Operation scene screening method and device of power distribution network, computer equipment, readable storage medium and program product

Abstract

The invention relates to an operation scene screening method and device of a power distribution network, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: obtaining the capacity of various network resources of the power distribution network in each operation scene; acquiring a comprehensive shadow price corresponding to the operation scene; obtaining various scene operation costs, demand side constraints and various power distribution network safe operation constraints of the power distribution network in the operation scene; based on the comprehensive shadow price, the multi-scene operation cost, the demand side constraint and the multiple power distribution network safe operation constraints, obtaining an economic dispatching model of the power distribution network in the operation scene; and based on the comprehensive shadow price, the economic dispatching model and the occurrence probability of the operation scene, obtaining a scene influence factor of the operation scene, and screening out a target operation scene from all the operation scenes based on the scene influence factor. According to the method provided by the invention, potential operation-limited scenes with relatively low probability of occurrence can be mined in a relatively large number of scene sets.

Description

Technical Field

[0001] The present application relates to the technical field of scenario generation of distribution networks, and in particular to a method, apparatus, computer equipment, computer-readable storage medium and computer program product for screening operation scenarios of distribution networks. Background Art

[0002] In recent years, due to the large-scale access and rapid development of photovoltaic power generation systems, the uncertainty and volatility of distribution networks have also increased, resulting in a large number of operation-restricted scenarios. The traditional distribution network planning method that only considers typical scenarios ignores potential operation-restricted scenarios with a low probability of occurrence, which may lead to poor economic efficiency of the resulting planning scheme in actual distribution network operation. Summary of the invention

[0003] Based on this, it is necessary to provide a method, device, computer equipment, computer-readable storage medium and computer program product for screening operation scenarios of a distribution network, which can improve the economy of the distribution network operation, in response to the above-mentioned technical problems.

[0004] In a first aspect, the present application provides a method for screening operation scenarios of a distribution network, the method comprising:

[0005] For each operation scenario of the distribution network, obtaining the capacity of multiple network resources of the distribution network under the operation scenario;

[0006] Obtaining a comprehensive shadow price corresponding to the operation scenario based on the capacity of the multiple network resources, the shadow price being used to evaluate the impact of the expansion of the network resources on the scheduling cost;

[0007] Obtaining multiple scenario operating costs, demand side constraints and multiple distribution network safety operation constraints of the distribution network under the operating scenario;

[0008] Based on the comprehensive shadow price, the operating costs of the multiple scenarios, the demand-side constraints and the multiple distribution network safety operation constraints, an economic dispatch model of the distribution network under the operation scenario is obtained;

[0009] Based on the comprehensive shadow price, the economic dispatch model and the occurrence probability of the operation scenario, the scenario impact factor of the operation scenario is obtained, and based on the scenario impact factor, a target operation scenario is screened out from all operation scenarios of the distribution network. The scenario impact factor is used to evaluate the scarcity of network resources of the distribution network under the operation scenario.

[0010] In one embodiment, the obtaining the comprehensive shadow price corresponding to the operation scenario based on the capacity of the multiple network resources includes:

[0011] Obtaining the initial shadow price corresponding to each network resource based on the capacity of each network resource and the primal-dual interior point method;

[0012] A comprehensive shadow price corresponding to the operating scenario is obtained based on all initial shadow prices corresponding to the operating scenario.

[0013] In one of the embodiments, the step of selecting a target operation scenario from all operation scenarios of the distribution network based on the scenario influencing factor includes:

[0014] For the distribution network, obtaining average values ​​of scenario impact factors of all operating scenarios;

[0015] Obtaining a larger value between the average value and a preset impact factor;

[0016] For each operation scenario of the distribution network, when the scenario impact factor of the operation scenario is not less than the larger value, the operation scenario is determined as the target operation scenario.

[0017] In one of the embodiments, the scenario operating costs include network loss costs, line operation and maintenance costs, energy storage system operation and maintenance costs, and wind and solar power abandonment and load loss penalty costs; the multiple distribution network safety operation constraints include distributed power source output constraints, power flow equation constraints, line capacity constraints, power purchase from the upper power grid constraints, node voltage constraints, load loss constraints, demand-side response constraints, and energy storage system constraints.

[0018] In one of the embodiments, before obtaining the economic dispatch model of the distribution network in the operation scenario based on the comprehensive shadow price, the multiple scenario operation costs, the demand side constraints and the multiple distribution network safety operation constraints, the further comprises:

[0019] Based on the second-order cone programming model, the power flow equation constraint and the node voltage constraint are respectively transformed into second-order cones to obtain corresponding linear constraints.

[0020] In one embodiment, the capacities of the various network resources include transmission line capacity, energy storage system capacity, energy storage system rated power, and demand-side response contract capacity.

[0021] In a second aspect, the present application further provides a device for screening operation scenarios of a distribution network, the device comprising:

[0022] A first acquisition module is used to acquire the capacity of multiple network resources of the distribution network in each operation scenario of the distribution network;

[0023] A second acquisition module is used to acquire a comprehensive shadow price corresponding to the operation scenario based on the capacity of the multiple network resources, and the shadow price is used to evaluate the impact of the expansion of the network resources on the scheduling cost;

[0024] A third acquisition module is used to obtain the operating costs of various scenarios of the distribution network under the operating scenario, demand-side constraints and various distribution network safety operation constraints;

[0025] A fourth acquisition module, configured to acquire an economic dispatch model of the distribution network under the operation scenario based on the comprehensive shadow price, the operation costs of the multiple scenarios, the demand-side constraints and the multiple distribution network safety operation constraints;

[0026] The fifth acquisition module is used to obtain the scenario impact factor of the operating scenario based on the comprehensive shadow price, the economic dispatch model and the occurrence probability of the operating scenario, and to screen out the target operating scenario from all operating scenarios of the distribution network based on the scenario impact factor, and the scenario impact factor is used to evaluate the scarcity of network resources of the distribution network under the operating scenario.

