CN115375082A

CN115375082A - Electric heating network cooperative operation decision processing method and device and electronic equipment

Info

Publication number: CN115375082A
Application number: CN202210768449.7A
Authority: CN
Inventors: 梁安琪; 曾爽; 丁屹峰; 李香龙; 杨旭; 马凯; 赵乐; 刘畅; 王钊; 邢其敬; 王喆; 赵伟
Original assignee: State Grid Suzhou Urban Energy Research Institute Co ltd; State Grid Corp of China SGCC; State Grid Beijing Electric Power Co Ltd
Current assignee: State Grid Suzhou Urban Energy Research Institute Co ltd; State Grid Corp of China SGCC; State Grid Beijing Electric Power Co Ltd
Priority date: 2022-07-01
Filing date: 2022-07-01
Publication date: 2022-11-22

Abstract

The invention discloses a method and a device for decision processing of cooperative operation of an electric heating network and electronic equipment. Wherein, the method comprises the following steps: acquiring a plurality of decision schemes corresponding to a target project and a plurality of decision indexes corresponding to the target project, wherein the target project is an operation project for performing energy complementation on a power grid and a heat supply network; determining absolute weight matrixes corresponding to the decision indexes by adopting an analytic hierarchy process; calculating by adopting a Delphi method based on a plurality of decision schemes and a plurality of decision indexes to obtain a primary decision matrix; calculating target dominance degrees corresponding to the decision schemes respectively by adopting an interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix; and determining to obtain a target decision scheme from the plurality of decision schemes according to the target dominance degrees respectively corresponding to the plurality of decision schemes. The invention solves the technical problems of low decision accuracy, low running mode rationality and low energy utilization efficiency in the related technology.

Description

Electric heating network cooperative operation decision processing method and device and electronic equipment

Technical Field

The invention relates to the field of decision evaluation, in particular to a method and a device for processing cooperative operation decision of an electric heating network and electronic equipment.

Background

At present, the cooperative operation of the electric heating network is an important component for constructing a novel electric power system. Due to the fact that the operation decision of the electric heating cooperative network relates to coupling and complementation of two different energy sources of electric energy and heat energy, dynamic differences exist and various uncertain factors are included. In the related technology, decision evaluation processing is often performed by setting a weight threshold and the like, so that the applicability of complex items with many influence indexes such as the cooperative operation of the electric heating network is poor, the decision evaluation accuracy is low, weak links in operation are not easily found, and the cooperative work efficiency of the electric heating network is low.

In view of the above problems, no effective solution has been proposed.

Disclosure of Invention

The embodiment of the invention provides a method and a device for decision processing of cooperative operation of an electric heating network and electronic equipment, and aims to at least solve the technical problems of low decision accuracy, low rationality of operation modes and low energy utilization efficiency in the related technology.

According to an aspect of an embodiment of the present invention, there is provided a method for processing a cooperative operation decision of an electric heating network, including: acquiring a plurality of decision schemes corresponding to a target project and a plurality of decision indexes corresponding to the target project, wherein the target project is an operation project for performing energy complementation on a power grid and a heat supply network; determining absolute weight matrixes corresponding to the decision indexes by adopting an analytic hierarchy process; calculating by adopting a Delphi method based on the decision schemes and the decision indexes to obtain a primary decision matrix; calculating target dominance degrees corresponding to the decision schemes respectively by adopting an interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix; and determining a target decision scheme from the decision schemes according to the target dominance degrees corresponding to the decision schemes respectively.

Optionally, the determining, by using an analytic hierarchy process, an absolute weight matrix corresponding to the plurality of decision indicators includes: determining initial weight matrixes corresponding to the decision indexes by adopting an analytic hierarchy process; judging whether the initial weight matrix meets a preset consistency test condition or not; and if the initial weight matrix meets the consistency check condition, taking the initial weight matrix as the absolute weight matrix.

Optionally, the calculating, according to the absolute weight matrix and the primary decision matrix, target dominance degrees corresponding to the multiple decision schemes by using an interactive multi-criterion decision method includes: calculating the single index dominance of any one decision scheme in the plurality of decision schemes relative to any other decision scheme under the plurality of decision indexes by adopting the interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix, wherein the other decision schemes are used for representing decision schemes other than the any decision scheme in the plurality of decision schemes; accumulating and calculating the single index dominance degree corresponding to each of the decision indexes to obtain a first comprehensive index dominance degree of any one decision scheme relative to any one other decision scheme; and performing accumulation calculation on the first comprehensive index dominance degrees respectively corresponding to the other decision schemes to obtain the target dominance degree of any one decision scheme relative to the other decision schemes.

Optionally, the calculating, by using the interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix, a single index dominance of any one decision scheme of the multiple decision schemes with respect to any other decision scheme under the multiple decision indexes includes: carrying out standardization processing on the primary decision matrix to obtain a target decision matrix; converting the absolute weight matrix to obtain a relative weight matrix; and calculating the single index dominance of any one decision scheme in the decision schemes relative to any other decision scheme under the multiple decision indexes by adopting the interactive multi-criterion decision method according to the target decision matrix and the relative weight matrix.

Optionally, the determining, according to the target dominance degrees respectively corresponding to the plurality of decision schemes, a target decision scheme from the plurality of decision schemes includes: obtaining ranking values corresponding to the decision schemes respectively by adopting a standardized ranking method according to the target dominance degrees corresponding to the decision schemes respectively; based on a preset sorting rule, sorting the sorting values respectively corresponding to the decision schemes to obtain a sorting result; and determining the target decision scheme from the plurality of decision schemes according to the sequencing result.

Optionally, the decision index includes at least: system outage rate, system outage duration, pipe network heat loss rate, infrastructure failure rate, full life cycle cost, equipment utilization, equipment operating cost savings, and carbon emission reduction.

