CN112508233A - Method and system for obtaining optimal operation scheme of multi-energy complementary energy system - Google Patents

Method and system for obtaining optimal operation scheme of multi-energy complementary energy system Download PDF

Info

Publication number
CN112508233A
CN112508233A CN202011287726.XA CN202011287726A CN112508233A CN 112508233 A CN112508233 A CN 112508233A CN 202011287726 A CN202011287726 A CN 202011287726A CN 112508233 A CN112508233 A CN 112508233A
Authority
CN
China
Prior art keywords
evaluation
index
weighting
indexes
formula
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
CN202011287726.XA
Other languages
Chinese (zh)
Inventor
屈小云
吴鸣
寇凌峰
丁保迪
李奇
赵凤展
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.)
China Online Shanghai Energy Internet Research Institute Co ltd
Electric Power Research Institute of State Grid Chongqing Electric Power Co Ltd
State Grid Corp of China SGCC
China Agricultural University
China Electric Power Research Institute Co Ltd CEPRI
State Grid Chongqing Electric Power Co Ltd
Original Assignee
China Online Shanghai Energy Internet Research Institute Co ltd
State Grid Corp of China SGCC
China Agricultural University
China Electric Power Research Institute Co Ltd CEPRI
State Grid Chongqing 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 China Online Shanghai Energy Internet Research Institute Co ltd, State Grid Corp of China SGCC, China Agricultural University, China Electric Power Research Institute Co Ltd CEPRI, State Grid Chongqing Electric Power Co Ltd filed Critical China Online Shanghai Energy Internet Research Institute Co ltd
Priority to CN202011287726.XA priority Critical patent/CN112508233A/en
Publication of CN112508233A publication Critical patent/CN112508233A/en
Pending legal-status Critical Current

Links

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"
    • 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
    • G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
    • G06Q10/06375—Prediction of business process outcome or impact based on a proposed change
    • 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/80—Management or planning
    • Y02P90/82—Energy audits or management systems therefor

Landscapes

  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Engineering & Computer Science (AREA)
  • Economics (AREA)
  • Strategic Management (AREA)
  • General Physics & Mathematics (AREA)
  • Tourism & Hospitality (AREA)
  • Theoretical Computer Science (AREA)
  • General Business, Economics & Management (AREA)
  • Marketing (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Physics & Mathematics (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Development Economics (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)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses a method and a system for obtaining an optimal operation scheme of a multi-energy complementary energy system, and belongs to the technical field of multi-energy complementary comprehensive energy systems. The method comprises the following steps: aiming at the evaluation indexes of the multi-energy complementary energy system, an evaluation index system is established; subjectively weighting a plurality of indexes in the unique index sequence relation according to the relative importance degree ratio; performing objective weighting on a plurality of indexes in the unique index order relation; performing deviation maximization weighting on a plurality of indexes in the unique index sequence relation according to subjective weighting and objective weighting to obtain a weighting result; and evaluating the operation scheme of the multi-energy complementary energy system according to the weighting result of the dispersion maximization weighting of the indexes, and determining the operation scheme with the highest evaluation grade as the optimal operation scheme. The invention provides scientific guidance for the optimized operation of the multi-energy complementary energy system.

