Adaptability evaluation method considering access of rural distributed integrated energy system to power distribution network

Abstract

The invention discloses an adaptability evaluation method considering the access of a rural distributed integrated energy system to a power distribution network, and the method comprises the steps: firstly, considering the influence of the rural distributed integrated energy system on the safe, economic and low-carbon operation of the power distribution network, and mining a new evaluation index; the method comprises the following steps: constructing a power distribution network adaptability evaluation index system integrated with a rural distributed integrated energy system from three dimensions of safety, economy and low-carbon property, then analyzing each index connotation and a calculation method in the index system, and then formulating a power distribution network adaptability evaluation index scoring curve. And the weight is determined by adopting the combination of an ordered weighting operator corrected AHP method and an entropy weight method. And finally obtaining a power distribution network adaptability evaluation process and a division standard. Meanwhile, objective factors and subjective factors are considered, the scientificity of subjective empowerment is improved, the evaluation result has higher adaptability, the method can be suitable for different conditions and different scenes, and a reliable evaluation mechanism and safety guarantee are provided for stable operation of the power distribution network connected into the rural distributed integrated energy system.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems and integrated energy systems, and in particular to a method for evaluating the adaptability of a rural distributed integrated energy system to a distribution network. Background Art

[0002] In recent years, energy issues have become increasingly prominent, and the implementation of the "dual carbon" goals has accelerated. At present, most rural areas rely on traditional energy. As an important part of China's modern energy system construction, rural energy model transformation and upgrading is imminent. Building a rural distributed integrated energy system with renewable energy as the main body has become a future development trend.

[0003] The rural distributed comprehensive energy system contains renewable energy sources such as wind power, photovoltaics, and biomass energy. The output of new energy has certain uncertainties. After being connected to the distribution network, it will bring certain risks and challenges to the safe and stable operation of the distribution network. The present invention constructs an adaptability evaluation method considering the access of rural distributed comprehensive energy systems to the distribution network, which can scientifically and effectively evaluate the safety issues of the access of rural distributed comprehensive energy systems to the distribution network, and provide effective protection for the safe operation of the distribution network. At the same time, it can also analyze the economy and low-carbon nature of the distribution network after being integrated into the rural distributed comprehensive energy system, comprehensively consider safety, economy, and low-carbon factors to establish evaluation indicators, formulate a distribution network adaptability evaluation indicator scoring curve, and use the AHP method modified by the ordered weighted operator and the entropy weight method to determine the weights, that is, considering objective factors and subjective factors, and the evaluation effect is relatively comprehensive. Finally, the distribution network adaptability evaluation process and classification standards are obtained, which provides a reliable evaluation mechanism for the stable operation of the distribution network connected to the rural distributed comprehensive energy system. Summary of the invention

[0004] The present invention proposes a method, device and storage medium for evaluating the adaptability of a rural distributed integrated energy system connected to a distribution network, which can solve at least one of the technical problems in the background technology.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for evaluating the adaptability of a rural distributed integrated energy system to a distribution network includes the following steps:

[0007] S100. Consider the impact of rural distributed integrated energy systems on the safe, economical and low-carbon operation of distribution networks, explore new evaluation indicators, and construct a distribution network adaptability evaluation indicator system that integrates rural distributed integrated energy systems from the three dimensions of safety, economy and low carbon;

[0008] S200, analyze the connotation and calculation method of each indicator in the distribution network adaptability evaluation index system;

[0009] S300, formulate a distribution network adaptability evaluation index scoring curve based on the connotation and calculation method of each index, and use the AHP method modified by the ordered weighted operator and the entropy weight method to determine the weight;

[0010] S400. Based on S100, S200 and S300, establish the distribution network adaptability evaluation process and classification standards.

[0011] Furthermore, the distribution network adaptability evaluation index system in step S100 of the present invention includes 3 primary indicators and 14 secondary indicators:

[0012] Among them, the three first-level indicators include safety index A, economic index B, and low-carbon index C;

[0013] The 14 secondary indicators include voltage qualification rate A1, voltage deviation rate A2, harmonic current exceeding rate A3, frequency deviation A4, transformer reliability A5, line reliability A6, capacity load ratio B1, line load rate B2, line overload rate B3, distributed photovoltaic absorption rate B4, grid line loss contribution rate B5, distributed energy penetration rate C1, distributed energy absorption rate C2, CO 2 Emission reduction C3.