[0027] In a third aspect, the present application further provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method in any one of the above embodiments when executing the computer program.

[0028] In a fourth aspect, the present application further provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method in any one of the above embodiments are implemented.

[0029] In a fifth aspect, the present application further provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the method in any one of the above embodiments are implemented.

[0030] The above-mentioned distribution network operation scenario screening method, device, computer equipment, computer-readable storage medium and computer program product, for each operation scenario of the distribution network, obtains the capacity of various network resources of the distribution network in the operation scenario; obtains the comprehensive shadow price corresponding to the operation scenario based on the capacity of various network resources, and the shadow price is used to evaluate the impact of the expansion of network resources on the dispatching cost; obtains the operation cost of various scenarios, demand-side constraints and various distribution network safety operation constraints of the distribution network in the operation scenario; obtains the economic dispatch model of the distribution network in the operation scenario based on the comprehensive shadow price, the operation cost of various scenarios, the demand-side constraints and various distribution network safety operation constraints; obtains the scenario influence factor of the operation scenario based on the comprehensive shadow price, the economic dispatch model and the occurrence probability of the operation scenario, and selects the target operation scenario from all the operation scenarios of the distribution network based on the scenario influence factor, and the scenario influence factor is used to evaluate the scarcity of network resources in the operation scenario of the distribution network. The method provided by the present application can mine potential operation-restricted scenarios with a low probability of occurrence from a large number of scenarios, thereby effectively improving the economy in the operation of the distribution network and ensuring the comprehensiveness and accuracy of the planning of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0032] FIG1 is a schematic diagram of a flow chart of a method for screening operation scenarios of a distribution network in one embodiment;

[0033] FIG2 is a schematic diagram of a flow chart of a method for obtaining a comprehensive shadow price in one embodiment;

[0034] FIG3 is a schematic flow chart of a method for screening operation scenarios of a distribution network in another embodiment;

[0035] FIG4 is a network topology diagram of a power distribution network in another embodiment;

[0036] FIG5 is a photovoltaic output curve diagram of a severely restricted scenario in another embodiment;

[0037] FIG6 is a wind power output curve diagram of a severely restricted scenario in another embodiment;

[0038] FIG7 is a structural block diagram of an operating scenario screening device for a distribution network in one embodiment;

[0039] FIG. 8 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0041] In one embodiment, as shown in FIG1 , a method for screening operation scenarios of a distribution network is provided. This embodiment uses the method applied to a terminal as an example for illustration. It is understandable that the method can also be applied to a server, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0042] S102: For each operation scenario of the distribution network, obtain the capacities of various network resources of the distribution network in the operation scenario.

[0043] Among them, the operation scenario of the distribution network refers to the various working conditions and operating environments involved in the actual operation of the distribution network; the capacity of network resources in the distribution network usually refers to the total amount of power resources that the distribution network can provide to users in a given area at a specific voltage level. This capacity includes the maximum load that network components such as lines, transformers, and busbars can carry. The size of the network resource capacity is directly related to the reliability and economy of power supply in the area.

[0044] S104. Obtain a comprehensive shadow price corresponding to the operation scenario based on the capacity of multiple network resources, where the shadow price is used to evaluate the impact of the expansion of network resources on the scheduling cost.

[0045] Among them, the shadow price represents the scheduling cost that can be reduced by expanding the capacity of a specific network resource by 1 unit when the constraints of the resource begin to take effect. The comprehensive shadow price is used to evaluate the degree of restriction of the operating scenario.

[0046] Specifically, the initial shadow price corresponding to each network resource can be obtained first, and then the comprehensive shadow price corresponding to the operation scenario can be obtained based on the initial shadow price. The initial shadow price of the network resource quantitatively evaluates the benefit of increasing the unit investment of the network resource on the optimization of the objective function, and reflects the resource scarcity of the network resource before planning.

[0047] S106. Obtaining various scenario operating costs, demand-side constraints, and various distribution network safety operation constraints under the distribution network operation scenarios.

[0048] Among them, the scenario operation cost refers to the total cost of completing power supply and related operation and maintenance work under a specific distribution network operation scenario. In this embodiment, the scenario operation cost may include network loss cost, line operation and maintenance cost, energy storage system operation and maintenance cost, and wind and solar power abandonment load penalty cost. In other embodiments, the scenario operation cost may also include other costs, which are not specifically limited in the embodiments of the present application; demand-side constraints refer to the restrictions or impacts on the operation of the power grid caused by the demand-side management measures of power users; distribution network safety operation constraints refer to a series of regulations and restrictions that must be followed during the operation of the distribution network to ensure the stability, reliability and safety of the power system.

[0049] S108. Based on the comprehensive shadow price, operating costs in various scenarios, demand-side constraints and various distribution network safety operation constraints, an economic dispatch model of the distribution network under the operating scenario is obtained.

