> <mrow> <msub> <mi>X</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow> <mrow> <msub> <mi>X</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>,</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>,</mo> <mfrac> <mrow> <msub> <mi>X</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> </mrow> <mrow> <msub> <mi>X</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>}</mo> <mo>,</mo> </mrow> </math> Xiand Y0Positive correlation
<math> <mrow> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mo>=</mo> <mo>{</mo> <mn>1</mn> <mo>,</mo> <mfrac> <mrow> <msub> <mi>c</mi> <mi>i</mi> </msub> <mo>-</mo> <msub> <mi>X</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow> <mrow> <msub> <mi>c</mi> <mi>i</mi> </msub> <mo>-</mo> <msub> <mi>X</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>,</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>&CenterDot;</mo> <mo>,</mo> <mfrac> <mrow> <msub> <mi>c</mi> <mi>i</mi> </msub> <mo>-</mo> <msub> <mi>X</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> </mrow> <mrow> <msub> <mi>c</mi> <mi>i</mi> </msub> <mo>-</mo> <msub> <mi>X</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>}</mo> <mo>,</mo> </mrow> </math> XiAnd Y0Negative correlation;
the gray correlation method of variable weight adopts a formula
Figure BDA0000400808880000076
Determining gray correlation degree of certain network loss influence factor after the weight is considered; wherein ω isijTo consider the gray degree of the weight, WiFor the associated weight of the factor i,
Figure BDA0000400808880000077
wherein
Figure BDA0000400808880000078
uikDetermining elements in the evaluation factor set U according to the change order relation and the additional influence of each network loss factor on the line loss;
and 4, step 4: determining weight according to the grey correlation degree, and obtaining a comprehensive loss reduction rate formula by using a weighting method so as to obtain the loss reduction potential of the Gansu power grid;
in step 4, calculating the loss reduction potential of the grids in Gansu province by using a weighting method, and adopting a formula:
<math> <mrow> <mi>&delta;</mi> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>&alpha;</mi> <mi>j</mi> </msub> <msub> <mi>&delta;</mi> <mi>j</mi> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>6</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow> </math>
wherein alpha isjThe gray correlation equivalent weight coefficient influenced by a certain network loss,
Figure BDA0000400808880000081
and delta is the loss reduction potential of the grids in Gansu province, and the loss reduction potential delta of the grids in Gansu province can be obtained through the obtained actual value of the loss reduction rate of a certain factor and the weight of the factor.
In the following, a power grid in the river west area of Gansu province in 2013 is taken as an embodiment of the invention, and the sweet taste of the embodiment is obtained And further explaining a depreciation potential analysis method of the depreciation power grid.
The grid wiring diagram of the areas of Hexi, Gansu is shown in FIG. 2. And calculating by using a power system analysis integrated program (PSASP) according to data packets of the winter and summer in the 2013 operation mode of the Gansu power grid, wherein the grid loss rate in the 2013 summer operation mode is 1.31%, and the grid loss rate in the 2013 winter operation mode is 1.27%. In the embodiment, the active loss of the lines with two voltage classes of 750kV and 330kV is mainly considered. The influence of the following factors on the network loss is considered: x1The influence of the change of the power flow distribution (the power flow is transferred to the transmission line with high voltage grade, which is equivalent to the improvement of the voltage grade of the phase change) on the network loss; x2The influence of the wind power output scale on the network loss is achieved; x3The effect on the network loss when changes occur (i.e. changes in the power factor) for reactive compensation.
Under the condition of ensuring reasonable system load flow, only a single factor is changed, and a power system analysis integration program (PSASP) is used for calculating the loss reduction rate delta caused by the single factorj
Factors of the fact Loss reduction Rate (%)
X1 0.31
X2 0.17
X3 0.22
Table 1: single factor decreasing rate table
Obtaining the grey correlation degree of each factor on the network loss by adopting variable weight grey correlation analysis, converting the grey correlation degree into the weight proportion of each factor considering the grey correlation degree on the network loss as alpha1=0.45,α2=0.3,α3Substituted as 0.25
Figure BDA0000400808880000082
The comprehensive loss reduction rate delta of the power grid in the Hexi area of Gansu is 0.2455% in consideration of the three factors.
In summary, the method for analyzing the loss reduction potential of the grids in the Gansu province according to the embodiments of the present invention is particularly suitable for the Gansu region, and includes: analyzing influence factors of grid loss of the grids in Gansu province, and analyzing the loss reduction potential of a single factor; respectively calculating the loss reduction rate aiming at a single influence factor; analyzing factors influencing the grid loss of the Gansu power grid by using a variable-weight grey correlation analysis method, and determining the grey correlation degree of a single influence factor on the influence of the Gansu power grid loss; and determining the weight according to the grey correlation degree, and obtaining a comprehensive loss reduction rate formula by using a weighting method so as to obtain the loss reduction potential of the Gansu power grid. The loss reduction potential analysis method for the Gansu power grid ensures that the Gansu power grid can operate under the most economic condition on the basis of ensuring safety and stability, and improves the transmission efficiency of the power grid.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (9)