According to another aspect of the embodiments of the present invention, there is provided a decision processing device for cooperative operation of an electric heating network, including: the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a plurality of decision schemes corresponding to a target project and a plurality of decision indexes corresponding to the target project, and the target project is an operation project for performing energy complementation on a power grid and a heat supply network; the first calculation module is used for determining absolute weight matrixes corresponding to the decision indexes by adopting an analytic hierarchy process; the second calculation module is used for calculating by adopting a Delphi method based on the decision schemes and the decision indexes to obtain a primary decision matrix; the third calculation module is used for calculating target dominance degrees corresponding to the decision schemes respectively by adopting an interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix; and the first determining module is used for determining and obtaining a target decision scheme from the plurality of decision schemes according to the target dominance degree.

Optionally, the third computing module comprises: a fourth calculating module, configured to calculate, according to the absolute weight matrix and the primary decision matrix, a single index dominance of any one decision scheme in the multiple decision schemes relative to any other decision scheme under the multiple decision indexes by using the interactive multi-criterion decision method, where the other decision schemes are used for representing decision schemes other than the any decision scheme in the multiple decision schemes; a fifth calculating module, configured to perform cumulative calculation on the single index dominance degrees corresponding to the multiple decision indexes, to obtain a first comprehensive index dominance degree of the arbitrary decision scheme relative to the arbitrary other decision scheme; a sixth calculating module, configured to perform cumulative calculation on the first comprehensive index superiority degrees corresponding to the other decision schemes, to obtain a second comprehensive index superiority degree of the any decision scheme relative to the other decision schemes; and the second determination module is used for taking the dominance degree of the second comprehensive index as the target dominance degree.

According to another aspect of the embodiment of the invention, a nonvolatile storage medium is provided, and the nonvolatile storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing any one of the electric heating network cooperative operation decision processing methods.

According to another aspect of the embodiments of the present invention, there is provided an electronic device including: one or more processors and memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement any of the electric heating network co-operation decision-making processing methods.

In the embodiment of the invention, a plurality of decision schemes corresponding to a target project and a plurality of decision indexes corresponding to the target project are obtained, wherein the target project is an operation project for performing energy complementation on a power grid and a heat supply network; determining absolute weight matrixes corresponding to the decision indexes by adopting an analytic hierarchy process; calculating by adopting a Delphi method based on the decision schemes and the decision indexes to obtain a primary decision matrix; calculating target dominance degrees corresponding to the decision schemes respectively by adopting an interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix; and determining a target decision scheme from the decision schemes according to the target dominance degrees corresponding to the decision schemes respectively. The method achieves the purposes of improving the rationality of operation decision and improving the cooperative operation mode of the electric heating network based on various algorithms, achieves the technical effects of improving the decision accuracy and further improving the rationality of cooperative operation of the electric heating network and improving the energy utilization efficiency, and further solves the technical problems of low decision accuracy, low rationality of the operation mode and low energy utilization efficiency in the related technology.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention and do not constitute a limitation of the invention. In the drawings:

fig. 1 is a flowchart of a decision processing method for cooperative operation of an electric heating network according to an embodiment of the present invention;

FIG. 2 is a schematic algorithm diagram of a decision processing method for cooperative operation of an electric heating network according to an embodiment of the invention;

FIG. 3 is a schematic diagram of a decision index of a method for processing a cooperative operation decision of a heating grid according to an embodiment of the present invention;

FIG. 4 is a schematic flow chart of a method for processing cooperative operation decision of a heating grid according to an embodiment of the present invention;

fig. 5 is a schematic diagram of a decision processing device for cooperative operation of an electric heating network according to an embodiment of the invention.

Detailed Description

In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, shall fall within the protection scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in other sequences than those illustrated or described herein. Moreover, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

For convenience of description, some terms or expressions referred to in the embodiments of the present application are explained below:

analytic Hierarchy Process (AHP), an algorithm in the field of operations and research, refers to a decision-making method for performing qualitative and quantitative analysis on the basis of decomposing elements related to decision into levels of targets, criteria, schemes, and the like.

The Delphi method (Delphi) is a feedback anonymous function inquiry method, and the evaluation experts score the index-scheme in an anonymous mode, check whether the scores of all the evaluation experts are consistent or not according to the returned scoring result, and if not, the experts score again; otherwise, an index-scheme decision matrix is formed.

An interactive multi-criterion decision method (Todim) is a preferred method, based on a foreground theoretical cost function, according to a relative dominance function which establishes a relative ratio of a certain scheme to other schemes, and according to the dominance, carrying out scheme selection, thereby determining an optimal scheme.

In accordance with an embodiment of the present invention, there is provided a method embodiment of a method for decision processing of electric heating network cooperative operation, it is noted that the steps illustrated in the flowchart of the drawings may be executed in a computer system such as a set of computer executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be executed in an order different than that illustrated or described herein.

Fig. 1 is a decision processing method for cooperative operation of an electric heating network according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:

step S102, obtaining a plurality of decision schemes corresponding to a target project and a plurality of decision indexes corresponding to the target project, wherein the target project is an operation project for performing energy complementation on a power grid and a heat supply network;

step S104, determining absolute weight matrixes corresponding to the decision indexes by adopting an analytic hierarchy process;

step S106, based on the decision schemes and the decision indexes, calculating by adopting a Delphi method to obtain a primary decision matrix;

step S108, calculating target dominance degrees corresponding to the decision schemes respectively by adopting an interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix;

step S110, determining a target decision scheme from the plurality of decision schemes according to the target dominance corresponding to each of the plurality of decision schemes.