[0050] Among them, the economic dispatch model is an optimization tool used to guide the operation and planning of the distribution network to maximize cost-effectiveness. The economic dispatch model can be shown as follows:

[0051]

[0052] In the formula, is the minimum operating cost in this operating scenario, is the network loss cost, is the line operation and maintenance cost, is the operation and maintenance cost of the energy storage system, Penalty costs for wind and solar power curtailment and load loss.

[0053] S110. Obtain the scenario impact factor of the operation scenario based on the comprehensive shadow price, economic dispatch model and the occurrence probability of the operation scenario, and screen out the target operation scenario from all the operation scenarios of the distribution network based on the scenario impact factor. The scenario impact factor is used to evaluate the scarcity of network resources in the distribution network under the operation scenario.

[0054] Among them, this embodiment takes into account that the blocking risk of the scene includes two dimensions: the probability of the scene occurring and the severity of the blocking, and defines the scene impact factor indicating the degree to which the operation scene is restricted by the planning decision The scenario impact factor is used as the evaluation index of complex operation restricted scenarios to screen the scenario library, and its expression is:

[0055]

[0056] In the formula, is the comprehensive shadow price; is the occurrence probability of the running scenario.

[0057] In the above-mentioned distribution network operation scenario screening method, for each operation scenario of the distribution network, the capacity of various network resources of the distribution network in the operation scenario is obtained; based on the capacity of various network resources, the corresponding comprehensive shadow price of the operation scenario is obtained, and the shadow price is used to evaluate the impact of the expansion of network resources on the dispatching cost; the operation costs of various scenarios of the distribution network in the operation scenario, demand-side constraints and various distribution network safety operation constraints are obtained; based on the comprehensive shadow price, the operation costs of various scenarios, the demand-side constraints and various distribution network safety operation constraints, the economic dispatch model of the distribution network in the operation scenario is obtained; based on the comprehensive shadow price, the economic dispatch model and the occurrence probability of the operation scenario, the scenario influence factor of the operation scenario is obtained, and the target operation scenario is screened from all the operation scenarios of the distribution network based on the scenario influence factor, and the scenario influence factor is used to evaluate the scarcity of network resources in the operation scenario of the distribution network. The method provided by the present application can mine potential operation-restricted scenarios with a low probability of occurrence from a large number of scenarios, thereby effectively improving the economy of the distribution network operation, and can ensure the comprehensiveness and accuracy of the planning of the power system.

[0058] In some embodiments, as shown in FIG2 , obtaining a comprehensive shadow price corresponding to an operation scenario based on the capacity of multiple network resources includes:

[0059] S202. Obtain the initial shadow price corresponding to each network resource based on the capacity of each network resource and the primal-dual interior point method.

[0060] S204. Obtain a comprehensive shadow price corresponding to the operation scenario based on all initial shadow prices corresponding to the operation scenario.

[0061] Among them, for each network resource, the primal-dual interior point method based on the KKT condition can be used to solve it based on the capacity of the network resource, and the Lagrange multiplier obtained by the solution is the initial shadow price corresponding to the network resource.

[0062] The comprehensive shadow price corresponding to the operating scenario can be calculated as follows:

[0063]

[0064] In the formula, is the Lagrange multiplier value of the demand-side response contract capacity constraint of the m-th type of load at node i in the scheduling period t under this operation scenario; and are the Lagrange multiplier values ​​of the upper and lower limit constraints of the line capacity of line ij in the scheduling period t under the operation scenario; and are the Lagrange multiplier values ​​of the energy storage system power upper limit constraint and the energy storage system capacity upper limit constraint of node i in the scheduling period t under the operation scenario; is the demand side response capacity cost of the mth type of load; is the unit length cost of the line of model r; and They are the construction cost per unit power and per unit capacity of the energy storage system respectively.

[0065] In this embodiment, based on the initial shadow price corresponding to each network resource, the comprehensive shadow price corresponding to the operation scenario is obtained, so that the economic scheduling model and scenario influencing factors subsequently determined based on the comprehensive shadow price are more accurate.

[0066] In some embodiments, a target operating scenario is screened out from all operating scenarios of the distribution network based on the scenario influence factor, including: for the distribution network, obtaining the average value of the scenario influence factors of all operating scenarios; obtaining the larger value between the average value and the preset influence factor; for each operating scenario of the distribution network, when the scenario influence factor of the operating scenario is not less than the larger value, determining the operating scenario as the target operating scenario.

[0067] In this embodiment, the scene influence factor It reflects the scarcity of the overall resources of the distribution network in scene s: if the resources in scene s are tight, (Comprehensive shadow price) is large, and the scene influence factor is large, it is included in the severely restricted scene set; if the scene s (The probability of occurrence of scenario s) is large, which means that the resource restriction lasts for a long time in a long period of time, and the economic loss it brings is proportional to the length of time. It is also necessary to configure the corresponding network load storage resources during planning, and give priority to solving the problem of operation restriction in such scenarios. In the scenario of severe restrictions, the unit investment in distribution network resources has a higher marginal benefit in reducing the scenario operation cost and risk. Therefore, the scenario impact factor can be used to objectively evaluate the risks of all operation scenarios, and the scenarios with greater marginal benefits of investment can be included in the severely restricted scenario set. In , the screening process can be expressed as:

[0068]

[0069] In the formula, is the total number of running scenarios; is the scene-affected shadow screening threshold. If the scene s , indicating that this scenario is highly restricted and needs to be included in the severely restricted scenario set and considered in the planning layer of the model. The severely restricted scenario screening process simulates the process of power system operators delivering planning suggestions to planners.

