CN112990559A - Method for selecting low-voltage business expansion power supply point - Google Patents
Method for selecting low-voltage business expansion power supply point Download PDFInfo
- Publication number
- CN112990559A CN112990559A CN202110232307.4A CN202110232307A CN112990559A CN 112990559 A CN112990559 A CN 112990559A CN 202110232307 A CN202110232307 A CN 202110232307A CN 112990559 A CN112990559 A CN 112990559A
- Authority
- CN
- China
- Prior art keywords
- formula
- power supply
- peak
- supply point
- power
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000011156 evaluation Methods 0.000 claims abstract description 99
- 238000012216 screening Methods 0.000 claims abstract description 3
- 239000011159 matrix material Substances 0.000 claims description 32
- 238000004364 calculation method Methods 0.000 claims description 25
- 239000005364 simax Substances 0.000 claims description 16
- 230000014509 gene expression Effects 0.000 claims description 7
- XXXSILNSXNPGKG-ZHACJKMWSA-N Crotoxyphos Chemical compound COP(=O)(OC)O\C(C)=C\C(=O)OC(C)C1=CC=CC=C1 XXXSILNSXNPGKG-ZHACJKMWSA-N 0.000 claims description 6
- 150000001875 compounds Chemical class 0.000 claims description 6
- NAWXUBYGYWOOIX-SFHVURJKSA-N (2s)-2-[[4-[2-(2,4-diaminoquinazolin-6-yl)ethyl]benzoyl]amino]-4-methylidenepentanedioic acid Chemical compound C1=CC2=NC(N)=NC(N)=C2C=C1CCC1=CC=C(C(=O)N[C@@H](CC(=C)C(O)=O)C(O)=O)C=C1 NAWXUBYGYWOOIX-SFHVURJKSA-N 0.000 claims description 4
- 238000010276 construction Methods 0.000 claims description 4
- 230000000694 effects Effects 0.000 claims description 4
- 238000010606 normalization Methods 0.000 claims description 3
- 230000005611 electricity Effects 0.000 claims description 2
- 238000010187 selection method Methods 0.000 claims description 2
- 238000006116 polymerization reaction Methods 0.000 claims 2
- 230000009286 beneficial effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/043—Optimisation of two dimensional placement, e.g. cutting of clothes or wood
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- Development Economics (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Educational Administration (AREA)
- Game Theory and Decision Science (AREA)
- Health & Medical Sciences (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to a method for selecting low-voltage industrial expansion power supply points, which comprises the following steps: firstly, calculating an openable capacity curve of a power supply point to be selected, then calculating a capacity margin curve of the power supply point to be selected according to the openable capacity curve of the power supply point to be selected and a maximum daily load curve of a power user to be accessed, preliminarily screening power supply points with capacity margins meeting requirements according to the capacity margin curve, constructing an evaluation index system aiming at the power supply points with the capacity margins meeting the requirements, solving a weight coefficient of each evaluation index in the evaluation index system by using an AHP algorithm, evaluating the power supply points with the capacity margins meeting the requirements by using a TOPSIS algorithm, and finally selecting an optimal low-voltage business expansion power supply point according to an evaluation result. The invention considers the distribution network distribution area of the power point to be selected and the time distribution characteristic of the load of the power user to be accessed, and provides scientific basis for the selection of the low-voltage business expansion power point.
Description
Technical Field
The invention relates to the technical field of electric power, in particular to a method for selecting low-voltage industrial expansion power supply points.
Background
At present, when an electric power worker selects the low-voltage business expansion power supply point, the difference value between the maximum load of a distribution network area to which the power supply point to be selected belongs and the rated capacity of a distribution transformer is calculated and used as the openable capacity of the power supply point, then the openable capacity of the power supply point to be selected, the maximum load of the power user to be accessed and the distance between the power supply point to be selected and the power user to be accessed are comprehensively considered, and a decision is made by experience so as to select the proper power supply point. The selection mode of the low-voltage power expansion point not only does not consider the distribution network area to which the power point to be selected belongs and the time distribution characteristic of the load of the power user to be accessed, but also has strong subjectivity and often has an unsatisfactory effect, and the capacity of a distribution transformer is easy to be idle or the investment of a power cable is easy to increase. Therefore, it is necessary to invent a method for selecting a low voltage expansion power supply point, which provides a scientific basis for selecting the low voltage expansion power supply point.
Disclosure of Invention
The invention aims to provide a scientific and reasonable selection method of a low-voltage industrial expansion power supply point.
The technical scheme of the invention is as follows:
firstly, calculating an openable capacity curve of a power supply point to be selected, then calculating a capacity margin curve of the power supply point to be selected according to the openable capacity curve of the power supply point to be selected and a maximum daily load curve of a power user to be accessed, preliminarily screening power supply points with capacity margins meeting requirements according to the capacity margin curve, constructing an evaluation index system aiming at the power supply points with the capacity margins meeting the requirements, solving a weight coefficient of each evaluation index in the evaluation index system by using an AHP algorithm, evaluating the power supply points with the capacity margins meeting the requirements by using a TOPSIS algorithm, and finally selecting an optimal low-voltage business expansion power supply point according to an evaluation result.