Through the steps, the purposes of improving the rationality of the operation decision and improving the cooperative operation mode of the electric heating network based on various algorithms can be achieved, the technical effects of improving the decision accuracy and further improving the cooperative operation rationality of the electric heating network and improving the energy utilization efficiency are achieved, and the technical problems that the decision accuracy is low, the rationality of the operation mode is low and the energy utilization efficiency is low in the related technology are solved.

In the electric heating network collaborative operation decision processing method provided by the embodiment of the invention, the target project is an operation project for energy complementation of the electric network and the heat supply network. Firstly, a plurality of decision schemes corresponding to a target project are obtained, and an analytic hierarchy process is adopted to obtain absolute weight matrixes corresponding to a plurality of decision indexes. And secondly, calculating by adopting a Delphi method to obtain a primary decision matrix based on a plurality of decision schemes and the plurality of decision indexes. And then, calculating by adopting an interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix to obtain the target dominance. Finally, a target decision scheme is selected from the plurality of decision schemes based on the target dominance. In order to objectively handle different influences of different decision schemes on a result when electric heating collaborative optimization is carried out, the method is favorable for obtaining a high-rationality electric heating network collaborative operation decision.

The weight matrix table means a mathematical expression method in which a plurality of weight values corresponding to the decision index are stored. Similarly, the decision matrix table means that a plurality of mathematical expression modes of the decision result corresponding to the decision scheme are stored. The mathematical expression may be, for example, a matrix, a set, or the like.

In an optional embodiment, the determining, by using an analytic hierarchy process, the absolute weight matrix corresponding to the plurality of decision indicators includes: determining initial weight matrixes corresponding to the decision indexes by adopting an analytic hierarchy process; judging whether the initial weight matrix meets a preset consistency check condition or not; and if the initial weight matrix meets the consistency check condition, taking the initial weight matrix as the absolute weight matrix.

It can be understood that an analytic hierarchy process is adopted to determine the initial weight matrix corresponding to the plurality of decision indexes, whether the initial weight matrix meets a preset consistency test condition or not is judged, and if the judgment result is that the initial weight matrix meets the preset consistency test condition, the initial weight matrix is used as an absolute weight matrix.

Optionally, the initial weight matrix may be various, for example: the importance of a plurality of decision indexes to the target item is compared pairwise, and the obtained result is stored in an initial weight matrix.

Optionally, if the initial weight matrix does not satisfy the consistency check condition, the initial weight matrix is reconstructed.

It should be noted that, through the consistency check, the following situations are avoided, for example: the obvious illogical situation occurs that the decision index A is more important than the decision index B, the decision index B is more important than the decision index C, and the decision index C is more important than the decision index A.

In an optional embodiment, the calculating, according to the absolute weight matrix and the primary decision matrix, target dominance degrees corresponding to the decision schemes by using an interactive multi-criteria decision method includes: calculating a single index dominance of any one decision scheme of the plurality of decision schemes relative to any other decision scheme under the plurality of decision indexes by adopting the interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix, wherein the other decision scheme is used for representing the decision scheme except the any decision scheme of the plurality of decision schemes; accumulating and calculating the dominance degrees of the single indexes respectively corresponding to the plurality of decision indexes to obtain a first comprehensive index dominance degree of any one decision scheme relative to any one other decision scheme; and accumulating and calculating the dominance degrees of the first comprehensive indexes respectively corresponding to the other decision schemes to obtain the target dominance degree of any one decision scheme relative to the other decision schemes.

It can be understood that according to the absolute weight matrix and the primary decision matrix, an interactive multi-criterion decision method is adopted, and firstly, under the condition of calculating a plurality of decision indexes, the single index dominance of any one decision scheme in the plurality of decision schemes relative to any other decision scheme is calculated. The single index dominance degree is the dominance degree between the schemes corresponding to one decision index. And secondly, accumulating and calculating the dominance of the single indexes to obtain a first comprehensive index dominance of any decision scheme relative to any other decision scheme (except the decision scheme). The first comprehensive index dominance degree is the dominance degree among all the schemes corresponding to all the decision indexes. And then, accumulating and calculating the dominance degrees of the first comprehensive indexes respectively corresponding to other decision schemes to obtain the target dominance degree of any one decision scheme relative to other decision schemes. The target dominance degree is the dominance degree of any decision scheme corresponding to all decision indexes to all other decision schemes (except for the decision indexes).

It should be noted that any one of the other decision schemes described above is meant to be any one of the other decision schemes except the decision scheme in the current calculation. In other words, compared with any other decision scheme, the obtained dominance of the first comprehensive index is a one-to-one dominance. The above other decision schemes are all other decision schemes except the decision scheme in the current calculation. In other words, compared with other decision schemes, the obtained dominance of the target index is represented by one-to-many dominance.

In an optional embodiment, the calculating, by using the interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix, a single-index dominance of any one decision scheme of the multiple decision schemes with respect to any other decision scheme includes: carrying out standardization processing on the primary decision matrix to obtain a target decision matrix; carrying out conversion processing on the absolute weight matrix to obtain a relative weight matrix; and calculating the single index dominance of any one decision scheme in the decision schemes relative to any other decision scheme under the multiple decision indexes by adopting the interactive multi-criterion decision method according to the target decision matrix and the relative weight matrix.

It will be appreciated that the primary decision matrix and the absolute weight matrix are processed in order to facilitate computation using an interactive multi-criteria algorithm. Firstly, the primary decision matrix is standardized to obtain a target decision matrix. And secondly, converting the absolute weight matrix to obtain a relative weight matrix. And then, calculating the dominance degree of the single index by adopting an interactive multi-criterion decision method based on the target decision matrix and the relative weight matrix.