1. A loss reduction potential analysis method for a Gansu power grid is characterized by comprising the following steps:
a. analyzing influence factors of the grid loss of the Gansu power grid, and analyzing the loss reduction potential of a single influence factor in the influence factors of the grid loss of the Gansu power grid;
b. based on the mean loss value of the grids of Gansu province obtained by analyzing the step a, the loss reduction rate delta aiming at a single influence factor is respectively calculated and adoptedi
c. B, calculating the loss reduction rate delta based on the step biApplying a variable-weight grey correlation analysis method to the loss of the grids in Gansu provinceThe influence factors are analyzed, and the grey correlation degree omega of the influence of the single influence factor on the grid loss of the Gansu power grid is determinedi
d. The grey correlation degree omega determined according to the step ciDetermining the weight, and obtaining a comprehensive loss reduction rate formula by using a weighting method to obtain the loss reduction potential of the Gansu power grid.
2. The analytical method for loss reduction potential of the grids of Gansu province according to claim 1, wherein in the step a, the influence factors of the grid loss of the Gansu province at least include influence of voltage levels on the grid loss, influence of line light/heavy loads on the grid loss, influence of reactive compensation configuration on the grid loss, and influence of wind power output power on the grid loss.
3. The grids and grids degradation potential analysis method of Gansu of claim 1 or 2, wherein in step a, the operation of analyzing the degradation potential of the single factor includes:
analyzing the influence of the voltage grade on the network loss, and adopting a formula:
<math> <mrow> <mi>&Delta;</mi> <mrow> <mo>(</mo> <mi>&Delta;P</mi> <mo>)</mo> </mrow> <mo>=</mo> <mi>&Delta;P</mi> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <mfrac> <msubsup> <mi>U</mi> <mn>1</mn> <mn>2</mn> </msubsup> <msubsup> <mi>U</mi> <mn>2</mn> <mn>2</mn> </msubsup> </mfrac> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow> </math>
wherein, Delta P is the active loss value before voltage boosting, U1For pre-boost voltage class, U, of the grid2Boosting the voltage grade of the power grid; mainly aiming at 330kV voltage class and750kV voltage class was analyzed.
4. The grids and grids degradation potential analysis method of Gansu of claim 1 or 2, wherein in step a, the operation of analyzing the degradation potential of the single factor further comprises:
analyzing the influence of reactive compensation configuration on network loss, and adopting a formula:
Figure FDA0000400808870000021
wherein,
Figure FDA0000400808870000022
the power factor of the power supply is the original power factor,
Figure FDA0000400808870000023
to improve the power factor.
5. The grids and grids degradation potential analysis method of Gansu of claim 1 or 2, wherein in step a, the operation of analyzing the degradation potential of the single factor further comprises:
analyzing the influence of the wind power output power on the grid loss, and adopting a formula for a power transmission system with n nodes:
<math> <mrow> <mi>&Delta;P</mi> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </munderover> <mo>[</mo> <msup> <mrow> <mo>(</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mi>i</mi> <mo>+</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mfrac> <msub> <mi>P</mi> <mi>j</mi> </msub> <msub> <mi>V</mi> <mi>j</mi> </msub> </mfrac> <mo>-</mo> <mfrac> <msub> <mi>P</mi> <mi>WF</mi> </msub> <msub> <mi>V</mi> <mi>n</mi> </msub> </mfrac> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>+</mo> <msup> <mrow> <mo>(</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mi>i</mi> <mo>+</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mfrac> <msub> <mi>Q</mi> <mi>j</mi> </msub> <msub> <mi>V</mi> <mi>j</mi> </msub> </mfrac> <mo>+</mo> <mfrac> <msub> <mi>Q</mi> <mi>WF</mi> </msub> <msub> <mi>V</mi> <mi>n</mi> </msub> </mfrac> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>]</mo> <msub> <mi>R</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>i</mi> <mo>+</mo> <mn>1</mn> </mrow> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow> </math>
wherein, the active and reactive power of the wind power plant are respectively PWF、QWFThe power consumption of each node of the system is Pj、QjThe voltage of each node of the system is Vj,j∈[1,n]。
6. The grids and grids degradation potential analysis method of Gansu of claim 1 or 2, wherein in step a, the operation of analyzing the degradation potential of the single factor further comprises:
and analyzing the influence of light/heavy load of the line on the network loss, performing curve analysis, and making a curve of the current magnitude of the head end of the line on the network loss by using a simulation result to obtain the influence trend of the transmission power of the line on the network loss.
7. The analytical method for loss reduction potential of grids of Gansu province according to claim 1, wherein in step b, the loss reduction rate δ for a single influence factor is adopted in calculationiComprising:
the loss reduction rate is calculated by adopting a formula:
<math> <mrow> <msub> <mi>&delta;</mi> <mi>i</mi> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>&Delta;P</mi> <mn>0</mn> </msub> <mo>-</mo> <msub> <mi>&Delta;P</mi> <mn>1</mn> </msub> </mrow> <mi>P</mi> </mfrac> <mo>*</mo> <mn>100</mn> <mo>%</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>4</mn> <mo>)</mo> </mrow> <mo>;</mo> </mrow> </math>
wherein, Δ P0Representing the grid loss, Δ P, before taking action1And (4) representing the grid loss value after a certain measure is taken, wherein P is the total active power generation amount.
8. The analytical method for loss reduction potential of grids of Gansu province according to claim 1, wherein in the step c, the operation of analyzing the influence factors of the grid loss of Gansu province by applying the variable-weight grey correlation analysis method specifically comprises:
the grey correlation analysis method for calculating the variable weight adopts a formula
Figure FDA0000400808870000031
Determining gray correlation degree of certain network loss influence factor after the weight is considered;
wherein, ω isijGray relevance without considering weight; wiAssociation weight for factor i:
Figure FDA0000400808870000032
wherein
Figure FDA0000400808870000033
uikDetermining elements in the evaluation factor set U according to the change order relation and the additional influence of each network loss factor on the line loss; any factor XiAnd Y0The gray correlation coefficient of (a) is:
<math> <mrow> <msub> <mi>&omega;</mi> <mi>ij</mi> </msub> <mo>=</mo> <mfrac> <mrow> <mo>(</mo> <munder> <mi>min</mi> <mi>i</mi> </munder> <munder> <mi>min</mi> <mi>j</mi> </munder> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>+</mo> <mi>&zeta;</mi> <mi>max</mi> <mi>max</mi> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>)</mo> </mrow> <mrow> <mo>(</mo> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mi>&zeta;</mi> <mi>max</mi> <mi>max</mi> <mo>|</mo> <msubsup> <mi>Y</mi> <mn>0</mn> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msubsup> <mi>X</mi> <mi>i</mi> <mo>*</mo> </msubsup> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>)</mo> </mrow> </mfrac> <mo>.</mo> </mrow> </math>
9. the analytical method for loss reduction potential of the grids of Gansu province according to claim 1, wherein in the step d, the loss reduction potential of the grids of Gansu province is calculated by a weighting method, and a formula is adopted:
<math> <mrow> <mi>&delta;</mi> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>&alpha;</mi> <mi>j</mi> </msub> <msub> <mi>&delta;</mi> <mi>j</mi> </msub> </mrow> </math>
wherein alpha isjGrey relation for certain network loss influence, etcThe weight coefficient of the value is such that,and the loss reduction potential delta of the grids in Gansu province can be obtained through the obtained actual value of the loss reduction rate of a certain factor and the weight of the factor.
CN201310505305.3A 2013-10-23 2013-10-23 Method for analyzing loss reduction potential of grids of Gansu Province Pending CN103530822A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201310505305.3A CN103530822A (en) 2013-10-23 2013-10-23 Method for analyzing loss reduction potential of grids of Gansu Province