1. Open-able capacity curve of candidate power point
Defining an openable capacity curve S of a power supply point to be selectedOAs shown in formula (1).
SO＝[so1,so2,…,soi…,son] (1)
(1) In the formula, soiThe open capacity of the power supply point to be selected at the ith load acquisition time in one day can be calculated according to the formula (2); and n is the load collection times of the electricity utilization information collection system in one day.
soi＝SN-simax (2)
(2) In the formula, SNRated capacity of a distribution transformer of a distribution network area to which a power supply point to be selected belongs; simaxThe power distribution station area maximum daily load curve is the ith element of the distribution station area maximum daily load curve to which the power supply point to be selected belongs.
The definition of the maximum daily load curve of the distribution network area to which the power supply point to be selected belongs is shown as a formula (3).
Smax＝[s1max,s2max,…,simax,…,snmax] (3)
(3) In the formula, simaxThe calculation method (2) is shown in the formula (4).
simax＝max(s1i,s2i,…,sji,…sNi) (4)
(4) In the formula, sjiThe load value of the ith load acquisition time of the j-th day in the statistical period of the distribution network area to which the power supply point to be selected belongs; n is the number of days in the statistical period.
2. Maximum daily load curve of power consumer to be accessed
Defining a maximum daily load curve L of a power consumer to be accessedmaxAs shown in formula (5).
Lmax＝[l1max,l2max,…,limax,…,lnmax] (5)
(5) In the formula IimaxThe maximum load value of the ith load acquisition time of the power consumer to be accessed in one day is estimated and obtained by the power consumer; n is defined as formula (1).
3. Candidate power point capacity margin research and judgment
Capacity margin curve S for defining power supply points to be selectedLAs shown in formula (6).
SL＝[sL1,sL2,...,sLi,...,sLn] (6)
(6) In the formula, sLiThe capacity margin of the power supply point to be selected at the ith load acquisition time in one day is calculated in the mode shown as the formula (7); n is defined as formula (1).
sLi＝soi-limax (7)
(7) In the formula, soiThe definition is the same as the formula (1); limaxThe same formula (5) is defined.
If the capacity margin curve S of the power supply point to be selectedLAnd (4) if the formula (8) is met, judging that the capacity margin of the power supply point to be selected meets the requirement.
(8) In the formula, eta is a margin coefficient and is preset by a worker; sNThe definition is the same as the formula (2).
4. Evaluation index system
Defining a power point set to be selected with capacity margin meeting the requirement as C, and constructing an evaluation index system aiming at each power point in the set C, wherein the evaluation index system comprises peak-to-peak load contact ratio PppPeak to valley loading ratio PpvAnd power point distance Ds. Peak to peak load contact ratio PppThe coincidence degree of the peak of the maximum daily load curve of the distribution network area to which the power supply point belongs and the peak of the maximum daily load curve of the power user to be accessed is represented, and the smaller the value of the peak is, the lower the probability of raising the original peak of the load of the distribution network area to which the power supply point belongs is after the power user is accessed is indicated; peak to valley load overlap ratio PpvThe coincidence degree of the high peak of the maximum daily load curve of the distribution network area to which the power supply point belongs and the low valley of the maximum daily load curve of the power consumer to be accessed and the low valley of the maximum daily load curve of the distribution network area to which the power supply point belongs and the high peak of the maximum daily load curve of the power consumer to be accessed are represented, and the larger the value is, the better the peak clipping and valley filling effect on the original load of the distribution network area to which the power supply point load belongs is; distance D of power supply pointsThe distance between the power supply point and the power consumer to be accessed is represented, and the smaller the value of the distance is, the smaller the investment of the power cable is.
4.1 Peak-to-Peak load contact ratio Ppp
Peak to peak load contact ratio PppThe calculation method is shown in the formula (9).
(9) In the formula, npThe peak load points in the maximum daily load curve of the distribution network area to which the power supply points belong are calculated in the mode shown as the formula (10); n isppThe calculation mode of the peak load coincidence point number is shown as the formula (13) of the maximum daily load curve of the distribution network area to which the power supply point belongs and the maximum daily load curve of the power user to be accessed.
(10) In the formula (f)spiIs s isimaxThe calculation method of the peak identifier of (2) is shown as (11).
(11) In the formula, SpeakMaximum daily load curve S of distribution network area to which power supply point belongsmaxThe peak value of (1) is calculated by the method shown in the formula (12); simaxThe definition is shown as the formula (2).
Speak＝max(s1max,s2max,…,simax,…,snmax) (12)
(13) In the formula (f)lpiIs 1imaxThe calculation method of the peak identifier (2) is shown as (14).
(14) In the formula, LpeakMaximum daily load curve L for planned access power consumermaxThe peak value of (1) is calculated by the method shown in the formula (15); limaxThe definition is shown as the formula (5).