[0070] In this embodiment, the screened target operation scenarios are all severely restricted scenarios. By screening out these scenarios, the staff can focus on the situations of these scenarios in the subsequent planning process.

[0071] In some embodiments, the scenario operating costs include network loss costs, line operation and maintenance costs, energy storage system operation and maintenance costs, and wind and solar power abandonment and load loss penalty costs; the various distribution network safety operation constraints include distributed power output constraints, power flow equation constraints, line capacity constraints, power purchase from the upper power grid constraints, node voltage constraints, load loss constraints, demand-side response constraints, and energy storage system constraints.

[0072] Among them, the distribution network purchases electricity from the upper power grid, and the purchase price is based on the time-of-use electricity price. The network loss cost is shown in the following formula:

[0073]

[0074] In the formula, s represents the sub-operation scenario; is the set of built lines; T is the number of time periods in the scheduling cycle; The main grid electricity purchase price in period t; is the network loss power of line l in time period t under scenario s; and They are respectively the active power flow and reactive power flow of the line; and are line resistance and reactance respectively; is the voltage amplitude of node i at the beginning of the line; The duration of the scheduling period.

[0075] The line operation and maintenance costs are as follows:

[0076]

[0077] In the formula, is the line maintenance cost per unit length, is the length of line ij.

[0078] The operation and maintenance cost of the energy storage system is as follows:

[0079]

[0080] In the formula, is the annual operating cost per unit capacity of the energy storage system.

[0081] The penalty cost for wind and solar power abandonment is as follows:

[0082]

[0083] In the formula, , and They are the unit penalty costs for abandoning solar power, abandoning wind power and losing load respectively; and They are the maximum output and actual output of distributed photovoltaic power generation respectively; and are the maximum output and actual output of the distributed wind power generation system respectively; is the load loss power.

[0084] The actual output of distributed power sources is subject to the maximum wind and solar curtailment rates. The output constraints of distributed power sources are shown in the following formula:

[0085]

[0086] In the formula, and They are the maximum wind curtailment rate and solar curtailment rate allowed by the system respectively.

[0087] The power flow equation constraints are as follows:

[0088]

[0089]

[0090]

[0091]

[0092] In the formula, and are respectively the active and reactive power at the head end of line ij in time period t under scenario s; and are the active and reactive power of node j in time period t under scenario s, respectively; , , , and are the load of node j in time period t under scenario s, power purchase from the upper power grid, wind power abandonment, solar power abandonment and reactive power compensated locally; and are the charging and discharging power of the energy storage system respectively.

[0093] In the active distribution network, power flow reverse transmission may occur, and the bidirectional power flow capacity constraint is considered. The line capacity constraint is as follows:

[0094]

[0095] In the formula, is the line capacity from node i to node j.

[0096] In order to prevent the distribution network from sending power back to the upper power grid, the power purchase constraint from the upper power grid is obtained as follows:

[0097]

[0098] The node voltage constraint is as follows:

[0099]

[0100] In the formula, is a 0-1 variable, indicating whether to build line ij; M is a sufficiently large real number (when a new line ij is built, the formula is consistent with the common distribution network flow formula; when line ij is not built, M makes the flow constraint of this line invalid, that is, and No connection exists); and are the minimum and maximum voltage amplitudes allowed at the node, respectively.

[0101] The load loss constraint is as follows:

[0102]

[0103] In the formula, is the maximum load loss rate.

[0104] Demand-side response loads are divided into curtailable loads and shiftable loads. Curtailable loads refer to loads that can be partially curtailed during the demand response period based on demand response potential, without the need for load compensation afterwards; shiftable loads refer to loads that can be temporarily curtailed during the demand-side response period, and that need to be compensated and restored before the end of the response period, i.e., load shifting operations.

[0105] The demand side response power of node i is as follows:

[0106]

[0107] In the formula, and are the state variables of load shedding and translation, respectively (0 means no load response, 1 means load shedding, and -1 means load compensation); and are load shedding and translational power, respectively.

[0108] The demand-side response load power is subject to the pre-agreed response capacity and response period constraints:

[0109]

[0110]

[0111] In the formula, and They are the start and end time periods of demand-side response, respectively.

[0112] In addition, the shiftable load is also constrained by the total amount of load reduction and the number of response state switching, as shown in the following formula:

[0113]

[0114]

[0115] In the formula, is a symbolic function; The upper limit of the number of switching times.

[0116] During operation, the energy storage system is subject to the charge and discharge state, charge and discharge power and capacity, charge and discharge timing, and conservation constraints of charge and discharge amount within the operation scheduling cycle:

[0117]

[0118] In the formula, and are the charging and discharging 0-1 state variables of the energy storage system of node i in period t in scenario s; is the remaining power level; is the self-discharge rate of energy storage per unit time period; and are the charging and discharging efficiency of the energy storage system respectively; and They are the upper and lower limits of the energy storage ratio of the energy storage system.

[0119] In some embodiments, based on the comprehensive shadow price, multiple scenario operating costs, demand-side constraints and multiple distribution network safety operation constraints, before obtaining the economic dispatch model of the distribution network under the operating scenario, it also includes: performing second-order cone transformation on the power flow equation constraints and node voltage constraints based on the second-order cone programming model to obtain corresponding linear constraints.