Description

Method and system for obtaining optimal operation scheme of multi-energy complementary energy system
Technical Field
The invention relates to the technical field of a multi-energy complementary comprehensive energy system, in particular to a method and a system for acquiring an optimal operation scheme of the multi-energy complementary energy system.
Background
The multi-energy complementary comprehensive energy system generally has input and output of various energy sources and a large amount of energy conversion equipment, forms a coupling relation among a power supply system, an air supply system and a heat supply/cooling system through a multi-energy network and an informatization technology, breaks through the inherent mode that the traditional single energy system supplies power, air and heat supply/cooling energy independently, and has important significance in the aspects of improving the utilization efficiency of energy sources, promoting the structural change of energy sources, promoting the harmony and coexistence between human and nature, ensuring the long-term public security of human society and the like.
The comprehensive multi-energy complementary energy system is continuously developed at home and abroad, in order to exert the maximum function and ensure the stability of system operation, an evaluation index system of a scientific system needs to be established, and a reasonable evaluation method is applied to comprehensively evaluate the overall performance of the multi-energy complementary energy system to obtain the grade of the system, so that a scientific theoretical basis is provided for the research, design, development, operation and the like of the multi-energy complementary energy system. Meanwhile, the determination of the weight in the evaluation method is an important link.
Disclosure of Invention
In order to solve the above problems, the present invention provides a method for obtaining an optimal operation scheme of a multi-energy complementary energy system, comprising:
aiming at the evaluation indexes of the multi-energy complementary energy system, an evaluation index system is established;
aiming at a plurality of indexes of the established evaluation index system, determining a unique index sequence relation, determining a relative importance degree ratio of two adjacent indexes of the unique index sequence relation, and subjectively weighting the plurality of indexes in the unique index sequence relation according to the relative importance degree ratio;
performing objective weighting on a plurality of indexes in the unique index order relation;
performing deviation maximization weighting on a plurality of indexes in the unique index sequence relation according to subjective weighting and objective weighting to obtain a weighting result;
and evaluating the operation scheme of the multi-energy complementary energy system according to the weighting result of the dispersion maximization weighting of the indexes, and determining the operation scheme with the highest evaluation grade as the optimal operation scheme.
Optionally, the evaluation index includes:
the system has the advantages of clean low carbon level, safe and reliable level, energy utilization level, efficient economic level and social service level;
the clean low carbon level comprises: CO22Annual emission and NOxAnnual emission;
the safe and reliable level comprises: the reliability, shortage and peak-to-valley difference of energy supply;
the energy utilization level comprises: the utilization rate of primary energy,
Figure BDA0002782917730000023
Efficiency and system green-to-electric ratio;
the efficient economic level comprises: initial investment cost, operation and maintenance cost, energy outsourcing cost and retirement disposal cost;
the social service level includes: popularity of the intelligent electric meter and operation rate on an energy service line.
Optionally, determining a unique index order relationship for a plurality of indexes of the established evaluation index system, determining a relative importance ratio of two adjacent indexes of the unique index order relationship, and subjectively weighting the plurality of indexes in the unique index order relationship according to the relative importance ratio, includes:
determining the least important index b of n evaluation indexesnThen, the least important index b in the n-1 indexes is determinedn-1And obtaining the unique index sequence relation until the n indexes are determined to be finished, wherein the unique index sequence relation comprises the following steps:
b1＞b2＞。。。。bn-1＞bn；
determining the relative importance degree ratio of the adjacent indexes of the unique index order relation, wherein the formula is as follows:
Figure BDA0002782917730000021
determination of the index bnThe weight is:
Figure BDA0002782917730000022
according to rkAnd bnAll indexes in the unique index sequence relation are determined, subjective weighting is completed, and the formula is as follows:
w'k-1＝rk·w'k,k＝n,n-1,...2。
optionally, the objective weighting is performed on a plurality of indexes in the unique index order relationship, including:
determining an average of ith index values of a plurality of indexes
Figure BDA0002782917730000031
The formula is as follows:
Figure BDA0002782917730000032
wherein m is the number of evaluation schemes, xijThe ith index value of the jth evaluation scheme;
determining the standard deviation of the ith index value, wherein the formula is as follows:
Figure BDA0002782917730000033
determining the coefficient of variation of the ith index value according to the following formula:
Figure BDA0002782917730000034
determining the weight of the ith index value, and finishing objective weighting, wherein the formula is as follows:
Figure BDA0002782917730000035
optionally, the performing dispersion maximization weighting on a plurality of indexes in the unique index order relation according to subjective weighting and objective weighting to obtain a weighting result, including:
determining weight vectors of subjective weighting and objective weighting, which are w 'and w', respectively, and the formula is as follows:
w'＝[w′i,w'2,...w'n]T
w”＝[w″i,w″2,...w″n]T
and determining the comprehensive weight vector as w according to w' and w ", wherein the formula is as follows:
w＝[w1,w2,...wn]T
determining the relationship of w ', w' and w, the formula is as follows:
w＝αw'+βw”,α≥0,β≥0,α2+β2＝1
and determining the total dispersion among the m evaluation objects according to the relation among w ', w' and w, wherein the formula is as follows:
Figure BDA0002782917730000041
in the formula, n is the index number, and m is the evaluation scheme number;
based on the dispersion maximization, an optimization model is established, wherein the optimization model comprises the following steps:
Figure BDA0002782917730000042
α2+β2＝1
α≥0，β≥0
establishing a Lagrange function solution optimization model, wherein the formula is as follows:
Figure BDA0002782917730000043
the derivation of the lagrange function is:
Figure BDA0002782917730000044
Figure BDA0002782917730000045
Figure BDA0002782917730000046
in order to ensure that the water-soluble organic acid,
Figure BDA0002782917730000047
obtaining:
Figure BDA0002782917730000051
Figure BDA0002782917730000052
Figure BDA0002782917730000053
the values of alpha and beta are substituted into w ═ alpha w '+ beta w' and normalized to obtain the comprehensive weight vector w ═ w [ + w-1,w2,...wn]TAnd using the comprehensive weight vector to complete weighting.
Optionally, the method for evaluating the operation scheme of the multi-energy complementary energy system according to the weighting result of the dispersion maximization weighting of the multiple indexes, and determining the operation scheme with the highest evaluation level as the optimal operation scheme includes:
acquiring an element matrix and an evaluation grade matrix of an operation scheme to be evaluated;
the element matrix is as follows:
Figure BDA0002782917730000054
the evaluation grade matrix is:
N＝[N1,N2,N3,N4]
wherein N is1,N2,N3,N4Respectively representing four evaluation grades of excellence, goodness, middle and difference;
according to the element matrix and the evaluation grade matrix, a classical domain element matrix is established, wherein the classical domain element matrix is as follows:
Figure BDA0002782917730000061
in the formula, RrThe classical domain object element matrix of the r evaluation level is obtained by taking r as 1,2,3,4, NrIs the r-th evaluation level, ciFor the ith evaluation index, i takes 1, 2.. n, Vri＝[ari,bri]The value range of the ith evaluation index of the r evaluation grade is obtained;
according to the classical domain matter element matrix, determining a section domain matter element matrix, wherein the section domain matter element matrix is as follows:
Figure BDA0002782917730000062
in the formula, RpIs a nodal domain object element matrix, Vpi＝[api,bpi]The evaluation index is the value range of the ith evaluation index, namely the section area, and p is the comprehensive evaluation grade of the multi-energy complementary energy system;
determining a comprehensive evaluation index correlation function of a scheme to be evaluated of the complementary energy system, wherein the formula is as follows:
Figure BDA0002782917730000063
in the formula, X, Xr、XpRespectively an index matter element value, a classical domain matter element value range, a section domain matter element value range, rho (X, X) of the operation scheme of the system to be evaluatedr) Is point X and interval Xr＝[ar,br]Distance of (d), ρ (X, X)p) Is point X and interval Xp＝[ap,bp]The distance of (d);
wherein the content of the first and second substances,
Figure BDA0002782917730000064
Figure BDA0002782917730000071
determining the comprehensive association degree, wherein the formula is as follows:
Figure BDA0002782917730000072
in the formula, wiIs the comprehensive weight, K, of the ith index of the system scheme to be evaluatedr(xi) Taking 1,2,3 and 4 as r for the correlation degree of the ith index of the operation scheme to be evaluated relative to the comprehensive evaluation grade r;
if there is
Kri＝max[Kr(xi)],r＝1,2,3,4,i＝1,2,...n
The comprehensive evaluation grade of the index i is r;
if there is
Krx＝max[Kr(Nx)],r＝1,2,3,4
And the comprehensive evaluation grade of the operation scheme to be evaluated is r, and the operation scheme with the highest comprehensive evaluation grade is selected from the m evaluation objects as the optimal decision-making scheme.
The invention also provides a system for obtaining the optimal operation scheme of the multi-energy complementary energy system, which comprises the following steps:
the index system establishing module is used for establishing an evaluation index system aiming at the evaluation indexes of the multi-energy complementary energy system;
the subjective weighting module determines a unique index sequence relation aiming at a plurality of indexes of the established evaluation index system, determines the relative importance degree ratio of two adjacent indexes of the unique index sequence relation, and subjectively weights the plurality of indexes in the unique index sequence relation according to the relative importance degree ratio;
the objective weighting module is used for carrying out objective weighting on a plurality of indexes in the unique index order relation;