Lpeak＝max(l1max,l2max,…,limax,…,lnmax) (15)
4.2 Peak-to-valley load contact ratio Ppv
Peak to valley load overlap ratio PpvThe calculation method is shown in the formula (16).
npvMaximum daily load curve of distribution network area of power supply pointThe calculation method of the coincidence point of the line peak load and the maximum daily load curve valley load of the power user to be accessed is shown as the formula (17); n isvpThe calculation method is shown as formula (19), and the calculation method is the coincidence point number of the maximum daily load curve low load of the distribution network area where the power supply point belongs and the maximum daily load curve high load of the power user to be accessed; n ispThe same formula (9) is defined; n isvThe number of the valley load points in the maximum daily load curve of the distribution network area to which the power supply point belongs is calculated in a mode shown as a formula (21);
fspithe same formula (10) is defined; f. oflviIs 1imaxThe calculation method of the valley mark of (2) is shown as (18).
(18) In the formula, LpeakThe same formula (14) is defined; limaxThe definition is shown as the formula (5). .
(19) In the formula (f)sviIs s isimaxThe calculation method of the valley mark of (2) is shown as (20); f. oflpiThe definition is shown as the formula (13).
(20) In the formula, PpeakThe same formula (11) is defined; simaxThe definition is shown as the formula (2).
(21) In the formula (f)sviThe definition is shown as formula (19).
4.3 Power Point distance Ds
Distance D of power supply pointsThe straight line distance between the power user and the power supply point is planned to be accessed, and can be obtained through a power GIS system.
5. Evaluation index weight coefficient
The invention firstly uses AHP algorithm to solve the weight coefficient of each evaluation index, and the concrete steps are as follows:
(1) constructing a decision matrix
And comparing the evaluation indexes pairwise to obtain a judgment matrix B as shown in the formula (22). Since the present invention has 3 evaluation indexes, B is a 3-order matrix.
Each element in B represents the result of comparing the importance of two compared evaluation indexes, such as B12The result of comparing the importance of the 1 st evaluation index and the 2 nd evaluation index is shown. The results of the comparison are marked using a 1-9 scale, as shown in Table 1.
TABLE 1 judge matrix Scale and implications
| Scale | Means of |
| 1 | Two evaluation indexes are equally important |
| 3 | The former being slightly more important than the latter |
| 5 | The former being significantly more important than the latter |
| 7 | The former being more important than the latter |
| 9 | The former being of extreme importance than the latter |
| 2,4,6,8 | At an intermediate value of the above-mentioned adjacent judgment |
If the scale of importance comparison between the evaluation index i and the evaluation index j is bijThe scale of the comparison of the importance of the evaluation index j and the evaluation index i is 1/bij。
(2) Consistency check
Since the judgment matrix B is influenced by the subjective judgment of the decision maker, a certain error inevitably exists, and consistency check must be performed, and the consistency ratio CR is defined as formula (23).
(23) In the formula, CI is a consistency index which can be obtained according to the formula (24); RI is an average random consistency index, and its values are shown in table 2.
(24) In the formula, λmaxIs the maximum feature root of the decision matrix B.
TABLE 2 RI values
And when CR <0.1, judging that the consistency of the matrix meets the requirement, and otherwise, reconstructing the judgment matrix.
(3) Weight coefficient calculation
After the judgment matrix B passes consistency check, the maximum characteristic root lambda thereofmaxThe corresponding feature vector W is expressed by expression (25), and the weight coefficient of each evaluation index can be obtained by expression (26).
W＝[w1,w2,w3]T (25)
(26) In the formula ujIs the weight coefficient of the jth evaluation index, wjIs the jth element in W. The weight coefficient matrix composed of the evaluation index weight coefficients is denoted as U, and is shown as (27).
A flowchart for solving the evaluation index weight coefficient by the AHP algorithm is shown in fig. 1.
6. Solving for optimal power supply point
The invention utilizes TOPSIS algorithm to evaluate each power supply point in the set C, and takes the power supply point with the largest evaluation value as the optimal power supply point, and the method comprises the following specific steps:
(1) construction of an evaluation matrix
Based on the evaluation index values at the respective power supply points, a corresponding evaluation matrix X is constructed as shown in formula (28).
(28) In the formula, m is the number of power supply points in the set C; x is the number ofijThe j-th evaluation index value of the ith power supply point in the set C. The 1 st evaluation index in the invention is the peak-to-peak degree of load contact Ppp(ii) a Peak-to-valley load coincidence for evaluation index 2Degree Ppv(ii) a The 3 rd evaluation index is the power point distance Ds. Degree of load contact P due to peak-to-valley loadpvThe index is positive (larger is more preferable), the other indexes are negative (larger is more worse), and for the convenience of calculation, the 2 nd evaluation index is the peak-valley negative loading degree of contact PpvConverting into negative type index, using peak-to-valley load contact ratio PpvThe difference from 1 indicates, i.e. 1-Ppv。
(2) Matrix normalization
In order to eliminate the influence of dimension and magnitude between indexes, each element of X is normalized according to the formula (29).
