CN104331773A - Comprehensive assessment method for power network planning schemes - Google Patents

Abstract

The invention discloses a method for comprehensive evaluation of power grid planning schemes. The specific steps are as follows: establishing a comprehensive evaluation index system for power grid planning schemes; quantifying relevant indicators; using the data envelopment method to determine the weights of different schemes; The program index set forms the program set matrix; the program set matrix is calculated by using the gray correlation degree to calculate the correlation coefficient matrix, and the correlation degree of each program is determined with the comprehensive weight to select the final program. It can be seen from the above that the comprehensive evaluation method of the power grid planning scheme of the present invention can effectively make up for the defects of the AHP and the data envelopment method, and use the gray correlation degree to improve the discrimination of the power grid planning scheme, which is conducive to comprehensively weighing each The advantages and disadvantages of the grid planning scheme, with high accuracy.

Description

A Comprehensive Evaluation Method for Power Network Planning Scheme

technical field

The present invention relates to a method for comprehensive evaluation of planning schemes, in particular to a method for comprehensive evaluation of power grid planning schemes. the

Background technique

Power grid planning is an important guarantee for the normal operation of the power industry. Whether a region's power grid operates well depends directly on whether the power grid planning is scientific and reasonable. With the gradual formation of the electricity market, power grid planning is no longer a single objective, but a complex nonlinear decision-making process with multiple objectives. The main problems in solving power grid planning are as follows: 1. There are many indicators in power grid planning, some of which are quantitative indicators, and some are qualitative indicators. Accurate quantification of each indicator is an important guarantee for scientific and rational planning of power grids; Restrictions not only depend on technology, but also consider the economics of investors and the influence of regional environmental factors. The selection ideas of the existing power grid planning schemes are mainly divided into two categories, one is completely dependent on the subjective judgment of the decision maker, due to the influence of the subjective judgment of the decision maker, there are many uncertain factors; the other is completely dependent on objective data , completely ignores the importance of decision makers in power grid planning, and weakens the ability of decision makers to grasp the overall situation. At the same time, the fault tolerance performance of these two types of methods is not good, and when the decision maker makes a wrong judgment or the objective data is wrong, it will bring immeasurable consequences. the

Contents of the invention

In order to overcome the deficiencies of the above-mentioned prior art, the present invention provides a comprehensive evaluation method for power grid planning, which provides objective basis for decision makers. Determine the weight of each index, and then calculate the correlation degree between each scheme and the optimal scheme through the gray correlation degree to realize the evaluation of the power grid planning scheme, which can effectively make up for the defects of the AHP and the data envelopment method, and use The degree of gray correlation improves the degree of differentiation of power grid planning schemes, which is conducive to comprehensively weighing the advantages and disadvantages of each power grid planning scheme, and has high accuracy. the

A method for comprehensive evaluation of power grid planning schemes, including a comprehensive evaluation index system for power grid planning, an evaluation method for power grid planning schemes, and a composition of power grid planning schemes. The specific steps are as follows:

1) Integrating the specific requirements of power grid planning, establishing a comprehensive evaluation index system for power grid planning schemes;

2) Analyze the characteristics of each power grid planning scheme, use the above index system to quantify each scheme, and use the Delphi method to quantify the qualitative indicators;

3) Use the AHP to determine the weight of each index to the scheme, divide the index into input index and output index, use the data envelopment method to determine the weight of different alternatives, and finally determine the comprehensive weight through the weight of the two methods;

4) Use the alternatives to determine the optimal scheme index set, and form the alternative scheme and the optimal scheme index set into a scheme set matrix;

5) Use the gray correlation degree to calculate the correlation coefficient matrix of the scheme set matrix, and determine the correlation degree of each scheme with the comprehensive weight to select the final scheme.

The comprehensive evaluation index system of the above power grid planning scheme is a tree structure, with 4 indicators in the first layer, 10 indicators in the second layer, and 16 indicators in the third layer. Among them, there are 21 indicators at the end of the branch. the

The further improvement scheme of the present invention is to use the relevant data and information of each scheme to give the specific numerical values of the indicators at the end of the branches of different schemes; for the indicators that cannot be given specific numerical values, the Delphi method is used to quantify them. the

A further improvement solution of the present invention is to use the analytic hierarchy process to obtain the weight of each evaluation index to the overall target.