[0120] Among them, the economic dispatch model proposed in this embodiment is a complex mixed integer non-convex nonlinear programming problem, and the traditional numerical solution cannot guarantee the global optimality of the solution. Therefore, this embodiment uses second-order cone programming (SOCP) to transform the AC distribution network flow constraints and node voltage constraints. The resulting constraints are linear constraints and meet the convex programming requirements, which can not only ensure the solution accuracy of the algorithm, but also improve the convergence of the solution of the planning problem.

[0121] Use the following formula to transform the power flow equation equivalently:

[0122]

[0123] We can get:

[0124]

[0125]

[0126]

[0127] Then, the second-order cone relaxation is performed on the power flow equation after equivalent deformation, and the relaxed constraint is obtained as follows:

[0128]

[0129] Through the above second-order cone transformation, the original problem is transformed into a simpler mixed intersecond order cone programming (MISOCP) problem, obtaining the global optimal solution and better solution speed.

[0130] In this embodiment, by converting the power flow equation constraints and the node voltage constraints into linear constraints, the calculation results of the subsequent economic dispatch model are made more accurate.

[0131] In some embodiments, the capacities of the various network resources include transmission line capacity, capacity of an energy storage system, rated power of the energy storage system, and demand-side response contracted capacity.

[0132] Among them, the demand-side response contracted capacity refers to the maximum power reduction that power users participating in the demand-side response project promise to provide within a specific period of time.

[0133] In this embodiment, by acquiring the capacities of multiple network resources, the determined comprehensive shadow price is made more accurate.

[0134] In one embodiment, another method for screening operation scenarios of a distribution network is provided, as shown in FIG3 , the method includes the following contents:

[0135] Step 1: Construct a comprehensive evaluation index for the constraints of transmission line capacity, energy storage capacity, and demand-side response power, and propose a method for establishing evaluation indicators for complex operation-constrained scenarios that consider scenario influencing factors.

[0136] Step 2: Based on the evaluation indicators of the complex operation-constrained scenarios obtained in step 1, a county distribution network economic dispatch model considering network constraints is constructed.

[0137] Step 3: Based on the economic dispatch model of the county distribution network considering network constraints obtained in step 2, a method for generating a set of complex operation restricted scenarios of the county distribution network is constructed to screen out severely restricted scenarios and generate a set of complex operation restricted scenarios.

[0138] Step 4: Solve the problem using built-in functions in MATLAB software to obtain a set of complex operation restricted scenarios for the county distribution network.

[0139] This embodiment uses a typical county distribution system in a real area as an example to verify and analyze the proposed model for establishing a set of complex operation restricted scenarios for the county distribution network. The distribution system contains 8 distributed power sources, 32 industrial load nodes, 7 commercial load nodes and 39 lines. The network topology of the distribution network is shown in Figure 4. The economic dispatch problem takes one day as a dispatch cycle, and one cycle contains 24 dispatch periods; except for the power supply node, the remaining nodes can be installed with energy storage systems. The planning model considers a set of operating scenarios consisting of 36 wind, light and load joint scenarios. The probability of the joint scenario is obtained by multiplying the probability of PV, WF and load single scenarios. The distributed power output operation scenario is generated according to the typical scenario generation method described in the previous section.

[0140] The photovoltaic output curve of the severely restricted scenario of the county distribution network solved by this embodiment is shown in FIG5 , and the wind power output curve is shown in FIG6 . The restricted conditions of the severely restricted scenario are shown in Table 1 .

[0141] Table 1

[0142]

[0143] In order to verify the effectiveness of the proposed severely restricted scenario screening method, this embodiment performs economic dispatch on all 36 typical scenarios, calculates their scenario impact factors, and then sorts the scenario impact factors from large to small. Table 1 shows the restricted conditions of the five most severely restricted operating scenarios in the severely restricted scenario set. Since the impact factor of the sixth ranked scenario is 56.5, which is significantly different from the impact factor of the sixth scenario, 93.2, and the impact factor difference with the remaining typical scenarios is small, the five severely restricted scenarios shown in Table 1 are selected to constitute the complex operation restricted scenario set of the county distribution network.

[0144] As can be seen from Table 1, the scene set of distribution network severe restriction contained typical scenes with a probability greater than the average value of 2.78%. This is because before the county distribution network planning, the various expandable resources have not optimized the results of economic dispatch, and the value of the scene impact factor obtained by the model solution is greatly affected by the probability of the scene. Scenario 35 is the scene with the largest impact factor in the distribution network severe restriction scene set, with a scene probability of 10.4%. After conversion, the number of days in a year is about 38 days, which needs to be given priority in the distribution network planning problem. By establishing a severely restricted scene set, the original 36 scenes are simplified to 5 scenes, which can reduce the amount of calculation and retain important information. Although the probability of the most serious scene 35 in the severely restricted scene set is 10.4%, which is higher than the average probability of 2.78% of the 36 scenes, it is lower than the average probability of 20% of directly selecting 5 typical scenes, so it can better reflect the actual situation. In addition, the constructed severely restricted scene set is obtained by screening actual data, rather than representative data in typical scenes, so it is more credible and effective.

[0145] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0146] Based on the same inventive concept, the embodiment of the present application also provides a distribution network operation scenario screening device for implementing the above-mentioned distribution network operation scenario screening method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations in the one or more distribution network operation scenario screening device embodiments provided below can refer to the limitations of the distribution network operation scenario screening method above, and will not be repeated here.