And finally obtaining the normalized matrix R.
(3) Construction of weighted normalized evaluation matrix
A weighted normalized evaluation matrix Y is obtained according to the expression (31).
yijIs the value of the element in row i and column j in Y, which is represented by rijAnd ujAnd (4) multiplying the two to obtain the product.
(4) Determining positive and negative ideal solutions
Solving a positive ideal solution Y according to the formulas (32) - (35)+And negative ideal solution Y-。
In the invention, the evaluation indexes are converted into negative indexes, namely, the smaller the evaluation index value is, the optimal power supply point to be selected is. Therefore, in the formula (32),
the minimum value in column 1 of Y can be obtained as shown in (33).
Y+The values of the other elements can be obtained by referring to the formula (33).
(34) In the formula (I), the compound is shown in the specification,
the maximum value in column 1 of Y can be obtained as shown in (35).
Y-The values of the other elements can be obtained by referring to the formula (35).
(5) Calculating the Euclidean distance
And calculating Euclidean distance between each power supply point in the set C and the positive and negative ideal solutions according to the expressions (36) to (37).
(36) In the formula (I), the compound is shown in the specification,
the Euclidean distance between the ith power supply point in the set C and the positive ideal solution is taken as the Euclidean distance;
is the minimum value in column j of Y.
(37) In the formula (I), the compound is shown in the specification,
the Euclidean distance between the ith power supply point in the set C and the negative ideal solution is obtained;
is the maximum value in column j of Y.
(6) Calculating an evaluation value
The evaluation value of each power supply point in the set C is calculated by the expression (38).
(38) In the formula, viThe evaluation value of the ith power supply point in the set C. The power point with the largest evaluation value is the optimal power point. The process of solving the optimal power supply point by using the TOPSIS algorithm is shown in figure 2.
7. Working procedure
S1, calculating the open capacity curve S of each power supply point to be selectedO。
S2, estimating the maximum daily load curve L of the power user to be accessedmax。
S3, calculating the capacity margin curve S of each candidate power supply pointL。
S4, according to the capacity margin curve S of each power supply point to be selectedLAnd obtaining a candidate power point set C with capacity margin meeting the requirement.
S5, calculating the evaluation index value of each power supply point in the set C, including the peak-to-peak load contact ratio PppPeak to valley loading ratio PpvAnd power point distance Ds。
And S6, solving the weight coefficient of each evaluation index by using an AHP algorithm.
And S7, evaluating each power supply point in the set C by using a TOPSIS algorithm, and taking the power supply point with the largest evaluation value as an optimal power supply point.
The overall flow chart is shown in fig. 3.
The invention has the beneficial effects that:
the invention considers the distribution network area of the power supply point to be selected and the time distribution characteristic of the load of the power user to be accessed, has stronger objectivity and ideal effect, and is not easy to cause the capacity of the distribution transformer to be idle or the investment of the power cable to be increased. The invention provides scientific basis for selecting the low-voltage industrial expansion power supply point.
Drawings
FIG. 1 is a flow chart of solving the evaluation index weight coefficients using the AHP algorithm;
FIG. 2 is a flow chart for solving the optimal power supply point using the TOPSIS algorithm;
FIG. 3 is an overall flow chart of the present invention.
Detailed Description
The overall flow chart is shown in FIG. 3:
s1, calculating the open capacity curve S of each power supply point to be selectedO。
S2, estimating the maximum daily load curve L of the power user to be accessedmax。
S3, calculating the capacity margin curve S of each candidate power supply pointL。
S4, according to the capacity margin curve S of each power supply point to be selectedLAnd obtaining a candidate power point set C with capacity margin meeting the requirement.
S5, calculating the evaluation index value of each power supply point in the set C, including the peak-to-peak load contact ratio PppPeak to valley loading ratio PpvAnd power point distance Ds。
And S6, solving the weight coefficient of each evaluation index by using an AHP algorithm.
And S7, evaluating each power supply point in the set C by using a TOPSIS algorithm, and taking the power supply point with the largest evaluation value as an optimal power supply point.
The method is used for analyzing 3 power supply points to be selected around a certain power user to be accessed, and the given margin coefficient is 15%. The capacity margins of the 3 candidate power supply points are calculated by analysis to meet the requirements. The weighting coefficients of the 3 evaluation indexes obtained by the AHP algorithm are 0.5714, 0.2857, and 0.1429, respectively. The evaluation index values calculated for the respective power supply points are shown in table 3.
TABLE 3 evaluation index values for respective power supply points
Evaluation values of the respective power supply points obtained by the TOPSIS algorithm are shown in table 4.
TABLE 4 evaluation value of each power supply point
| Power supply point | Evaluation value |
| 1 | 0.65 |
| 2 | 0.90 |
| 3 | 0.03 |
As can be seen from table 4, the 2 nd power supply point is the optimum power supply point.