Optionally, the absolute weight matrix may be converted to obtain a relative weight matrix, which may be a plurality of types, for example: calculating the relative index weight of the operation decision index of the electric heating cooperative network as W, wherein the calculation formula is as follows:

wherein, W _jr Relative weight, W, representing the jth decision index _r Represents the maximum weight in the decision scheme of the target item, and Wj represents the absolute weight of the jth decision index.

Optionally, the preliminary decision matrix is normalized to obtain a target decision matrixThe normalization process may be various, for example: and the primary decision matrix is subjected to standardization processing, so that unnecessary influence of different decision indexes on the dominance of a decision scheme is avoided. The primary decision matrix is subjected to the standard processing expression as follows:

wherein D is _ij Expressed as an objective decision matrix, d _ij Expressed as the primary decision matrix value, max (d), of the i-th decision scheme under the j-th decision index _ij ) Expressed as the maximum value of the primary decision matrix in all the scenarios under the jth decision index, min (d) _ij ) Expressed as the minimum value of the primary decision matrix in all decision schemes under the jth decision index.

In an optional embodiment, the determining, according to the target dominance degrees respectively corresponding to the plurality of decision schemes, a target decision scheme from the plurality of decision schemes includes: obtaining ranking values corresponding to the decision schemes respectively by adopting a standardized ranking method according to the target dominance degrees corresponding to the decision schemes respectively; based on a preset sorting rule, sorting the sorting values respectively corresponding to the plurality of decision schemes to obtain a sorting result; and determining the target decision scheme from the decision schemes according to the sequencing result.

It can be understood that, according to the target dominance, a standardized sorting method is adopted to obtain sorting values corresponding to the multiple decision schemes, and a sorting result is obtained according to the sorting values based on a preset sorting rule. And determining a target decision scheme in the plurality of decision schemes according to the sorting result.

Optionally, the above normalized sorting method may be various, for example: firstly, the dominance degree of the target is normalized, and the normalized degree is expressed as epsilon _i ，ε _i The mathematical expression of (a) is:

wherein epsilon _i Represents the composite score, p, normalized by the i-th decision scheme _i Indicating the target dominance of the ith decision scheme over the other schemes. Epsilon _i The larger the value ρ _i The better the scheme of (c). Second, for epsilon _i Sorting the values, setting the preset sorting rule to be in a sorting range of 1 to 3, wherein '1' represents the best, and '3' represents the worst, if epsilon _i The larger the selected goal decision scheme is.

In an optional embodiment, the decision index at least includes: system outage rate, system outage duration, pipe network heat loss rate, infrastructure failure rate, full life cycle cost, equipment utilization, equipment operation cost savings, and carbon emission reduction.

It can be understood that, in order to fully evaluate the operation decision of the electric heating network, a plurality of decision indexes are selected, and the decision indexes at least comprise: system outage rate, system outage duration, pipe network heat loss rate, infrastructure failure rate, full life cycle cost, equipment utilization, equipment operation cost savings, and carbon emission reduction.

Optionally, the system outage rate may be various, for example: the system outage rate refers to the ratio of the average time of the system for stopping supplying energy to the time of supplying energy in the required time, and the specific formula is as follows:

wherein, delta _i Is the system outage rate, x _i Average off-time, N, for energy i _i The supply time of the energy source i.

Optionally, the system outage duration may be various, for example: the system outage duration refers to the average outage time borne by each energy source in the system within the demand time, and the specific formula is as follows:

wherein x is _i Average off-time, M, for energy i _i Is the number of times of power supply interruption, t, of energy source i _i,j For the jth off-time of energy i, h _i,j The number of households influenced by the jth outage time of the energy i is shown, and F is the total number of the users.

Alternatively, the system de-energization energy loss rate may be various, for example: the system energy loss rate when the energy is stopped refers to the average loss rate of each energy source in the required time, and the specific formula is as follows:

wherein alpha is _i Is the average loss rate of energy i, A _i,j The j-th outage loss amount, Q, of energy i _i The total energy supply in the statistical time is obtained.

Optionally, the heat loss rate of the pipe network may be various, for example: the heat loss rate of the pipe network refers to the heat loss rate when heat is transmitted to users from the beginning, and the specific formula is as follows:

mu is the heat loss rate of the pipe network, Y is the length of the directly buried pipeline of the ground source heat pump system, R is the heat loss per unit length of the pipe, and D _r Actual heating time, Z, for ground source heat pump system _r The heat supply is provided for the ground source heat pump system.

Alternatively, the above-mentioned infrastructure failure rate may be various, for example: the infrastructure fault rate represents an average value of the ratio of the fault duration of the equipment to the total use duration of the equipment in the normal operation of the system, and the specific formula is as follows:

wherein, F _N Mean failure rate of equipment throughout the year, h _i Time of failure, S, for devices of the ith class _i And N is the total number of the devices.

Optionally, the full life cycle cost may be various, for example: the full life cycle cost refers to all expenses of the operation decision system in the full life cycle from initial construction to scrapping, and comprises investment expense, operation and maintenance expense, energy purchasing expense and the like, and the specific formula is as follows:

wherein, C _total,cap For investment expenditure, I _nvtech To purchase various equipment expenses, C _aptech The capacity is optimized for each device. C _op For operating maintenance costs, C _fuel For energy purchase costs, d is the various equipment in the system, C _re,d For the fixed cost of the equipment, I _va,d Maintenance costs for the equipment unit; the subscript t is the value corresponding to time t, P _d,t Operating power for the apparatus time by time, c _e,t And c _g Respectively the electricity and gas purchasing unit price, P _e,t To purchase electric power, P _g The gas purchasing power refers to the energy released by complete combustion of gas purchasing quantity per unit time.