[0014] Furthermore, the calculation method of transformer reliability A5 and line reliability A6 in the safety index A of the present invention is as follows:

[0015] Transformer reliability refers to the proportion of transformer equipment that meets the N-1 level in the distribution network after distributed energy is connected to the distribution network, reflecting the reliability of the transformer equipment in the distribution network.

[0016]

[0017] Where Ntrans is the total number of transformer equipment in the distribution network; Ntrans_N-1 is the number of transformer equipment reaching the N-1 level;

[0018] Line reliability is the ratio of the number of lines that meet the N-1 level to the total number of lines in the distribution network, which reflects the safety of the lines in the distribution network.

[0019]

[0020] Where Nlines is the total number of lines in the distribution network; Nlines_N-1 is the number of distribution network lines that meet the N-1 principle.

[0021] Furthermore, the calculation method of the capacity-load ratio B1, line load rate B2, line overload rate B3, distributed photovoltaic consumption rate of return B4, and grid line loss contribution rate B5 in the economic index B of the present invention is as follows:

[0022] The capacity load ratio refers to the ratio of the total installed capacity of the transformer in the distribution network to the peak load. It reflects the operating status and utilization efficiency of the transformer for the transformer capacity load rate. The value within the recommended range indicates that the substation equipment has better adaptability to the access of new energy. The calculation formula of the capacity load ratio is as follows:

[0023]

[0024] In the formula is the annual peak load of the distribution network, in kW; Ctrans is the total capacity of the distribution network transformer, in kVA;

[0025] The line load rate is the ratio of the daily average power load of the distribution network to the peak load of the same year, which reflects the load of the distribution network line. The calculation formula is as follows:

[0026]

[0027] Where Pave L is the average daily power load of the distribution network, in kW;

[0028] The line overload rate is the ratio of the number of lines with a load rate greater than 80% to the total number of lines in the distribution network when the distribution network is operating normally. The lower the line overload rate, the better the line operation condition and the higher the adaptability to the access of new energy such as energy. The calculation formula is as follows:

[0029]

[0030] Where Nlines_over is the number of overloaded lines in the distribution network;

[0031] The consumption process of distributed energy access to the distribution network can bring benefits such as delaying distribution network investment, peak shaving and valley filling, and improving distribution network reliability. At the same time, it also increases the operation and maintenance costs of the distribution network. The distributed energy consumption rate of return is the ratio of the economic benefits brought by the grid-connected consumption of distributed energy to the overall operation and maintenance costs of the distribution network. The calculation formula is as follows:

[0032]

[0033] Where Cin, Cpls, Cres are the delayed grid investment benefits, peak-shaving and valley-filling benefits, and improved reliability benefits brought by distributed energy grid connection, and Cop is the distribution network operation and maintenance cost;

[0034] The access of distributed energy changes the power flow of distribution network lines, causing changes in distribution network line losses, which generally show a trend of first decreasing and then increasing. The contribution rate of distribution network line losses is defined as the ratio of the grid loss caused by the grid connection of distributed energy to the grid loss before the grid connection. The calculation method is as follows:

[0035]

[0036] Where △PADN is the change in line loss of the distribution network caused by the grid connection of distributed energy, in kw; P0 is the total loss of the distribution network before the grid connection of distributed energy, in kW.

[0037] Furthermore, the distributed energy penetration rate C1, distributed energy consumption rate C2, CO 2 The calculation method of emission reduction C3 is as follows:

[0038] The calculation method of distributed energy penetration rate C1 is as follows:

[0039] The penetration rate reflects the impact of distributed energy on the distribution network. The distributed energy penetration rate is defined as a weighted combination of static penetration rate and effective penetration rate. The formula is as follows:

[0040]

[0041] Where η is the weight, which is 0.5; Sst and Sva are the static permeability and effective permeability respectively; PL are the maximum load power and actual load power of the distribution network, in kW; Ppv, They are the rated power and actual power of distributed energy, in kW;

[0042] The calculation method of distributed energy consumption rate is as follows:

[0043] The distributed energy consumption rate is the ratio of the actual output of distributed energy to the maximum allowable output during the operation of the distribution network.

[0044]

[0045] In the formula The maximum allowable output of distributed energy in the distribution network, in kW;

[0046] CO 2 The calculation method of emission reduction benefits is as follows:

[0047] CO 2 The emission reduction benefit is defined as the proportion of the environmental benefits of distributed energy over its entire life cycle to the initial investment.