the comprehensive weighting module is used for performing deviation maximization weighting on a plurality of indexes in the unique index sequence relation according to subjective weighting and objective weighting to obtain a weighting result;
and the evaluation module is used for evaluating the operation scheme of the multi-energy complementary energy system according to the weighting result of the dispersion maximization weighting of the indexes and determining the operation scheme with the highest evaluation grade as the optimal operation scheme.
Optionally, the evaluation index includes:
the system has the advantages of clean low carbon level, safe and reliable level, energy utilization level, efficient economic level and social service level;
the clean low carbon level comprises: CO22Annual emission and NOxAnnual emission;
the safe and reliable level comprises: the reliability, shortage and peak-to-valley difference of energy supply;
the energy utilization level comprises: the utilization rate of primary energy,
Figure BDA0002782917730000085
Efficiency and system green-to-electric ratio;
the efficient economic level comprises: initial investment cost, operation and maintenance cost, energy outsourcing cost and retirement disposal cost;
the social service level includes: popularity of the intelligent electric meter and operation rate on an energy service line.
Optionally, determining a unique index order relationship for a plurality of indexes of the established evaluation index system, determining a relative importance ratio of two adjacent indexes of the unique index order relationship, and subjectively weighting the plurality of indexes in the unique index order relationship according to the relative importance ratio, includes:
determining the least important index b of n evaluation indexesnThen, the least important index b in the n-1 indexes is determinedn-1And obtaining the unique index sequence relation until the n indexes are determined to be finished, wherein the unique index sequence relation comprises the following steps:
b1＞b2＞。。。。bn-1＞bn；
determining the relative importance degree ratio of the adjacent indexes of the unique index order relation, wherein the formula is as follows:
Figure BDA0002782917730000081
determination of the index bnThe weight is:
Figure BDA0002782917730000082
according to rkAnd bnAll indexes in the unique index sequence relation are determined, subjective weighting is completed, and the formula is as follows:
w'k-1＝rk·w'k,k＝n,n-1,...2。
optionally, the objective weighting is performed on a plurality of indexes in the unique index order relationship, including:
determining an average of ith index values of a plurality of indexes
Figure BDA0002782917730000083
The formula is as follows:
Figure BDA0002782917730000084
wherein m is the number of evaluation schemes, xijThe ith index value of the jth evaluation scheme;
determining the standard deviation of the ith index value, wherein the formula is as follows:
Figure BDA0002782917730000091
determining the coefficient of variation of the ith index value according to the following formula:
Figure BDA0002782917730000092
determining the weight of the ith index value, and finishing objective weighting, wherein the formula is as follows:
Figure BDA0002782917730000093
optionally, the performing dispersion maximization weighting on a plurality of indexes in the unique index order relation according to subjective weighting and objective weighting to obtain a weighting result, including:
determining weight vectors of subjective weighting and objective weighting, which are w 'and w', respectively, and the formula is as follows:
w'＝[wi',w'2,...w'n]T
w”＝[w″i,w″2,...w″n]T
and determining the comprehensive weight vector as w according to w' and w ", wherein the formula is as follows:
w＝[w1,w2,...wn]T
determining the relationship of w ', w' and w, the formula is as follows:
w＝αw'+βw”,α≥0,β≥0,α2+β2＝1
and determining the total dispersion among the m evaluation objects according to the relation among w ', w' and w, wherein the formula is as follows:
Figure BDA0002782917730000094
in the formula, n is the index number, and m is the evaluation scheme number;
based on the dispersion maximization, an optimization model is established, wherein the optimization model comprises the following steps:
Figure BDA0002782917730000101
α2+β2＝1
α≥0，β≥0
establishing a Lagrange function solution optimization model, wherein the formula is as follows:
Figure BDA0002782917730000102
the derivation of the lagrange function is:
Figure BDA0002782917730000103
Figure BDA0002782917730000104
Figure BDA0002782917730000105
in order to ensure that the water-soluble organic acid,
Figure BDA0002782917730000106
obtaining:
Figure BDA0002782917730000107
Figure BDA0002782917730000108
Figure BDA0002782917730000111
the values of alpha and beta are substituted into w ═ alpha w '+ beta w' and normalized to obtain the comprehensive weight vector w ═ w [ + w-1,w2,...wn]TAnd using the comprehensive weight vector to complete weighting.
Optionally, the method for evaluating the operation scheme of the multi-energy complementary energy system according to the weighting result of the dispersion maximization weighting of the multiple indexes, and determining the operation scheme with the highest evaluation level as the optimal operation scheme includes:
acquiring an element matrix and an evaluation grade matrix of an operation scheme to be evaluated;
the element matrix is as follows:
Figure BDA0002782917730000112
the evaluation grade matrix is:
N＝[N1,N2,N3,N4]
wherein N is1,N2,N3,N4Respectively representing four evaluation grades of excellence, goodness, middle and difference;
according to the element matrix and the evaluation grade matrix, a classical domain element matrix is established, wherein the classical domain element matrix is as follows:
Figure BDA0002782917730000113
in the formula, RrThe classical domain object element matrix of the r evaluation level is obtained by taking r as 1,2,3,4, NrIs the r-th evaluation level, ciFor the ith evaluation index, i takes 1, 2.. n, Vri＝[ari,bri]The value range of the ith evaluation index of the r evaluation grade is obtained;
according to the classical domain matter element matrix, determining a section domain matter element matrix, wherein the section domain matter element matrix is as follows:
Figure BDA0002782917730000121
in the formula, RpIs a nodal domain object element matrix, Vpi＝[api,bpi]The evaluation index is the value range of the ith evaluation index, namely the section area, and p is the comprehensive evaluation grade of the multi-energy complementary energy system;
determining a comprehensive evaluation index correlation function of a scheme to be evaluated of the complementary energy system, wherein the formula is as follows:
Figure BDA0002782917730000122
in the formula, X, Xr、XpRespectively an index matter element value, a classical domain matter element value range, a section domain matter element value range, rho (X, X) of the operation scheme of the system to be evaluatedr) Is point X and interval Xr＝[ar,br]Distance of (d), ρ (X, X)p) Is point X and interval Xp＝[ap,bp]The distance of (d);
wherein the content of the first and second substances,
Figure BDA0002782917730000123
Figure BDA0002782917730000124
determining the comprehensive association degree, wherein the formula is as follows:
Figure BDA0002782917730000125
in the formula, wiIs the comprehensive weight, K, of the ith index of the system scheme to be evaluatedr(xi) Taking 1,2,3 and 4 as r for the correlation degree of the ith index of the operation scheme to be evaluated relative to the comprehensive evaluation grade r;
if there is
Kri＝max[Kr(xi)],r＝1,2,3,4,i＝1,2,...n
The comprehensive evaluation grade of the index i is r;
if there is
Krx＝max[Kr(Nx)],r＝1,2,3,4
And the comprehensive evaluation grade of the operation scheme to be evaluated is r, and the operation scheme with the highest comprehensive evaluation grade is selected from the m evaluation objects as the optimal decision-making scheme.
The comprehensive evaluation method combines subjective weighting and objective weighting according to the dispersion maximization optimization model to obtain the comprehensive evaluation grade result of each operation optimization scheme of the system, selects the scheme with the highest evaluation grade, namely the optimal decision scheme, and provides scientific guidance for the optimized operation of the system.
Drawings
FIG. 1 is a flow chart of a method for obtaining an optimal operating scheme of a multi-energy complementary energy system according to the present invention;
fig. 2 is a system configuration diagram for obtaining an optimal operation scheme of the multi-energy complementary energy system according to the present invention.
Detailed Description
The exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, however, the present invention may be embodied in many different forms and is not limited to the embodiments described herein, which are provided for complete and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention. In the drawings, the same units/elements are denoted by the same reference numerals.
Unless otherwise defined, terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Further, it will be understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense.
The invention provides a method for obtaining an optimal operation scheme of a multi-energy complementary energy system, which comprises the following steps of:
aiming at the evaluation indexes of the multi-energy complementary energy system, an evaluation index system is established;
aiming at a plurality of indexes of the established evaluation index system, determining a unique index sequence relation, determining a relative importance degree ratio of two adjacent indexes of the unique index sequence relation, and subjectively weighting the plurality of indexes in the unique index sequence relation according to the relative importance degree ratio;
performing objective weighting on a plurality of indexes in the unique index order relation;
performing deviation maximization weighting on a plurality of indexes in the unique index sequence relation according to subjective weighting and objective weighting to obtain a weighting result;
and evaluating the operation scheme of the multi-energy complementary energy system according to the weighting result of the dispersion maximization weighting of the indexes, and determining the operation scheme with the highest evaluation grade as the optimal operation scheme.
An evaluation index comprising:
the system has the advantages of clean low carbon level, safe and reliable level, energy utilization level, efficient economic level and social service level;
clean low carbon levels, including: CO22Annual emission and NOxAnnual emission;
safe and reliable level, including: the reliability, shortage and peak-to-valley difference of energy supply;
energy utilization levels, comprising: the utilization rate of primary energy,
Figure BDA0002782917730000142
Efficiency and system green-to-electric ratio;
an efficient economic level comprising: initial investment cost, operation and maintenance cost, energy outsourcing cost and retirement disposal cost;
a social service level comprising: popularity of the intelligent electric meter and operation rate on an energy service line.
Aiming at a plurality of indexes of an established evaluation index system, determining a unique index sequence relation, determining a relative importance degree ratio of two adjacent indexes of the unique index sequence relation, and subjectively weighting the plurality of indexes in the unique index sequence relation according to the relative importance degree ratio, wherein the method comprises the following steps:
determining the least important index b of n evaluation indexesnThen, the least important index b in the n-1 indexes is determinedn-1And obtaining the unique index sequence relation until the n indexes are determined to be finished, wherein the unique index sequence relation comprises the following steps:
b1＞b2＞。。。。bn-1＞bn；
determining the relative importance degree ratio of the adjacent indexes of the unique index order relation, wherein the formula is as follows:
Figure BDA0002782917730000141
determination of the index bnThe weight is:
Figure BDA0002782917730000151
according to rkAnd bnAll indexes in the unique index sequence relation are determined, subjective weighting is completed, and the formula is as follows:
w'k-1＝rk·w'k,k＝n,n-1,...2。
objectively weighting a plurality of indexes in a unique index order relationship, including:
determining an average of ith index values of a plurality of indexes
Figure BDA0002782917730000152
The formula is as follows:
Figure BDA0002782917730000153
wherein m is the number of evaluation schemes, xijThe ith index value of the jth evaluation scheme;
determining the standard deviation of the ith index value, wherein the formula is as follows:
Figure BDA0002782917730000154
determining the coefficient of variation of the ith index value according to the following formula:
Figure BDA0002782917730000155
determining the weight of the ith index value, and finishing objective weighting, wherein the formula is as follows:
Figure BDA0002782917730000156
the method comprises the following steps of carrying out deviation maximization weighting on a plurality of indexes in the unique index sequence relation according to subjective weighting and objective weighting, and obtaining a weighting result, wherein the weighting method comprises the following steps:
determining weight vectors of subjective weighting and objective weighting, which are w 'and w', respectively, and the formula is as follows:
w'＝[wi',w'2,...w'n]T
w”＝[w″i,w″2,...w″n]T
and determining the comprehensive weight vector as w according to w' and w ", wherein the formula is as follows:
w＝[w1,w2,...wn]T
determining the relationship of w ', w' and w, the formula is as follows:
w＝αw'+βw”,α≥0,β≥0,α2+β2＝1
and determining the total dispersion among the m evaluation objects according to the relation among w ', w' and w, wherein the formula is as follows:
Figure BDA0002782917730000161
in the formula, n is the index number, and m is the evaluation scheme number;
based on the dispersion maximization, an optimization model is established, wherein the optimization model comprises the following steps:
Figure BDA0002782917730000162
α2+β2＝1
α≥0，β≥0
establishing a Lagrange function solution optimization model, wherein the formula is as follows:
Figure BDA0002782917730000163
the derivation of the lagrange function is:
Figure BDA0002782917730000164
Figure BDA0002782917730000165
Figure BDA0002782917730000166
in order to ensure that the water-soluble organic acid,
Figure BDA0002782917730000171
obtaining:
Figure BDA0002782917730000172
Figure BDA0002782917730000173
Figure BDA0002782917730000174
the values of alpha and beta are substituted into w ═ alpha w '+ beta w' and normalized to obtain the comprehensive weight vector w ═ w [ + w-1,w2,...wn]TAnd using the comprehensive weight vector to complete weighting.
According to the weighting result of the dispersion maximization weighting of a plurality of indexes, the operation scheme of the multi-energy complementary energy system is evaluated, and the operation scheme with the highest evaluation grade is determined to be the optimal operation scheme, and the method comprises the following steps:
acquiring an element matrix and an evaluation grade matrix of an operation scheme to be evaluated;
the element matrix is as follows:
Figure BDA0002782917730000175
the evaluation grade matrix is:
N＝[N1,N2,N3,N4]
wherein N is1,N2,N3,N4Respectively representing four evaluation grades of excellence, goodness, middle and difference;
according to the element matrix and the evaluation grade matrix, a classical domain element matrix is established, wherein the classical domain element matrix is as follows:
Figure BDA0002782917730000181
in the formula, RrThe classical domain object element matrix of the r evaluation level is obtained by taking r as 1,2,3,4, NrIs the r-th evaluation level, ciFor the ith evaluation index, i takes 1, 2.. n, Vri＝[ari,bri]The value range of the ith evaluation index of the r evaluation grade is obtained;
according to the classical domain matter element matrix, determining a section domain matter element matrix, wherein the section domain matter element matrix is as follows:
Figure BDA0002782917730000182
in the formula, RpIs a nodal domain object element matrix, Vpi＝[api,bpi]The evaluation index is the value range of the ith evaluation index, namely the section area, and p is the comprehensive evaluation grade of the multi-energy complementary energy system;
determining a comprehensive evaluation index correlation function of a scheme to be evaluated of the complementary energy system, wherein the formula is as follows:
Figure BDA0002782917730000183
in the formula, X, Xr、XpRespectively an index matter element value, a classical domain matter element value range, a section domain matter element value range, rho (X, X) of the operation scheme of the system to be evaluatedr) Is point X and interval Xr＝[ar,br]Distance of (d), ρ (X, X)p) Is point X and interval Xp＝[ap,bp]The distance of (d);
wherein the content of the first and second substances,
Figure BDA0002782917730000191
Figure BDA0002782917730000192
determining the comprehensive association degree, wherein the formula is as follows:
Figure BDA0002782917730000193
in the formula, wiIs the comprehensive weight, K, of the ith index of the system scheme to be evaluatedr(xi) Taking 1,2,3 and 4 as r for the correlation degree of the ith index of the operation scheme to be evaluated relative to the comprehensive evaluation grade r;
if there is
Kri＝max[Kr(xi)],r＝1,2,3,4,i＝1,2,...n
The comprehensive evaluation grade of the index i is r;
if there is
Krx＝max[Kr(Nx)],r＝1,2,3,4
And the comprehensive evaluation grade of the operation scheme to be evaluated is r, and the operation scheme with the highest comprehensive evaluation grade is selected from the m evaluation objects as the optimal decision-making scheme.
The index system model is as follows:
(1) energy supply reliability A1The following are:
Figure BDA0002782917730000194
in the formula, tenergy-lossAverage disable time for the user. "disabling" includes power off, heat/cold off, gas off. t is tstatThe statistical time is obtained.
(2) Energy supply shortage rate A2The following are:
Figure BDA0002782917730000195
Figure BDA0002782917730000196
Figure BDA0002782917730000201
Figure BDA0002782917730000202
Figure BDA0002782917730000203
in the formula,. DELTA.WE、ΔWG、ΔWH、ΔWCInsufficient power, kW.h, is supplied for system electricity, gas, heat and cold energy respectively;
Figure BDA0002782917730000204
planned supply quantities of electricity, gas, heat and cold energy, kW.h respectively;
Figure BDA0002782917730000205
load power consumption, heat consumption and cold consumption are respectively kW.h;
Figure BDA0002782917730000206
planned supply for natural gas, m 3;
Figure BDA0002782917730000207
m3 for load gas consumption; rGFor the constant of the low-grade heat value of the natural gas, 9.7 kW.h/m 3 is generally taken.
(3) Peak-to-valley difference rate A3The following were used:
Figure BDA0002782917730000208
in the formula (I), the compound is shown in the specification,
Figure BDA0002782917730000209
the maximum load electric power of the system is kW;
Figure BDA00027829177300002010
the system minimum load electric power is kW.
(4) Primary energy utilization ratio B1The following were used:
Figure BDA00027829177300002011
in the formula (I), the compound is shown in the specification,
Figure BDA00027829177300002012
outputting electric power, kW, for the gas turbine;
Figure BDA00027829177300002013
kW is the heating power of the heat exchanger;
Figure BDA00027829177300002014
is the refrigeration power of an absorption refrigerator, kW; Δ t is the running time, which is generally 1 hour;
Figure BDA00027829177300002015
m3 for gas turbine natural gas consumption; rGFor the constant of the low-grade heat value of the natural gas, 9.7 kW.h/m 3 is generally taken.
(5)
Figure BDA00027829177300002017
Efficiency B2The following were used:
Figure BDA00027829177300002016
in the formula, λE、λH、λC、λGRespectively the energy and mass coefficients of electricity, heat consumption, cold consumption and natural gas.
Figure BDA0002782917730000211
Load power consumption, heat consumption and cold consumption are respectively kW.h;
Figure BDA0002782917730000212
m3 for load gas consumption; vG∑(t) is the total flow of natural gas input to the regional energy system, m 3; rGThe low-grade heat value constant of the natural gas is generally 9.7 kW.h/m 3; w is the electric quantity input into the system by an external power grid, kW.h;
Figure BDA0002782917730000213
the electric power, kW, generated by the ith wind generating set at the moment t;
Figure BDA0002782917730000214
the electric power, kW, generated by the jth photovoltaic generator set at the moment t; n isi、njThe number of the distributed wind and light units is respectively.
(6) System green to electric ratio B3The following were used:
Figure BDA0002782917730000215
in the formula (I), the compound is shown in the specification,
Figure BDA0002782917730000216
the electric power, kW, generated by the ith wind generating set at the moment t;
Figure BDA0002782917730000217
the electric power, kW, generated by the jth photovoltaic generator set at the moment t;
Figure BDA0002782917730000218
the power generated by the ith wind generating set all the year round, kW.h;
Figure BDA0002782917730000219
the power generated by the jth photovoltaic generator set all the year round, namely kW.h; n isi、njThe number of the distributed wind and light units is respectively;
Figure BDA00027829177300002110
outputting electric power, kW, for the gas turbine; Δ t is the running time, which is generally 1 hour; w is the electric quantity input into the system by an external power grid, kW.h.
(7) Initial investment cost C1The following were used:
Figure BDA00027829177300002111
in the formula Ibuy,kPurchasing cost for system equipment k; vkOptimally designing capacity for the equipment k; k is various devices in the system; n iskIs the total number of devices in the system.
(8) Cost of operation and maintenance C2The following were used:
Figure BDA00027829177300002112
in the formula Iwork,k、Ipro,kRespectively the annual operating cost per unit capacity and the annual maintenance cost per unit capacity of the equipment(ii) a Optimally designing capacity for the equipment k; k is various devices in the system; n iskIs the total number of devices in the system.
(9) Cost of energy outsourcing C3The following were used:
C3＝IEbuy,tPE,t+IGbuy,tVG∑(t)
in the formula IEbuy,t、IGbuy,tRespectively unit electricity purchasing unit price and unit gas purchasing unit price at the time t; pE,tPower, kW, is purchased at the time t; vG∑(t) is the total natural gas consumed by the system, m 3.
(10) Retirement disposal cost C4The following were used:
Figure BDA0002782917730000221
