Method for improving power supply reliability of power distribution network

Abstract

The invention relates to a power distribution network power supply reliability improving method, and belongs to the technical field of power distribution network power supply. The method comprises the following steps: integrating a power supply reliability evaluation index system of a power distribution network, and collecting all power supply reliability index data of a to-be-evaluated power distribution network; calculating the weight of each power supply reliability evaluation index by adopting a hierarchical sequence relationship method; calculating an evaluation value of the c-th type of users to the i-th power distribution network, and accumulating the evaluation values of all types of users to the i-th power distribution network to obtain an evaluation value of the users to the i-th power distribution network; and judging whether the power distribution network is subjected to power supply optimization or not based on the evaluation value of the user on the ith power distribution network, and if so, performing power supply optimization on the power distribution network. Accurate evaluation and efficient optimization of the power supply reliability of the power distribution network are achieved, a scientific basis is provided for operation management of a power system, remarkable social and economic benefits are achieved, and the power supply reliability and user satisfaction of the power distribution network can be remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power supply of distribution networks, and particularly relates to a method for improving the reliability of power supply of distribution networks. Background Art

[0002] With the rapid development of power systems and the increasing demand for power quality from users, the reliability of distribution networks has become a key indicator for measuring power service levels. Traditional power supply reliability assessment methods rely primarily on a single indicator (such as average outage duration) or a simple weighted average, which has the following drawbacks:

[0003] Unreasonable indicator weight distribution: The actual impact of different indicators on power supply reliability is not taken into account, resulting in evaluation results deviating from the actual situation.

[0004] The differentiated needs of users are not reflected: the sensitivity of different user types (such as industrial, residential, and commercial) to power supply reliability is not distinguished, and the evaluation results lack specificity.

[0005] Insufficient basis for optimization decision-making: Existing methods only provide evaluation results and do not establish clear optimization thresholds, resulting in delayed or excessive power supply optimization measures.

[0006] In existing technologies, when the distribution network in a certain region is evaluated using traditional methods, the average duration of power outages (SAIDI) is 2.5 hours / year and the average number of power outages per user (SAIFI) is 1.8 times / year. However, after optimization, actual user satisfaction only increases by 5%, indicating that traditional methods fail to effectively identify key issues.

[0007] Therefore, there is an urgent need for a method to improve the power supply reliability of the distribution network to solve the above problems. Summary of the Invention

[0008] The purpose of the present invention is to address the deficiencies of the prior art and provide a method for improving the reliability of power supply in a distribution network. This method achieves accurate assessment and efficient optimization of the reliability of power supply in the distribution network through multi-index weight analysis and user classification evaluation, provides a scientific basis for power system operation and management, and has significant social and economic benefits.

[0009] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0010] A method for improving power supply reliability of a distribution network comprises the following steps:

[0011] Step (1) collects the power supply reliability evaluation index system of the distribution network and collects all power supply reliability index data of the distribution network to be evaluated, wherein the power supply reliability index data includes the average duration of power outages of the distribution network, the average number of power outages for users, the amount of power shortage caused by power outages, and the voltage qualification rate;

[0012] Step (2), using the hierarchical sequence relationship method to calculate the weight of each power supply reliability evaluation index;

[0013] Step (3), based on the weight of each power supply reliability evaluation index and all power supply reliability index data of the distribution network, calculate the evaluation value of the c-th user on the i-th distribution network, and accumulate the evaluation values of all types of users on the i-th distribution network to obtain the user's evaluation value on the i-th distribution network;

[0014] Step (4): based on the user's evaluation value of the i-th distribution network, determine whether the distribution network is to be optimized for power supply; if so, optimize the power supply of the distribution network.

[0015] Furthermore, preferably, the specific method of step (2) is:

[0016] Step (2.1) is to establish a hierarchical model, where the hierarchical structure includes the goal layer, the criterion layer and the measure layer;

[0017] Step (2.2), construct the judgment matrix: determine the number of relevant influencing factors m at each level, and construct the power supply reliability evaluation index system set U, in, is the average duration of power outage indicator subset, is the average power outage times indicator subset for users, is a subset of power outage and power shortage indicators, For the voltage qualification rate indicator subset, two indicator subsets in the same level are taken from the set U for comparison. The importance ratio is represented by M, and the corresponding importance is assigned according to the preset ratio. The importance of each level is combined to form a judgment matrix.

[0018] Step (2.3), calculate the maximum eigenvalue γ of the judgment matrix:

[0019]

[0020] Among them, v αβ It is the matrix obtained by normalizing each column vector of the judgment matrix. The values of α and β are 1, 2...m, w α is the matrix v αβ The elements of are added row by row to obtain the vector and then normalized into a matrix, w β is the matrix v αβ Add the elements of column by column to obtain the vector and then normalize the matrix;

[0021] Step (2.4), consistency test of the judgment matrix:

[0022] When the judgment matrix has only one non-zero eigenvalue, it indicates that the matrix is completely consistent; if the judgment matrix has more than one eigenvalue, the consistency index CI is used:

[0023]

[0024] Among them, k represents the order of the judgment matrix. The smaller the CI value, the better the consistency, and vice versa.

[0025] In step (2.5), the CI value is multiplied by the initial proportion value corresponding to the indicator subset to obtain the weight of each power supply reliability evaluation indicator, wherein each indicator subset corresponds to a preset initial proportion value.

[0026] Furthermore, preferably, the preset initial ratio value of the average duration of power outage indicator subset is 0.4, and the preset initial ratio value of the average number of power outages per user indicator subset is 0.3.

[0027] Furthermore, preferably, the preset initial ratio value of the power outage and power shortage indicator subset is 0.2, and the preset initial ratio value of the voltage qualification rate indicator subset is 0.1.

[0028] Furthermore, preferably, the specific method of step (3) is:

[0029] Step (3.1): for the c-th user in the ith distribution network, obtain the average duration of power outage based on all power supply reliability index data of the distribution network, obtain the preset average duration of power outage based on the power supply reliability evaluation index system of the distribution network, and calculate the difference A between the average duration of power outage and the preset average duration of power outage;

[0030] Step (3.2): For the c-th user in the ith distribution network, obtain the average number of power outages for the user based on all power supply reliability index data of the distribution network, obtain the average number of power outages for the preset user based on the power supply reliability evaluation index system of the distribution network, and calculate the difference B between the average number of power outages for the user and the average number of power outages for the preset user;

[0031] Step (3.3): for the c-th user in the ith distribution network, obtain the power outage shortage amount based on all power supply reliability index data of the distribution network, obtain the preset power outage shortage amount based on the power supply reliability evaluation index system of the distribution network, and calculate the difference C between the power outage shortage amount and the preset power outage shortage amount;

[0032] Step (3.4): For the c-th user in the ith distribution network, obtain the voltage qualification rate based on all power supply reliability index data of the distribution network, obtain the preset voltage qualification rate based on the power supply reliability evaluation index system of the distribution network, and calculate the difference D between the voltage qualification rate and the preset voltage qualification rate;

[0033] In step (3.5), the difference values A, B, C, and D are substituted into the evaluation value calculation formula of the c-th user for the i-th distribution network to calculate the evaluation value LMS of the c-th user for the n-th distribution network. The formula is as follows:

[0034]

[0035] Among them, K1 represents the weight of the average duration of power outages, K2 represents the weight of the average number of power outages per user, K3 represents the weight of the power outage shortage, K4 represents the weight of the voltage qualification rate, and E represents the evaluation reference value corresponding to the c-th category user.

[0036] Furthermore, preferably, before calculating the evaluation value of the c-th user for the n-th distribution network based on the weight of each power supply reliability evaluation index and all index data of the distribution network, it also includes classifying the users into three categories according to their fields of employment.

[0037] Furthermore, preferably, the specific method for classifying users is:

[0038] Users engaged in precision instruments, computer manufacturing, communications, medicine, electronics, electrical appliances, transportation, machinery, plastics, glass, hardware manufacturing, chemicals and ceramics are classified into the first category;

[0039] Users engaged in food, clothing, shoemaking, leather goods, toys, printing, furniture, papermaking, textiles and agricultural product processing are classified as the second category;

[0040] Users engaged in logistics, real estate, service industry, commerce, exhibition, residents and agriculture are divided into the third category, where the values of c are one, two and three.

[0041] Furthermore, preferably, the specific method of step (4) is:

[0042] The evaluation value threshold is loaded to determine whether the user's evaluation value of the i-th distribution network exceeds the evaluation value threshold. If so, it is determined that the distribution network needs to be optimized for power supply; if not, it is determined that the distribution network does not need to be optimized for power supply.

[0043] Furthermore, preferably, the power supply optimization of the distribution network specifically includes the following process:

[0044] The power flow constraint of the distribution network system is as follows:

[0045]

[0046] Among them, P i，t , Q i，t are the active power and reactive power of the load at node i in period t respectively; are the active power and reactive power generated by renewable energy generation, respectively; is the reactive power of the capacitor bank at node i in the distribution network system during period t; U i，t and U j，t is the node voltage amplitude between node i and node j in period t; G ij 、B ij are the conductance and susceptance values between nodes i and j in the distribution network system during period t; θ ij is the phase angle difference between nodes i and j;

[0047] During optimization, the above active power, reactive power, and node voltage amplitude are made to satisfy the above equations as much as possible.

[0048] In the present invention, the power supply reliability evaluation index system of the distribution network is an existing one, which includes the average continuous power outage time of the distribution network, the average power outage times of users, the power shortage amount and the voltage qualification rate.

[0049] In the present invention, the number m of relevant influencing factors of the determination level is determined based on the number of influencing factors affecting the average duration of power outages, the number of indices affecting the average number of power outages for users, the number of indices affecting the amount of power shortages caused by power outages, and the number of indices affecting the voltage qualification rate. It can be determined based on the actual situation of the distribution network, for example, including fault repair time; equipment aging and failure rate (such as transformer and cable failures); backup power supply switching time (such as automatic switch action time); planned power outage duration; load transfer capacity (whether power can be supplied through other lines); number and redundancy of interconnecting lines; proportion of distributed power supply access; equipment failure frequency; equipment quality (such as high failure rate of old switchgear); external environment (such as line tripping caused by lightning strikes and tree barriers); sensitivity of protection devices; coverage rate of automatic switches; duration and scope of power outages; load density in the fault-affected area (such as power outage losses in commercial areas are much greater than those in residential areas); load curve characteristics (power outages and power shortages are greater during peak hours); capacity of emergency generators or energy storage systems; island operation capability of distributed power sources; deviation between actual load and predicted load during power outages; power supply radius and line impedance.

[0050] In step (2.2), M is used to represent the importance ratio, and the corresponding importance is assigned according to the preset ratio, as shown in Table 1.

[0051] Table 1

[0052]

[0053] In step (2.3) of the present invention, each column of the judgment matrix is normalized, that is, each column element is divided by the sum of the column to obtain the normalized matrix element, thereby obtaining the corresponding matrix.

[0054] In step (2.5) of the present invention, the average duration of power outage (SAIDI):

[0055] The preset initial scale value is 0.4;

[0056] Reason: SAIDI is one of the key indicators for measuring distribution network reliability. It directly reflects the average duration of power outages for users and has a significant impact on user experience and power supply service quality.

[0057] Average number of power outages per customer (SAIFI):

[0058] The preset initial scale value is 0.3;

[0059] Reasoning: SAIFI reflects the average number of power outages experienced by consumers each year and is an important indicator of distribution network reliability. Although it does not directly reflect the duration of power outages as SAIDI, frequent power outages can still affect customer satisfaction.

[0060] Power outage and power shortage:

[0061] The preset initial scale value is 0.2;

[0062] Reasoning: Power outage shortfall measures the amount of electricity lost due to a power outage, reflecting the economic impact of a power outage on power supply companies and users. While this indicator is also important, it is generally not as direct and critical as SAIDI and SAIFI in reliability assessments.

[0063] Voltage qualification rate:

[0064] The preset initial scale value is 0.1;

[0065] Rationale: Voltage compliance is an important indicator for measuring power supply quality, but it reflects voltage stability and the performance of power supply equipment more than direct power outages. Therefore, its weight may be relatively low in distribution network reliability assessments.

[0066] In steps (3.1) to (3.4) of the present invention, the average duration of power outages is obtained based on all power supply reliability index data of the distribution network, the average number of power outages for users is obtained based on all power supply reliability index data of the distribution network, the power outage shortage is obtained based on all power supply reliability index data of the distribution network, and the voltage qualification rate is obtained based on all power supply reliability index data of the distribution network. These data are directly collected in step (1).

[0067] In the present invention, E represents the evaluation reference value corresponding to the c-th type user, and its value is set by the distribution network.

[0068] In the present invention, the preset average duration of power outages, the preset average number of power outages for users, the preset power outage shortage amount, and the preset voltage qualification rate evaluation value threshold are all set according to the actual situation of the distribution network, and the present invention does not impose any restrictions on this.

[0069] The present invention has the following characteristics

[0070] 1. Accurately quantify power supply reliability and improve scientific assessment

[0071] By constructing a multi-dimensional indicator system encompassing the average duration of outages (SAIDI), the average number of outages per user (SAIFI), the amount of power lost due to outages, and voltage compliance, the system comprehensively covers the core elements of distribution network reliability. The hierarchical order relationship method (G1 method) is used to calculate indicator weights, avoiding arbitrary subjective weighting and ensuring that the weight assignment closely matches the actual impact of the indicator. This allows for an objective and accurate evaluation of the distribution network's power supply capacity, providing a reliable basis for subsequent optimization decisions.

[0072] 2. Dynamically reflect user perception and enhance the pertinence of evaluation

[0073] Based on indicator weights and measured data, the personalized evaluation value of the cth category of users (e.g., industrial, residential, and commercial users) for the i-th distribution network is calculated and accumulated to obtain a comprehensive evaluation value for the entire network. This method, through differentiated user classification and data-driven evaluation, dynamically reflects the sensitivity and needs of different user groups regarding power supply reliability, making the evaluation results more closely aligned with actual user experience and providing guidance for targeted optimization.

[0074] 3. Closed-loop drive power supply optimization to achieve proactive operation and maintenance

[0075] By setting the evaluation value threshold, the power supply optimization process is automatically triggered, forming a "monitoring-evaluation-optimization" closed-loop management. For example:

[0076] Fast fault response: If SAIDI or SAIFI exceeds the standard, equipment in high-prone areas can be upgraded or the network structure can be optimized first;

[0077] Improve voltage quality: Deploy voltage regulators or distributed power sources in areas with low voltage compliance rates.

[0078] Load balancing management: Through power outage and power shortage analysis, optimize load transfer strategies and reduce the scope of power outages.

[0079] The method of the present invention can promote the transformation of the distribution network from passive repair to active prevention, and significantly improve power supply reliability and user satisfaction.

[0080] Compared with the prior art, the present invention has the following beneficial effects:

[0081] The present invention achieves accurate evaluation and efficient optimization of distribution network power supply reliability through multi-index weight analysis and user classification evaluation, provides a scientific basis for power system operation and management, has significant social and economic benefits, and can significantly improve the power supply reliability and user satisfaction of the distribution network. The specific advantages of the present invention are as follows

[0082] (1) Scientific weight allocation: Dynamically adjust indicator weights through the hierarchical order relationship method to improve evaluation accuracy.

[0083] (2) User differentiated evaluation: Calculate evaluation values by type to accurately reflect the needs of different users.

[0084] (3) Quantify the optimization threshold: clarify the optimization trigger conditions to avoid excessive or delayed optimization.

[0085] (4) Significant improvement: The accuracy of optimization decisions increased by 53%, user satisfaction increased by 26%, and power supply reliability increased by 100%.

[0086] At the same time, the method of the present invention was compared with the traditional method, and the results are shown in Table 2.

[0087] Table 2

[0088] index Traditional methods Method of the present invention Improvement Optimize decision accuracy 60％ 92％ +53％ User satisfaction 70％ 88％ +26％ Power supply reliability improvement rate 15％ 30％ +100％ Optimize resource utilization 55％ 85％ +55％

[0089] After applying the method of the present invention to a certain distribution network, SAIDI decreased from 2.0 hours / year to 1.4 hours / year (a decrease of 30%); the average number of power outages for users decreased from 1.5 times / year to 1.0 times / year (a decrease of 33%); the power shortage due to power outages decreased from 1200kWh / year to 800kWh / year (a decrease of 33%); and the voltage compliance rate increased from 99.5% to 99.8% (an increase of 0.3%). BRIEF DESCRIPTION OF THE DRAWINGS

[0090] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0091] Figure 1 It is a flow chart of the method for improving power supply reliability of the distribution network of the present invention;

[0092] Figure 2 This is a flow chart of the present invention for calculating the user's evaluation value of the i-th distribution network. DETAILED DESCRIPTION

[0093] The present invention is described in further detail below with reference to the embodiments.

[0094] Those skilled in the art will understand that the following examples are intended to illustrate the present invention only and should not be construed as limiting the scope of the present invention. Where specific techniques or conditions are not specified in the examples, the techniques or conditions described in the literature in the art or in the product specifications were used. Materials or equipment used without manufacturer identification are commercially available conventional products.

[0095] In addition, the described features, structures or characteristics can be combined in any suitable manner in one or more example embodiments. In the following description, many specific details are provided to provide a full understanding of the example embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure can be practiced while omitting one or more of the specific details, or other methods, components, steps, etc. can be adopted. In other cases, well-known structures, methods, implementations or operations are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0096] This embodiment provides a method for improving the reliability of power supply in a distribution network. Figure 1 This is a workflow diagram of a method for improving power supply reliability of a distribution network according to an embodiment of the present invention. Figure 1 As shown, the method includes the following steps:

[0097] Step (1) collects the power supply reliability evaluation index system of the distribution network and collects all power supply reliability index data of the distribution network to be evaluated, wherein the power supply reliability index data includes the average duration of power outages of the distribution network, the average number of power outages for users, the amount of power shortage caused by power outages, and the voltage qualification rate;

[0098] Step (2), using the hierarchical sequence relationship method to calculate the weight of each power supply reliability evaluation index;

[0099] Step (3), based on the weight of each power supply reliability evaluation index and all power supply reliability index data of the distribution network, calculate the evaluation value of the c-th user on the i-th distribution network, and accumulate the evaluation values of all types of users on the i-th distribution network to obtain the user's evaluation value on the i-th distribution network;

[0100] Step (4): based on the user's evaluation value of the i-th distribution network, determine whether the distribution network is to be optimized for power supply; if so, optimize the power supply of the distribution network.

[0101] In summary, the present invention obtains a power supply reliability evaluation index system for a distribution network, obtains all index data of the distribution network to be evaluated, and uses a hierarchical order relationship method to calculate the weight of each power supply reliability evaluation index; based on the weight of each power supply reliability evaluation index and all index data of the distribution network, the evaluation value of the c-th user on the i-th distribution network is calculated, and the evaluation value of the user on the i-th distribution network is accumulated by all types of users. Based on the user's evaluation value of the i-th distribution network, it is determined whether the distribution network is to be optimized for power supply, and if so, the distribution network is to be optimized for power supply. The present invention realizes real-time monitoring of the operating status of the distribution network, rapid response and recovery to faults, and optimization and improvement of power supply capacity.

[0102] In some embodiments, the weight of each power supply reliability evaluation index is calculated using the hierarchical sequence relationship method, which specifically includes the following process:

[0103] Step (2.1) is to establish a hierarchical model, where the hierarchical structure includes the goal layer, the criterion layer and the measure layer;

[0104] Step (2.2), construct the judgment matrix: determine the number of relevant influencing factors m at each level, and construct the power supply reliability evaluation index system set U, in, is the average duration of power outage indicator subset, is the average power outage times indicator subset for users, is a subset of power outage and power shortage indicators, For the voltage qualification rate indicator subset, two indicator subsets in the same level are taken from the set U for comparison. The importance ratio is represented by M, and the corresponding importance is assigned according to the preset ratio. The importance of each level is combined to form a judgment matrix.

[0105] Step (2.3), calculate the maximum eigenvalue γ of the judgment matrix:

[0106]

[0107] Among them, v αβ It is the matrix obtained by normalizing each column vector of the judgment matrix. The values of α and β are 1, 2...m, w α is the matrix v αβ The elements of are added row by row to obtain the vector and then normalized into a matrix, w β is the matrix v αβ Add the elements of column by column to obtain the vector and then normalize the matrix;

[0108] Step (2.4), consistency test of the judgment matrix:

[0109] When the judgment matrix has only one non-zero eigenvalue, it means that the matrix is completely consistent. If the judgment matrix has more than one eigenvalue, the consistency index CI can be used:

[0110]

[0111] Among them, k represents the order of the judgment matrix. The smaller the CI value, the better the consistency, and vice versa.

[0112] In step (2.5), the CI value is multiplied by the initial proportion value corresponding to the indicator subset to obtain the weight of each power supply reliability evaluation indicator, wherein each indicator subset corresponds to a preset initial proportion value.

[0113] In some embodiments, Figure 2 FIG. 1 is a flowchart of another method for improving power supply reliability of a distribution network according to an embodiment of the present invention. Figure 2 As shown in Figure 2, the calculation of the evaluation value of the c-th user on the i-th distribution network based on the weight of each power supply reliability evaluation index and all index data of the distribution network specifically includes the following process:

[0114] Step (3.1): for the c-th user in the ith distribution network, obtain the average duration of power outage based on all power supply reliability index data of the distribution network, obtain the preset average duration of power outage based on the power supply reliability evaluation index system of the distribution network, and calculate the difference A between the average duration of power outage and the preset average duration of power outage;

[0115] Step (3.2): For the c-th user in the ith distribution network, obtain the average number of power outages for the user based on all power supply reliability index data of the distribution network, obtain the average number of power outages for the preset user based on the power supply reliability evaluation index system of the distribution network, and calculate the difference B between the average number of power outages for the user and the average number of power outages for the preset user;

[0116] Step (3.3): for the c-th user in the ith distribution network, obtain the power outage shortage amount based on all power supply reliability index data of the distribution network, obtain the preset power outage shortage amount based on the power supply reliability evaluation index system of the distribution network, and calculate the difference C between the power outage shortage amount and the preset power outage shortage amount;

[0117] Step (3.4): For the c-th user in the ith distribution network, obtain the voltage qualification rate based on all power supply reliability index data of the distribution network, obtain the preset voltage qualification rate based on the power supply reliability evaluation index system of the distribution network, and calculate the difference D between the voltage qualification rate and the preset voltage qualification rate;

[0118] In step (3.5), the difference values A, B, C, and D are substituted into the evaluation value calculation formula of the c-th user for the i-th distribution network to calculate the evaluation value LMS of the c-th user for the n-th distribution network. The formula is as follows:

[0119]

[0120] Among them, K1 represents the weight of the average duration of power outages, K2 represents the weight of the average number of power outages per user, K3 represents the weight of the power outage shortage, K4 represents the weight of the voltage qualification rate, and E represents the evaluation reference value corresponding to the c-th category user.

[0121] In some embodiments, before calculating the evaluation value of the c-th user for the n-th distribution network based on the weight of each power supply reliability evaluation index and all index data of the distribution network, the method further includes classifying the users:

[0122] Users engaged in precision instruments, computer manufacturing, communications, medicine, electronics, electrical appliances, transportation, machinery, plastics, glass, hardware manufacturing, chemicals and ceramics are classified into the first category;

[0123] Users engaged in food, clothing, shoemaking, leather goods, toys, printing, furniture, papermaking, textiles and agricultural product processing are classified as the second category;

[0124] Users engaged in logistics, real estate, service industry, commerce, exhibition, residents and agriculture are divided into the third category, where the values of c are one, two and three.

[0125] In some embodiments, judging whether to optimize power supply of the distribution network based on the user's evaluation value of the i-th distribution network specifically includes the following process:

[0126] The evaluation value threshold is loaded to determine whether the user's evaluation value of the i-th distribution network exceeds the evaluation value threshold. If so, it is determined that the distribution network needs to be optimized for power supply; if not, it is determined that the distribution network does not need to be optimized for power supply.

[0127] In some embodiments, optimizing the power supply of the distribution network specifically includes the following processes:

[0128] The power flow constraint of the distribution network system is as follows:

[0129]

[0130] Among them, P i，t , Q i，t are the active power and reactive power of the load at node i in period t respectively; are the active power and reactive power generated by renewable energy generation, respectively; is the reactive power of the capacitor bank at node i in the distribution network system during period t; U i，t and U j，t is the node voltage amplitude between node i and node j in period t; G ij 、B ij are the conductance and susceptance values between nodes i and j in the distribution network system during period t; θ ij is the phase angle difference between nodes i and j. During optimization, the active power, reactive power, and node voltage amplitude are made to satisfy the above equations as much as possible.

[0131] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0132] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0133] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0134] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is only for some logical functions. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0135] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0136] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the foregoing embodiments. The foregoing embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for improving power supply reliability of a distribution network, characterized in that: The steps include: Step (1) collects the power supply reliability evaluation index system of the distribution network and collects all power supply reliability index data of the distribution network to be evaluated, wherein the power supply reliability index data includes the average duration of power outages of the distribution network, the average number of power outages for users, the amount of power shortage caused by power outages, and the voltage qualification rate; Step (2), using the hierarchical sequence relationship method to calculate the weight of each power supply reliability evaluation index; Step (3), based on the weight of each power supply reliability evaluation index and all power supply reliability index data of the distribution network, calculate the evaluation value of the c-th user on the i-th distribution network, and accumulate the evaluation values of all types of users on the i-th distribution network to obtain the user's evaluation value on the i-th distribution network; Step (4): based on the user's evaluation value of the i-th distribution network, determine whether the distribution network is to be optimized for power supply; if so, optimize the power supply of the distribution network.

2. The method for improving power supply reliability of a distribution network according to claim 1, characterized in that: The specific method of step (2) is: Step (2.1) is to establish a hierarchical model, where the hierarchical structure includes the goal layer, the criterion layer and the measure layer; Step (2.2), construct the judgment matrix: determine the number of relevant influencing factors m at each level, and construct the power supply reliability evaluation index system set U, in, is the average duration of power outage indicator subset, is the average power outage times indicator subset for users, is a subset of power outage and power shortage indicators, For the voltage qualification rate indicator subset, two indicator subsets in the same level are taken from the set U for comparison. The importance ratio is represented by M, and the corresponding importance is assigned according to the preset ratio. The importance of each level is combined to form a judgment matrix. Step (2.3), calculate the maximum eigenvalue γ of the judgment matrix: Among them, v αβ It is the matrix obtained by normalizing each column vector of the judgment matrix. The values of α and β are 1, 2...m, w α is the matrix v αβ The elements of are added row by row to obtain the vector and then normalized into a matrix, w β is the matrix v αβ Add the elements of column by column to obtain the vector and then normalize the matrix; Step (2.4), consistency test of the judgment matrix: When the judgment matrix has only one non-zero eigenvalue, it indicates that the matrix is completely consistent; if the judgment matrix has more than one eigenvalue, the consistency index CI is used: Where k represents the order of the judgment matrix; In step (2.5), the CI value is multiplied by the initial proportion value corresponding to the indicator subset to obtain the weight of each power supply reliability evaluation indicator, wherein each indicator subset corresponds to a preset initial proportion value.

3. The method for improving power supply reliability of a distribution network according to claim 2, characterized in that: The preset initial ratio value of the average duration of power outage indicator subset is 0.4, and the preset initial ratio value of the average number of power outages per user indicator subset is 0.

3.

4. The method for improving power supply reliability of a distribution network according to claim 2, characterized in that: The preset initial ratio value of the power outage and power shortage indicator subset is 0.2, and the preset initial ratio value of the voltage qualification rate indicator subset is 0.

1.

5. The method for improving power supply reliability of a distribution network according to claim 1, characterized in that: The specific method of step (3) is: Step (3.1): for the c-th user in the ith distribution network, obtain the average duration of power outage based on all power supply reliability index data of the distribution network, obtain the preset average duration of power outage based on the power supply reliability evaluation index system of the distribution network, and calculate the difference A between the average duration of power outage and the preset average duration of power outage; Step (3.2): For the c-th user in the ith distribution network, obtain the average number of power outages for the user based on all power supply reliability index data of the distribution network, obtain the average number of power outages for the preset user based on the power supply reliability evaluation index system of the distribution network, and calculate the difference B between the average number of power outages for the user and the average number of power outages for the preset user; Step (3.3): for the c-th user in the ith distribution network, obtain the power outage shortage amount based on all power supply reliability index data of the distribution network, obtain the preset power outage shortage amount based on the power supply reliability evaluation index system of the distribution network, and calculate the difference C between the power outage shortage amount and the preset power outage shortage amount; Step (3.4): For the c-th user in the ith distribution network, obtain the voltage qualification rate based on all power supply reliability index data of the distribution network, obtain the preset voltage qualification rate based on the power supply reliability evaluation index system of the distribution network, and calculate the difference D between the voltage qualification rate and the preset voltage qualification rate; In step (3.5), the difference values A, B, C, and D are substituted into the evaluation value calculation formula of the c-th user for the i-th distribution network to calculate the evaluation value LMS of the c-th user for the n-th distribution network. The formula is as follows: Among them, K1 represents the weight of the average duration of power outages, K2 represents the weight of the average number of power outages per user, K3 represents the weight of the power outage shortage, K4 represents the weight of the voltage qualification rate, and E represents the evaluation reference value corresponding to the c-th category user.

6. The method for improving power supply reliability of a distribution network according to claim 1 or 5, characterized in that: Before calculating the evaluation value of the c-th user on the n-th distribution network based on the weight of each power supply reliability evaluation index and all index data of the distribution network, it also includes classifying the users into three categories according to their fields of work.

7. The method for improving power supply reliability of a distribution network according to claim 6, characterized in that: The specific methods for classifying users are: Users engaged in precision instruments, computer manufacturing, communications, medicine, electronics, electrical appliances, transportation, machinery, plastics, glass, hardware manufacturing, chemicals and ceramics are classified into the first category; Users engaged in food, clothing, shoemaking, leather goods, toys, printing, furniture, papermaking, textiles and agricultural product processing are classified as the second category; Users engaged in logistics, real estate, service industry, commerce, exhibition, residents and agriculture are divided into the third category, where the values of c are one, two and three.

8. The method for improving power supply reliability of a distribution network according to claim 1, characterized in that: The specific method of step (4) is: The evaluation value threshold is loaded to determine whether the user's evaluation value of the i-th distribution network exceeds the evaluation value threshold. If so, it is determined that the distribution network needs to be optimized for power supply; if not, it is determined that the distribution network does not need to be optimized for power supply.

9. The method for improving power supply reliability of a distribution network according to claim 1, characterized in that: The power supply optimization of the distribution network specifically includes the following processes: The power flow constraint of the distribution network system is as follows: Among them, P i，t , Q i，t are the active power and reactive power of the load at node i in period t respectively; are the active power and reactive power generated by renewable energy generation, respectively; is the reactive power of the capacitor bank at node i in the distribution network system during period t; U i，t and U j，t is the node voltage amplitude between node i and node j in period t; G ij 、B ij are the conductance and susceptance values between nodes i and j in the distribution network system during period t; θ ij is the phase angle difference between nodes i and j; During optimization, the above active power, reactive power, and node voltage amplitude are made to satisfy the above equations as much as possible.

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