[0048]

[0049] Where T is the carbon dioxide emission per unit of electricity produced by the coal-fired unit, which is 822.8 g / (kw·h); pcarbon is the real-time price of the carbon emission trading market; Qpv,i is the power generation of the i-th distributed energy statistical period, kw·h; c1 is the investment cost of distributed energy per unit capacity, which is 5.4 yuan / W.

[0050] Furthermore, in S300 of the present invention, a distribution network adaptability evaluation index scoring curve is formulated based on the connotation of each index as follows:

[0051]

[0052] Furthermore, the method for determining weights by combining the AHP method modified by the ordered weighting operator and the entropy weight method in S300 of the present invention is as follows:

[0053] S320, improve AHP based on ordered weighted operator to revise subjective weights;

[0054] S330, use entropy weight method to carry out objective weighting;

[0055] S340 , calculating the combined weight based on S320 and S330 .

[0056] Furthermore, the method for revising subjective weights based on the ordered weighted operator-improved AHP in S320 of the present invention is as follows:

[0057] The initial weight matrix B of n indicators for m experts who have passed the consistency test m*n , for the i-th indicator weight (b il ,b i2 ,....,b im ) in descending order, and the new sequence is (p0, p1, ..., p m-1 ), select t data in the sequence and combine them into C t m-1 , then the ordered weighted vector v t for:

[0058]

[0059] Get the absolute weight of the i-th indicator for:

[0060]

[0061] Then the subjective weight after OWA operator correction is:

[0062]

[0063] Furthermore, the calculation method of the combined weight based on the improved AHP method and the entropy weight method in S340 of the present invention is as follows: Based on the minimum information recognition principle, the subjective and objective weights are combined so that the distribution distance of the two weights is minimized. The calculation formula of the combined weight is:

[0064]

[0065] Among them, wj is the combined weight, w ij is the subjective weight of the jth indicator, w 2j is the objective weight of the j-th indicator, j = 1, 2, ..., n.

[0066] It can be seen from the above technical scheme that the present invention constructs an adaptability evaluation method considering the access of rural distributed integrated energy systems to the distribution network, comprehensively considers the three factors of safety, economy, and low carbon to establish an evaluation index system. On the premise of evaluating the safe operation of the distribution network, it can also analyze the economy and low carbon of the distribution network after integrating into the rural distributed integrated energy system, and the evaluation angle is richer and the effect is more comprehensive. After the evaluation system and the scoring curve are established, the present invention adopts the AHP method modified by the ordered weighted operator and the entropy weight method to determine the weights, that is, considering objective factors, and taking subjective factors into account, which improves the scientific nature of subjective weighting, and the evaluation results are more scientific and effective, with stronger adaptability, and can be adjusted accordingly in combination with different scenarios and different conditions, and have stronger applicability. Provide a reliable evaluation mechanism and security guarantee for the stable operation of the distribution network connected to the rural distributed integrated energy system. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 is a flow chart of the method of the present invention;

[0068] Figure 2 Evaluate processes for distribution networks. DETAILED DESCRIPTION

[0069] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments.

[0070] like Figure 1 As shown, the adaptability evaluation method considering the rural distributed integrated energy system connected to the distribution network described in this embodiment includes the following steps:

[0071] S100. Consider the impact of rural distributed integrated energy systems on the safe, economical and low-carbon operation of distribution networks, explore new evaluation indicators, and construct a distribution network adaptability evaluation indicator system that integrates rural distributed integrated energy systems from the three dimensions of safety, economy and low carbon;

[0072] S200, analyze the connotation and calculation method of each indicator in the distribution network adaptability evaluation index system;

[0073] S300, formulate a distribution network adaptability evaluation index scoring curve based on the connotation and calculation method of each index, and use the AHP method modified by the ordered weighted operator and the entropy weight method to determine the weight;

[0074] S400, based on S100, S200 and S300, establish the distribution network adaptability evaluation process and classification standards;

[0075] like Figure 2 As shown in the figure, the distribution network evaluation process of the present invention is described in detail by taking the actual distribution network data of a rural area A in Anhui as an example and combining it with a specific application:

[0076] The total power supply area in Region A is 119.25 square kilometers, and the total power supply population is 98,000. There are 3 110kV substations and 5 main transformers in the area, with a total substation capacity of 180MWA. There are 8 110kV lines with a total length of 800km. There are 56 10kV public lines with a total length of 20km. The average length of the trunk line is 6.85km, and the average distribution and transformation capacity of a single line is 9.17MWA. The average load rate of 10kV public lines in the power supply area is 52.34%, and the overall load situation is good. The total load of the distribution network is 48.28MW, the load power factor is 0.9, and the distributed energy adopts a constant power factor control method, and the total grid-connected capacity is 12.3MW.