Optionally, the device utilization rate may be various, for example: the equipment utilization rate is the ratio of the actual working time and the actual provided energy of the system access equipment to the planned working time and the energy provided amount, and the specific formula is as follows:

wherein ε is the equipment utilization, J _i,m For m actual operating time, T, of the apparatus providing the energy i _i,m Planning the working hours, G, for a device m providing an energy source i _i,m The amount of energy i provided to the device m.

Alternatively, the cost savings in operating the above-described apparatus may be many, for example: the equipment operation cost saving refers to the sum of the electric charge saved by each equipment and the heat supply charge saved by the equipment accessed to the system in the system operation time, and the specific formula is as follows: τ = ∑ P _m +H _m Wherein τ saves costs for operating the plant, P _m Electric power charge saved for the apparatus m, H _m The heat supply cost for the equipment m is saved.

Alternatively, the carbon reduction amount may be various, for example: the total electric quantity saved by the system in the electric heating cooperative network operation decision evaluation system is converted into carbon emission reduction quantity according to a carbon dioxide emission reduction coefficient, and the specific formula is as follows:

the carbon emission reduction amount is the carbon emission reduction amount, the total electric quantity saved by the target system in the statistical time is the carbon dioxide emission reduction coefficient.

Based on the foregoing examples and optional examples, the present invention provides an optional implementation manner, fig. 2 is an algorithm schematic diagram of a decision processing method for cooperative operation of a heating network provided according to the implementation manner of the present invention, fig. 3 is a decision index schematic diagram of the decision processing method for cooperative operation of a heating network provided according to the implementation manner of the present invention, and fig. 4 is a flow schematic diagram of the decision processing method for cooperative operation of a heating network provided according to the implementation manner of the present invention. As shown in fig. 2, the algorithm specifically comprises the following steps:

step S210, analyzing decision indexes of the operation influence decision of the electric heating cooperative network, obtaining a plurality of decision schemes corresponding to the target project and a plurality of decision indexes corresponding to the target project, and obtaining an expression mode of the operation decision indexes of the electric heating cooperative network.

Optionally, the decision index at least includes: system outage rate, system outage duration, pipe network heat loss rate, infrastructure failure rate, full life cycle cost, equipment utilization, equipment operating cost savings, and carbon emission reduction.

Step S220, determining absolute weight matrixes corresponding to a plurality of decision indexes by adopting an analytic hierarchy process, and comprising the following substeps:

step S221, determining initial weight matrixes corresponding to a plurality of decision indexes by adopting an analytic hierarchy process;

step S222, judging whether the initial weight matrix meets a preset consistency check condition; and if the initial weight matrix meets the consistency check condition, taking the initial weight matrix as an absolute weight matrix.

And step S230, calculating by adopting a Delphi method based on a plurality of decision schemes and a plurality of decision indexes to obtain a primary decision matrix.

Step S240, calculating target dominance degrees corresponding to the multiple decision schemes by using an interactive multi-criteria decision method according to the absolute weight matrix and the primary decision matrix, including the following substeps:

step S241, carrying out standardization processing on the primary decision matrix to obtain a target decision matrix;

step S242, converting the absolute weight matrix to obtain a relative weight matrix;

step S243, calculating the single index dominance of any one decision scheme in a plurality of decision schemes relative to any other decision scheme under a plurality of decision indexes by adopting an interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix, wherein the other decision schemes are used for representing the decision schemes except any one decision scheme in the plurality of decision schemes;

step S244, performing cumulative calculation on the single index dominance degrees corresponding to the multiple decision indexes to obtain a first comprehensive index dominance degree;

step S245, the dominance degrees of the first comprehensive indexes respectively corresponding to the other decision schemes are accumulated and calculated to obtain the target dominance degree of any one decision scheme relative to the other decision schemes.

Step S250, obtaining ranking values corresponding to the decision schemes respectively by adopting a standardized ranking method according to the target dominance degrees corresponding to the decision schemes respectively; based on a preset sorting rule, sorting the sorting values respectively corresponding to the multiple decision schemes to obtain a sorting result; and determining a target decision scheme from the multiple decision schemes according to the sequencing result.

For the sake of understanding, a specific example is shown in fig. 4, which includes the following steps:

step S410, analyzing decision indexes of the operation influence decision of the electric heating cooperative network, obtaining a plurality of decision schemes corresponding to the target project and a plurality of decision indexes corresponding to the target project, and obtaining an expression mode of the operation decision indexes of the electric heating cooperative network. As shown in fig. 3, 9 different decision indicators, such as system outage rate, system outage duration, pipe network heat loss rate, infrastructure failure rate, full life cycle cost, equipment utilization rate, equipment operation cost saving, carbon emission reduction and the like, are selected for the target project, and an expression mode corresponding to the decision indicators is determined.

Step S420, determining absolute weight matrixes corresponding to the decision indexes by adopting an analytic hierarchy process. Firstly, according to the decision indexes, establishing an initial weight matrix of the target item and a plurality of decision indexes, and establishing the initial weight matrixThe importance of each decision index to the target project is compared pairwise, such as: establishing an initial weight matrix Z, Z = { b = } _ij N, where i and j represent the labels of the decision indexes and n represents the number of the decision indexes, the method comprises the following substeps:

in step S421, the weight and the feature value are calculated. And respectively carrying out row-column normalization and row normalization calculation on the established initial weight matrix to obtain the weight value Wn of each decision index. And calculating characteristic values according to the obtained Wn, wherein the calculation formula is expressed as Z x Wn = lambda x Wn, lambda is expressed as the characteristic value, lambda max is the maximum characteristic value, lambda max = max (lambda) is the maximum characteristic root, and Wn is the weight for judging the initial weight matrix Z.