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201310505305.3A CN103530822A (en) 2013-10-23 2013-10-23 Method for analyzing loss reduction potential of grids of Gansu Province

Publications (1)

Publication Number Publication Date
CN103530822A true CN103530822A (en) 2014-01-22

Family

ID=49932806

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201310505305.3A Pending CN103530822A (en) 2013-10-23 2013-10-23 Method for analyzing loss reduction potential of grids of Gansu Province

Country Status (1)

Country Link
CN (1) CN103530822A (en)

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103886513A (en) * 2014-02-25 2014-06-25 国家电网公司 Modeling method of surface roughness change model for wind power plant micro-sitting selection
CN104810827A (en) * 2015-05-12 2015-07-29 华北电力大学 Line optimum transmission power calculation method considering parallel connection reactor and corona loss
CN106451413A (en) * 2016-06-02 2017-02-22 国网江西省电力公司赣东北供电分公司 Method for intelligently generating power loss statistical region based on power grid topological structure
CN106684858A (en) * 2016-11-07 2017-05-17 国网甘肃省电力公司电力科学研究院 Power distribution network loss reduction measure determining method and device
CN106779282A (en) * 2016-11-14 2017-05-31 国电南瑞科技股份有限公司 Network loss a reference value modification method in a kind of assessment period
CN108550084A (en) * 2018-03-21 2018-09-18 广东电网有限责任公司佛山供电局 A method of based on history electricity charge information assessment distribution transforming drop damage potentiality