Claims (10)
1. A method for selecting a low-voltage business expansion power supply point is characterized by comprising the following steps: firstly, calculating an openable capacity curve of a power supply point to be selected, then calculating a capacity margin curve of the power supply point to be selected according to the openable capacity curve of the power supply point to be selected and a maximum daily load curve of a power user to be accessed, preliminarily screening power supply points with capacity margins meeting requirements according to the capacity margin curve, constructing an evaluation index system aiming at the power supply points with the capacity margins meeting the requirements, solving a weight coefficient of each evaluation index in the evaluation index system by using an AHP algorithm, evaluating the power supply points with the capacity margins meeting the requirements by using a TOPSIS algorithm, and finally selecting an optimal low-voltage business expansion power supply point according to an evaluation result.
2. The method for selecting the low-voltage commercial power expansion point according to claim 1, wherein the method for calculating the open capacity curve of the power point to be selected comprises the following steps:
defining an openable capacity curve S of a power supply point to be selectedOAs shown in formula (1):
SO＝[so1,so2,…,soi…,son] (1)
(1) in the formula, soiCalculating the open capacity of the power supply point to be selected at the ith load acquisition time in one day according to the formula (2); n is the load collection times of the electricity consumption information collection system in one day;
soi＝SN-simax (2)
(2) in the formula, SNRated capacity of a distribution transformer of a distribution network area to which a power supply point to be selected belongs; simaxThe power source point to be selected is the ith element of the maximum daily load curve of the distribution network area to which the power source point belongs;
the definition of the maximum daily load curve of the distribution network area to which the power supply point to be selected belongs is shown as the formula (3):
Smax＝[s1max,s2max,…,simax,…,snmax] (3)
(3) in the formula, simaxThe calculation method of (2) is shown in the formula (4);
simax＝max(s1i,s2i,…,sji,…sNi) (4)
(4) in the formula, sjiThe load value of the ith load acquisition time of the j-th day in the statistical period of the distribution network area to which the power supply point to be selected belongs; n is the number of days in the statistical period.
3. The method for selecting the low voltage commercial power expansion point according to claim 1, wherein the method for calculating the maximum daily load curve of the power consumer to be accessed comprises the following steps:
defining a maximum daily load curve L of a power consumer to be accessedmaxAs shown in formula (5):
Lmax＝[l1max,l2max,…,limax,…,lnmax] (5)
(5) in the formula IimaxThe maximum load value of the ith load acquisition time of the power consumer to be accessed in one day is estimated and obtained by the power consumer; n is defined as formula (1).
4. The method for selecting the low voltage commercial power expansion power supply point according to claim 1, wherein the step of calculating the capacity margin curve of the power supply point to be selected comprises the following steps:
capacity margin curve S for defining power supply points to be selectedLAs shown in formula (6):
SL＝[sL1,sL2,...,sLi,...,sLn] (6)
(6) in the formula, sLiThe capacity margin of the power supply point to be selected at the ith load acquisition time in one day is calculated in the mode shown as the formula (7); n is defined as formula (1);
sLi＝soi-limax (7)
(7) in the formula, soiThe definition is the same as the formula (1); limaxThe same formula (5) is defined;
if the capacity margin curve S of the power supply point to be selectedLIf the formula (8) is met, judging that the capacity margin of the power supply point to be selected meets the requirement;
(8) in the formula, eta is a margin coefficient and is preset by a worker; sNDefinition ofThe same as the formula (2).
5. The method for selecting the low-voltage commercial power expansion point according to claim 1, wherein the method for constructing the evaluation index system comprises the following steps of: defining a power point set to be selected with capacity margin meeting the requirement as C, and constructing an evaluation index system aiming at each power point in the set C, wherein the evaluation index system comprises peak-to-peak load contact ratio PppPeak to valley loading ratio PpvAnd power point distance Ds(ii) a Peak to peak load contact ratio PppThe coincidence degree of the peak of the maximum daily load curve of the distribution network area to which the power supply point belongs and the peak of the maximum daily load curve of the power user to be accessed is represented, and the smaller the value of the peak is, the lower the probability of raising the original peak of the load of the distribution network area to which the power supply point belongs is after the power user is accessed is indicated; peak to valley load overlap ratio PpvThe coincidence degree of the high peak of the maximum daily load curve of the distribution network area to which the power supply point belongs and the low valley of the maximum daily load curve of the power consumer to be accessed and the low valley of the maximum daily load curve of the distribution network area to which the power supply point belongs and the high peak of the maximum daily load curve of the power consumer to be accessed are represented, and the larger the value is, the better the peak clipping and valley filling effect on the original load of the distribution network area to which the power supply point load belongs is; distance D of power supply pointsThe distance between the power supply point and the power consumer to be accessed is represented, and the smaller the value of the distance is, the smaller the investment of the power cable is.