Step S422, carrying out level consistency check, wherein in order to avoid the situation that the decision index A is more important than the decision index B, the decision index B is more important than the decision index C, and the decision index C is more important than the decision index A, the consistency check is required, and the check result directly influences whether objective sequencing among the decision indexes is truly reflected or not. The preset consistency check condition is c.r. = c.i/r.i <0.1, where c.i is the consistency of the initial weight matrix expressed as c.i = (λ max-n)/(n-1), r.i is expressed as a random consistency index, and c.r is expressed as a consistency check result. If the c.r. = c.i/r.i <0.1, the consistency check of the initial weight matrix Z is passed, step S424 is executed, otherwise, consistency correction is performed, and step S423 is executed.

In step S423, consistency correction is performed, the initial weight matrix is reconstructed, and step S420 is performed.

In step S424, an absolute weight matrix is obtained.

And step S430, calculating by adopting a Delphi method based on a plurality of decision schemes and a plurality of decision indexes to obtain a primary decision matrix. And evaluating and scoring by using a Delphi method according to the operation decision scheme of the electric heating cooperative network and the corresponding indexes. Assume the primary decision matrix is: t = [ d ] _ij ]mn, m is expressed as the total number of decision schemes corresponding to the operation target items of the electric heating cooperative network, n represents the total number of decision indexes of the operation target items of the electric heating cooperative network, i represents the ith decision scheme, j represents the jth operation decision index,d _ij and (4) representing the decision matrix value of the ith scheme under the jth index. T is denoted as primary decision matrix.

Step S440, calculating by using an interactive multi-criteria decision method according to the absolute weight matrix and the primary decision matrix.

Step S441, the primary decision matrix is normalized to obtain a target decision matrix. In order to avoid the influence of different indexes on the dominance of the scheme. The normalization formula is expressed as:

wherein, d _ij The target decision matrix value, max (d), representing the i-th decision scheme under the j-th decision index _ij ) Represents the maximum value of the target decision matrix in all decision schemes under the jth decision index, min (d) _ij ) And representing the minimum value of the target decision matrix in all decision schemes under the jth decision index. D _ij Represented as an objective decision matrix.

Step S442, calculating a relative weight value, and converting the absolute weight matrix to obtain a relative weight matrix

Calculating the relative index weight of the decision index as W, wherein the calculation formula is as follows:

wherein, W _jr Relative weight, W, representing the jth decision index _r Maximum weight, W, in a decision scheme representing a target item _j j denotes the absolute weight of the jth decision index.

Step S443, calculating the dominance of local single indexes of different schemes under each decision index according to the decision index j, and deciding the scheme A _i With respect to decision scheme A _k Single index dominance degree phi _j (A _i ,A _k ) The calculation formula is expressed as:

where θ is the attenuation coefficient representing the loss, which can be decided according to the decisionThe preference of the user adjusts the value of the loss so that the influence of the loss is relatively large when θ < 1, relatively small when θ > 1, and a common value when θ = 1.

Step S443, calculating dominance degrees among schemes corresponding to all the decision indexes to obtain a first comprehensive index dominance degree. Decision scheme A _i With respect to decision scheme A _k First comprehensive index dominance degree phi (A) _i ，A _k ) The calculation formula is expressed as:

wherein, phi (A) _i ，A _k ) Representing the comprehensive comparison of the decision scheme A according to all decision indexes _i With respect to decision scheme A _k The degree of superiority of (c).

Step S444, calculating the target dominance of the ith decision scheme to all other m-1 decision schemes in the target project. Decision scheme A _i Compared with the sum of the dominance of other decision schemes, the calculation formula is expressed as:

where ρ is _i Representing the target dominance of the ith decision scheme over the other decision schemes, A _i Denotes the ith decision scheme, A _k Representing the kth decision scheme.

Step S450, obtaining ranking values corresponding to the decision schemes respectively by adopting a standardized ranking method according to the target dominance degrees corresponding to the decision schemes respectively; based on a preset sorting rule, sorting the sorting values respectively corresponding to the multiple decision schemes to obtain a sorting result; and determining a target decision scheme from the multiple decision schemes according to the sequencing result. Standardizing the dominance degree of the target, wherein the standardized processing formula is epsilon _i And is based on epsilon _i The values are ordered for the decision scheme (assuming ordering ranges from 1 to 3, where "1" means best and "3" means worst) if ε _i The larger the selected goal decision scheme is. Epsilon _i Is expressed as:

wherein epsilon _i Represents the composite score, p, normalized by the i-th decision scheme _i Indicating the normalized target dominance of the ith decision scheme over other decision schemes. Epsilon _i The larger the value ρ _i The better the goal decision scheme.

At least one of the following effects can be achieved by the above alternative embodiment: 1. the decision processing is carried out on the electric heating cooperative network, so that unreasonable decisions can be found in time, weak links in operation can be found, the electric heating cooperative network is reconstructed and constructed, and reasonable guidance suggestions are provided for optimizing the operation mode. 2. When the electric heating cooperative optimization is carried out on the power grid and the heat supply network, different operating decision schemes have different influences on operating results, the influence factors in the operation process of the electric heating cooperative network are multiple, the project complexity is high, an objective and reasonable decision processing method is established, objective and reasonable operation decisions can be obtained, accordingly, complementation of two heterogeneous energy sources of the power grid and the heat supply network is achieved, and the energy utilization efficiency is improved.

It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.

In this embodiment, a decision processing device for cooperative operation of an electric heating network is further provided, and the device is used for implementing the above embodiments and preferred embodiments, which have already been described and will not be described again. As used hereinafter, the terms "module" and "apparatus" may refer to a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware or a combination of software and hardware is also possible and contemplated.

According to an embodiment of the present invention, an embodiment of an apparatus for implementing a method for processing a cooperative operation decision of a heating grid is further provided, and fig. 5 is a schematic diagram of a device for processing a cooperative operation decision of a heating grid according to an embodiment of the present invention, where as shown in the figure, the device for processing a cooperative operation decision of a heating grid includes a first obtaining module 502, a first calculating module 504, a second calculating module 506, a third calculating module 508, and a first determining module 510, which will be described below.