[0147] In an exemplary embodiment, as shown in FIG7 , a distribution network operation scenario screening device 700 is provided, comprising: a first acquisition module 701, a second acquisition module 702, a third acquisition module 703, a fourth acquisition module 704 and a fifth acquisition module 705, wherein:

[0148] The first acquisition module 701 is used to acquire the capacities of various network resources of the distribution network in each operation scenario of the distribution network.

[0149] The second acquisition module 702 is used to obtain the comprehensive shadow price corresponding to the operation scenario based on the capacity of the multiple network resources, and the shadow price is used to evaluate the impact of the expansion of the network resources on the scheduling cost.

[0150] The third acquisition module 703 is used to obtain various scenario operation costs, demand-side constraints and various distribution network safety operation constraints of the distribution network under the operation scenario.

[0151] The fourth acquisition module 704 is used to acquire the economic dispatch model of the distribution network under the operation scenario based on the comprehensive shadow price, the operation costs of the multiple scenarios, the demand-side constraints and the multiple distribution network safety operation constraints.

[0152] The fifth acquisition module 705 is used to obtain the scenario impact factor of the operating scenario based on the comprehensive shadow price, the economic dispatch model and the occurrence probability of the operating scenario, and to screen out the target operating scenario from all operating scenarios of the distribution network based on the scenario impact factor, and the scenario impact factor is used to evaluate the scarcity of network resources of the distribution network under the operating scenario.

[0153] In some embodiments, the second acquisition module 702 is also used to obtain the initial shadow price corresponding to the network resource based on the capacity of each network resource and the primal-dual interior point method; and to obtain the comprehensive shadow price corresponding to the operating scenario based on all the initial shadow prices corresponding to the operating scenario.

[0154] In some embodiments, the fifth acquisition module 705 is also used to obtain an average value of the scenario impact factors of all operating scenarios for the distribution network; obtain a larger value between the average value and a preset impact factor; and for each operating scenario of the distribution network, if the scenario impact factor of the operating scenario is not less than the larger value, determine the operating scenario as a target operating scenario.

[0155] In some embodiments, the operation scenario screening device 700 of the distribution network is specifically used for scenario operation costs including network loss costs, line operation and maintenance costs, energy storage system operation and maintenance costs, and wind and solar power abandonment and load loss penalty costs; the various distribution network safety operation constraints include distributed power output constraints, power flow equation constraints, line capacity constraints, power purchase from the upper power grid constraints, node voltage constraints, load loss constraints, demand-side response constraints, and energy storage system constraints.

[0156] In some embodiments, the operation scenario screening device 700 of the distribution network is also used to perform second-order cone transformation on the power flow equation constraint and the node voltage constraint respectively based on the second-order cone programming model to obtain corresponding linear constraints.

[0157] In some embodiments, the distribution network operation scenario screening device 700 is also used for the capacity of various network resources including transmission line capacity, energy storage system capacity, energy storage system rated power and demand-side response contract capacity.

[0158] Each module in the above-mentioned distribution network operation scenario screening device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0159] In an exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be shown in FIG8. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, the memory, and the input / output interface are connected via a system bus, and the communication interface, the display unit, and the input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, a near field communication (NFC) or other technologies. When the computer program is executed by the processor, a method for screening operation scenarios of a distribution network is implemented.

[0160] Those skilled in the art will understand that the structure shown in FIG. 8 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0161] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the following steps when executing the computer program: for each operation scenario of a distribution network, obtaining the capacity of various network resources of the distribution network in the operation scenario; obtaining the comprehensive shadow price corresponding to the operation scenario based on the capacity of the various network resources, and the shadow price is used to evaluate the impact of the expansion of the network resources on the dispatching cost; obtaining the operation costs of various scenarios of the distribution network in the operation scenario, demand-side constraints and various distribution network safety operation constraints; obtaining the economic dispatch model of the distribution network in the operation scenario based on the comprehensive shadow price, the operation costs of the various scenarios, the demand-side constraints and the various distribution network safety operation constraints; obtaining the scenario impact factor of the operation scenario based on the comprehensive shadow price, the economic dispatch model and the occurrence probability of the operation scenario, and screening out the target operation scenario from all the operation scenarios of the distribution network based on the scenario impact factor, and the scenario impact factor is used to evaluate the scarcity of network resources of the distribution network in the operation scenario.

[0162] In one embodiment, the method implemented when the processor executes a computer program to obtain the comprehensive shadow price corresponding to the operating scenario based on the capacity of the multiple network resources includes: obtaining the initial shadow price corresponding to the network resource based on the capacity of each network resource and the primal-dual interior point method; and obtaining the comprehensive shadow price corresponding to the operating scenario based on all the initial shadow prices corresponding to the operating scenario.

[0163] In one embodiment, the method implemented by the processor executing a computer program to select a target operating scenario from all operating scenarios of the distribution network based on the scenario influence factor includes: for the distribution network, obtaining an average value of the scenario influence factors of all operating scenarios; obtaining a larger value between the average value and a preset influence factor; for each operating scenario of the distribution network, if the scenario influence factor of the operating scenario is not less than the larger value, determining the operating scenario as the target operating scenario.

[0164] In one embodiment, the scenario operating costs realized when the processor executes the computer program include network loss costs, line operation and maintenance costs, energy storage system operation and maintenance costs, and wind and solar power abandonment and load loss penalty costs; the multiple distribution network safety operation constraints include distributed power source output constraints, power flow equation constraints, line capacity constraints, power purchase from the upper power grid constraints, node voltage constraints, load loss constraints, demand-side response constraints, and energy storage system constraints.

[0165] In one embodiment, the processor executes a computer program based on the comprehensive shadow price, the multiple scenario operating costs, the demand-side constraints and the multiple distribution network safety operation constraints, before obtaining the economic dispatch model of the distribution network under the operating scenario, it also includes: performing second-order cone transformation on the power flow equation constraints and the node voltage constraints based on a second-order cone programming model to obtain corresponding linear constraints.

[0166] In one embodiment, the capacities of the various network resources implemented when the processor executes the computer program include transmission line capacity, energy storage system capacity, energy storage system rated power, and demand-side response contract capacity.

[0167] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: for each operation scenario of a distribution network, the capacity of various network resources of the distribution network in the operation scenario is obtained; based on the capacity of the various network resources, a comprehensive shadow price corresponding to the operation scenario is obtained, and the shadow price is used to evaluate the impact of the expansion of the network resources on the dispatching cost; the operation costs of various scenarios of the distribution network in the operation scenario, demand-side constraints and various distribution network safety operation constraints are obtained; based on the comprehensive shadow price, the operation costs of the various scenarios, the demand-side constraints and the various distribution network safety operation constraints, an economic dispatch model of the distribution network in the operation scenario is obtained; based on the comprehensive shadow price, the operation costs of the various scenarios, the demand-side constraints and the various distribution network safety operation constraints, a scenario impact factor of the operation scenario is obtained based on the comprehensive shadow price, the economic dispatch model and the occurrence probability of the operation scenario, and a target operation scenario is screened out from all the operation scenarios of the distribution network based on the scenario impact factor, and the scenario impact factor is used to evaluate the scarcity of network resources of the distribution network in the operation scenario.

[0168] In one embodiment, the computer program implemented when executed by the processor obtains the comprehensive shadow price corresponding to the operating scenario based on the capacity of the multiple network resources, including: obtaining the initial shadow price corresponding to the network resource based on the capacity of each network resource and the primal-dual interior point method; obtaining the comprehensive shadow price corresponding to the operating scenario based on all the initial shadow prices corresponding to the operating scenario.

[0169] In one embodiment, the computer program implemented when executed by the processor selects a target operating scenario from all operating scenarios of the distribution network based on the scenario influence factor, including: for the distribution network, obtaining an average value of the scenario influence factors of all operating scenarios; obtaining a larger value between the average value and a preset influence factor; for each operating scenario of the distribution network, if the scenario influence factor of the operating scenario is not less than the larger value, determining the operating scenario as the target operating scenario.

[0170] In one embodiment, the scenario operating costs realized when the computer program is executed by the processor include network loss costs, line operation and maintenance costs, energy storage system operation and maintenance costs, and wind and solar power abandonment and load loss penalty costs; the multiple distribution network safety operation constraints include distributed power source output constraints, power flow equation constraints, line capacity constraints, power purchase from the upper power grid constraints, node voltage constraints, load loss constraints, demand side response constraints, and energy storage system constraints.

[0171] In one embodiment, the computer program implemented when executed by the processor based on the comprehensive shadow price, the operating costs of the multiple scenarios, the demand-side constraints and the multiple distribution network safety operation constraints, before obtaining the economic dispatch model of the distribution network under the operating scenario, also includes: performing second-order cone transformation on the power flow equation constraints and the node voltage constraints based on the second-order cone programming model to obtain corresponding linear constraints.

[0172] In one embodiment, the capacities of various network resources implemented when the computer program is executed by a processor include transmission line capacity, energy storage system capacity, energy storage system rated power, and demand-side response contract capacity.

[0173] In one embodiment, a computer program product is provided, comprising a computer program, which implements the following steps when executed by a processor: for each operation scenario of a distribution network, obtaining the capacities of various network resources of the distribution network in the operation scenario; obtaining a comprehensive shadow price corresponding to the operation scenario based on the capacities of the various network resources, the shadow price being used to evaluate the degree of influence of the expansion of the network resources on the dispatching cost; obtaining the operation costs of various scenarios of the distribution network in the operation scenario, demand-side constraints and various distribution network safety operation constraints; obtaining an economic dispatch model of the distribution network in the operation scenario based on the comprehensive shadow price, the operation costs of the various scenarios, the demand-side constraints and the various distribution network safety operation constraints; obtaining a scenario impact factor of the operation scenario based on the comprehensive shadow price, the economic dispatch model and the occurrence probability of the operation scenario, and screening out a target operation scenario from all operation scenarios of the distribution network based on the scenario impact factor, the scenario impact factor being used to evaluate the scarcity of network resources of the distribution network in the operation scenario.

[0174] In one embodiment, the computer program implemented when executed by the processor obtains the comprehensive shadow price corresponding to the operating scenario based on the capacity of the multiple network resources, including: obtaining the initial shadow price corresponding to the network resource based on the capacity of each network resource and the primal-dual interior point method; obtaining the comprehensive shadow price corresponding to the operating scenario based on all the initial shadow prices corresponding to the operating scenario.