in the formula, the following components are mixed; i ispeopleThe labor cost for decommissioning the system is treated; i iscarTransportation costs for decommissioned equipment; omega is the scrapping conversion coefficient of retired equipment; alpha is social discount rate; l is the service life of the equipment;
Figure BDA0002782917730000222
is equal year value;
(11) CO2 year discharge D1The following were used:
D1＝VG∑(t)·RG·NCO2
in the formula, A1The emission of CO2 years is kg for a multi-energy complementary energy system; vG∑(t) total gas consumption per year for gas turbines, m 3; rGThe low-grade heat value constant of the natural gas is generally 9.7 kW.h/m 3; n is a radical ofCO2For the carbon dioxide emission coefficient of the combustion natural gas, 0.198kgCO 2/kW.h was taken.
(12) Annual NOx emission D2The following were used:
Figure BDA0002782917730000231
in the formula, A2The annual emission of NOx in a multi-energy complementary energy system is kg; vG∑(t) total annual natural gas consumption of the multi-energy complementary energy system, m 3; rGThe low-grade heat value constant of the natural gas is generally 9.7 kW.h/m 3;
Figure BDA0002782917730000232
for the nitrogen oxide generation coefficient of combustion natural gas, 6.3kg/m3 was generally taken.
(13) Popularity E of intelligent electric meter1The following were used:
Figure BDA0002782917730000233
in the formula, ninThe number of users for installing the intelligent ammeter is the number of users; n isuserIs the total number of users in the system area.
(14) Energy business online operation rate E2The following were used:
Figure BDA0002782917730000234
in the formula, nonlineThe times of handling energy services (such as payment, reservation, repair and the like) for residents through online intelligent service platforms (such as APP, public numbers and the like); n isdeal is the total times of handling the energy service online and offline.
The present invention further provides a system 200 for obtaining an optimal operation scheme of a multi-energy complementary energy system, as shown in fig. 2, including:
an index system establishing module 201, which is used for establishing an evaluation index system aiming at the evaluation index of the multi-energy complementary energy system;
the subjective weighting module 202 determines a unique index sequence relation according to a plurality of indexes of the established evaluation index system, determines a relative importance degree ratio of two adjacent indexes of the unique index sequence relation, and subjectively weights the plurality of indexes in the unique index sequence relation according to the relative importance degree ratio;
the objective weighting module 203 is used for carrying out objective weighting on a plurality of indexes in the unique index sequence relation;
the comprehensive weighting module 204 is used for performing deviation maximization weighting on a plurality of indexes in the unique index sequence relation according to subjective weighting and objective weighting to obtain a weighting result;
the evaluation module 205 evaluates the operation scheme of the multi-energy complementary energy system according to the weighting result of the dispersion maximization weighting of the multiple indexes, and determines the operation scheme with the highest evaluation level as the optimal operation scheme.
An evaluation index comprising:
the system has the advantages of clean low carbon level, safe and reliable level, energy utilization level, efficient economic level and social service level;
clean low carbon levels, including: CO22Annual emission and NOxAnnual emission;
safe and reliable level, including: the reliability, shortage and peak-to-valley difference of energy supply;
energy utilization levels, comprising: the utilization rate of primary energy,
Figure BDA0002782917730000243
Efficiency and system green-to-electric ratio;
an efficient economic level comprising: initial investment cost, operation and maintenance cost, energy outsourcing cost and retirement disposal cost;
a social service level comprising: popularity of the intelligent electric meter and operation rate on an energy service line.
Aiming at a plurality of indexes of an established evaluation index system, determining a unique index sequence relation, determining a relative importance degree ratio of two adjacent indexes of the unique index sequence relation, and subjectively weighting the plurality of indexes in the unique index sequence relation according to the relative importance degree ratio, wherein the method comprises the following steps:
determining the least important index b of n evaluation indexesnThen, the least important index b in the n-1 indexes is determinedn-1And obtaining the unique index sequence relation until the n indexes are determined to be finished, wherein the unique index sequence relation comprises the following steps:
b1＞b2＞。。。。bn-1＞bn；
determining the relative importance degree ratio of the adjacent indexes of the unique index order relation, wherein the formula is as follows:
Figure BDA0002782917730000241
determination of the index bnThe weight is:
Figure BDA0002782917730000242
according to rkAnd bnAll indexes in the unique index sequence relation are determined, subjective weighting is completed, and the formula is as follows:
w'k-1＝rk·w'k,k＝n,n-1,...2。
optionally, the objective weighting is performed on a plurality of indexes in the unique index order relationship, including:
determining an average of ith index values of a plurality of indexes
Figure BDA0002782917730000251
The formula is as follows:
Figure BDA0002782917730000252
wherein m is the number of evaluation schemes, xijThe ith index value of the jth evaluation scheme;
determining the standard deviation of the ith index value, wherein the formula is as follows:
Figure BDA0002782917730000253
determining the coefficient of variation of the ith index value according to the following formula:
Figure BDA0002782917730000254
determining the weight of the ith index value, and finishing objective weighting, wherein the formula is as follows:
Figure BDA0002782917730000255
the method comprises the following steps of carrying out deviation maximization weighting on a plurality of indexes in the unique index sequence relation according to subjective weighting and objective weighting, and obtaining a weighting result, wherein the weighting method comprises the following steps:
determining weight vectors of subjective weighting and objective weighting, which are w 'and w', respectively, and the formula is as follows:
w'＝[wi',w'2,...w'n]T
w”＝[w″i,w″2,...w″n]T
and determining the comprehensive weight vector as w according to w' and w ", wherein the formula is as follows:
w＝[w1,w2,...wn]T
determining the relationship of w ', w' and w, the formula is as follows:
w＝αw'+βw”,α≥0,β≥0,α2+β2＝1
and determining the total dispersion among the m evaluation objects according to the relation among w ', w' and w, wherein the formula is as follows:
Figure BDA0002782917730000261
in the formula, n is the index number, and m is the evaluation scheme number;
based on the dispersion maximization, an optimization model is established, wherein the optimization model comprises the following steps:
Figure BDA0002782917730000262
α2+β2＝1
α≥0，β≥0
establishing a Lagrange function solution optimization model, wherein the formula is as follows:
Figure BDA0002782917730000263
the derivation of the lagrange function is:
Figure BDA0002782917730000264
Figure BDA0002782917730000265
Figure BDA0002782917730000266
in order to ensure that the water-soluble organic acid,
Figure BDA0002782917730000267
obtaining:
Figure BDA0002782917730000271
Figure BDA0002782917730000272
Figure BDA0002782917730000273
the values of alpha and beta are substituted into w ═ alpha w '+ beta w' and normalized to obtain the comprehensive weight vector w ═ w [ + w-1,w2,...wn]TUsing the integrated weight vectorBecome entitled.
According to the weighting result of the dispersion maximization weighting of a plurality of indexes, the operation scheme of the multi-energy complementary energy system is evaluated, and the operation scheme with the highest evaluation grade is determined to be the optimal operation scheme, and the method comprises the following steps:
acquiring an element matrix and an evaluation grade matrix of an operation scheme to be evaluated;
the element matrix is as follows:
Figure BDA0002782917730000274
the evaluation grade matrix is:
N＝[N1,N2,N3,N4]
wherein N is1,N2,N3,N4Respectively representing four evaluation grades of excellence, goodness, middle and difference;
according to the element matrix and the evaluation grade matrix, a classical domain element matrix is established, wherein the classical domain element matrix is as follows:
Figure BDA0002782917730000281
in the formula, RrThe classical domain object element matrix of the r evaluation level is obtained by taking r as 1,2,3,4, NrIs the r-th evaluation level, ciFor the ith evaluation index, i takes 1, 2.. n, Vri＝[ari,bri]The value range of the ith evaluation index of the r evaluation grade is obtained;
according to the classical domain matter element matrix, determining a section domain matter element matrix, wherein the section domain matter element matrix is as follows:
Figure BDA0002782917730000282
in the formula, RpIs a nodal domain object element matrix, Vpi＝[api,bpi]Is the value range of the ith evaluation index, namely the section area, and p is the multi-energy complementary energyComprehensively evaluating the grade of a source system;
determining a comprehensive evaluation index correlation function of a scheme to be evaluated of the complementary energy system, wherein the formula is as follows:
Figure BDA0002782917730000283
in the formula, X, Xr、XpRespectively an index matter element value, a classical domain matter element value range, a section domain matter element value range, rho (X, X) of the operation scheme of the system to be evaluatedr) Is point X and interval Xr＝[ar,br]Distance of (d), ρ (X, X)p) Is point X and interval Xp＝[ap,bp]The distance of (d);
wherein the content of the first and second substances,
Figure BDA0002782917730000284
Figure BDA0002782917730000291
determining the comprehensive association degree, wherein the formula is as follows:
Figure BDA0002782917730000292
in the formula, wiIs the comprehensive weight, K, of the ith index of the system scheme to be evaluatedr(xi) Taking 1,2,3 and 4 as r for the correlation degree of the ith index of the operation scheme to be evaluated relative to the comprehensive evaluation grade r;
if there is
Kri＝max[Kr(xi)],r＝1,2,3,4,i＝1,2,...n
The comprehensive evaluation grade of the index i is r;
if there is
Krx＝max[Kr(Nx)],r＝1,2,3,4
And the comprehensive evaluation grade of the operation scheme to be evaluated is r, and the operation scheme with the highest comprehensive evaluation grade is selected from the m evaluation objects as the optimal decision-making scheme.
The comprehensive evaluation method combines subjective weighting and objective weighting according to the dispersion maximization optimization model to obtain the comprehensive evaluation grade result of each operation optimization scheme of the system, selects the scheme with the highest evaluation grade, namely the optimal decision scheme, and provides scientific guidance for the optimized operation of the system.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. The scheme in the embodiment of the application can be implemented by adopting various computer languages, such as object-oriented programming language Java and transliterated scripting language JavaScript.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.