A first obtaining module 502, configured to obtain multiple decision schemes corresponding to a target project and multiple decision indicators corresponding to the target project, where the target project is an operation project in which energy complementation is performed on a power grid and a heat supply network;

a first calculating module 504, connected to the first obtaining module 502, configured to determine, by using an analytic hierarchy process, absolute weight matrices corresponding to the multiple decision indexes;

a second calculating module 506, connected to the first calculating module 504, configured to calculate by using a delphi method based on the multiple decision schemes and the multiple decision indexes to obtain a primary decision matrix;

a third calculating module 508, connected to the second calculating module 506, for calculating target dominance degrees corresponding to the decision schemes respectively by using an interactive multi-criteria decision method according to the absolute weight matrix and the primary decision matrix;

a first determining module 510, connected to the third calculating module 508, configured to determine a target decision scheme from the multiple decision schemes according to the target dominance.

In the device for processing the collaborative operation decision of the electric heating network, which is provided by the embodiment of the invention, a first acquisition module is arranged and is used for acquiring a plurality of decision schemes corresponding to a target project and a plurality of decision indexes corresponding to the target project, wherein the target project is an operation project for performing energy complementation on a power grid and a heat supply network; the first calculation module is used for determining absolute weight matrixes corresponding to the decision indexes by adopting an analytic hierarchy process; the second calculation module is used for calculating by adopting a Delphi method based on the decision schemes and the decision indexes to obtain a primary decision matrix; a third calculating module, configured to calculate, according to the absolute weight matrix and the primary decision matrix, target dominance degrees corresponding to the multiple decision schemes by using an interactive multi-criterion decision method; and the first determining module is used for determining and obtaining a target decision scheme from the plurality of decision schemes according to the target dominance degree. The method achieves the purposes of improving the rationality of operation decision and improving the cooperative operation mode of the electric heating network based on various algorithms, achieves the technical effects of improving the decision accuracy and further improving the rationality of cooperative operation of the electric heating network and improving the energy utilization efficiency, and further solves the technical problems of low decision accuracy, low rationality of the operation mode and low energy utilization efficiency in the related technology.

As an optional embodiment, the electric heating grid cooperative operation decision processing apparatus provided in the embodiment of the present invention further includes:

a fourth calculating module 512, configured to calculate, according to the absolute weight matrix and the primary decision matrix, a single index dominance of any one of the decision schemes relative to any other decision scheme under the multiple decision indexes by using the interactive multi-criterion decision method, where the other decision schemes are used for representing decision schemes other than the any decision scheme;

a fifth calculating module 514, connected to the fourth calculating module 512, configured to perform cumulative calculation on the single index dominance degrees corresponding to the multiple decision indexes, respectively, to obtain a first composite index dominance degree of any one decision scheme relative to any one of the other decision schemes;

a sixth calculating module 516, connected to the fifth calculating module 514, configured to perform cumulative calculation on the dominance of the first composite index corresponding to each of the other decision schemes, so as to obtain a second composite index dominance of the any decision scheme relative to the other decision schemes;

and a second determining module 518, connected to the sixth calculating module 516, for using the second composite index dominance degree as the target dominance degree.

It should be noted that the above modules may be implemented by software or hardware, for example, for the latter, the following may be implemented: the modules can be located in the same processor; alternatively, the modules may be located in different processors in any combination.

It should be noted here that the first obtaining module 502, the first calculating module 504, the second calculating module 506, the third calculating module 508, and the first determining module 510 correspond to steps S102 to S110 in the embodiment, and the modules are the same as the corresponding steps in the implementation example and the application scenario, but are not limited to the disclosure in the embodiment. It should be noted that the modules described above may be implemented in a computer terminal as part of an apparatus.

It should be noted that, for optional or preferred embodiments of the present embodiment, reference may be made to the relevant description in the embodiment, and details are not described herein again.

The virtual learning scenario construction apparatus based on the power system may further include a processor and a memory, where the first obtaining module 502, the first calculating module 504, the second calculating module 506, the third calculating module 508, the first determining module 510, and the like are all stored in the memory as program units, and the processor executes the program units stored in the memory to implement corresponding functions.

The processor comprises a kernel, and the kernel calls the corresponding program unit from the memory. One or more cores may be provided. The memory may include volatile memory in a computer readable medium, random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM), including at least one memory chip.

The embodiment of the invention provides a nonvolatile storage medium, wherein a program is stored on the nonvolatile storage medium, and when the program is executed by a processor, the program realizes a decision processing method for cooperative operation of a heating network.

The embodiment of the invention provides electronic equipment, which comprises a processor, a memory and a program which is stored on the memory and can run on the processor, wherein the processor executes the program and realizes the following steps: acquiring a plurality of decision schemes corresponding to a target project and a plurality of decision indexes corresponding to the target project, wherein the target project is an operation project for performing energy complementation on a power grid and a heat supply network; determining absolute weight matrixes corresponding to the decision indexes by adopting an analytic hierarchy process; calculating by adopting a Delphi method based on the decision schemes and the decision indexes to obtain a primary decision matrix; calculating target dominance degrees corresponding to the decision schemes respectively by adopting an interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix; and determining a target decision scheme from the decision schemes according to the target dominance degrees corresponding to the decision schemes respectively. The device herein may be a server, a PC, etc.