[0077] S100. Consider the impact of rural distributed integrated energy systems on the safe, economical and low-carbon operation of distribution networks, explore new evaluation indicators, and construct a distribution network adaptability evaluation indicator system that integrates rural distributed integrated energy systems from the three dimensions of safety, economy and low carbon;

[0078] The distribution network adaptability evaluation index system specifically includes:

[0079] Based on the grid adaptability analysis theory and the research results related to distribution network adaptability, a distribution network adaptability evaluation index system integrated into the rural distributed integrated energy system is constructed from three dimensions: safety, economy, and low carbon. It includes 3 first-level indicators and 14 second-level indicators, as shown in Table 1.

[0080] Table 1 Distribution network adaptability evaluation index system integrated into rural distributed integrated energy system

[0081]

[0082]

[0083] S200. Analyze the connotation and calculation method of each indicator in the indicator system.

[0084] In the established indicator system, the voltage, current, frequency and other indicator values ​​are calculated using power system simulation software, and other indicator values ​​are indirectly measured based on distribution network parameters and operating data. The meaning and calculation method of each indicator are explained as follows.

[0085] Safety indicators:

[0086] (1) Voltage qualification rate A1

[0087] The voltage qualification rate refers to the percentage of time that the voltage at the measuring point is within the qualified range during the normal operation of the power grid to the total measurement time.

[0088] (2) Voltage deviation rate A2

[0089] The voltage deviation rate refers to the allowable deviation of the power supply voltage of the power distribution system. According to the standard GB12325-1990, the voltage deviation rate is related to the voltage level, where the sum of the absolute values ​​of positive and negative deviations of 35kV and above is less than 10%, and the sum of the absolute values ​​of positive and negative deviations of 10kV and below is less than 7%.

[0090] (3) Harmonic current exceeding standard rate A3

[0091] The harmonic current excess rate refers to the increase in the proportion of nodes with harmonic current exceeding the standard after distributed energy is connected to the distribution network. According to the standard GB / T14549-93, 10kV is qualified within 4% and 220V is qualified within 5%.

[0092] (4) Frequency deviation A4

[0093] Frequency deviation is the difference between the actual value and the nominal value of the power system frequency under normal operating conditions. The allowable value of frequency deviation in China's power system is ±0.2Hz.

[0094] (5) Transformer reliability A5

[0095] Transformer reliability refers to the proportion of transformer equipment that meets the N-1 level in the distribution network after distributed energy is connected to the distribution network, reflecting the reliability of the transformer equipment in the distribution network.

[0096]

[0097] Where N trans is the total number of transformer equipment in the distribution network; N trans_N-1 The number of transformer equipment required to reach the N-1 level.

[0098] (6) Line reliability A6

[0099] Line reliability is the ratio of the number of lines that meet the N-1 level to the total number of lines in the distribution network, which reflects the safety of the lines in the distribution network.

[0100]

[0101] Where N lines is the total number of lines in the distribution network; N lines_N-1 The number of distribution network lines that meets the N-1 principle.

[0102] Economic indicators:

[0103] (1) Load capacity ratio B1

[0104] The load-to-capacity ratio refers to the ratio of the total installed capacity of the transformer in the distribution network to the peak load. It reflects the operating status and utilization efficiency of the transformer. The load-to-capacity ratio of transformers on the market is: 1.6-1.9 for 220kV and 1.8-2.1 for 35-110kV. Therefore, for the transformer load-to-capacity ratio, the value within the recommended range indicates that the substation equipment has better adaptability to the access of new energy. The calculation formula of the load-to-capacity ratio is as follows:

[0105]

[0106] In the formula is the annual peak load of the distribution network, in kW; C trans is the total capacity of the distribution network transformer, in kVA.

[0107] (2) Line load factor B2

[0108] The line load rate is the ratio of the daily average power load of the distribution network to the peak load of the same year, which reflects the load of the distribution network line. The calculation formula is as follows:

[0109]

[0110] In the formula It is the average daily power load of the distribution network, in kW.

[0111] (3) Line overload rate B3

[0112] The line overload rate is the ratio of the number of lines with a load rate greater than 80% to the total number of lines in the distribution network when the distribution network is operating normally. The lower the line overload rate, the better the line operation condition and the higher the adaptability to the access of new energy sources such as energy. The calculation formula is as follows:

[0113]

[0114] Where N lines_over is the number of overloaded lines in the distribution network.