Claims (12)

1. A method of obtaining an optimal operating scheme for a multi-energy complementary energy system, the method comprising:
aiming at the evaluation indexes of the multi-energy complementary energy system, an evaluation index system is established;
aiming at a plurality of indexes of the established evaluation index system, determining a unique index sequence relation, determining a relative importance degree ratio of two adjacent indexes of the unique index sequence relation, and subjectively weighting the plurality of indexes in the unique index sequence relation according to the relative importance degree ratio;
performing objective weighting on a plurality of indexes in the unique index order relation;
performing deviation maximization weighting on a plurality of indexes in the unique index sequence relation according to subjective weighting and objective weighting to obtain a weighting result;
and evaluating the operation scheme of the multi-energy complementary energy system according to the weighting result of the dispersion maximization weighting of the indexes, and determining the operation scheme with the highest evaluation grade as the optimal operation scheme.
2. The method of claim 1, the evaluation index comprising:
the system has the advantages of clean low carbon level, safe and reliable level, energy utilization level, efficient economic level and social service level;
the clean low carbon level comprises: CO22Annual emission and NOxAnnual emission;
the safe and reliable level comprises: the reliability, shortage and peak-to-valley difference of energy supply;
the energy utilization level comprises: the utilization rate of primary energy,
Figure FDA0002782917720000011
Efficiency and system green-to-electric ratio;
the efficient economic level comprises: initial investment cost, operation and maintenance cost, energy outsourcing cost and retirement disposal cost;
the social service level includes: popularity of the intelligent electric meter and operation rate on an energy service line.
3. The method according to claim 1, wherein the determining a unique index order relationship for a plurality of indexes of the established evaluation index system, determining a relative importance ratio of two adjacent indexes of the unique index order relationship, and subjectively weighting the plurality of indexes in the unique index order relationship according to the relative importance ratio comprises:
determining the least important index b of n evaluation indexesnThen, the least important index b in the n-1 indexes is determinedn-1And obtaining the unique index sequence relation until the n indexes are determined to be finished, wherein the unique index sequence relation comprises the following steps:
b1＞b2＞。。。。bn-1＞bn；
determining the relative importance degree ratio of the adjacent indexes of the unique index order relation, wherein the formula is as follows:
Figure FDA0002782917720000021
determination of the index bnThe weight is:
Figure FDA0002782917720000022
according to rkAnd bnAll indexes in the unique index sequence relation are determined, subjective weighting is completed, and the formula is as follows:
w'k-1＝rk·w'k,k＝n,n-1,...2。
4. the method of claim 1, the objectively weighting a plurality of metrics in a unique metric-order relationship, comprising:
determining an average of ith index values of a plurality of indexes
Figure FDA0002782917720000023
The formula is as follows:
Figure FDA0002782917720000024
wherein m is the number of evaluation schemes, xijThe ith index value of the jth evaluation scheme;
determining the standard deviation of the ith index value, wherein the formula is as follows:
Figure FDA0002782917720000025
determining the coefficient of variation of the ith index value according to the following formula:
Figure FDA0002782917720000026
determining the weight of the ith index value, and finishing objective weighting, wherein the formula is as follows:
Figure FDA0002782917720000027
5. the method according to claim 1, wherein the weighting for the plurality of indexes in the unique index order relation by performing dispersion maximization weighting according to subjective weighting and objective weighting to obtain the weighting result comprises:
determining weight vectors of subjective weighting and objective weighting, which are w 'and w', respectively, and the formula is as follows:
w'＝[w′i,w′2,...w′n]T
w″＝[w″i,w″2,...w″n]T
and determining the comprehensive weight vector as w according to w' and w ", wherein the formula is as follows:
w＝[w1,w2,...wn]T
determining the relationship of w ', w' and w, the formula is as follows:
w＝αw'+βw”,α≥0,β≥0,α2+β2＝1
and determining the total dispersion among the m evaluation objects according to the relation among w ', w' and w, wherein the formula is as follows:
Figure FDA0002782917720000031
in the formula, n is the index number, and m is the evaluation scheme number;
based on the dispersion maximization, an optimization model is established, wherein the optimization model comprises the following steps:
Figure FDA0002782917720000032
α2+β2＝1
α≥0，β≥0
establishing a Lagrange function solution optimization model, wherein the formula is as follows:
Figure FDA0002782917720000033
the derivation of the lagrange function is:
Figure FDA0002782917720000034
Figure FDA0002782917720000041
Figure FDA0002782917720000042
in order to ensure that the water-soluble organic acid,
Figure FDA0002782917720000043
obtaining:
Figure FDA0002782917720000044
Figure FDA0002782917720000045
Figure FDA0002782917720000046
the values of alpha and beta are substituted into w ═ alpha w '+ beta w' and normalized to obtain the comprehensive weight vector w ═ w [ + w-1,w2,...wn]TAnd using the comprehensive weight vector to complete weighting.
6. The method according to claim 1, wherein the evaluating the operation scheme of the multi-energy complementary energy system according to the weighted result of the dispersion maximization weighting of the plurality of indexes and determining the operation scheme with the highest evaluation grade as the optimal operation scheme comprises:
acquiring an element matrix and an evaluation grade matrix of an operation scheme to be evaluated;
the element matrix is as follows:
Figure FDA0002782917720000047
the evaluation grade matrix is:
N＝[N1,N2,N3,N4]
wherein N is1,N2,N3,N4Respectively representing four evaluation grades of excellence, goodness, middle and difference;
according to the element matrix and the evaluation grade matrix, a classical domain element matrix is established, wherein the classical domain element matrix is as follows:
Figure FDA0002782917720000051
in the formula, RrThe classical domain object element matrix of the r evaluation level is obtained by taking r as 1,2,3,4, NrIs the r-th evaluation level, ciFor the ith evaluation index, i takes 1, 2.. n, Vri＝[ari,bri]The value range of the ith evaluation index of the r evaluation grade is obtained;
according to the classical domain matter element matrix, determining a section domain matter element matrix, wherein the section domain matter element matrix is as follows:
Figure FDA0002782917720000052
in the formula, RpIs a nodal domain object element matrix, Vpi＝[api,bpi]The evaluation index is the value range of the ith evaluation index, namely the section area, and p is the comprehensive evaluation grade of the multi-energy complementary energy system;
determining a comprehensive evaluation index correlation function of a scheme to be evaluated of the complementary energy system, wherein the formula is as follows:
Figure FDA0002782917720000061
in the formula, X, Xr、XpRespectively an index matter element value, a classical domain matter element value range, a section domain matter element value range, rho (X, X) of the operation scheme of the system to be evaluatedr) Is point X and interval Xr＝[ar,br]Distance of (d), ρ (X, X)p) Is point X and interval Xp＝[ap,bp]The distance of (d);
wherein the content of the first and second substances,
Figure FDA0002782917720000062
Figure FDA0002782917720000063
determining the comprehensive association degree, wherein the formula is as follows:
Figure FDA0002782917720000064
in the formula, wiTo be evaluated by the systemThe comprehensive weight of the i-th index, Kr(xi) Taking 1,2,3 and 4 as r for the correlation degree of the ith index of the operation scheme to be evaluated relative to the comprehensive evaluation grade r;
if there is
Kri＝max[Kr(xi)],r＝1,2,3,4,i＝1,2,...n
The comprehensive evaluation grade of the index i is r;
if there is
Krx＝max[Kr(Nx)],r＝1,2,3,4
And the comprehensive evaluation grade of the operation scheme to be evaluated is r, and the operation scheme with the highest comprehensive evaluation grade is selected from the m evaluation objects as the optimal decision-making scheme.
7. A system for obtaining an optimal operating scenario for a multi-energy complementary energy system, the system comprising:
the index system establishing module is used for establishing an evaluation index system aiming at the evaluation indexes of the multi-energy complementary energy system;