A further improvement scheme of the present invention is to determine the weights of different schemes through normalization processing of residual variables and slack variable methods. the

A further improvement solution of the present invention is to use the Z-score method to standardize the data processing of each scheme set matrix. the

The beneficial effects of the present invention are:

The selection of power grid planning scheme is a system engineering that spans multiple disciplines and disciplines in the power system. Difficult to quantify, complex decision-making objectives, uncertain factors and many other problems. Analytic Hierarchy Process is a practical multi-objective decision-making method, which can quantify the preference of subjective decision-makers and reflect it through weights, which is very suitable for reflecting the tendency of decision-makers to choose power grid schemes. The data envelopment method is a method for evaluating the relative effectiveness of multiple decision-making units of the same type. Its advantages are simple structure, no need to consider weight factors, no interference from human factors, and strong objectivity. It is very suitable for reflecting alternatives. reasonable in practice. Combining the AHP and the data envelopment method for the comprehensive evaluation of power grid planning scheme selection, it can not only weigh the subjective decision-maker's preference and the actual objective rationality, but also effectively solve the problem that the indicators in the power grid planning scheme selection are difficult to quantify. , complex decision-making objectives, uncertain factors and many other issues.

Compared with the prior art, the benefits and advantages of the present invention are that the present invention establishes a complete evaluation system for grid planning schemes, which can comprehensively weigh subjective and objective factors, not only reflect the preference of decision makers, but also consider various options In the situation of objective factors, the present invention has higher accuracy. the

Description of drawings

Fig. 1 is the flow chart that the present invention establishes;

Figure 2 is a structural diagram of the index system of the present invention.

Detailed ways

The present invention is composed of a comprehensive evaluation index system for grid planning, an evaluation method for grid planning schemes, and a grid planning scheme. The flow process that the present invention establishes is as shown in Figure 1, and concrete realization steps are as follows:

1) Establishment of grid planning index system.

  In the tree structure index system shown in Figure 2, there are four first-level indicators: technical, economical, land occupation and environmental indicators, and adaptability. There are 10 indicators in the second layer. The technical indicators include: reliability, grid structure, and power supply quality; the economic indicators include: total investment and operating costs; the land occupation and environmental indicators include: the total number of high-voltage stations in the planning area, Impact on the global environment; determine the adaptability indicators include: economy when load growth is slow, site waste in various regions, and scalability. There are 16 indicators in the third layer. The indicators for determining the high-voltage network include: high-voltage user T-connection, the scope of power outages at the upper level, the average length of lines, the number of lines, and the singleness of voltage level; the indicators for determining the medium-voltage network include: the number of high-voltage stations, medium-voltage The average length of the voltage line; the determination of grid structure indicators includes: the rationality of the structure of the medium voltage network and the rationality of the structure of the high voltage network; the determination of the quality indicators of the power supply includes: the rationality of the power flow, the minimum voltage level, and the rationality of the short-circuit current; the determination of the operating cost indicators includes : Medium-voltage network loss rate, high-voltage network loss rate; Determining scalability indicators include: upper-level station storage margin, upper-level station power supply outside the area. Among them, there are 21 branch end indicators. the

2) Use AHP to determine the weight of the end of the branch to the target. the

 Using the analytic hierarchy process, select the indicators under the same level in the same indicator set, evaluate the relative importance of the indicators in pairs, and form a comparison matrix of the evaluation indicators. the

Choose to use the 1-9 scale method.

Use the range method to construct the judgment matrix:

in: is the matrix sum of elements in each row; is a constant, which is the relative importance of the range element pair given in advance according to some standard. become extremely poor, , . matrix is the consistency judgment matrix.

Find the judgment matrix The largest eigenvalue of and its corresponding eigenvectors , that is, the weight vector ,right The relative weight of each evaluation index of a certain level index with respect to its upper level index can be obtained by performing normalization processing.

According to the relative weight of the solution, the relative weight of the 21 indicators at the end of the tree branch is composed into a vector as .