6. The method for selecting the low-voltage industrial power expansion point according to claim 1, wherein an AHP algorithm is used for solving the weight coefficient of each evaluation index, and the method comprises the following specific steps:
(a) constructing a decision matrix
Comparing the evaluation indexes pairwise to obtain a judgment matrix B as shown in a formula (22); since the invention has 3 evaluation indexes, B is a 3-order matrix;
b elements each representing the result of comparing the importance of two evaluation indexes to be compared, B12The importance comparison result of the 1 st evaluation index and the 2 nd evaluation index is shown; the comparison results are marked by a 1-9 scale method; if the scale of importance comparison between the evaluation index i and the evaluation index j is bijThe scale of the comparison of the importance of the evaluation index j and the evaluation index i is 1/bij；
(b) Consistency check
Since the judgment matrix B is influenced by the subjective judgment of the decision maker, consistency check is carried out, and the consistency ratio CR is defined as the formula (23):
(23) wherein CI is a consistency index, which is obtained according to the formula (24); RI is the average random consistency index:
(24) in the formula, λmaxJudging the maximum characteristic root of the matrix B;
when CR is less than 0.1, judging that the consistency of the matrix meets the requirement, otherwise, reconstructing the judgment matrix;
(c) weight coefficient calculation
After the judgment matrix B passes consistency check, the maximum characteristic root lambda thereofmaxThe corresponding feature vector W is expressed by expression (25), and the weight coefficient of each evaluation index can be obtained by expression (26):
W＝[w1,w2,w3]T (25)
(26) in the formula ujIs the weight coefficient of the jth evaluation index, wjIs the jth element in W; a weight coefficient matrix composed of the weight coefficients of the evaluation indexes is recorded as U, as shown in (27);
7. the method for selecting the low-voltage commercial power expansion point according to claim 1, wherein each power point in the set C is evaluated by using a TOPSIS algorithm, and the power point with the largest evaluation value is used as an optimal power point, and the method comprises the following specific steps:
(a) construction of an evaluation matrix
Constructing a corresponding evaluation matrix X according to the evaluation index values of the power supply points, wherein the evaluation matrix X is represented by the formula (28):
(28) in the formula, m is the number of power supply points in the set C; x is the number ofijThe j evaluation index value of the ith power supply point in the set C; the 1 st evaluation index is the peak-to-peak degree of load contact Ppp(ii) a Peak-to-valley degree of load contact P for evaluation index No. 2pv(ii) a The 3 rd evaluation index is the power point distance Ds(ii) a Degree of load contact P due to peak-to-valley loadpvThe positive index is larger, the better the positive index is, the other indexes are negative indexes, the larger the positive index is, the worse the negative index is, the peak-valley negative degree of polymerization P is used as the 2 nd evaluation indexpvConverting into negative type index, using peak-to-valley load contact ratio PpvThe difference from 1 indicates, i.e. 1-Ppv；
(b) Matrix normalization
In order to eliminate the influence of dimension and magnitude between indexes, each element of X is subjected to standardization treatment according to a formula (29):
xijthe j evaluation index value of the ith power supply point in the set C; r isijIs xijCarrying out normalization processing on the result;
finally, obtaining a normalized matrix R:
(c) construction of weighted normalized evaluation matrix
Obtaining a weighted normalized evaluation matrix Y according to the formula (31):
yijis the value of the element in row i and column j in Y, which is represented by rijAnd ujMultiplying to obtain;
(d) determining positive and negative ideal solutions
Solving a positive ideal solution Y according to the formulas (32) - (35)+And negative ideal solution Y-；
The evaluation indexes are converted into negative indexes, namely the smaller the evaluation index value is, the optimal power supply point to be selected is; therefore, in the formula (32),
the minimum value in column 1 of Y is obtained as (33):
Y+the values of the other elements are obtained by referring to the formula (33):
(34) in the formula (I), the compound is shown in the specification,
the maximum value in column 1 of Y was obtained as (35):
Y-the values of the other elements are obtained by referring to the formula (35);
(e) calculating the Euclidean distance
And (4) calculating Euclidean distances between each power supply point in the set C and the positive and negative ideal solutions according to the formulas (36) to (37):
(36) in the formula (I), the compound is shown in the specification,
the Euclidean distance between the ith power supply point in the set C and the positive ideal solution is taken as the Euclidean distance;
is the minimum value of the j column in Y;
(37) in the formula (I), the compound is shown in the specification,
the Euclidean distance between the ith power supply point in the set C and the negative ideal solution is obtained;
is the maximum value in the jth column of Y;
(f) calculating an evaluation value
Calculating the evaluation value of each power supply point in the set C according to the formula (38);
(38) in the formula, viAnd the evaluation value of the ith power supply point in the set C is obtained, and the power supply point with the largest evaluation value is the optimal power supply point.