the subjective weighting module determines a unique index sequence relation aiming at a plurality of indexes of the established evaluation index system, determines the relative importance degree ratio of two adjacent indexes of the unique index sequence relation, and subjectively weights the plurality of indexes in the unique index sequence relation according to the relative importance degree ratio;
the objective weighting module is used for carrying out objective weighting on a plurality of indexes in the unique index order relation;
the comprehensive weighting module is used for performing deviation maximization weighting on a plurality of indexes in the unique index sequence relation according to subjective weighting and objective weighting to obtain a weighting result;
and the evaluation module is used for evaluating the operation scheme of the multi-energy complementary energy system according to the weighting result of the dispersion maximization weighting of the indexes and determining the operation scheme with the highest evaluation grade as the optimal operation scheme.
8. The system of claim 7, the evaluation index comprising:
the system has the advantages of clean low carbon level, safe and reliable level, energy utilization level, efficient economic level and social service level;
the clean low carbon level comprises: CO22Annual emission and NOxAnnual emission;
the safe and reliable level comprises: the reliability, shortage and peak-to-valley difference of energy supply;
the energy utilization level comprises: the utilization rate of primary energy,
Figure FDA0002782917720000073
Efficiency and system green-to-electric ratio;
the efficient economic level comprises: initial investment cost, operation and maintenance cost, energy outsourcing cost and retirement disposal cost;
the social service level includes: popularity of the intelligent electric meter and operation rate on an energy service line.
9. The system according to claim 7, wherein the determining a unique index order relationship for a plurality of indexes of the established evaluation index system, determining a relative importance ratio of two adjacent indexes of the unique index order relationship, and subjectively weighting the plurality of indexes in the unique index order relationship according to the relative importance ratio comprises:
determining the least important index b of n evaluation indexesnThen, the least important index b in the n-1 indexes is determinedn-1And obtaining the unique index sequence relation until the n indexes are determined to be finished, wherein the unique index sequence relation comprises the following steps:
b1＞b2＞。。。。bn-1＞bn；
determining the relative importance degree ratio of the adjacent indexes of the unique index order relation, wherein the formula is as follows:
Figure FDA0002782917720000071
determination of the index bnThe weight is:
Figure FDA0002782917720000072
according to rkAnd bnAll indexes in the unique index sequence relation are determined, subjective weighting is completed, and the formula is as follows:
w'k-1＝rk·w'k,k＝n,n-1,...2。
10. the system of claim 7, the objective weighting of a plurality of metrics in a unique metric-order relationship, comprising:
determining an average of ith index values of a plurality of indexes
Figure FDA0002782917720000081
The formula is as follows:
Figure FDA0002782917720000082
wherein m is the number of evaluation schemes, xijThe ith index value of the jth evaluation scheme;
determining the standard deviation of the ith index value, wherein the formula is as follows:
Figure FDA0002782917720000083
determining the coefficient of variation of the ith index value according to the following formula:
Figure FDA0002782917720000084
determining the weight of the ith index value, and finishing objective weighting, wherein the formula is as follows:
Figure FDA0002782917720000085
11. the system of claim 7, wherein the weighting of the plurality of indicators in the unique indicator order relationship according to subjective weighting and objective weighting for dispersion maximization to obtain the weighting result comprises:
determining weight vectors of subjective weighting and objective weighting, which are w 'and w', respectively, and the formula is as follows:
w'＝[w′i,w′2,...w′n]T
w”＝[w″i,w″2,...w″n]T
and determining the comprehensive weight vector as w according to w' and w ", wherein the formula is as follows:
w＝[w1,w2,...wn]T
determining the relationship of w ', w' and w, the formula is as follows:
w＝αw'+βw”,α≥0,β≥0,α2+β2＝1
and determining the total dispersion among the m evaluation objects according to the relation among w ', w' and w, wherein the formula is as follows:
Figure FDA0002782917720000091
in the formula, n is the index number, and m is the evaluation scheme number;
based on the dispersion maximization, an optimization model is established, wherein the optimization model comprises the following steps:
Figure FDA0002782917720000092
α2+β2＝1
α≥0，β≥0
establishing a Lagrange function solution optimization model, wherein the formula is as follows:
Figure FDA0002782917720000093
the derivation of the lagrange function is:
Figure FDA0002782917720000094
Figure FDA0002782917720000095
Figure FDA0002782917720000096
in order to ensure that the water-soluble organic acid,
Figure FDA0002782917720000101
obtaining:
Figure FDA0002782917720000102
Figure FDA0002782917720000103
Figure FDA0002782917720000104
the values of alpha and beta are substituted into w ═ alpha w '+ beta w' and normalized to obtain the comprehensive weight vector w ═ w [ + w-1,w2,...wn]TAnd using the comprehensive weight vector to complete weighting.
12. The system of claim 7, wherein the evaluating the operating schemes of the multi-energy complementary energy system according to the weighted result of the dispersion maximization weighting of the plurality of indexes and determining the operating scheme with the highest evaluation grade as the optimal operating scheme comprises:
acquiring an element matrix and an evaluation grade matrix of an operation scheme to be evaluated;
the element matrix is as follows:
Figure FDA0002782917720000105
the evaluation grade matrix is:
N＝[N1,N2,N3,N4]
wherein N is1,N2,N3,N4Respectively representing four evaluation grades of excellence, goodness, middle and difference;
according to the element matrix and the evaluation grade matrix, a classical domain element matrix is established, wherein the classical domain element matrix is as follows:
Figure FDA0002782917720000111
in the formula, RrThe classical domain object element matrix of the r evaluation level is obtained by taking r as 1,2,3,4, NrIs the r-th evaluation level, ciFor the ith evaluation index, i takes 1, 2.. n, Vri＝[ari,bri]The value range of the ith evaluation index of the r evaluation grade is obtained;
according to the classical domain matter element matrix, determining a section domain matter element matrix, wherein the section domain matter element matrix is as follows:
Figure FDA0002782917720000112
in the formula, RpIs a nodal domain object element matrix, Vpi＝[api,bpi]Is the value range of the ith evaluation index, namely the section areaP is the comprehensive evaluation grade of the multi-energy complementary energy system;
determining a comprehensive evaluation index correlation function of a scheme to be evaluated of the complementary energy system, wherein the formula is as follows:
Figure FDA0002782917720000113
in the formula, X, Xr、XpRespectively an index matter element value, a classical domain matter element value range, a section domain matter element value range, rho (X, X) of the operation scheme of the system to be evaluatedr) Is point X and interval Xr＝[ar,br]Distance of (d), ρ (X, X)p) Is point X and interval Xp＝[ap,bp]The distance of (d);
wherein the content of the first and second substances,
Figure FDA0002782917720000121
Figure FDA0002782917720000122
determining the comprehensive association degree, wherein the formula is as follows:
Figure FDA0002782917720000123
in the formula, wiIs the comprehensive weight, K, of the ith index of the system scheme to be evaluatedr(xi) Taking 1,2,3 and 4 as r for the correlation degree of the ith index of the operation scheme to be evaluated relative to the comprehensive evaluation grade r;
if there is
Kri＝max[Kr(xi)],r＝1,2,3,4,i＝1,2,...n
The comprehensive evaluation grade of the index i is r;
if there is
Krx＝max[Kr(Nx)],r＝1,2,3,4
And the comprehensive evaluation grade of the operation scheme to be evaluated is r, and the operation scheme with the highest comprehensive evaluation grade is selected from the m evaluation objects as the optimal decision-making scheme.
CN202011287726.XA 2020-11-17 2020-11-17 Method and system for obtaining optimal operation scheme of multi-energy complementary energy system Pending CN112508233A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202011287726.XA CN112508233A (en) 2020-11-17 2020-11-17 Method and system for obtaining optimal operation scheme of multi-energy complementary energy system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202011287726.XA CN112508233A (en) 2020-11-17 2020-11-17 Method and system for obtaining optimal operation scheme of multi-energy complementary energy system