3) Determine residual variables and slack variables using super-efficiency data envelopment method. the

  Use the relevant data of the alternatives to organize the specific values of 21 indicators, and use the Delphi method to quantify the indicators that cannot be quantified by specific values. the

The operation process of the Delphi method is: conduct anonymous comments on the comprehensive decision-making indicators initially proposed, put forward revision opinions, and give the importance of each indicator according to the predetermined index importance series and value, and then according to the number of experts and each The weighted average of the importance given by experts is the quantitative value of the qualitative index. the

Super efficient data envelopment method solution: Yes decision-making units (decision-making units are alternatives), each decision-making unit has 10 input indicators and 11 output indicators, and the corresponding input quantity is ,in for the first The input volume of a decision-making unit; the output volume is ,in for the first The output of a decision-making unit.

Solve the formula by input and output

in, The non-Archimedean infinitesimal quantity is actually 10 ^-5 ; , is a 10-dimensional vector; , is an 11-dimensional vector; , , , the solution of the objective function, is the super efficiency value, is the remaining variable, is the slack variable. Calculation of residual variables under different schemes by super-efficiency data envelopment method and slack variables , then the first The vector composed of residual variables and slack variables of each scheme is .

right normalized to , which is the weight of the data envelopment method.

4) Solve the comprehensive weight through the weight obtained by AHP and DEA .

Introduce preference coefficient ( ), reflecting the proportion of each model weight.

make

5) Determine the optimal solution index set ,in ( ) means the first The optimal value of an index among all alternatives.

6) Establish a scheme set matrix

in, ( ) for the set of program indicators.

Normalize the scheme set matrix, the characteristics of the power grid planning data, and the large differences between the data, the Z-score method is used for data standardization. the

( )

in, , respectively B The mean and standard deviation of the column elements.

7) Determine the correlation coefficient matrix. the

The gray relational analysis method can be used to calculate the No. 1 of the plan The correlation coefficient between an index and its corresponding optimal index .

It is the resolution coefficient, usually 0.5.

8) By correlation coefficient matrix row vector in with combined weight Calculate the first Relevance of programs .

Correlation The larger the value, the closer the solution is to the optimal solution. use The schemes can then be sorted to determine the final selected scheme.

Case Analysis:

The invention applies the proposed comprehensive evaluation method to grid planning. According to the distribution network planning of a planning area, only 110kV and 220kV can be connected to the power grid in this area. Therefore, 110kV (Scheme 1), 220kV scheme (Scheme 2) and a mixed scheme of 110kV and 220kV (Scheme 3) can be selected. ). The technical, economical, land occupation indicators and other indicators of the above three schemes are as follows: 

Table 1 Relevant data of each scheme

Take decision maker A's business level equivalent in all aspects of decision-making as 0.95 (the highest value is 1), use the present invention to process the input and output data of the above three schemes, and calculate the weights and final Decision ranking results. At the same time, the calculation and decision results of AHP-DEA without gray relation, AHP method and AHP-DEA with gray relation of the present invention are listed in comparison.

Table 2 Decision-making results of each method of decision maker A

Take decision-maker B's business level equivalent in all aspects of decision-making as 0.65 (the highest value is 1), use the present invention to process the input and output data of the above three schemes, and calculate the weights and final Decision ranking results. At the same time, the calculation and decision results of AHP-DEA without gray relation, AHP method and AHP-DEA with gray relation of the present invention are listed in comparison.

Table 3 Decision-making results of each method of decision maker B

In actual operation, the collected data may not be as detailed as listed in Table 1, and when the amount of data collected on site is incomplete, such as when the original data lacks the upper-level station position margin and upper-level The two parameters of the power supply from the station to the outside area, and then take the business level equivalent of decision maker A's decision-making in all aspects as 0.95 (the highest value is 1), use the present invention to process the input and output data of the above three schemes, and calculate the The weights and final decision ranking results of the three planning scenarios in the region. At the same time, the calculation and decision results of AHP-DEA without gray relation, AHP method and AHP-DEA with gray relation of the present invention are listed in comparison.

Table 4 Decision-making results of each method of decision maker A under the condition of incomplete objective data

In the actual situation, the order of the three schemes is scheme 3 > scheme 2 > scheme 1, and the final scheme of power grid construction is scheme 3.

From the data in Table 2 and Table 3, it can be seen that the rankings obtained by two decision makers with different business levels in various aspects of decision-making through three different methods are as follows:

The ranking results of the two decision makers through the AHP method are not the same twice, and the decision results may change when the business level of the decision makers changes. When the decision-maker's decision-making level is relatively high (decision-maker A's business level equivalent in all aspects of decision-making is 0.95), based on objective data, more accurate results can be obtained (that is, the results obtained by the AHP method in Table 2 are the same as the actual situation ), but when the decision-maker’s decision-making level is low (decision-maker B’s business level equivalent of all aspects of decision-making is 0.65), even based on relatively detailed objective data, the results obtained are not accurate (that is, in Table 3 The results obtained by the AHP method are different from the actual situation). In fact, after calculation, it can be seen that when the business level of all aspects of decision-making of the decision-maker is equivalent in the range of 0.4-1.0, the three methods in Table 2 and Table 3 are applicable, and when the business level of all aspects of decision-making of the decision-maker is equal to When the valence is greater than or equal to 0.72, the results obtained by the AHP method are the same as those obtained by the AHP-DEA method with gray correlation. It can be seen from this that the decision-maker must have a certain level of business in all aspects of decision-making before he can make a decision; in addition, when the level of business in all aspects of decision-making reaches a certain level, the decision-maker can make accurate decisions in the face of the same objective data. Decision-making; however, according to the amount of objective data, the business level of all aspects of decision-making that decision-makers can achieve to make decisions and the business level of various aspects of decision-making that can be achieved to make accurate decisions are not the same.

It can be seen from the data in Table 2 and Table 4 that the decision makers with high business level are ranked as follows by three different methods under the condition of different completeness of objective data:

The ranking results of decision maker A with high business level are not the same twice through the AHP method, indicating that when the objective data is incomplete, decision maker A who could have made the correct decision cannot make the correct decision; Decision Maker A with a high professional level uses the combination of subjective and objective AHP-DEA method without gray correlation to sort results: under the condition of complete objective data, the sorting results are scheme three, scheme one, and scheme two; under the condition of incomplete objective data, the ranking is Scheme 1, Scheme 3, and Scheme 2, in the case of incomplete objective data, the sorting result of the AHP-DEA method without gray relation is different from the actual sorting result, compared with the case of complete objective data through AHP without gray relation - The sorting results of the DEA method are much different from the actual sorting results, indicating that the results obtained by this method have a great relationship with the completeness of the objective data. When the data is not perfect, even if the decision-maker has a high professional level, The ranking of its decisions is also inaccurate.

In the above three cases, the final result determined by using the present invention is the recommended scheme 3, and the sequence of scheme 3, scheme 2, and scheme 1 is the same as the final scheme of actual power grid construction. Therefore, the AHP-DEA method with gray correlation of the present invention can effectively combine the subjective evaluation of the decision-maker with the objective evaluation, and effectively make up for the defects in the independent use of the two. At the same time, the present invention also has great advantages in data fault tolerance . the

Claims (5)

1. A network planning scheme comprehensive evaluation method is characterized in that: comprise the network planning comprehensive evaluation index system, the evaluation method of the grid planning scheme and the grid planning scheme composition, concrete steps are as follows: 1) Combined with the actual requirements of power grid planning, establish a comprehensive evaluation index system for power grid planning schemes; 2) Combining the characteristics of various power grid planning schemes, quantify relevant indicators, and use Delphi method to quantify qualitative indicators; 3) Determine the weight of each indicator to the scheme through the analytic hierarchy process, divide the indicators into input indicators and output indicators in the process, and use the data envelopment method to determine the weight of different schemes; 4) Establish an optimal program index set for all alternatives, and form the alternative program and the optimal program index set into a program set matrix; 5) Use the gray correlation degree to calculate the correlation coefficient matrix of the scheme set matrix, and determine the correlation degree of each scheme with the comprehensive weight to select the final scheme. 2. a kind of novel network planning scheme comprehensive evaluation method according to claim 1, it is characterized in that: utilize the relevant data and information of each scheme, provide the specific numerical value of different schemes at the branch end index; Can not provide specific numerical value for The indicators are quantified using the Delphi method. 3. A method for comprehensive evaluation of a power grid planning scheme according to claim 1, characterized in that: the weight of each evaluation index to the overall target is obtained by using the AHP. 4. A method for comprehensive evaluation of power grid planning schemes according to claim 1, characterized in that: the weights of different schemes are determined through normalization processing of residual variables and slack variable methods. 5. A method for comprehensive evaluation of power grid planning schemes according to claim 1, characterized in that: standardize data processing of each scheme set matrix using the Z-score method.