[0115] (4) Distributed energy consumption rate of return B4

[0116] The consumption process of distributed energy access to the distribution network can bring benefits such as delaying distribution network investment, shaving peaks and filling valleys, and improving distribution network reliability, but it also increases the operation and maintenance costs of the distribution network. The distributed energy consumption rate of return is the ratio of the economic benefits brought by the grid-connected consumption of distributed energy to the overall operation and maintenance costs of the distribution network. The calculation formula is as follows:

[0117]

[0118] Where C in , C pls , C res They are the delayed grid investment benefits, peak load reduction and valley filling benefits, and improved reliability benefits brought by distributed energy grid connection, C op It is the operation and maintenance cost of the distribution network.

[0119] (5) Distribution network line loss contribution rate B5

[0120] The access of distributed energy changes the power flow of distribution network lines, causing changes in distribution network line losses, which generally show a trend of first decreasing and then increasing. The contribution rate of distribution network line losses is defined as the ratio of the grid loss caused by the grid connection of distributed energy to the grid loss before the grid connection. The calculation method is as follows:

[0121]

[0122] Where △P ADN is the change in line loss of the distribution network caused by the grid connection of distributed energy, in kw; P0 is the total loss of the distribution network before the grid connection of distributed energy, in kW.

[0123] Low carbon index:

[0124] (1) Distributed energy penetration rate C1

[0125] The penetration rate reflects the impact of distributed energy on the distribution network. The distributed energy penetration rate is defined as a weighted combination of static penetration rate and effective penetration rate. The formula is as follows:

[0126]

[0127] Where η is the weight, which is 0.5; S st , S va They are static permeability and effective permeability respectively; P L are the maximum load power and actual load power of the distribution network, in kW; P pv , They are the rated power and actual power of distributed energy respectively, in kW.

[0128] (2) Distributed energy consumption rate C2

[0129] The distributed energy consumption rate is the ratio of the actual output of distributed energy to the maximum allowable output during the operation of the distribution network.

[0130]

[0131] In the formula It is the maximum allowable output of distributed energy in the distribution network, in kW.

[0132] (3) CO2 emission reduction benefits C3

[0133] The CO2 emission reduction benefit is defined as the proportion of the environmental benefits of distributed energy over its entire life cycle to the initial investment.

[0134]

[0135] In formula (10), T is the carbon dioxide emission per unit of electricity produced by the coal-fired unit, which is 822.8 g / (kw·h); carbon It is the real-time price of carbon emission trading market. pv,i is the power generation of the i-th distributed energy statistical period, kw·h; c1 is the investment cost of distributed energy per unit capacity, which is 5.4 yuan / W.

[0136] S300, formulate a distribution network adaptability evaluation index scoring curve based on the connotation of each index, and use the AHP method modified by the ordered weighted operator and the entropy weight method to determine the weight;

[0137] The method for developing a scoring curve for distribution network adaptability evaluation indicators includes:

[0138] Since the calculated values ​​of the evaluation indicators listed above have different dimensions and cannot be directly weighted, a distribution network adaptability evaluation index scoring curve is developed based on national standards and combined with expert experience as shown in Table 2.

[0139] Table 2 Distribution network adaptability evaluation index scoring curve

[0140]

[0141] In the DIgSILENT15.1 environment, the voltage, current and other safety index values ​​of the distribution network are simulated and calculated in two scenarios before and after the integration of the distributed integrated energy system. Other index values ​​are calculated according to the distribution network parameters and operation data, and the calculated values ​​of each index are evaluated according to the scoring curve. The calculation results and scores are shown in Table 3.

[0142] Table 3 Calculated values ​​and scores of distribution network adaptability indicators

[0143]

[0144] From the calculation results in Table 3, it can be seen that after the rural distribution network is integrated into the distributed integrated energy system, the access to distributed energy can optimize the indicators such as the load rate and capacity load ratio of the distribution network line. This is because the distributed energy plays a role of "peak shaving and valley filling" in the distribution network, reducing the peak load of the distribution network. At the same time, in terms of environmental benefits, the penetration rate and absorption rate of distributed energy have promoted the energy transformation and friendly development of the distribution network. However, from a numerical point of view, the CO2 emission reduction benefit is relatively low. This is because the current transaction price of my country's carbon market is extremely low. In the future, as the carbon market matures and the transaction price rises, the carbon emission reduction benefits brought by distributed energy will be improved. In addition, due to the time-varying nature of distributed energy generation and the use of inverters to connect to the grid, harmonics are easily generated, which increases the voltage and current deviations of the distribution network. Therefore, in the adaptive transformation of the distribution network, special attention should be paid to the transformation of equipment and protection devices.

[0145] The weight determination method of the AHP method modified by the ordered weighted operator and the entropy weight method is as follows:

[0146] In order to calculate the comprehensive evaluation results of the adaptability of the distribution network with distributed energy access, the index scores need to be weighted and summed. In order to ensure the scientific nature of the weights, a combination of subjective and objective methods is used for weighting: that is, the AHP is improved based on the ordered weighted operator (OWA operator) to revise the subjective weights to reduce the subjective influence of experts on the accuracy of the weights. At the same time, the entropy weight method is used for objective weighting, and finally, the combination weighting is performed based on the principle of minimum information identification.

[0147] S320: Modifying subjective weights based on the ordered weighted operator-based AHP (OWA-AHP method)

[0148] Taking the criterion layer as an example, first, the initial weight matrix B of n indicators for m experts who have passed the consistency test is m*n , for the i-th indicator weight (b il ,b i2 ,....,b im ) in descending order, and the new sequence is (p0, p1, ..., p m-1 ), select t data in the sequence and combine them into C t m-1 , then the ordered weighted vector v t for:

[0149]

[0150] Thus, the absolute weight of the i-th indicator is obtained for:

[0151]

[0152] Then the subjective weight after OWA operator correction is:

[0153]

[0154] S330, objective weighting using entropy weight method

[0155] The entropy weight method is a way to introduce the concept of "entropy" into information theory to measure the uncertainty of information. The smaller the entropy value, the higher the information validity and the stronger the orderliness. This method calculates the entropy value of each indicator based on information entropy and then analyzes the trend change of the indicator. It also uses the entropy weight to correct the weight value of each indicator to achieve the purpose of obtaining more objective indicator weights. The specific steps are as follows:

[0156] (1) Establishing an indicator matrix

[0157] Assume that the evaluation object is m and the evaluation index is n, then the index value x ij (i=1,2,...,m;j=1,2,...,n) The corresponding indicator matrix is:

[0158]

[0159] (2) Normalization of indicator matrix

[0160] After normalizing the indicator matrix X, we get the matrix G = (g ij ) m*n , where the normalized index values ​​g ij :

[0161]

[0162] (3) Calculate the characteristic weight of the index h ij

[0163]

[0164] (4) Calculate the entropy weight of the indicator

[0165]

[0166] (5) Calculate the differentiation coefficient p of the indicator j

[0167] p j =1-k j Formula (18)

[0168] (6) Calculate the indicator weight q j

[0169]

[0170] S340: Calculate the combined weight based on S320 and S330

[0171] In order to obtain scientific and reasonable indicator weights, based on the principle of minimum information identification, the subjective and objective weights are combined to minimize the distribution distance of the two weights. The calculation formula for the combined weight is:

[0172]

[0173] Among them, w j is the combined weight, w ij is the subjective weight of the jth indicator, w 2j is the objective weight of the j-th indicator, j = 1, 2, ..., n.

[0174] Experts in the distribution network field were invited to use the AHP, OWA-AHP method, and entropy weight method to determine the subjective weight of each indicator before improvement, and the subjective and objective weights after improvement, and calculate the comprehensive weights of the indicators. The comprehensive weights of the distribution network adaptability evaluation indicators are shown in Table 4.

[0175] Table 4 Weights of distribution network adaptability evaluation indicators

[0176]

[0177] By comparing with the traditional AHP method, it is found that the OWA operator reduces the negative impact of expert decision-making on the weight in a descending manner, allocates the data maximum and minimum values ​​to the area with less impact, and thus improves the scientific nature of subjective weighting. Then, the comprehensive weight of each indicator is summed to obtain the comprehensive score of distribution network adaptability in the two scenarios of distributed energy not connected and connected.

[0178] S400. Based on S100, S200 and S300, establish the distribution network adaptability evaluation process and classification standards.

[0179] The adaptability evaluation process of distributed energy access to distribution network is as follows: Figure 2 The distribution network adaptability evaluation classification standards are shown in Table 5.

[0180] Table 5 Distribution network adaptability evaluation classification standards

[0181]

[0182] Based on the evaluation level classification, the adaptability results can be obtained as shown in Table 6.

[0183] Table 6 Results of comprehensive evaluation indexes of distribution network equipment adaptability

[0184]

[0185] From the calculation results in Table 6, it can be seen that according to the distribution network adaptability classification standard, although the adaptability level of the distribution network before and after the integration of the distributed integrated energy system in the rural area has not changed, the comprehensive adaptability score has been improved. In the future, as the intelligence level of distribution network equipment improves and the carbon market matures, the adaptability of indicators such as voltage qualification rate, voltage deviation rate, distributed energy consumption rate of return, and CO2 emission reduction benefit in the distribution network in the region will be improved, and the comprehensive adaptability of the distribution network will be further enhanced.

[0186] Considering the impact of rural distributed integrated energy systems on the safe, economical, and low-carbon operation of distribution networks, a distribution network adaptability evaluation index system integrated with rural distributed integrated energy systems is constructed. The connotation and calculation method of each indicator in the index system are analyzed. A scoring curve for distribution network adaptability evaluation indicators is formulated, and the AHP method modified by the ordered weighted operator and the entropy weight method are combined to determine the weights. A distribution network adaptability evaluation process and classification standards are formulated.

[0187] Each embodiment in this specification is described in a related manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0188] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the adaptability of rural distributed integrated energy systems to distribution networks, characterized in that: The following steps are involved: S100. Consider the impact of rural distributed integrated energy systems on the safe, economical and low-carbon operation of distribution networks, explore new evaluation indicators, and construct a distribution network adaptability evaluation indicator system that integrates rural distributed integrated energy systems from the three dimensions of safety, economy and low carbon; S200, analyze the connotation and calculation method of each indicator in the distribution network adaptability evaluation index system; S300, formulate a distribution network adaptability evaluation index scoring curve based on the connotation and calculation method of each index, and use the AHP method modified by the ordered weighted operator and the entropy weight method to determine the weight; S400. Based on S100, S200 and S300, establish the distribution network adaptability evaluation process and classification standards.

2. The method for evaluating the adaptability of rural distributed integrated energy systems to distribution networks according to claim 1 is characterized in that: The distribution network adaptability evaluation index system in step S100 includes 3 primary indicators and 14 secondary indicators: Among them, the three first-level indicators include safety index A, economic index B, and low-carbon index C; The 14 secondary indicators include voltage qualification rate A1, voltage deviation rate A2, harmonic current exceeding rate A3, frequency deviation A4, transformer reliability A5, line reliability A6, capacity load ratio B1, line load rate B2, line overload rate B3, distributed photovoltaic absorption rate B4, grid line loss contribution rate B5, distributed energy penetration rate C1, distributed energy absorption rate C2, CO 2 Emission reduction C3.

3. The method for evaluating the adaptability of rural distributed integrated energy systems to distribution networks according to claim 2 is characterized in that: The calculation method of transformer reliability A5 and line reliability A6 in the safety index A is as follows: Transformer reliability refers to the proportion of transformer equipment that meets the N-1 level in the distribution network after distributed energy is connected to the distribution network, reflecting the reliability of transformer equipment in the distribution network; Where Ntrans is the total number of transformer equipment in the distribution network; Ntrans_N-1 is the number of transformer equipment reaching the N-1 level; Line reliability is the ratio of the number of lines that meet the N-1 level to the total number of lines in the distribution network, which reflects the safety of the lines in the distribution network; Where Nlines is the total number of lines in the distribution network; Nlines_N-1 is the number of distribution network lines that meet the N-1 principle.