8. The method for selecting a low voltage power extension point according to claim 1, wherein the peak-to-peak negative loading degree of polymerization PppPeak to valley loading ratio PpvAnd power point distance DsThe specific calculation method is as follows:
(a) peak to peak load contact ratio Ppp
Peak to peak load contact ratio PppThe calculation method is shown as the formula (9):
(9) in the formula, npThe peak load points in the maximum daily load curve of the distribution network area to which the power supply points belong are calculated in the mode shown as the formula (10); n isppThe calculation mode of the peak load coincidence point number is shown as a formula (13) of the maximum daily load curve of the distribution network area to which the power supply point belongs and the maximum daily load curve of the power user to be accessed;
(10) in the formula (f)spiIs s isimaxThe calculation method of the peak identifier (2) is shown as (11):
(11) in the formula, SpeakMaximum daily load curve S of distribution network area to which power supply point belongsmaxThe peak value of (1) is calculated by the method shown in the formula (12); simaxThe definition is shown as the formula (2):
Speak＝max(s1max,s2max,…,simax,…,snmax) (12)
(13) in the formula (f)lpiIs 1imaxThe calculation method of the peak identifier (2) is shown as (14).
(14) In the formula, LpeakMaximum daily load curve L for planned access power consumermaxThe peak value of (1) is calculated by the method shown in the formula (15); limaxThe definition is shown as the formula (5):
Lpeak＝max(l1max,l2max,…,limax,…,lnmax) (15)。
9. the method for selecting a low voltage commercial power expansion point according to claim 1,
(b) peak to valley load overlap ratio Ppv
Peak to valley load overlap ratio PpvThe calculation method is shown as the formula (16):
npvthe peak load of the maximum daily load curve of the distribution network area where the power supply point belongs to and the valley of the maximum daily load curve of the power user to be accessedThe number of load coincidence points is calculated by the method shown in the formula (17); n isvpThe calculation method is shown as formula (19), and the calculation method is the coincidence point number of the maximum daily load curve low load of the distribution network area where the power supply point belongs and the maximum daily load curve high load of the power user to be accessed; n ispThe same formula (9) is defined; n isvThe number of the valley load points in the maximum daily load curve of the distribution network area to which the power supply point belongs is calculated in a mode shown as a formula (21);
fspithe same formula (10) is defined; f. oflviIs 1imaxThe calculation method of the valley mark is as shown in (18):
(18) in the formula, LpeakThe same formula (14) is defined; limaxThe definition is shown as the formula (5):
(19) in the formula (f)sviIs s isimaxThe calculation method of the valley mark of (2) is shown as (20); f. oflpiThe definition is shown as the formula (13):
(20) in the formula, PpeakThe same formula (11) is defined; simaxThe definition is shown as the formula (2):
(21) in the formula，fsviThe definition is shown as the formula (19);
(c) distance D of power supply points
Distance D of power supply pointsThe method comprises the steps of indicating the linear distance between a power user and a power supply point, and obtaining the linear distance through a power GIS system.
10. The method for selecting the low-voltage industrial power expansion point according to claim 1, wherein the specific working steps of the selection method comprise the following steps:
s1, calculating the open capacity curve S of each power supply point to be selectedO；
S2, estimating the maximum daily load curve L of the power user to be accessedmax；
S3, calculating the capacity margin curve S of each candidate power supply pointL；
S4, according to the capacity margin curve S of each power supply point to be selectedLObtaining a power point set C to be selected with capacity margin meeting the requirement;
s5, calculating the evaluation index value of each power supply point in the set C, including the peak-to-peak load contact ratio PppPeak to valley loading ratio PpvAnd power point distance Ds；
S6, solving the weight coefficient of each evaluation index by using an AHP algorithm;
and S7, evaluating each power supply point in the set C by using a TOPSIS algorithm, and taking the power supply point with the largest evaluation value as an optimal power supply point.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110232307.4A CN112990559B (en) | 2021-03-02 | 2021-03-02 | Method for selecting low-voltage business expansion power supply point |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110232307.4A CN112990559B (en) | 2021-03-02 | 2021-03-02 | Method for selecting low-voltage business expansion power supply point |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112990559A true CN112990559A (en) | 2021-06-18 |
| CN112990559B CN112990559B (en) | 2022-11-18 |
Family
ID=76352172
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110232307.4A Active CN112990559B (en) | 2021-03-02 | 2021-03-02 | Method for selecting low-voltage business expansion power supply point |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112990559B (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105184511A (en) * | 2015-10-13 | 2015-12-23 | 国家电网公司 | Power supply business expansion service system |
| CN106709634A (en) * | 2016-12-02 | 2017-05-24 | 国网天津市电力公司 | Method for assessing electric car-accessed active distribution network carrying capacity |