Publications (1)

Publication Number Publication Date
CN112508233A true CN112508233A (en) 2021-03-16

Family

ID=74956547

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202011287726.XA Pending CN112508233A (en) 2020-11-17 2020-11-17 Method and system for obtaining optimal operation scheme of multi-energy complementary energy system

Country Status (1)

Country Link
CN (1) CN112508233A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113592561A (en) * 2021-08-09 2021-11-02 国网上海市电力公司 Green power index generation method based on big power economy data

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104143052A (en) * 2014-08-13 2014-11-12 天津大学 Method for evaluating quality of steady state electric energy in grid-connected photovoltaic power generation system
CN105678453A (en) * 2016-01-05 2016-06-15 国网山东省电力公司泰安供电公司 Multi-dimension evaluation method on the basis of power grid index evaluation system
KR20180060071A (en) * 2016-11-28 2018-06-07 그린에코스 주식회사 Development of System for Cost-Benefit Model Interface, Using Energy Outlook Model and Integrating Inventory Database
CN108256773A (en) * 2018-01-25 2018-07-06 华电电力科学研究院有限公司 A kind of quantitative analysis method of built small power station's generating capacity assessment indicator system suitable for venture evaluation
CN108460525A (en) * 2018-02-24 2018-08-28 南方电网科学研究院有限责任公司 A kind of comprehensive energy utilization ratio appraisal procedure for distribution system of providing multiple forms of energy to complement each other
CN108802576A (en) * 2018-03-09 2018-11-13 国网山西省电力公司检修分公司 A kind of subjective and objective integration appraisal procedure of oil immersed type capacitance graded bushing operating status
CN110222973A (en) * 2019-05-31 2019-09-10 国网安徽省电力有限公司经济技术研究院 A kind of integrated energy system evaluation method and system based on optimal weights combination
CN110428168A (en) * 2019-07-31 2019-11-08 广东电网有限责任公司 It is a kind of meter and energy storage multiple-energy-source distribution system coordinated scheduling integrated evaluating method
WO2020041955A1 (en) * 2018-08-28 2020-03-05 大连理工大学 Method for evaluating comprehensive performance of numerical control machine tool based on improved pull-apart grade method
CN111340359A (en) * 2020-02-25 2020-06-26 西安交通大学 Comprehensive evaluation method for multi-energy complementary distributed energy system

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104143052A (en) * 2014-08-13 2014-11-12 天津大学 Method for evaluating quality of steady state electric energy in grid-connected photovoltaic power generation system
CN105678453A (en) * 2016-01-05 2016-06-15 国网山东省电力公司泰安供电公司 Multi-dimension evaluation method on the basis of power grid index evaluation system
KR20180060071A (en) * 2016-11-28 2018-06-07 그린에코스 주식회사 Development of System for Cost-Benefit Model Interface, Using Energy Outlook Model and Integrating Inventory Database
CN108256773A (en) * 2018-01-25 2018-07-06 华电电力科学研究院有限公司 A kind of quantitative analysis method of built small power station's generating capacity assessment indicator system suitable for venture evaluation
CN108460525A (en) * 2018-02-24 2018-08-28 南方电网科学研究院有限责任公司 A kind of comprehensive energy utilization ratio appraisal procedure for distribution system of providing multiple forms of energy to complement each other
CN108802576A (en) * 2018-03-09 2018-11-13 国网山西省电力公司检修分公司 A kind of subjective and objective integration appraisal procedure of oil immersed type capacitance graded bushing operating status
WO2020041955A1 (en) * 2018-08-28 2020-03-05 大连理工大学 Method for evaluating comprehensive performance of numerical control machine tool based on improved pull-apart grade method
CN110222973A (en) * 2019-05-31 2019-09-10 国网安徽省电力有限公司经济技术研究院 A kind of integrated energy system evaluation method and system based on optimal weights combination
CN110428168A (en) * 2019-07-31 2019-11-08 广东电网有限责任公司 It is a kind of meter and energy storage multiple-energy-source distribution system coordinated scheduling integrated evaluating method
CN111340359A (en) * 2020-02-25 2020-06-26 西安交通大学 Comprehensive evaluation method for multi-energy complementary distributed energy system

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
刘兵;李群湛;董祥;: "基于时变权重的电能质量综合评估研究", 电力系统保护与控制, no. 14 *
叶琪超;楼可炜;张宝;白洪宸;: "多能互补综合能源系统设计及优化", 浙江电力, no. 07, pages 212 - 213 *
张新建: "离差最大化赋权的蚁群聚类算法", 计算机时代, pages 1 - 4 *
赵鹏翔;范莹;周喜超;李阳;刘方;: "面向园区综合能源系统的评价方法", 电源技术, no. 09 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113592561A (en) * 2021-08-09 2021-11-02 国网上海市电力公司 Green power index generation method based on big power economy data

Similar Documents

Publication Publication Date Title
Gu et al. Residential CCHP microgrid with load aggregator: Operation mode, pricing strategy, and optimal dispatch
WO2023134254A1 (en) Equipment model selection method for energy interconnection system
Wang et al. Wasserstein and multivariate linear affine based distributionally robust optimization for CCHP-P2G scheduling considering multiple uncertainties
Siqin et al. A two-stage distributionally robust optimization model for P2G-CCHP microgrid considering uncertainty and carbon emission
Yang et al. A two-stage optimization model for Park Integrated Energy System operation and benefit allocation considering the effect of Time-Of-Use energy price
Zeng et al. Day-ahead interval optimization for CCHP system considering uncertainty of wind power and PV
Wang et al. Optimal scheduling of the RIES considering time-based demand response programs with energy price
CN113592648A (en) Multi-agent transaction method and system of comprehensive energy system
CN112308411B (en) Comprehensive energy station random planning method and system based on dynamic carbon trading model
Yuan et al. A new hybrid multi-criteria decision-making approach for developing integrated energy systems in industrial parks
Dai et al. Optimization of CCHP integrated with multiple load, replenished energy, and hybrid storage in different operation modes
Zhao et al. Economic dispatch of multi-energy system considering seasonal variation based on hybrid operation strategy
Qin et al. Robust optimal dispatching of integrated electricity and gas system considering refined power-to-gas model under the dual carbon target
Tang et al. Power generation mix evolution based on rolling horizon optimal approach: A system dynamics analysis
Wang et al. Pathways of carbon emissions reduction under the water-energy constraint: A case study of Beijing in China
Cui et al. Optimal electricity allocation model under China's planning-market double-track mechanism considering bidding game of generation companies
Fan et al. Multi-stage time sequence planning model of integrated energy system considering extreme scenarios and uncertainty
CN112508233A (en) Method and system for obtaining optimal operation scheme of multi-energy complementary energy system
Guan et al. Chance-constrained optimization of hybrid solar combined cooling, heating and power system considering energetic, economic, environmental, and flexible performances
Li et al. Energy transition roadmap towards net-zero communities: A case study in Japan
CN107622331B (en) Optimization method and device for direct transaction mode of generator set and power consumer
Serrat et al. Ground source heat pump driven by reciprocating engine firing biomethane from wastewater treatment plant sludge in a cogeneration for district heating and cooling. A case study in Spain
Liu et al. Potential Analysis and Optimization of Combined Cooling, Heating, and Power (CCHP) Systems for Eco-Campus Design Based on Comprehensive Performance Assessment
CN114358601A (en) Method and device for constructing multi-dimensional evaluation index system of multi-energy system
Gopila et al. Random decision forest (RDF) and crystal structure algorithm (CryStAl) for uncertainty consideration of RES & load demands with optimal design of hybrid CCHP systems

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
TA01 Transfer of patent application right
TA01 Transfer of patent application right

Effective date of registration: 20210609

Address after: 200131 4 / F and 5 / F, building 1, No. 251 libing road and 28 Faraday Road, China (Shanghai) pilot Free Trade Zone, Pudong New Area, Shanghai

Applicant after: China Online Shanghai Energy Internet Research Institute Co.,Ltd.

Applicant after: STATE GRID CORPORATION OF CHINA

Applicant after: CHINA ELECTRIC POWER RESEARCH INSTITUTE Co.,Ltd.

Applicant after: STATE GRID CHONGQING ELECTRIC POWER Co.

Applicant after: State Grid Chongqing Electric Power Company Electric Power Research Institute

Applicant after: CHINA AGRICULTURAL University

Address before: 200131 4 / F and 5 / F, building 1, No. 251 libing road and 28 Faraday Road, China (Shanghai) pilot Free Trade Zone, Pudong New Area, Shanghai

Applicant before: China Online Shanghai Energy Internet Research Institute Co.,Ltd.

Applicant before: STATE GRID CORPORATION OF CHINA

Applicant before: CHINA ELECTRIC POWER RESEARCH INSTITUTE Co.,Ltd.

Applicant before: STATE GRID CHONGQING ELECTRIC POWER Co.

Applicant before: CHINA AGRICULTURAL University

SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination