A distribution network reliability optimization method, system, device and medium

Abstract

The present invention relates to a distribution network reliability optimization method, system, equipment and medium, comprising the following steps: structural analysis of the distribution network under the background of regional energy interconnection, and calculation of the reliability efficiency of the distribution network under the background of regional energy interconnection; building a cost-benefit model of the distribution network reliability optimization scheme under the background of regional energy interconnection; using the cost-benefit analysis method of the distribution network reliability optimization scheme under the background of regional energy interconnection, and performing cost-benefit analysis results of reliability optimization measures; based on the cost-benefit model of the distribution network reliability optimization scheme, building and solving the distribution network reliability optimization scheme optimization model based on regional energy interconnection, and obtaining the distribution network reliability optimization scheme. The present invention can be widely used in the field of distribution network reliability optimization technology.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network reliability optimization, and in particular to a distribution network reliability optimization method, system, equipment and medium based on regional energy interconnection. Background Art

[0002] With the continuous development of economy, the total energy consumption in the world continues to grow. Integrating and optimizing the power network, heat network, energy transmission network and data network including new energy and fossil energy is the inevitable way to achieve sustainable development of world energy. The integration of energy and information is an effective way to solve the energy crisis and environmental crisis.

[0003] Energy interconnection is the key to the realization and application of concepts such as multi-energy mutual assistance and energy cascade utilization. At present, domestic research in this field is still in its initial stage, requiring extensive participation from national institutions, energy suppliers and local users. Regional energy Internet is the specific embodiment of the geographical distribution and functional realization of energy Internet, which contains energy coupling and integration mechanisms. Different regional energy Internets have different energy conversion, distribution and utilization scenarios. According to geographical factors and energy generation / transmission / distribution / use characteristics, energy Internet can be divided into cross-regional level, regional level and user level. Regional energy Internet is composed of coupled and interconnected energy supply networks such as intelligent distribution system, medium and low pressure natural gas system, heating / cooling / water system, etc., which plays a "connecting" role in energy transmission, distribution, conversion and balance. It takes active distribution network, hybrid energy storage, energy conversion and other technologies as the core, and there is a strong coupling between energy systems. The participation of regional energy Internet in the energy supply link of power system, especially distribution system, will affect the original energy supply reliability assessment method and reliability level of distribution system, and form new factors affecting power supply reliability and measures to improve power supply reliability.

[0004] The power system is mainly composed of power plants, substations, transmission and distribution lines, and power loads. The distribution system at the end of the power system chain is the key link for connecting the power system with users and distributing electric energy. Once a power outage occurs in the distribution network, it will directly cause power outages for users. According to statistics, more than 80% of user power outages occur in the distribution system. Therefore, conducting research on the optimization model and algorithm of distribution network reliability measures based on regional energy Internet reliability constraints will be of great significance to improving the power supply reliability of the power system, improving the management level of power supply enterprises, and guiding and promoting power grid construction under the background and trend of energy interconnection.

[0005] Under the background of energy interconnection, the reliability optimization model and algorithm of regional energy interconnected distribution network are studied, aiming to obtain the economic level of each reliability optimization measure by conducting cost-benefit analysis on the reliability optimization measures of traditional distribution network and new distribution network reliability optimization measures such as regional energy interconnection; the reliability optimization method of energy interconnected distribution network based on reliability constraints and with the goal of minimizing costs is studied to achieve the optimal configuration method of the economic optimal reliability optimization scheme of energy interconnected distribution network considering the reliability optimization level. The proposed reliability optimization method will lay a theoretical and technical foundation for the planning, construction, transformation and expansion of energy interconnected distribution network, and has engineering practical value. The expected results of the research have the value of promotion and application within the company and even the industry, and provide support for the improvement and transformation of weak links in the power supply reliability of the distribution network. Summary of the invention

[0006] In view of the above problems, the purpose of the present invention is to provide a distribution network reliability optimization method, system, equipment and medium based on regional energy interconnection, which can provide a technical basis and support for the distribution network reliability optimization of the regional energy interconnection system.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides a distribution network reliability optimization method, which comprises the following steps: analyzing the structure of the distribution network under the background of regional energy interconnection, and calculating the reliability efficiency of the distribution network under the background of regional energy interconnection; based on the reliability efficiency, building a cost-benefit model of the distribution network reliability optimization scheme under the background of regional energy interconnection; using the cost-benefit analysis method of the distribution network reliability optimization scheme under the background of regional energy interconnection, and performing a cost-benefit analysis result of the reliability optimization measures; based on the cost-benefit model of the distribution network reliability optimization scheme and the cost-benefit analysis result, building and solving an optimization model of the distribution network reliability optimization scheme based on regional energy interconnection, and obtaining a distribution network reliability optimization scheme.

[0009] Furthermore, the method for structurally analyzing the distribution network under the background of regional energy interconnection and calculating the reliability efficiency improvement of the distribution network under the background of regional energy interconnection includes: obtaining independent energy supply and regional energy interconnection energy supply network loads, component failure rates, and energy hub configuration parameters; based on the obtained relevant parameters, performing power supply shortage expectation analysis when the distribution network fails, and obtaining the power supply shortage expectation under independent energy supply and regional energy interconnection energy supply conditions; based on the obtained power supply shortage expectation when the distribution network fails under the independent energy supply and regional energy interconnection energy supply conditions, calculating the reliability efficiency improvement of the distribution network under the background of regional energy interconnection.

[0010] Furthermore, the cost-benefit model of the distribution network reliability optimization scheme under the background of regional energy interconnection includes a cost model and a benefit model;

[0011] The cost model is:

[0012] C cost =C I +C O +C M +C D

[0013] In the formula, C cost is the life cycle cost; C I is the initial investment cost, including the design cost in the design phase, the equipment procurement cost, and the construction and installation cost in the construction phase; C O is the operating cost, including equipment loss and operator training cost; C M is the maintenance cost; C D For the cost of abandonment;

[0014] The benefit model is:

[0015]

[0016] In the formula, C benefit The overall benefit after implementing the reliability optimization plan for the distribution network; C benefit_1 Power outage compensation expenses saved for the power grid company; C benefit_2 Increased electricity sales revenue for the power grid company; i is the unit electricity price at load point i; p i is the unit power outage loss at load point i; E' EENS,i E is the power shortage expectation before the implementation of the distribution network reliability optimization plan; EENS,i Expected power supply shortage after the implementation of the distribution network reliability optimization plan.

[0017] Furthermore, the method of using the cost-benefit analysis method of the distribution network reliability optimization scheme under the background of regional energy interconnection to obtain the cost-benefit analysis results of the reliability optimization measures includes: obtaining the system network structure, component reliability data and load data before the implementation of the reliability optimization measures; using the regional energy interconnection distribution network reliability assessment method based on Monte Carlo simulation to calculate the reliability index and system reliability index of the load point before the implementation of the reliability optimization measures; selecting the reliability optimization measures to be implemented, and correcting the component reliability data based on the factors affecting the reliability assessment of the reliability optimization measures; using the regional energy interconnection distribution network reliability assessment method based on Monte Carlo simulation again to calculate the reliability index and system reliability index of the load point after the implementation of the reliability optimization measures; considering the implementation cost and implementation scale of the reliability optimization measures, calculating the implementation cost of the reliability optimization measures; based on the improvement effect of the reliability index, calculating the implementation benefit of the reliability optimization measures; using the distribution network reliability optimization method cost-benefit analysis method based on marginal cost and marginal benefit to perform a cost-benefit analysis of the reliability optimization measures.

[0018] Furthermore, the method of cost-benefit analysis of reliability optimization measures using a distribution network reliability optimization method cost-benefit analysis method based on marginal cost and marginal benefit includes: decomposing the reliability marginal cost curve into multiple curves according to different reliability optimization measures, finding a reliability marginal cost curve closest to the X-axis from the starting segment of the reliability cost-benefit analysis curve, and searching backward from the starting point of the curve; if it intersects with another reliability marginal cost curve, then continue to search backward from this curve, and so on, until the reliability target or investment cost target is reached; all line segments distributed on the search path are connected to form a reliability marginal cost optimization curve considering multiple optimization measures; based on the obtained reliability marginal cost optimization curve, the total investment cost under the reliability level, the investment cost required for the corresponding optimization measure, and the optimal reliability level corresponding to each reliability optimization measure are obtained.

[0019] Furthermore, the optimization model of the distribution network reliability optimization scheme based on regional energy interconnection includes an objective function and constraints, and the objective function is:

[0020] maxF(X)=C cost (X)

[0021] In the formula, X is the reliability optimization scheme; F(X) is the optimization target of the reliability optimization scheme; C cost (X) is the equivalent annual cost after the reliability optimization plan is implemented;

[0022] The constraints include reliability index requirements of important load points, reliability index requirements of energy hubs and system reliability index requirements;

[0023] Among them, the constraints required for the reliability index of the important load points are:

[0024] λ LP (X)≤λ LP

[0025] u LP (X)≤u LP

[0026] ASAI-LP(X)≥ASAI-LP

[0027] ENS-LP(X)≤ENS-LP

[0028] In the formula, λ LP (X), λ LP are the expected value of the load point outage rate and the target for improving the expected value of the load point outage rate after the implementation of the reliability optimization scheme X; u LP (X),u LP are the expected value of load point power outage time and the target for improving the expected value of load point power outage time after the implementation of reliability optimization plan X; ASAI-LP(X) and ASAI-LP are the expected value of load point power supply reliability rate and the target for improving the expected value of load point power supply reliability rate after the implementation of reliability optimization plan X; ENS-LP(X) and ENS-LP are the expected value of load point power shortage and the target for improving the expected value of load point power shortage after the implementation of reliability optimization plan X;

[0029] The constraints required by the energy hub reliability index are:

[0030] ARDI e (X)≤ARDI e

[0031] ARDI h (X)≤ARDI h

[0032] EENS e (X)≤EENS e

[0033] EENS h (X)≤EENS h

[0034] ASAI e (X)≥ASAI e

[0035] ASAI h (X)≥ASAI h

[0036] Where, ARDI e (X)ARDI e are the expected annual average reduction duration of the energy hub electric load after the implementation of reliability optimization plan X and the target for improving the expected annual average reduction duration of the energy hub electric load; ARDI h (X)ARDI h They are the expected value of the annual average reduction duration of the energy hub heat load after the implementation of reliability optimization plan X and the target of improving the expected value of the annual average reduction duration of the energy hub heat load; EENS e (X), EENS e They are the expected annual power shortage of the energy hub after the implementation of reliability optimization solution X and the target for improving the expected annual power shortage of the energy hub; EENS h (X), EENS h They are the expected annual thermal energy shortage of the energy hub after the implementation of reliability optimization solution X and the expected improvement target of the annual thermal energy shortage of the energy hub; ASAI e (X), ASAI e They are the annual average power supply availability of the energy hub after the implementation of reliability optimization solution X and the improvement target of the annual average power supply availability of the energy hub; ASAI h (X), ASAI h They are the annual average heating availability of the energy hub and the improvement target of the annual average heating availability of the energy hub after the implementation of the reliability optimization scheme X;

[0037] The constraints required by the system reliability index are:

[0038] SAIFI(X)≤SAIFI

[0039] SAIDI(X)≤SAIDI

[0040] ASAI(X)≥ASAI

[0041] ENS(X)≤ENS

[0042] Where, SAIFI(X) and SAIFI are the expected value of the average power outage frequency and the target for improving the expected value of the average power outage frequency after the implementation of the reliability optimization scheme X; SAIDI(X) and SAIDI are the expected value of the average power outage time and the target for improving the expected value of the average power outage time after the implementation of the reliability optimization scheme X; ASAI(X) and ASAI are the expected value of the average power supply reliability rate and the target for improving the expected value of the average power supply reliability rate after the implementation of the reliability optimization scheme X; ENS(X) and ENS are the expected value of the power shortage and the target for improving the expected value of the power shortage after the implementation of the reliability optimization scheme X.

[0043] In a second aspect, the present invention provides a distribution network reliability optimization system, comprising:

[0044] The reliability efficiency calculation module is used to perform structural analysis on the distribution network under the background of regional energy interconnection and calculate the reliability efficiency of the distribution network under the background of regional energy interconnection;

[0045] Cost-benefit model building module, used to build a cost-benefit model for distribution network reliability optimization scheme under the background of regional energy interconnection;

[0046] The cost-benefit analysis module is used to obtain the cost-benefit analysis results of reliability optimization measures by adopting the cost-benefit analysis method of distribution network reliability optimization scheme under the background of regional energy interconnection;

[0047] The scheme optimization module is used to build and solve the distribution network reliability optimization scheme optimization model based on regional energy interconnection based on the cost-benefit model of the distribution network reliability optimization scheme, and obtain the distribution network reliability optimization scheme.

[0048] Furthermore, the reliability efficiency improvement calculation module includes: a parameter acquisition module, which is used to obtain the network load, component failure rate, and energy hub configuration parameters of independent energy supply and regional energy interconnection energy supply; a power shortage expectation calculation module, which is used to analyze the power shortage expectation when the distribution network fails based on the acquired relevant parameters, and obtain the power shortage expectation under independent energy supply and regional energy interconnection energy supply; a calculation module, which is used to calculate the reliability efficiency improvement of the distribution network under the background of regional energy interconnection based on the obtained power shortage expectation when the distribution network fails under the independent energy supply and regional energy interconnection energy supply conditions.

[0049] In a third aspect, the present invention provides a processing device, which includes at least a processor and a memory, wherein a computer program is stored in the memory, and when the processor runs the computer program, the steps of the distribution network reliability optimization method are executed.

[0050] In a fourth aspect, the present invention provides a computer storage medium having computer-readable instructions stored thereon, wherein the computer-readable instructions can be executed by a processor to implement the steps of the distribution network reliability optimization method.

[0051] The present invention adopts the above technical solution, which has the following advantages:

[0052] 1. The present invention analyzes the reliability efficiency improvement of the distribution network under the background of regional energy interconnection, establishes a cost-benefit model of the reliability optimization plan, realizes the cost-benefit analysis of each reliability optimization measure, and establishes an optimization model of the distribution network reliability optimization plan based on the cost-benefit analysis results. It is of great significance to improve the power supply reliability of the power system, enhance the management level of power supply enterprises, and guide and promote the construction of power grids under the background and trend of energy interconnection.

[0053] 2. The present invention aims to optimize the net benefit of the distribution network reliability optimization scheme, takes the reliability index requirements of important load points, the reliability index requirements of energy hubs and the reliability index requirements of the system as constraints, and establishes an optimization model for the distribution network reliability optimization scheme based on regional energy interconnection.

[0054] 3. The present invention adopts a non-fast dominating sorting genetic algorithm to intelligently solve the optimization model, thereby selecting a combination of reliability optimization measures that meets the constraints and target requirements from a pre-selected set of reliability optimization measures to form a distribution network reliability optimization plan.

[0055] Therefore, the present invention can be widely applied to the field of distribution network reliability optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Throughout the accompanying drawings, the same reference numerals are used to represent the same components. In the accompanying drawings:

[0057] Figure 1 The reliability efficiency improvement calculation process of the distribution network under the background of regional energy interconnection provided by the embodiment of the present invention;

[0058] Figure 2 It is a schematic diagram of regional energy internet energy supply provided by an embodiment of the present invention;

[0059] Figure 3 It is a schematic diagram of the network structure of an independent energy supply and distribution network provided by an embodiment of the present invention;

[0060] Figure 4 It is a regional energy interconnection power supply and distribution network structure provided by an embodiment of the present invention;

[0061] Figure 5 is a reliability cost-benefit analysis curve provided by an embodiment of the present invention;

[0062] Figure 6 It is a partial enlarged diagram of the reliability cost-benefit analysis curve provided by an embodiment of the present invention;

[0063] Figure 7 It is a cost-benefit analysis process of a distribution network reliability improvement solution under the background of regional energy interconnection provided by an embodiment of the present invention;

[0064] Figure 8 is a flow chart of NSGA-II provided by an embodiment of the present invention;

[0065] Fig. 9 This is a chromosome gene screening diagram provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0066] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present invention.

[0067] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0068] In some embodiments of the present invention, a distribution network reliability optimization method is provided, which includes the following steps: analyzing the structure of the distribution network under the background of regional energy interconnection, and calculating the reliability efficiency of the distribution network under the background of regional energy interconnection; based on the reliability efficiency, building a cost-effectiveness model of the distribution network reliability optimization scheme under the background of regional energy interconnection; using the cost-effectiveness analysis method of the distribution network reliability optimization scheme under the background of regional energy interconnection, and performing a cost-effectiveness analysis result of the reliability optimization measures; based on the cost-effectiveness model of the distribution network reliability optimization scheme and the cost-effectiveness analysis result, building an optimization model of the distribution network reliability optimization scheme based on regional energy interconnection and solving it, and obtaining a distribution network reliability optimization scheme. The present invention takes the net benefit optimization of the distribution network reliability optimization scheme as the goal, takes the reliability optimization requirements of three levels of important load point reliability index requirements, energy hub reliability index requirements and system reliability index requirements as constraints, and establishes an optimization model of the distribution network reliability optimization scheme based on regional energy interconnection. The present invention uses a non-fast dominating sorting genetic algorithm to intelligently solve the optimization model, so as to select a combination of reliability optimization measures that meet the constraints and target requirements in the pre-selected set of reliability optimization measures to form a distribution network reliability optimization scheme. It is of great significance to improve the power supply reliability of the power system, enhance the management level of power supply enterprises, and guide and promote the construction of power grids under the background and trend of energy interconnection.

[0069] Correspondingly, some other embodiments of the present invention provide a distribution network reliability optimization system, device and medium.

[0070] Example 1

[0071] This embodiment provides a distribution network reliability optimization method based on regional energy interconnection, which includes the following steps:

[0072] 1) Analyze the structure of the distribution network under the background of regional energy interconnection, and calculate the reliability efficiency of the distribution network under the background of regional energy interconnection;

[0073] 2) Based on the calculated reliability efficiency, a cost-effectiveness model of distribution network reliability optimization scheme in the context of regional energy interconnection is established;

[0074] 3) Using the cost-benefit analysis method of distribution network reliability optimization scheme under the background of regional energy interconnection, the cost-benefit analysis results of reliability optimization measures are obtained;

[0075] 4) Based on the cost-benefit model of the distribution network reliability optimization plan and the results of the cost-benefit analysis, build an optimization model for the distribution network reliability optimization plan based on regional energy interconnection;

[0076] 5) Solve the optimization model of distribution network reliability optimization scheme to obtain the distribution network reliability optimization scheme.

[0077] Further, in the above step 1), if Figure 1 As shown in the figure, the reliability efficiency calculation method of distribution network under the background of regional energy interconnection includes the following contents:

[0078] 1.1) Obtain parameters such as independent energy supply and regional energy interconnection energy supply network load, component failure rate, energy hub configuration, etc.

[0079] 1.2) Based on the relevant parameters obtained, the power supply shortage expectation analysis is carried out when the distribution network fails, and the power supply shortage expectation under independent energy supply and regional energy interconnection energy supply is obtained.

[0080] 1.3) Based on the expected power shortage when the distribution network fails under independent energy supply and regional energy interconnection energy supply, the reliability gain of the distribution network under the background of regional energy interconnection is calculated.

[0081] Furthermore, in the above step 1.2), the method for analyzing the expected power shortage when the regional energy Internet distribution network fails includes the following contents:

[0082] (1) Expected power shortage of distribution network under independent power supply of electricity, gas and heat

[0083] Expected energy not supplied (EENS) indicates the expected value of the power shortage caused by the power supply system outage to users, and is an important power supply reliability evaluation indicator. EENS comprehensively represents the number of power outages, average duration and average power outage power, reflecting the severity of power outages in the power supply system. At the same time, the expected power shortage reflects the power supply company's reduced sales of electricity due to power outages, and then the power supply company's loss of electricity sales revenue caused by power outages can be calculated, becoming a bridge connecting reliability and economy.

[0084] The calculation method is as follows: first, traverse all possible faulty components in the network and count the load points where the power supply is interrupted due to their faults; then, based on the component failure rate, that is, the average number of component failures per year, and the component failure repair time, that is, the power outage time caused by the component failure, combined with the load data of the load point where the power supply is interrupted due to the component failure, calculate the expected power supply shortage of the system caused by the component failure; finally, add up the expected power supply shortage of the system caused by all possible faulty components in the distribution network to obtain the expected overall power supply shortage of the system.

[0085] Among them, the calculation formula for the expected overall power shortage of the system under the condition of independent power supply of electricity, gas and heat is:

[0086]

[0087] In the formula, EENS独立供能 is the expected power shortage of the distribution network under the condition of independent power supply of electricity, gas and heat; N is the total number of components that may fail in the distribution network; μ i is the failure rate of component i; TTR i is the fault repair time for each fault of component i; L is the total number of load points in the distribution network; Le l,0,t is the load demand of load point l at time t of fault repair; α l,i is the impact coefficient of component i failure on load point l. When component i failure causes load point l to lose power supply from the distribution network, α l,i The value is 1, when the failure of component i will not cause the load point l to lose the power supply of the distribution network l,i The value is 0.

[0088] by Figure 2 As an example, the distribution network structure under the condition of independent energy supply of electricity, gas and heat is as follows: Figure 3 As shown in the figure, assuming that line 3 fails, through the operation of the circuit breaker and the disconnector, the circuit breaker CB is disconnected during the fault recovery period, and the disconnector S2 is opened to isolate the distribution line between the fault section CB to S2 from the distribution network, and the load points Le1 and Le2 lose power supply. At the same time, since this section of the line is a radial network, it is impossible to supply energy to the load points Le3, Le4 and Le5 located downstream of the fault through load transfer. Therefore, in the case of line 3 failure, the load points Le1-Le5 will lose power supply and be in a state of shortage, and the component failure influence coefficient α is 1.

[0089] (2) Expected power supply shortage of distribution network under the situation of regional energy interconnection of electricity, gas and heat

[0090] by Figure 2 As an example, the distribution network structure under the condition of electricity-gas-heat regional energy interconnection supply is as follows Figure 4 shown.

[0091] Compared with independent energy supply, the energy hub model is added to the distribution network structure in the case of interconnected energy supply. When the distribution network fails and some load points lose energy supply, the energy hub can continue to supply energy to the load area directly supplied (such as Figure 4 The energy hub can supply electricity to the distribution network through the interconnection line between the distribution network and other load points in the same area (for example, if line 3 fails, the energy hub EH can supply energy to Le4 and Le5 in the downstream area of ​​the fault). The energy supplied by the energy hub comes from the distributed generation devices and energy storage devices configured inside the energy hub, as well as the energy support obtained from the natural gas network through energy coupling elements such as CHP units.

[0092] When calculating the power shortage expectation, the power shortage expectation of the distribution network under the regional energy interconnection reduces the power support of the energy hub to the electric load. Since the power support of the energy hub needs to meet the supply and demand balance constraint, that is, the power support is not greater than the load demand, the actual power supply of the energy hub to the electric load is the actual support capacity P elec,t for:

[0093]

[0094] In the formula, β l,i,EH is the energy supply coefficient of load point l and energy hub when component i fails. When component i fails and load point l loses energy supply from the distribution network, and load point l and energy hub are located in the same fault area, they can obtain power supply through the energy hub. l,i,EH Take 1; on the contrary, when the failure of component i does not cause the load point l to lose the energy supply of the distribution network, or although the failure of component i causes the load point l to lose the energy supply of the distribution network, the load point l is not in the same energy supply area as the energy hub and cannot obtain energy through the energy hub, β l,i,EH Take 0.

[0095] The expected power shortage of the system under the interconnected energy supply is:

[0096]

[0097] In the formula, EENS 互联供能 The power supply of the system in the case of electricity-gas-heat interconnection is insufficient; P elec,t The actual supporting capacity of the energy hub for the electrical load at time t for fault repair.

[0098] by Figure 4 Taking the network in as an example, it is still assumed that line 3 fails. As in the case of independent energy supply, the distribution line between CB and S2 is isolated from the distribution network through the operation of the circuit breaker and the disconnector during the fault recovery period, and the load points Le1 and Le2 lose power supply, and α is 1. At the same time, since the power supply capacity of the energy hub does not necessarily meet the full load demand of the load points, Le3, Le4, and Le5 are still facing the risk of shortage, and α is 1. After the CB to S2 line is isolated, Le3, Le4, and Le5 are in the same energy supply area as the energy hub, and the energy hub will use the generated power to supply the electric loads Le3, Le4, and Le5. At this time, when line 3 fails, the energy supply coefficient β of the energy hub of Le3, Le4, and Le5 is 1, and the β of the other load points is 0.

[0099] Furthermore, in the above step 1.3), when analyzing the reliability gain of the distribution network under the background of regional energy interconnection, the reliability improvement of regional energy interconnection energy supply compared with independent energy supply is reflected by the expected power shortage of the distribution network, and the efficiency increase is also calculated by the difference in the expected power shortage between the interconnected energy supply and the independent energy supply. The economic benefits increased by the reliability optimization of the distribution network are divided into two parts. The first part is the direct benefit generated by the power supply company's increased power sales revenue due to the optimization of power supply reliability, and the second part is the indirect benefit generated by the reduction of social and economic losses after the power supply reliability of the power supply company is optimized. The direct benefit generated by the increase in power sales revenue can be obtained by multiplying the difference in the expected power shortage of the system before and after reliability optimization by the unit power sales price. The indirect benefit generated by the reduction of social and economic losses after the optimization of power supply reliability is generally calculated based on the GDP output value corresponding to the unit electricity output, and the specific value can be determined based on local electricity and economic data.

[0100] R 增效 =R 售电收入 +R 社会效益 (4)

[0101] R 售电收入 =(EENS 独立供能 -EENS 互联供能 )c1 (5)

[0102] R 社会效益 =(EENS 独立供能 -EENS 互联供能 )c2 (6)

[0103] In the formula, R 增效 The reliability of the distribution network brought by the interconnection of electricity, gas and heat; 售电收入 Increased electricity sales revenue for distribution network reliability optimization; R 社会效益 The social benefits brought by the reliability optimization of the distribution network; c1 and c2 are the GDP output values ​​corresponding to the unit electricity price and unit electricity volume respectively.

[0104] It can be seen from the above formula that the key to calculating the reliability efficiency improvement brought by the electricity-gas-heat interconnected energy supply to the distribution network lies in the calculation of the expected power shortage of the system before and after the interconnection.

[0105] Furthermore, in the above step 2), the cost-benefit model of the distribution network reliability optimization scheme under the background of regional energy interconnection is analyzed from the aspects of cost and benefit.

[0106] 2.1) Cost Model

[0107] The economic benefits of capital income and expenditure are not only related to the amount of capital, but also to the time when the capital occurs. Even without considering the inflation factor, the current amount of capital is more valuable than the same amount of capital in the future. Therefore, the capital invested in the project at different times and the benefits obtained also have different values, which is the essence of the time value of capital.

[0108] In the economic analysis of engineering projects, there are usually several ways to express the time value of money:

[0109] I. Present value P (present value): Present value represents the value of funds at the beginning of a specific time series. In interest calculation, it represents the principal. In engineering economic analysis, it represents the investment amount at the starting point 0 on the cash flow diagram. It can also represent the value of the cash flow of the investment project converted to 0.

[0110] II. Future value F: The future value represents the value of funds at the end point of a specific time series. It means the new value generated by the initial funds (principal) after n times of interest calculation under a certain interest rate, that is, the future value or the sum of principal and interest. Because of the existence of interest, the future value F is always greater than P in any investment system.

[0111] III. Annuity: Annuity refers to the amount of equal income or expenditure in each year, usually expressed as an equal amount series, that is, equal amounts of income or expenditure at equal intervals during a specific time series period.

[0112] The present value and terminal value of funds are both one-time payments. In the economic analysis of engineering projects, unless otherwise specified, the present value occurs at the beginning of the first year of project implementation, the terminal value occurs at the end of the last year of the project life, and the equal annual value occurs at the end of each year. In the above cost calculation, it is often necessary to convert the funds involved into the same form of quantity to achieve comparative analysis. In economic analysis, the basic formula for the mutual conversion of the three types of funds is shown in formula (7):

[0113] X=Y*(X / Y,r,t) (7)

[0114] In the formula, r is the interest rate or social discount rate; t is the time when the cost occurs, usually in years; (X / Y, r, t) is the conversion factor from y-type value to x-type value under the consideration of variables r and t. The formulas for converting between the present value, terminal value and equivalent annual value of funds are shown in Table 1.

[0115] Table 1 Conversion formulas between present value, terminal value and equivalent annual value of funds

[0116]

[0117]

[0118] The cost elements of the entire reliability optimization scheme mainly include planning and design costs, construction and installation costs, operation and maintenance costs, and abandonment costs. Among them, planning and design costs mainly include: research fees, feasibility study fees, preliminary design fees, construction drawing design fees, etc.; construction and installation costs mainly include: equipment purchase costs, land acquisition costs, infrastructure construction and equipment installation costs, resident demolition and resettlement, greening and other costs; operation and maintenance costs mainly include: power loss costs, equipment maintenance, equipment renewal and other costs; abandonment costs mainly include: equipment removal costs and equipment residual value. Cost control in the design stage directly affects the costs of the construction stage and the operation stage. The full life cycle cost model of the entire reliability optimization scheme is shown in formula (8):

[0119] C cost =C I +C O +C M +C D (8)

[0120] In the formula, C cost is the life cycle cost; C I is the initial investment cost, including the design cost in the design phase, the equipment procurement cost, and the construction and installation cost in the construction phase; C O is the operating cost, including equipment loss and operator training cost; C M is the maintenance cost; C D For the cost of abandonment.

[0121] LCC management can be used in all stages of the life cycle management, but its focus is on the design stage, because more than 90% of the LCC can be determined in this stage. This requires that in the initial investment stage of the equipment, the owner must pay full attention to the LCC evaluation of the equipment procurement plan and the LCC evaluation of the equipment maintenance costs in the operation stage. After comprehensively considering the costs of each stage, calculate the LCC of the equipment and compare the LCC of each investment plan.

[0122] In order to accurately compare the LCC of each reliability optimization scheme, it is necessary to convert all expenditures at each stage of the scheme's life cycle into present value or terminal value based on the social discount rate and the time when the costs occur, and then make a comparison.

[0123] Present value or terminal value calculation is a balancing device that allows the initial investment and various costs incurred in the future operation phase to be added together. Future costs can be divided into two categories: one-time investment costs and recurring costs. Recurring costs are costs that occur every year within the study period. The initial investment in the reliability optimization project is a one-time cost. The initial investment occurs in the base year of the study period and is usually considered to occur at the beginning of the base year. Various costs in the operation phase occur in any year between the base year and the end of the study period and are usually considered to occur at the end of each year. Sometimes the cost of replacing equipment in the operation phase is also a one-time cost, which is usually considered to occur at the end of the year. The present value model of the full life cycle cost of the distribution reliability optimization solution is shown in formula (9):

[0124] C cost =C I +C O PV sum +C M PV sum +C D PV (9)

[0125] In the formula, is the present value of annual investment costs and; r is the social discount rate; is the discount factor; t is the time when the cost occurs, usually in years; T is the life cycle, usually in years. If the construction period is long, the initial investment should also be discounted.

[0126] Reliability optimization plans can be divided into short-term, medium-term and long-term plans. Due to the long cycle of medium-term and long-term projects, in order to dynamically consider the changes in the system in different time periods, the project cost is often considered in several stages.

[0127] ① Initial investment cost C in stage k Ik

[0128] Initial investment cost refers to the one-time cost paid during the planning, design and construction of the kth stage of the distribution network, mainly including equipment procurement cost, design, construction and installation cost. Except for the first stage, the C of other stages is used in calculating LCC. Ik Need to discount, C Ik The expression is as follows:

[0129]

[0130] In the formula, C Ik,i is the purchase cost of equipment i; β is the ratio of design, construction and installation costs to equipment purchase cost.

[0131] ② Annual operating cost C of stage k Ok

[0132] CMk Refers to the annual operating cost of the k-th order reliability optimization measure, which mainly includes the operating network loss costs caused by newly added equipment such as VSC, the costs incurred during the operation of the reliability optimization measures such as the power consumption cost of the distribution automation equipment, and the personnel costs, vehicle costs, safety costs, equipment usage costs, etc. incurred by non-stop operations.

[0133] ③ Annual maintenance cost C in stage k Mk

[0134] C Mk Refers to the cost of maintenance personnel, equipment failure repair and other costs throughout the entire equipment life cycle. At present, the vast majority of power supply companies manage the maintenance and repair costs of power supply equipment by taking a certain proportion of the initial investment based on the annual total cost plan. The maintenance cost is mostly approximately 4% of the initial investment cost.

[0135] ④ Kth stage scrapping cost C Dk

[0136] The scrapping cost refers to the cost of various post-processing of equipment during its retirement. In addition to paying the necessary post-processing costs (such as waste disposal, etc.), some equipment residual value can also be recovered. The residual value of equipment that is retired before its service life also includes the residual value of equipment depreciation. Dk The calculation formula is shown in formula (11):

[0137]

[0138] Where: C Dk,l The residual value of a reliability-optimized device is analyzed based on actual distribution network equipment data. After the service life, the average residual value of the distribution network equipment is about 2% of the initial investment of the equipment.

[0139] 2) Benefit model

[0140] From the perspective of the power supply company, the benefits brought by the optimization of the reliability of the distribution network are divided into two parts: one is the increased revenue from electricity sales, and the other is the saved compensation for power outages. The compensation for power outages given by the power supply company to power users should be equivalent to the losses caused by the power outages to the power users.

[0141] Power outage loss refers to the social and economic losses caused by power outage due to insufficient power supply. The power outage loss assessment methods suitable for China are: average electricity price conversion multiple method, power generation ratio method and total ownership cost method. The above power outage loss calculation method assumes that the physical life of the component is its investment life, which mainly depends on the quality, use and maintenance of the component, and does not take into account the economic life of the component, that is, the time from the use of the component to the discontinuation of use due to economic uneconomical. Considering the actual investment time of the component, it is more accurate to evaluate the power outage loss from the perspective of economic life. The expected power shortage and expected power outage loss in the initial year are used as the basis for solving the component investment life, and then the accurate power outage loss is reversed from the obtained component investment life.

[0142] Expected energy not supplied (EENS) is a monetary value indicator suitable for evaluating reliability. The corresponding economic indicator is expected damage cost (EDC), which is the power outage loss caused by the outage of system components. The expected energy not supplied and expected power outage loss at load point i are expressed as follows:

[0143] E EENSi =D i U i (12)

[0144] C EDCi = pE EENS (13)

[0145] Where: D i is the average load at load point i; U i is the annual average power outage time of load point i; p is the unit power outage loss.

[0146] Considering the different unit power outage losses of different user types, users are divided into large industrial users, small industrial users, residential users, commercial users and agricultural users, and 10kV distribution transformers are used as a user statistical unit. A detailed investigation of the power outage losses of various types of power users at different times was conducted, and the power outage losses per hour were used as reference data for subsequent research, as shown in Table 2.

[0147] Table 2 Survey data on power outage losses for power users

[0148] User Classification (Yuan / kWh) Large industrial users 15.575 Small industrial users 63.595 Business Users 59.864 Agricultural users 4.543 Residential users 3.374 Government organizations 10.444 Office users 147.455

[0149] The power outage compensation expenses saved by the power grid company are:

[0150]

[0151] Where: p iis the unit power outage loss at load point i; E' EENS,i is the expected power shortage before the distribution network reliability optimization scheme is implemented; E EENS,i It is the expected power shortage after the distribution network reliability optimization scheme is implemented.

[0152] The increased electricity sales revenue of the power grid company is also closely related to the expected power shortage, which is the product of the expected power shortage and the electricity sales price:

[0153]

[0154] Where: c i is the unit electricity price at load point i. The electricity price is shown in Table 3.

[0155] Table 3 Survey data on electricity prices

[0156] User Classification Electricity sales price (yuan / kWh) Large industrial users 0.677 Small industrial users 0.860 Business Users 0.860 Agricultural users 0.611 Residential users 0.478 Government organizations 0.860 Office users 0.860

[0157] The overall benefits of implementing the reliability optimization scheme for the distribution network are:

[0158]

[0159] Further, in the above step 3), if Figure 5 As shown in FIG. 1 , the method for cost-benefit analysis of the distribution network reliability optimization scheme under the background of regional energy interconnection includes the following steps:

[0160] 3.1) Obtain system network structure, component reliability data, load data, etc. before implementing reliability optimization measures;

[0161] 3.2) Using the regional energy interconnection distribution network reliability assessment method based on Monte Carlo simulation, calculate the reliability index of the load point and the system reliability index before the implementation of reliability optimization measures;

[0162] 3.3) Select the reliability optimization measures to be implemented, and modify the component reliability data based on the factors affecting the reliability optimization measures on the reliability assessment;

[0163] 3.4) The reliability assessment method of regional energy interconnected distribution network based on Monte Carlo simulation is used again to calculate the reliability index of the load point and the system reliability index after the implementation of reliability optimization measures;

[0164] 3.5) Considering the implementation cost and implementation scale of reliability optimization measures, calculate the implementation cost of reliability optimization measures;

[0165] 3.6) Based on the improvement effect of reliability indicators, calculate the implementation benefits of reliability optimization measures;

[0166] 3.7) Use the cost-benefit analysis method of distribution network reliability optimization based on marginal cost and marginal benefit to conduct cost-benefit analysis of reliability optimization measures.

[0167] Furthermore, in the above step 3.7), when the cost-benefit analysis method of the distribution network reliability optimization method based on marginal cost and marginal benefit is adopted, the concepts of reliability marginal cost and marginal benefit are used for explanation, wherein the reliability marginal cost is defined as: the additional investment cost required to increase the reliability level by one unit. The reliability marginal benefit is defined as: the benefit obtained by increasing the reliability level by one unit.

[0168] like Figure 6 As shown in the figure, it is the reliability cost-benefit analysis curve, where C U is the reliability marginal cost curve; C C is the reliability marginal benefit curve; C T is the marginal power supply total cost curve. When the reliability marginal cost is equal to the reliability marginal benefit, the marginal power supply total cost is the lowest, and the corresponding reliability level R m is the optimal reliability level. When the increase in grid construction investment is less than the reduction in power shortage costs, the improvement in reliability requires less investment, and the increase in investment can generate benefits (i.e. Figure 6 When the marginal increase in investment cost is completely offset by the marginal reduction in power outage loss cost, the total power supply cost reaches the minimum (i.e. Figure 6 When the increase in grid construction investment is greater than the reduction in power shortage costs, the improvement of system reliability requires a large increase in investment costs, and the increase in investment can no longer generate benefits (i.e. Figure 6 Segments B and D to the right of point E).

[0169] Using the lean analysis model, the reliability marginal cost curve C U By decomposing according to different reliability optimization measures, we can more accurately understand the impact of different reliability optimization measures on reliability, so as to obtain the most economical and reasonable reliability optimization plan to achieve a certain set reliability rate, so as to realize lean control of distribution network planning cost-effectiveness.

[0170] Will Figure 6 C in the reliability cost-benefit analysis curve U The C curve (i.e., the reliability marginal cost curve) is further decomposed into multiple curves according to different reliability optimization measures, thus laying the foundation for the lean analysis of various types of partitions under different reliability optimization measures. UThe curve represents the marginal reliability cost when the measure is used alone to reach its ultimate reliability level, and its integral with the reliability level is the investment cost required for the measure. If the cross-impact of all reliability optimization measures is taken into account, the selection of the optimization method and the operability of its algorithm are very difficult and basically impossible to operate. Therefore, when analyzing the marginal cost, the present invention assumes that a certain measure is implemented alone under the condition that other conditions are given. Since there is no direct correlation between the various decomposed reliability optimization measures, such as the improvement of the primary network, it cannot change the degree of distribution automation, nor can it change the scope of implementation of live work, so the error is relatively small.

[0171] In addition, since the benefit of improving the unit reliability rate in a given area is a constant, the reliability marginal benefit curves corresponding to multiple reliability optimization measures can be proposed as one curve, which is convenient for simplifying the analysis process and is more practical.

[0172] To summarize, in the actual optimization process, we first need to determine the analysis object, which may be a partition or several lines. Then, analyze the main reliability influencing factors, select the reliability optimization measure group, and decompose it. After that, for each reliability optimization measure, determine its limit average marginal benefit (power shortage cost) and limit average marginal cost (investment cost) through predictive reliability evaluation, and obtain the reliability cost-benefit curve. For different optimization objectives (optimizing investment or optimizing reliability), adopt reasonable optimization strategies and formulate optimization plans. The decomposition curves of different reliability optimization measure groups are as follows: Figure 7 shown.

[0173] Specifically, in this embodiment, a step-by-step search process is used to optimize the reliability optimization measures, and the specific steps are as follows:

[0174] 3.7.1) Decompose the reliability marginal cost curve into multiple curves according to different reliability optimization measures, and find the reliability marginal cost curve closest to the X-axis from the starting section of the reliability cost-benefit analysis curve, such as Figure 7 The reliability marginal cost curve for the “automation level” in , and search backwards from the starting point of the curve.

[0175] 3.7.2) If it intersects with another reliability marginal cost curve (such as Figure 6 If it intersects with the "management level" curve, then continue searching backward from this curve, and so on, until the reliability target or investment cost target is reached.

[0176] 3.7.3) All line segments distributed on the search path are connected to form a reliability marginal cost optimization curve considering multiple optimization measures.

[0177] 3.7.4) Based on the obtained reliability marginal cost optimization curve, the integral of the reliability rate from the starting point to the target point is the total investment cost at the corresponding reliability level.

[0178] 3.7.5) On the reliability marginal cost optimization curve, the integral of the reliability rate between two adjacent intersection points is the investment cost required for the corresponding optimization measure.

[0179] 3.7.6) The intersection of the reliability marginal benefit curve and any marginal cost curve is the optimal reliability level corresponding to the use of the measure alone; these intersections are essentially the marginal power supply total cost curve C under each measure. T The purpose of optimization is to try to find the lowest point of total marginal power supply cost under the comprehensive application of various measures. However, due to the marginal benefit curve C T is the same curve, so C T The reliability rate corresponding to the intersection point is the corresponding C U The reliability rate corresponding to the intersection point can therefore be omitted from the marginal total cost curve of power supply.

[0180] Furthermore, in the above step 4), an optimization model for the distribution network reliability optimization scheme based on regional energy interconnection is established, including determining the objective function and constraints.

[0181] 4.1) Objective Function

[0182] Based on the characteristics of regional energy internet, economic factors are taken into consideration, and a model for optimizing measures is established with the goal of minimizing the comprehensive investment cost of the distribution network reliability optimization plan, including primary investment costs and operation and maintenance costs. The objective function consists of the various costs of various transformation measures. The reliability requirements for various types of regions in the action plan are included in the model as constraints. In addition, the constraints also include the feasible space constraints for various transformation measures. The objective function model can be mathematically expressed as follows:

[0183] max F(X)=C cost (X) (17)

[0184] In the formula, X is the reliability optimization scheme; F(X) is the optimization target of the reliability optimization scheme; C cost (X) is the equivalent annual cost after the implementation of the reliability optimization plan.

[0185] X is a vector whose number of elements is the number of alternative reliability optimization measures, and the value range of each element in vector X is 0-1. The value of each element in vector X is the optimization variable of the measure optimization model.

[0186]

[0187] Ccost (X) The calculation method is the sum of the annual cost of each reliability optimization measure included in the reliability optimization plan, that is:

[0188] C cost (X) = ∑[X(i)(C I,i +C O,i +C M,i +C D,i )] (19)

[0189] In the formula, C I,i is the initial investment cost of reliability optimization measure i; C O,i is the operating cost of reliability optimization measure i; C M,i is the maintenance cost of reliability optimization measure i; C D,i is the abandonment cost of reliability optimization measure i.

[0190] Considering the impact of the reliability optimization measures included in the reliability optimization plan, the system operation after the implementation of the reliability optimization plan is simulated, and the system reliability indicators after the implementation of the reliability optimization plan are simulated.

[0191] 4.2) Constraints

[0192] The constraints of the optimization model for the reliability optimization of the distribution network based on regional energy interconnection depend on the target requirements for the reliability optimization level. The constraints can be divided into reliability index requirements for important load points, reliability index requirements for energy hubs, and system reliability index requirements. The various reliability index requirements can be further divided into the number of outages, outage duration, power supply reliability rate, and expected supply energy.

[0193] 4.2.1) Constraints for improving the reliability level of important load points

[0194] λ LP (X)≤λ LP (20)

[0195] u LP (X)≤u LP (twenty one)

[0196] ASAI-LP(X)≥ASAI-LP (22)

[0197] ENS-LP(X)≤ENS-LP (23)

[0198] In the formula, λ LP (X), λ LP are the expected value of the load point outage rate and the target for improving the expected value of the load point outage rate after the implementation of the reliability optimization scheme X; u LP (X),u LPare the expected value of power outage time at the load point after the implementation of reliability optimization scheme X and the target for improving the expected value of power outage time at the load point; ASAI-LP(X) and ASAI-LP are the expected value of power supply reliability rate at the load point after the implementation of reliability optimization scheme X and the target for improving the expected value of power supply reliability rate at the load point; ENS-LP(X) and ENS-LP are the expected value of power shortage at the load point after the implementation of reliability optimization scheme X and the target for improving the expected value of power shortage at the load point.

[0199] 4.2.2) Constraints on improving the reliability level of energy hubs

[0200] ARDI e (X)≤ARDI e (twenty four)

[0201] ARDI h (X)≤ARDI h (25)

[0202] EENS e (X)≤EENS e (26)

[0203] EENS h (X)≤EENS h (27)

[0204] ASAI e (X)≥ASAI e (28)

[0205] ASAI h (X)≥ASAI h (29)

[0206] Where, ARDI e (X)ARDI e are the expected annual average reduction duration of the energy hub electric load after the implementation of reliability optimization plan X and the target for improving the expected annual average reduction duration of the energy hub electric load; ARDI h (X)ARDI h They are the expected value of the annual average reduction duration of the energy hub heat load after the implementation of reliability optimization plan X and the target of improving the expected value of the annual average reduction duration of the energy hub heat load; EENS e (X), EENS e They are the expected annual power shortage of the energy hub after the implementation of reliability optimization solution X and the target for improving the expected annual power shortage of the energy hub; EENS h (X), EENS hThey are the expected annual thermal energy shortage of the energy hub after the implementation of reliability optimization solution X and the expected improvement target of the annual thermal energy shortage of the energy hub; ASAI e (X), ASAI e They are the annual average power supply availability of the energy hub after the implementation of reliability optimization solution X and the improvement target of the annual average power supply availability of the energy hub; ASAI h (X), ASAI h They are the annual average heating availability of the energy hub after the implementation of reliability optimization scheme X and the annual average heating availability improvement target of the energy hub.

[0207] 4.2.3) Constraints for improving system reliability

[0208] SAIFI(X)≤SAIFI (30)

[0209] SAIDI(X)≤SAIDI (31)

[0210] ASAI(X)≥ASAI (32)

[0211] ENS(X)≤ENS (33)

[0212] Where, SAIFI(X) and SAIFI are the expected value of the average power outage frequency and the target for improving the expected value of the average power outage frequency after the implementation of the reliability optimization scheme X; SAIDI(X) and SAIDI are the expected value of the average power outage time and the target for improving the expected value of the average power outage time after the implementation of the reliability optimization scheme X; ASAI(X) and ASAI are the expected value of the average power supply reliability rate and the target for improving the expected value of the average power supply reliability rate after the implementation of the reliability optimization scheme X; ENS(X) and ENS are the expected value of the power shortage and the target for improving the expected value of the power shortage after the implementation of the reliability optimization scheme X.

[0213] The optimization objective can be any item or any combination of items in equations (30) to (33).

[0214] Furthermore, in the above step 5), when solving the optimization model of the reliability optimization scheme of the distribution network based on regional energy interconnection, since the objective function of the optimization model is to combine and optimize the reliability optimization measures to generate the final reliability optimization scheme, that is, for n different transformation projects, n different integers are used to represent n projects, and m (0 < m ≤ n) integers that meet the constraints need to be selected from the n integers for optimization until the target is met, which belongs to the integer optimization problem. The non-fast dominance sorting genetic algorithm (NSGA-2) is suitable for solving such problems, and this method has high convergence.

[0215] Specifically, Figure 8 As shown in Figure 2, the process of solving the reliability optimization measure combination model using the non-fast dominated sorting genetic algorithm (NSGA-2) includes:

[0216] 5.1) Use sequential coding method.

[0217] When there are n transformation projects in a plan, a chromosome X0 = (x1, x2, ..., x n ) to represent the scheme, and the sequential encoding is to assign n different integers to the n gene positions of the chromosome, as follows:

[0218] X0=(x1 x2 x3 … x n )=(3 5 2 1 … n) (34)

[0219] Among them, each integer 1, 2, 3...n represents a transformation project respectively, and the chromosome represents the plans of different transformation projects.

[0220] 5.2) Initialize the population.

[0221] Execute step 5.1) m times, and a population of m chromosomes can be generated. Substitute the chromosome gene bit values ​​into the constraints one by one in order. When the constraint is satisfied, Then the first k variables X′0=(x1, x2, …, x k ) as a feasible solution chromosome, where W is the upper limit of the constraints in the model. Similarly, each chromosome in the population is screened.

[0222] For example, Fig. 9 As shown, a chromosome is X={x1 x2 x3 x4}={3 1 2 4}. Since w3+w1+w2≤W≤w3+w1+w2+w4, the feasible solution chromosome obtained by deleting the gene segments that do not meet the constraints is X′={x1 x2 x3}={3 1 2}.

[0223] 5.3) Chromosome crossing over.

[0224] From step 5.2), we can see that the lengths of chromosomes of individuals in the screened population will be different.

[0225] 5.3.1) Randomly select two chromosomes P1 and P2 from the screened population, and randomly select two gene crossover sites l1 and l2 according to the length of the two chromosomes.

[0226] 5.3.2) Using the crossover site as the boundary, exchange the gene fragments between the two crossover sites to regenerate chromosomes P′1 and P′2.

[0227] 5.3.3) Check whether there are duplicate gene loci on the chromosome. If so, delete them to generate P″1 and P″2.

[0228] 5.3.4) Execute step (5.2) to screen the P″1 and P″2 gene segments according to the constraints to generate P″′1 and P″′2.

[0229] 5.4) Chromosome mutation.

[0230] Randomly delete a gene site, and then randomly find a gene site to insert a gene that is not on the original chromosome.

[0231] Example 2

[0232] The above-mentioned embodiment 1 provides a distribution network reliability optimization method, and correspondingly, this embodiment provides a distribution network reliability optimization system. The system provided in this embodiment can implement a distribution network reliability optimization method of embodiment 1, and the system can be implemented by software, hardware, or a combination of software and hardware. For example, the system may include integrated or separate functional modules or functional units to execute the corresponding steps in each method of embodiment 1. Since the system of this embodiment is basically similar to the method embodiment, the process described in this embodiment is relatively simple, and the relevant parts can refer to the partial description of embodiment 1. The embodiment of the system provided in this embodiment is only illustrative.

[0233] This embodiment provides a distribution network reliability optimization system, including:

[0234] The reliability efficiency calculation module is used to perform structural analysis on the distribution network under the background of regional energy interconnection and calculate the reliability efficiency of the distribution network under the background of regional energy interconnection;

[0235] Cost-benefit model building module, used to build a cost-benefit model for distribution network reliability optimization scheme under the background of regional energy interconnection;

[0236] The cost-benefit analysis module is used to obtain the cost-benefit analysis results of reliability optimization measures by adopting the cost-benefit analysis method of distribution network reliability optimization scheme under the background of regional energy interconnection;

[0237] The scheme optimization module is used to build and solve the distribution network reliability optimization scheme optimization model based on regional energy interconnection based on the cost-benefit model of the distribution network reliability optimization scheme, and obtain the distribution network reliability optimization scheme.

[0238] Example 3

[0239] This embodiment provides a processing device corresponding to a distribution network reliability optimization method provided in this embodiment 1. The processing device may be a processing device for a client, such as a mobile phone, a laptop computer, a tablet computer, a desktop computer, etc., to execute the method of embodiment 1.

[0240] The processing device includes a processor, a memory, a communication interface and a bus, and the processor, the memory and the communication interface are connected through the bus to complete mutual communication. The memory stores a computer program that can be run on the processor, and the processor executes a distribution network reliability optimization method provided in this embodiment 1 when running the computer program.

[0241] In some embodiments, the memory may be a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory.

[0242] In other embodiments, the processor may be a central processing unit (CPU), a digital signal processor (DSP), or other general-purpose processors of various types, which are not limited herein.

[0243] Example 4

[0244] A distribution network reliability optimization method of this embodiment 1 can be specifically implemented as a computer program product. The computer program product may include a computer-readable storage medium on which computer-readable program instructions for executing the distribution network reliability optimization method described in this embodiment 1 are loaded.

[0245] Computer readable storage media can be tangible devices that hold and store instructions used by instruction execution devices. Computer readable storage media can be, for example, but not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any combination thereof.

[0246] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0247] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0248] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0249] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0250] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. 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 distribution network reliability optimization method, characterized in that The following steps are involved: The structure of the distribution network under the background of regional energy interconnection is analyzed, and the reliability efficiency improvement of the distribution network under the background of regional energy interconnection is calculated; Based on reliability efficiency improvement, a cost-effectiveness model for distribution network reliability optimization scheme under the background of regional energy interconnection is established; The cost-benefit analysis results of reliability optimization measures were obtained by using the cost-benefit analysis method of distribution network reliability optimization scheme under the background of regional energy interconnection; Based on the cost-benefit model of the distribution network reliability optimization plan and the results of cost-benefit analysis, an optimization model for the distribution network reliability optimization plan based on regional energy interconnection was built and solved using a non-fast dominating sorting genetic algorithm to obtain a distribution network reliability optimization plan. The method of analyzing the structure of the distribution network under the background of regional energy interconnection and calculating the reliability efficiency improvement of the distribution network under the background of regional energy interconnection includes: Obtain independent energy supply and regional energy interconnection energy supply network load, component failure rate, and energy hub configuration parameters; Based on the relevant parameters obtained, the power supply shortage expectation analysis is carried out when the distribution network fails, and the power supply shortage expectation under independent energy supply and regional energy interconnection energy supply is obtained; Based on the expected power shortage when the distribution network fails under the conditions of independent energy supply and regional energy interconnection, the reliability efficiency improvement of the distribution network under the background of regional energy interconnection is calculated; The distribution network reliability optimization scheme optimization model based on regional energy interconnection includes an objective function and constraint conditions; The objective function is: In the formula, X is the reliability optimization scheme; F(X) is the optimization target of the reliability optimization scheme; The equivalent annual cost after the reliability optimization solution is implemented; The constraints include reliability index requirements of important load points, reliability index requirements of energy hubs and system reliability index requirements.

2. A distribution network reliability optimization method according to claim 1, characterized in that: The cost-benefit model of the distribution network reliability optimization scheme under the background of regional energy interconnection includes a cost model and a benefit model; The cost model is: In the formula, is the life cycle cost; The initial investment cost includes the design cost in the design phase, the equipment purchase cost, and the construction and installation cost in the construction phase; Operating costs, including equipment wear and tear and operator training costs; For maintenance costs; For the cost of abandonment; The benefit model is: In the formula, The overall benefits of implementing reliability optimization solutions for distribution networks; The power outage compensation expenses saved for the power grid company; Increased electricity sales revenue for power grid companies; is the unit electricity price at load point i; is the unit power outage loss at load point i; The power shortage expectation before the implementation of the distribution network reliability optimization plan; Expected power supply shortage after the implementation of the distribution network reliability optimization plan.

3. A distribution network reliability optimization method according to claim 1, characterized in that: The method of using the cost-benefit analysis method of the distribution network reliability optimization scheme under the background of regional energy interconnection to perform a cost-benefit analysis of the reliability optimization measures includes: Obtain system network structure, component reliability data, load data, etc. before implementing reliability optimization measures; A reliability assessment method for regional energy interconnected distribution networks based on Monte Carlo simulation is used to calculate the reliability index of the load point and the system reliability index before the implementation of reliability optimization measures; Select the reliability optimization measures to be implemented, and modify the component reliability data based on the factors affecting the reliability evaluation by the reliability optimization measures; The reliability assessment method of regional energy interconnected distribution network based on Monte Carlo simulation is used again to calculate the reliability index of load points and system reliability index after the implementation of reliability optimization measures; Considering the implementation cost and implementation scale of reliability optimization measures, calculate the implementation cost of reliability optimization measures; Calculate the benefits of implementing reliability optimization measures based on the improvement effect of reliability indicators; The cost-benefit analysis method of distribution network reliability optimization based on marginal cost and marginal benefit is adopted to conduct cost-benefit analysis of reliability optimization measures.

4. A distribution network reliability optimization method as claimed in claim 3, characterized in that: The method of conducting cost-benefit analysis of reliability optimization measures by using a distribution network reliability optimization method cost-benefit analysis method based on marginal cost and marginal benefit includes: Decompose the reliability marginal cost curve into multiple curves according to different reliability optimization measures, find the reliability marginal cost curve closest to the X-axis from the starting section of the reliability cost-benefit analysis curve, and search backward from the starting point of the curve; If it intersects with another reliability marginal cost curve, it will turn to this curve and continue to search backward, and so on, until the reliability target or investment cost target is reached; All line segments distributed on the search path are connected to form a reliability marginal cost optimization curve considering multiple optimization measures; Based on the obtained reliability marginal cost optimization curve, the total investment cost under the reliability level, the investment cost required for the corresponding optimization measures, and the optimal reliability level corresponding to each reliability optimization measure are obtained.

5. A distribution network reliability optimization method according to claim 1, characterized in that: The constraints required for the reliability index of the important load points are: In the formula, , They are the expected value of the load point outage rate and the target for improving the expected value of the load point outage rate after the implementation of the reliability optimization scheme X; , They are the expected value of load point outage time after the implementation of reliability optimization scheme X and the target for improving the expected value of load point outage time; , They are the expected value of the load point power supply reliability rate and the target for improving the expected value of the load point power supply reliability rate after the implementation of the reliability optimization plan X; , They are the expected value of power shortage at the load point after the implementation of reliability optimization scheme X and the target for improving the expected value of power shortage at the load point; The constraints required by the energy hub reliability index are: In the formula, , They are the expected value of the annual average reduction duration of the energy hub electric load after the implementation of the reliability optimization plan X and the improvement target of the expected value of the annual average reduction duration of the energy hub electric load; , They are the expected value of the annual average reduction duration of the energy hub heat load after the implementation of the reliability optimization plan X and the improvement target of the expected value of the annual average reduction duration of the energy hub heat load; , They are the expected annual power shortage of the energy hub after the implementation of the reliability optimization plan X and the expected improvement target of the annual power shortage of the energy hub; , They are the expected annual thermal energy shortage of the energy hub after the implementation of reliability optimization plan X and the target for improving the expected annual thermal energy shortage of the energy hub; , They are the annual average power supply availability of the energy hub after the implementation of the reliability optimization plan X and the target for improving the annual average power supply availability of the energy hub; , They are the annual average heating availability of the energy hub and the improvement target of the annual average heating availability of the energy hub after the implementation of the reliability optimization plan X; The constraints required by the system reliability index are: In the formula, , They are the expected value of the average power outage frequency of the system and the target for improving the expected value of the average power outage frequency of the system after the implementation of the reliability optimization plan X; , They are the expected value of the average power outage time of the system after the implementation of the reliability optimization plan X and the improvement target of the expected value of the average power outage time of the system; , They are the expected value of the average power supply reliability rate of the system and the improvement target of the expected value of the average power supply reliability rate of the system after the implementation of the reliability optimization plan X; , They are the expected value of system power shortage after the implementation of reliability optimization plan X and the target for improving the expected value of system power shortage.

6. A distribution network reliability optimization system, characterized in that include: The reliability efficiency calculation module is used to perform structural analysis on the distribution network under the background of regional energy interconnection and calculate the reliability efficiency of the distribution network under the background of regional energy interconnection; Cost-benefit model building module, used to build a cost-benefit model for distribution network reliability optimization scheme under the background of regional energy interconnection; The cost-benefit analysis module is used to obtain the cost-benefit analysis results of reliability optimization measures by adopting the cost-benefit analysis method of distribution network reliability optimization scheme under the background of regional energy interconnection; The scheme optimization module is used to build a distribution network reliability optimization scheme optimization model based on the regional energy interconnection based on the cost-effectiveness model of the distribution network reliability optimization scheme and use the non-fast dominating sorting genetic algorithm to solve it, so as to obtain the distribution network reliability optimization scheme; The reliability efficiency calculation module includes: A parameter acquisition module is used to obtain the load of independent energy supply and regional energy interconnection energy supply network, component failure rate, and energy hub configuration parameters; The power shortage expectation calculation module is used to analyze the power shortage expectation when the distribution network fails based on the acquired relevant parameters, and obtain the power shortage expectation under the conditions of independent energy supply and regional energy interconnection energy supply; A calculation module is used to calculate the reliability efficiency improvement of the distribution network under the background of regional energy interconnection based on the expected power shortage when the distribution network fails under the conditions of independent energy supply and regional energy interconnection energy supply; The distribution network reliability optimization scheme optimization model based on regional energy interconnection includes an objective function and constraint conditions; The objective function is: In the formula, X is the reliability optimization scheme; F(X) is the optimization target of the reliability optimization scheme; The equivalent annual cost after the reliability optimization solution is implemented; The constraints include reliability index requirements of important load points, reliability index requirements of energy hubs and system reliability index requirements.

7. A processing device, the processing device comprising at least a processor and a memory, the memory storing a computer program, characterized in that: When the processor runs the computer program, the computer program is executed to implement the steps of the distribution network reliability optimization method according to any one of claims 1 to 5.

8. A computer storage medium, characterized in that: Computer-readable instructions are stored thereon, and the computer-readable instructions can be executed by a processor to implement the steps of the distribution network reliability optimization method according to any one of claims 1 to 5.

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