[0175] In one embodiment, the computer program implemented when executed by the processor selects a target operating scenario from all operating scenarios of the distribution network based on the scenario influence factor, including: for the distribution network, obtaining an average value of the scenario influence factors of all operating scenarios; obtaining a larger value between the average value and a preset influence factor; for each operating scenario of the distribution network, if the scenario influence factor of the operating scenario is not less than the larger value, determining the operating scenario as the target operating scenario.

[0176] In one embodiment, the scenario operating costs realized when the computer program is executed by the processor include network loss costs, line operation and maintenance costs, energy storage system operation and maintenance costs, and wind and solar power abandonment and load loss penalty costs; the multiple distribution network safety operation constraints include distributed power source output constraints, power flow equation constraints, line capacity constraints, power purchase from the upper power grid constraints, node voltage constraints, load loss constraints, demand side response constraints, and energy storage system constraints.

[0177] In one embodiment, the computer program implemented when executed by the processor based on the comprehensive shadow price, the operating costs of the multiple scenarios, the demand-side constraints and the multiple distribution network safety operation constraints, before obtaining the economic dispatch model of the distribution network under the operating scenario, also includes: performing second-order cone transformation on the power flow equation constraints and the node voltage constraints based on the second-order cone programming model to obtain corresponding linear constraints.

[0178] In one embodiment, the capacities of various network resources implemented when the computer program is executed by a processor include transmission line capacity, energy storage system capacity, energy storage system rated power, and demand-side response contract capacity.

[0179] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0180] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0181] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0182] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for screening operation scenarios of a distribution network, characterized in that: The method comprises: For each operation scenario of the distribution network, obtaining the capacity of multiple network resources of the distribution network under the operation scenario; Obtaining a comprehensive shadow price corresponding to the operation scenario based on the capacity of the multiple network resources, the shadow price being used to evaluate the impact of the expansion of the network resources on the scheduling cost; Obtaining multiple scenario operating costs, demand side constraints and multiple distribution network safety operation constraints of the distribution network under the operating scenario; Based on the comprehensive shadow price, the operating costs of the multiple scenarios, the demand-side constraints and the multiple distribution network safety operation constraints, an economic dispatch model of the distribution network under the operation scenario is obtained; Based on the comprehensive shadow price, the economic dispatch model and the occurrence probability of the operation scenario, the scenario impact factor of the operation scenario is obtained, and based on the scenario impact factor, a target operation scenario is screened out from all operation scenarios of the distribution network. The scenario impact factor is used to evaluate the scarcity of network resources of the distribution network under the operation scenario.

2. The method according to claim 1, characterized in that The obtaining of the comprehensive shadow price corresponding to the operation scenario based on the capacity of the multiple network resources includes: Obtaining the initial shadow price corresponding to each network resource based on the capacity of each network resource and the primal-dual interior point method; A comprehensive shadow price corresponding to the operating scenario is obtained based on all initial shadow prices corresponding to the operating scenario.

3. The method according to claim 1, characterized in that The step of selecting a target operation scenario from all operation scenarios of the distribution network based on the scenario influencing factor includes: For the distribution network, obtaining average values ​​of scenario impact factors of all operating scenarios; Obtaining a larger value between the average value and a preset impact factor; For each operation scenario of the distribution network, when the scenario impact factor of the operation scenario is not less than the larger value, the operation scenario is determined as the target operation scenario.

4. The method according to claim 1, characterized in that The scenario operating costs include network loss costs, line operation and maintenance costs, energy storage system operation and maintenance costs, and wind and solar power abandonment and load loss penalty costs; the various distribution network safety operation constraints include distributed power source output constraints, power flow equation constraints, line capacity constraints, power purchase from the upper power grid constraints, node voltage constraints, load loss constraints, demand-side response constraints, and energy storage system constraints.

5. The method according to claim 4, characterized in that Before obtaining the economic dispatch model of the distribution network in the operation scenario based on the comprehensive shadow price, the multiple scenario operation costs, the demand side constraints and the multiple distribution network safety operation constraints, the method further includes: Based on the second-order cone programming model, the power flow equation constraint and the node voltage constraint are respectively transformed into second-order cones to obtain corresponding linear constraints.

6. The method according to claim 1, characterized in that The capacities of the various network resources include transmission line capacity, energy storage system capacity, energy storage system rated power and demand-side response contract capacity.

7. A distribution network operation scenario screening device, characterized in that: The device comprises: A first acquisition module is used to acquire the capacity of multiple network resources of the distribution network in each operation scenario of the distribution network; A second acquisition module is used to acquire a comprehensive shadow price corresponding to the operation scenario based on the capacity of the multiple network resources, and the shadow price is used to evaluate the impact of the expansion of the network resources on the scheduling cost; A third acquisition module is used to obtain the operating costs of various scenarios of the distribution network under the operating scenario, demand-side constraints and various distribution network safety operation constraints; A fourth acquisition module, configured to acquire an economic dispatch model of the distribution network under the operation scenario based on the comprehensive shadow price, the operation costs of the multiple scenarios, the demand-side constraints and the multiple distribution network safety operation constraints; The fifth acquisition module is used to obtain the scenario impact factor of the operating scenario based on the comprehensive shadow price, the economic dispatch model and the occurrence probability of the operating scenario, and to screen out the target operating scenario from all operating scenarios of the distribution network based on the scenario impact factor, and the scenario impact factor is used to evaluate the scarcity of network resources of the distribution network under the operating scenario.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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