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2010011711A (en) * 2008-06-30 2010-01-14 Kawasaki Heavy Ind Ltd Microgrid using electric railroad system
CN102129506A (en) * 2011-01-07 2011-07-20 浙江省电力试验研究院 Method for predicting theoretical line loss
CN102567645A (en) * 2012-01-10 2012-07-11 河北省电力公司 Method for counting equipment of power grid and computing transmission losses on basis of on-line theoretical transmission loss computation

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2010011711A (en) * 2008-06-30 2010-01-14 Kawasaki Heavy Ind Ltd Microgrid using electric railroad system
CN102129506A (en) * 2011-01-07 2011-07-20 浙江省电力试验研究院 Method for predicting theoretical line loss
CN102567645A (en) * 2012-01-10 2012-07-11 河北省电力公司 Method for counting equipment of power grid and computing transmission losses on basis of on-line theoretical transmission loss computation

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
刁瑞盛: "风力发电对电网的影响研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 *
邱泽晶 等: "改进灰关联的配电网降损潜力评估", 《中国农村水利水电》 *
陈炜,武美惠: "农网降损技术措施及其效果", 《华北电力技术》 *

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103886513A (en) * 2014-02-25 2014-06-25 国家电网公司 Modeling method of surface roughness change model for wind power plant micro-sitting selection
CN103886513B (en) * 2014-02-25 2017-06-16 国家电网公司 A kind of wind power plant microcosmic structure modeling method of roughness of ground surface variation model
CN104810827A (en) * 2015-05-12 2015-07-29 华北电力大学 Line optimum transmission power calculation method considering parallel connection reactor and corona loss
CN106451413A (en) * 2016-06-02 2017-02-22 国网江西省电力公司赣东北供电分公司 Method for intelligently generating power loss statistical region based on power grid topological structure
CN106684858A (en) * 2016-11-07 2017-05-17 国网甘肃省电力公司电力科学研究院 Power distribution network loss reduction measure determining method and device
CN106684858B (en) * 2016-11-07 2019-05-07 国网甘肃省电力公司电力科学研究院 A kind of determination method and device of power distribution network reducing loss measure
CN106779282A (en) * 2016-11-14 2017-05-31 国电南瑞科技股份有限公司 Network loss a reference value modification method in a kind of assessment period
CN108550084A (en) * 2018-03-21 2018-09-18 广东电网有限责任公司佛山供电局 A method of based on history electricity charge information assessment distribution transforming drop damage potentiality

Similar Documents

Publication Publication Date Title
CN109325694B (en) Power distribution network optimization method based on bearing capacity
CN103530822A (en) Method for analyzing loss reduction potential of grids of Gansu Province
CN106849057B (en) Distributed wind power supply optimization method based on modern interior point method and Sensitivity Analysis Method
CN104037776B (en) The electric network reactive-load capacity collocation method of random inertial factor particle swarm optimization algorithm
CN109599892A (en) A kind of appraisal procedure of 10 kilovolts of planning power grid distributed photovoltaic digestion capability
Krishnan et al. Evaluating the value of high spatial resolution in national capacity expansion models using ReEDS
CN106600459A (en) Optimization method for overcoming voltage deviation of photovoltaic access point
CN105978016A (en) Optimization control method based on optimal power flow for multi-terminal flexible direct current transmission system
CN103986193B (en) A kind of method that maximum wind grid connection capacity obtains
CN107947192A (en) A kind of optimal reactive power allocation method of droop control type isolated island micro-capacitance sensor
CN108376996B (en) Practical power distribution network distributed photovoltaic receiving capacity estimation method
CN105826944A (en) Method and system for predicting power of microgrid group
CN104463357A (en) Method for evaluating random intermittent DG optimized integration based on random optimal power flow
CN113489003B (en) Source network coordination planning method considering wind-light-water integrated complementary operation
CN107230999B (en) Regional distributed photovoltaic maximum capacity access evaluation method
CN102855592A (en) Multi-target peak regulation optimizing method and system
CN103346573B (en) Planing method that wind power system based on golden section cloud particle swarm optimization algorithm is idle
CN106229995B (en) Based on the backup power source shunt reactor parameter optimization method under the Anti-Typhoon operational mode of wind power plant
CN109214713B (en) Planning method for active power distribution network containing distributed power supply
CN103824124B (en) A kind of energy potential evaluation method for grid company
CN114069687A (en) Distributed photovoltaic planning method considering reactive power regulation effect of inverter
CN105262148B (en) The planning year power balance method of meter and wind power output characteristic
CN113919635A (en) Park comprehensive energy system evaluation method based on energy efficiency-economy-environment
CN104242354B (en) Meter and the new energy of honourable output correlation, which are concentrated, sends operation characteristic appraisal procedure outside
CN104657910A (en) Daily operation evaluation method for power grid

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20140122

RJ01 Rejection of invention patent application after publication