The invention also provides a computer program product adapted to perform a program for initializing the following method steps when executed on a data processing device: acquiring a plurality of decision schemes corresponding to a target project and a plurality of decision indexes corresponding to the target project, wherein the target project is an operation project for performing energy complementation on a power grid and a heat supply network; determining absolute weight matrixes corresponding to the decision indexes by adopting an analytic hierarchy process; calculating by adopting a Delphi method based on the decision schemes and the decision indexes to obtain a primary decision matrix; calculating target dominance degrees corresponding to the decision schemes respectively by adopting an interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix; and determining a target decision scheme from the decision schemes according to the target dominance degrees corresponding to the decision schemes respectively.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention 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 present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.

The above are merely examples of the present invention, and are not intended to limit the present invention. Various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A decision processing method for cooperative operation of an electric heating network is characterized by comprising the following steps:

acquiring a plurality of decision schemes corresponding to a target project and a plurality of decision indexes corresponding to the target project, wherein the target project is an operation project for performing energy complementation on a power grid and a heat supply network;

determining absolute weight matrixes corresponding to the decision indexes by adopting an analytic hierarchy process;

calculating by adopting a Delphi method based on the decision schemes and the decision indexes to obtain a primary decision matrix;

calculating target dominance degrees corresponding to the decision schemes respectively by adopting an interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix;

and determining a target decision scheme from the decision schemes according to the target dominance degrees corresponding to the decision schemes respectively.

2. The method of claim 1, wherein determining the absolute weight matrix corresponding to the plurality of decision metrics by using an analytic hierarchy process comprises:

determining initial weight matrixes corresponding to the decision indexes by adopting an analytic hierarchy process;

judging whether the initial weight matrix meets a preset consistency check condition or not;

and if the initial weight matrix meets the consistency check condition, taking the initial weight matrix as the absolute weight matrix.

3. The method according to claim 1, wherein calculating the respective target dominance degrees of the plurality of decision schemes by using an interactive multi-criteria decision method according to the absolute weight matrix and the primary decision matrix comprises:

calculating the single index dominance of any one decision scheme in the plurality of decision schemes relative to any other decision scheme under the plurality of decision indexes by adopting the interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix, wherein the other decision schemes are used for representing decision schemes other than the any decision scheme in the plurality of decision schemes;

accumulating and calculating the dominance of the single index corresponding to the decision indexes respectively to obtain a first comprehensive index dominance;

and performing accumulation calculation on the first comprehensive index dominance degrees respectively corresponding to the other decision schemes to obtain the target dominance degree of any one decision scheme relative to the other decision schemes.

4. The method according to claim 3, wherein said calculating the single index dominance of any one decision scenario in the plurality of decision scenarios relative to any other decision scenario under the plurality of decision metrics using the interactive multi-criteria decision making method based on the absolute weight matrix and a primary decision matrix comprises:

carrying out standardization processing on the primary decision matrix to obtain a target decision matrix;

converting the absolute weight matrix to obtain a relative weight matrix;

and calculating the single index dominance of any one decision scheme in the decision schemes relative to any other decision scheme under the multiple decision indexes by adopting the interactive multi-criterion decision method according to the target decision matrix and the relative weight matrix.

5. The method according to claim 1, wherein the determining a target decision scheme from the plurality of decision schemes according to the target dominance degrees corresponding to the plurality of decision schemes respectively comprises:

obtaining ranking values corresponding to the decision schemes respectively by adopting a standardized ranking method according to the target dominance degrees corresponding to the decision schemes respectively;

based on a preset sorting rule, sorting the sorting values respectively corresponding to the decision schemes to obtain a sorting result;

and determining the target decision scheme from the plurality of decision schemes according to the sequencing result.

6. The method according to any of claims 1 to 5, wherein the decision index comprises at least: system outage rate, system outage duration, pipe network heat loss rate, infrastructure failure rate, full life cycle cost, equipment utilization, equipment operating cost savings, and carbon emission reduction.

7. A decision processing device for cooperative operation of an electric heating network is characterized by comprising:

the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring a plurality of decision schemes corresponding to a target project and a plurality of decision indexes corresponding to the target project, and the target project is an operation project for performing energy complementation on a power grid and a heat supply network;

the first calculation module is used for determining absolute weight matrixes corresponding to the decision indexes by adopting an analytic hierarchy process;

the second calculation module is used for calculating by adopting a Delphi method based on the decision schemes and the decision indexes to obtain a primary decision matrix;

the third calculation module is used for calculating target dominance degrees corresponding to the decision schemes respectively by adopting an interactive multi-criterion decision method according to the absolute weight matrix and the primary decision matrix;

and the first determining module is used for determining a target decision scheme from the plurality of decision schemes according to the target dominance degree.

8. The apparatus of claim 7, wherein the third computing module comprises:

a fourth calculating module, configured to calculate, according to the absolute weight matrix and the primary decision matrix, a single index dominance of any one decision scheme in the multiple decision schemes relative to any other decision scheme under the multiple decision indexes by using the interactive multi-criterion decision method, where the other decision schemes are used for representing decision schemes other than the any decision scheme in the multiple decision schemes;

a fifth calculating module, configured to perform cumulative calculation on the single index dominance degrees corresponding to the multiple decision indexes, to obtain a first comprehensive index dominance degree of the arbitrary decision scheme relative to the arbitrary other decision scheme;

a sixth calculating module, configured to perform cumulative calculation on the first comprehensive index superiority degrees corresponding to the other decision schemes, to obtain a second comprehensive index superiority degree of the any decision scheme relative to the other decision schemes;

and the second determination module is used for taking the dominance degree of the second comprehensive index as the target dominance degree.

9. A non-volatile storage medium, characterized in that the non-volatile storage medium stores a plurality of instructions, the instructions are suitable for being loaded by a processor and executing the electric heating network cooperative operation decision processing method according to any one of claims 1 to 6.

10. An electronic device, comprising: one or more processors and memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the grid co-operation decision-making process of any of claims 1-6.