4. The method for evaluating the adaptability of rural distributed integrated energy systems to distribution networks according to claim 2 is characterized in that: The calculation methods of the capacity-load ratio B1, line load rate B2, line overload rate B3, distributed photovoltaic consumption rate of return B4, and grid line loss contribution rate B5 in the economic index B are as follows: The capacity load ratio refers to the ratio of the total installed capacity of the transformer in the distribution network to the peak load. It reflects the operating status and utilization efficiency of the transformer for the transformer capacity load rate. The value within the recommended range indicates that the substation equipment has better adaptability to the access of new energy. The calculation formula of the capacity load ratio is as follows: In the formula is the annual peak load of the distribution network, in kW; Ctrans is the total capacity of the distribution network transformer, in kVA; The line load rate is the ratio of the daily average power load of the distribution network to the peak load of the same year, which reflects the line load of the distribution network. The calculation formula is as follows: Where Pave L is the average daily power load of the distribution network, in kW; The line overload rate is the ratio of the number of lines with a load rate greater than 80% to the total number of lines in the distribution network when the distribution network is operating normally. The lower the line overload rate, the better the line operation condition and the higher the adaptability to the access of new energy such as energy. The calculation formula is as follows: Where Nlines_over is the number of overloaded lines in the distribution network; The consumption process of distributed energy access to the distribution network can bring benefits such as delaying distribution network investment, peak shaving and valley filling, and improving distribution network reliability. At the same time, it also increases the operation and maintenance costs of the distribution network. The distributed energy consumption rate of return is the ratio of the economic benefits brought by the grid-connected consumption of distributed energy to the overall operation and maintenance costs of the distribution network. The calculation formula is as follows: Where Cin, Cpls, Cres are the delayed grid investment benefits, peak load reduction and valley filling benefits, and improved reliability benefits brought by distributed energy grid connection, and Cop is the operation and maintenance cost of the distribution network; The access of distributed energy changes the power flow of distribution network lines, causing changes in distribution network line losses, which generally show a trend of first decreasing and then increasing. The contribution rate of distribution network line losses is defined as the ratio of the grid loss caused by the grid connection of distributed energy to the grid loss before the grid connection. The calculation method is as follows: Where △PADN is the change in line loss of the distribution network caused by the grid connection of distributed energy, in kw; P0 is the total loss of the distribution network before the grid connection of distributed energy, in kW.

5. The method for evaluating the adaptability of rural distributed integrated energy systems to distribution networks according to claim 2 is characterized in that: The low-carbon index C includes distributed energy penetration rate C1, distributed energy consumption rate C2, CO 2 The calculation method of emission reduction C3 is as follows: The calculation method of distributed energy penetration rate C1 is as follows: The penetration rate reflects the impact of distributed energy on the distribution network. The distributed energy penetration rate is defined as a weighted combination of static penetration rate and effective penetration rate. The formula is as follows: Where η is the weight, which is 0.5; Sst and Sva are the static permeability and effective permeability respectively; PL are the maximum load power and actual load power of the distribution network, in kW; Ppv, They are the rated power and actual power of distributed energy, in kW; The calculation method of distributed energy consumption rate is as follows: The distributed energy consumption rate is the ratio of the actual output of distributed energy to the maximum allowable output during the operation of the distribution network. In the formula The maximum allowable output of distributed energy in the distribution network, in kW; CO 2 The calculation method of emission reduction benefits is as follows: CO 2 Emission reduction benefits are defined as the proportion of environmental benefits of distributed energy over its entire life cycle to the initial investment; Where T is the carbon dioxide emission per unit of electricity produced by the coal-fired unit, which is 822.8 g / (kw·h); pcarbon is the real-time price of the carbon emission trading market, Qpv,i is the power generation of the i-th distributed energy statistical period, kw·h; c1 is the investment cost of distributed energy per unit capacity, which is 5.4 yuan / W.

6. The method for evaluating the adaptability of rural distributed integrated energy systems to distribution networks according to claim 1 is characterized in that: In S300, the distribution network adaptability evaluation index scoring curve is formulated based on the connotation of each index as follows: 。 7. The method for evaluating the adaptability of rural distributed integrated energy systems to distribution networks according to claim 1 is characterized in that: The method for determining weights by combining the AHP method modified by the ordered weighting operator and the entropy weight method in S300 is as follows: S320, improve AHP based on ordered weighted operator to revise subjective weights; S330, use entropy weight method to carry out objective weighting; S340 , calculating the combined weight based on S320 and S330 .

8. The method for evaluating the adaptability of rural distributed integrated energy systems to distribution networks according to claim 7 is characterized in that: The method for revising subjective weights based on the ordered weighted operator improved AHP in S320 is as follows: The initial weight matrix of n indicators for m experts who have passed the consistency test For the i-th indicator weight (b il ,b i2 ,....,b im ) in descending order, and the new sequence is (p0, p1, ..., p m-1 ), select t data in the sequence and combine them into C tm-1 , then the ordered weighted vector v t for: Get the absolute weight of the i-th indicator for: Then the subjective weight after OWA operator correction is:

9. The method for evaluating the adaptability of rural distributed integrated energy systems to distribution networks according to claim 7, characterized in that: The calculation method of the combined weight based on the improved AHP method and the entropy weight method in S340 is as follows: Based on the minimum information recognition principle, the subjective and objective weights are combined so that the distribution distance of the two weights is minimized. The calculation formula of the combined weight is: Among them, w j is the combined weight, w ij is the subjective weight of the jth indicator, w 2j is the objective weight of the j-th indicator, j = 1, 2, ..., n.

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