| CN106875058A (en) * | 2017-02-17 | 2017-06-20 | 江苏方天电力技术有限公司 | A kind of electric power industry expands can open capacity intelligent determination method |
| CN107122924A (en) * | 2017-05-31 | 2017-09-01 | 国家电网公司 | A kind of intelligent distribution system bearing capacity evaluation method |
| CN109636137A (en) * | 2018-11-23 | 2019-04-16 | 浙江华云电力工程设计咨询有限公司 | Electric automobile charging station planning and distributing method and system based on step analysis |
| CN109784589A (en) * | 2019-03-19 | 2019-05-21 | 广东电网有限责任公司 | A kind of power grid Business Process System user accesses optimization method, device and equipment |
| CN111950783A (en) * | 2020-07-31 | 2020-11-17 | 广东卓维网络有限公司 | Business expansion auxiliary installation method based on marketing and distribution information integration platform |
| CN112308458A (en) * | 2020-11-23 | 2021-02-02 | 广东电网有限责任公司计量中心 | Low-voltage transformer area measurement data evaluation method and system |
-
2021
- 2021-03-02 CN CN202110232307.4A patent/CN112990559B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105184511A (en) * | 2015-10-13 | 2015-12-23 | 国家电网公司 | Power supply business expansion service system |
| CN106709634A (en) * | 2016-12-02 | 2017-05-24 | 国网天津市电力公司 | Method for assessing electric car-accessed active distribution network carrying capacity |
| CN106875058A (en) * | 2017-02-17 | 2017-06-20 | 江苏方天电力技术有限公司 | A kind of electric power industry expands can open capacity intelligent determination method |
| CN107122924A (en) * | 2017-05-31 | 2017-09-01 | 国家电网公司 | A kind of intelligent distribution system bearing capacity evaluation method |
| CN109636137A (en) * | 2018-11-23 | 2019-04-16 | 浙江华云电力工程设计咨询有限公司 | Electric automobile charging station planning and distributing method and system based on step analysis |
| CN109784589A (en) * | 2019-03-19 | 2019-05-21 | 广东电网有限责任公司 | A kind of power grid Business Process System user accesses optimization method, device and equipment |
| CN111950783A (en) * | 2020-07-31 | 2020-11-17 | 广东卓维网络有限公司 | Business expansion auxiliary installation method based on marketing and distribution information integration platform |
| CN112308458A (en) * | 2020-11-23 | 2021-02-02 | 广东电网有限责任公司计量中心 | Low-voltage transformer area measurement data evaluation method and system |
Non-Patent Citations (2)
| Title |
|---|
| Z.ISMAIL等: ""Forecasting Peak Load Electricity Demand Using Statistics and Rule Based Approach"", 《AMERICAN JOURNAL OF APPLIED ACIENCES》 * |
| 张小斐: ""基于负荷特性的大用户业扩辅助分析方法"", 《电测与仪表》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112990559B (en) | 2022-11-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2021213192A1 (en) | Load prediction method and load prediction system employing general distribution | |
| CN109829604A (en) | A kind of grid side energy-accumulating power station operational effect comprehensive estimation method | |
| Long et al. | The relationship between foreign direct investment, electricity consumption and economic growth in Vietnam | |
| CN108009667A (en) | A kind of energy demand total amount and structure prediction system | |
| CN105117810A (en) | Residential electricity consumption mid-term load prediction method under multistep electricity price mechanism | |
| CN110111024A (en) | Scientific and technological achievement market value evaluation method based on AHP fuzzy comprehensive evaluation model | |
| CN104933627A (en) | Energy efficiency combination evaluation method of machine tool product manufacture system | |
| CN108734321A (en) | A kind of short-term load forecasting method based on the Elman neural networks for improving ABC algorithms | |
| CN106845777A (en) | Case workload evaluation method, judge's performance evaluation techniques, modeling method, computing device and computer-readable recording medium | |
| CN112766809A (en) | Evaluation method of comprehensive energy system | |
| CN111861089A (en) | Comprehensive evaluation method for electric power spot market | |
| CN111798333A (en) | Energy utilization evaluation and electricity utilization safety analysis method and system | |
| CN112650894A (en) | Multidimensional analysis and diagnosis method for user electricity consumption behaviors based on combination of analytic hierarchy process and deep belief network | |
| CN113595071A (en) | Transformer area user identification and voltage influence evaluation method | |
| CN112132481A (en) | Comprehensive evaluation method for regional energy efficiency | |
| CN116151464A (en) | Photovoltaic power generation power prediction method, system and storable medium | |
| CN115796915A (en) | Electricity price prediction method and system for electricity trading market | |
| CN113450031B (en) | Method and device for selecting intelligent energy consumption service potential transformer area of residents | |
| CN109615246B (en) | Method for determining economic operation state of active power distribution network | |
| CN115238948A (en) | Method and device for predicting power generation capacity of small hydropower station | |
| CN113361946B (en) | Power quality assessment method and device based on distributed photovoltaic grid-connected system | |
| CN112990559B (en) | Method for selecting low-voltage business expansion power supply point | |
| CN112508254A (en) | Method for determining investment prediction data of transformer substation engineering project | |
| CN117040020A (en) | Solving method for regional integral photovoltaic new energy source dissipatable capacity index distribution | |
| CN107067180A (en) | A kind of power distribution network low-voltage contribution degree evaluation method based on grey correlation analysis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |