A distribution network optimization scheduling method and system considering power supply capacity

Abstract

The present invention relates to a method and system for optimizing and dispatching a distribution network that takes power supply capacity into account. The method comprises: determining the optimal output of each power source node in the distribution network and the optimal switching state of each line in the distribution network based on the load demand of each load node in the distribution network; and controlling the output of each power source node in the distribution network and the switching state of each line in the distribution network to achieve the optimal output and optimal switching state. The technical solution provided by the present invention coordinates and dispatches controllable resources based on full consideration of the system's power supply capacity, thereby improving the system's distributed power supply absorption capacity, reducing network losses, and enhancing the power quality of the power system.

Description

Technical Field

[0001] The present invention relates to the field of power systems and automation thereof, and in particular to a distribution network optimization scheduling method and system taking power supply capacity into consideration. Background Art

[0002] Energy is one of the key factors influencing the level of socioeconomic development. With the current global trend of rapid clean energy development, renewable energy-based DG has experienced rapid growth. It is a means of addressing the energy crisis and a key support for the transformation of the "large grid" model.

[0003] Traditional distribution networks are now transitioning to active distribution networks (ADNs). Active distribution networks fully utilize controllable resources and are an effective means of supporting large-scale DG integration into distribution networks. Active control of various controllable resources, such as distributed power sources (DGs), battery energy storage systems (BESs), controllable loads, and grid structures, achieves the coordinated optimization goals of active distribution networks. The key to active distribution networks is the proactive integration of DGs into the controllable domain.

[0004] Coordinated control of power generation, grid, load, and storage plays a crucial role in optimizing system operation. Active distribution network coordinated control integrates demand-side management features, considers the multi-timescale characteristics of DG, controllable loads, and BES, incorporates information such as electricity prices and load forecasts, and leverages the ability of tie switches to adjust the grid structure. This technology dispatches controllable resources in the system while ensuring grid security and reliability.

[0005] However, the current literature on the use of coordinated control technology of source, grid, load and storage for controllable resource scheduling has not considered the impact of demand-side load changes on the system's power supply capacity, and its power supply stability needs to be improved. Summary of the Invention

[0006] In view of the shortcomings of the existing technology, the purpose of the present invention is to provide a distribution network optimization scheduling method that takes power supply capacity into consideration. This method coordinates and schedules controllable resources on the basis of fully considering the power supply capacity of the system, thereby improving the absorption capacity of distributed power sources in the system, reducing network losses, and improving the power quality level of the power system.

[0007] The purpose of the present invention is achieved by adopting the following technical solutions:

[0008] The present invention provides a distribution network optimization scheduling method considering power supply capacity, wherein the method comprises:

[0009] Determine the optimal output of each power node in the distribution network and the optimal switching state of each line in the distribution network according to the load demand of each load node in the distribution network;

[0010] Respectively controlling the output of each power node in the distribution network and the switch state of each line in the distribution network to be the optimal output and optimal switch state;

[0011] Wherein, the power supply node is a new energy node or a distributed power supply node.

[0012] Preferably, the optimal output includes optimal active output and optimal reactive output, and determining the optimal output of each power node in the distribution network and the optimal switching state of each line in the distribution network according to the load demand of each load node in the distribution network includes:

[0013] Step a: Substituting the load demand of each load node in the distribution network into a pre-built optimal operation scheduling model, solving the pre-built optimal operation scheduling model, and obtaining the optimal output of each power node in the distribution network and the optimal switching state of each line in the distribution network;

[0014] Step b: amplifying the load demand of each load node in the distribution network, substituting the amplified load demand of each load node in the distribution network, the optimal active output of each new energy node in the power supply node in the distribution network, and the optimal switching state of each line in the distribution network into a pre-established verification model, solving the pre-established verification model, and obtaining the objective function value output by the verification model;

[0015] Step c: Determine whether the objective function value output by the test model is 0. If so, output the optimal active output and optimal reactive output of each power node in the distribution network and the optimal switching state of each line in the distribution network. Otherwise, add test constraints to the pre-built optimal operation scheduling model and return to step a.

[0016] The present invention provides a distribution network optimization scheduling system taking into account power supply capacity, wherein the improvement is that the system comprises:

[0017] A determination module is used to determine the optimal output of each power node in the distribution network and the optimal switching state of each line in the distribution network according to the load demand of each load node in the distribution network;

[0018] A control module, configured to control the output of each power node in the distribution network and the switch state of each line in the distribution network to be the optimal output and optimal switch state respectively;

[0019] Wherein, the power supply node is a new energy node or a distributed power supply node.

[0020] Preferably, the determining module includes:

[0021] A first substitution unit is used to substitute the load demand of each load node in the distribution network into a pre-built optimal operation scheduling model, solve the pre-built optimal operation scheduling model, and obtain the optimal output of each power node in the distribution network and the optimal switching state of each line in the distribution network;

[0022] a second substitution unit, configured to amplify the load demand of each load node in the distribution network, substitute the amplified load demand of each load node in the distribution network, the optimal active output of each new energy node in the power supply node in the distribution network, and the optimal switching state of each line in the distribution network into a pre-established verification model, solve the pre-established verification model, and obtain an objective function value output by the verification model;

[0023] The judgment unit is used to judge whether the objective function value output by the test model is 0. If so, the optimal active output and optimal reactive output of each power node in the distribution network and the optimal switching state of each line in the distribution network are output; otherwise, the test constraint conditions are added to the pre-built optimal operation scheduling model, and the process returns to step a.

[0024] Compared with the closest prior art, the present invention has the following beneficial effects:

[0025] The technical solution provided by the present invention determines the optimal output of each power supply node in the distribution network and the optimal switching state of each line in the distribution network according to the load demand of each load node in the distribution network; controls the output of each power supply node in the distribution network and the switching state of each line in the distribution network to be the optimal output and optimal switching state respectively; coordinates and dispatches controllable resources on the basis of fully considering the power supply capacity of the system, thereby improving the absorption capacity of distributed power sources in the system, reducing network losses, and improving the power quality level of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of a method for optimizing the dispatch of a distribution network taking into account the power supply capacity;

[0027] Figure 2 It is a structural diagram of a distribution network optimization scheduling system that takes power supply capacity into consideration. DETAILED DESCRIPTION

[0028] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0030] In order to give full play to the regulation and complementary characteristics of controllable resources such as grid, distributed energy, and energy storage, the present invention provides a distribution network optimization scheduling method that takes power supply capacity into consideration. This method establishes an optimal operation scheduling model with multiple objectives, such as maximizing renewable energy utilization and minimizing the number of line switch operations, and a verification model that can ensure the power supply capacity of the system. By coordinating the optimal operation scheduling model and the verification model, the optimal scheduling of controllable resources in the system is achieved while ensuring the power supply reliability of the system. Figure 1 As shown, the method includes:

[0031] Step 101. Determine the optimal output of each power node in the distribution network and the optimal switching state of each line in the distribution network according to the load demand of each load node in the distribution network;

[0032] Step 102: Control the output of each power node in the distribution network and the switch state of each line in the distribution network to the optimal output and optimal switch state respectively;

[0033] Wherein, the power supply node is a new energy node or a distributed power supply node.

[0034] Specifically, the optimal output includes optimal active output and optimal reactive output. Step 101 includes:

[0035] Step a: Substituting the load demand of each load node in the distribution network into a pre-built optimal operation scheduling model, solving the pre-built optimal operation scheduling model, and obtaining the optimal output of each power node in the distribution network and the optimal switching state of each line in the distribution network;

[0036] Step b: amplifying the load demand of each load node in the distribution network, substituting the amplified load demand of each load node in the distribution network, the optimal active output of each new energy node in the power supply node in the distribution network, and the optimal switching state of each line in the distribution network into a pre-established verification model, solving the pre-established verification model, and obtaining the objective function value output by the verification model;

[0037] Step c: Determine whether the objective function value output by the test model is 0. If so, output the optimal active output and optimal reactive output of each power node in the distribution network and the optimal switching state of each line in the distribution network. Otherwise, add test constraints to the pre-built optimal operation scheduling model and return to step a.

[0038] Furthermore, the objective function of the optimal operation scheduling model is determined as follows:

[0039] minF=w1·f1+w2·f2

[0040] Where F is the objective function value of the optimal operation scheduling model, w1 is the weight corresponding to the utilization rate of renewable energy, f1 is the inverse of the utilization rate of renewable energy in the distribution network during the control period, w2 is the weight corresponding to the number of line switch operations in the distribution network, and f2 is the number of line switch operations in the distribution network during the control period.

[0041] Among them, the new energy utilization rate f1 of the distribution network during the control period is determined by the following formula:

[0042]

[0043] Where, is the output of the xth new energy node in the power supply node of the distribution network consumed at the tth moment of the control cycle, P NE,x (t) is the actual output of the xth new energy node in the power node of the distribution network at the tth moment of the control period, t∈(1~N T ), N T is the total number of control cycle moments, x∈(1~N J ), N J is the total number of new energy nodes in the power nodes of the distribution network;

[0044] The number of line switch operations f2 of the distribution network in the control cycle is determined by the following formula:

[0045]

[0046] Where μ ij,t is the switching state of line ij in the distribution network at the tth moment of the control cycle, μ ij,t-1 is the switch state of line ij in the distribution network at the t-1th moment of the control cycle, ij∈(1~N B ), N B is the total number of lines in the distribution network;

[0047] Among them, at the tth moment of the control cycle, the switch state of line ij in the distribution network is open, then μ ij,t =1, otherwise, μ ij,t =0;

[0048] At the t-1th moment of the control cycle, the switch state of line ij in the distribution network is open, then μ ij,t-1 =1, otherwise, μ ij,t-1 =0.

[0049] Furthermore, the interactive output constraints of the active distribution network and the large power grid in the objective function of the optimal operation scheduling model are determined as follows:

[0050]

[0051]

[0052] Where, is the equivalent current of active power output provided by the large power grid to node i in the distribution network at the tth moment of the control cycle, is the preset minimum value of the equivalent current of the active power output provided by the large power grid to node i in the distribution network, is the preset maximum value of the equivalent current of the active power output provided by the large power grid to node i in the distribution network, is the equivalent current of reactive power output provided by the large power grid to node i in the distribution network at the tth moment of the control period, is the preset minimum value of the equivalent current of the reactive power output provided by the large power grid to node i in the distribution network, is the preset maximum value of the equivalent current of the reactive power output provided by the large power grid to node i in the distribution network;

[0053] The output linear power flow constraint condition of the objective function of the optimal operation scheduling model is determined as follows:

[0054]

[0055]

[0056] Where G ij is the conductance of line ij in the distribution network, B ij is the susceptance of line ij in the distribution network, β ij,t is the product of the switch state of line ij in the distribution network and the imaginary part of the voltage at node j in the distribution network at the tth moment of the control cycle, β ji,t is the product of the switch state of line ij in the distribution network and the imaginary part of the voltage of node i in the distribution network at the tth moment of the control period, α ij,t is the product of the switch state of line ij in the distribution network and the real part of the voltage of node j in the distribution network at the tth moment of the control period, α ji,t is the product of the switch state of line ij in the distribution network and the real part of the voltage of node i in the distribution network at the tth moment of the control period, is the equivalent current of active power output provided by the large power grid to node i in the distribution network at the tth moment of the control cycle, is the equivalent current of the active output of the distributed generation input to node i in the distribution network at the tth moment of the control period, is the real part of the voltage at node i in the distribution network at the tth moment of the control cycle, is the equivalent current of the renewable energy active power input to node i in the distribution network at the tth moment of the control period, is the imaginary part of the voltage at node i in the distribution network at the tth moment of the control cycle, is the equivalent current of reactive power output provided by the large power grid to node i in the distribution network at the tth moment of the control period, is the equivalent current of the reactive output of the distributed generation input to node i in the distribution network at the tth moment of the control period, is the equivalent current of the renewable energy reactive power input to node i in the distribution network at the tth moment of the control period, is the equivalent current of the active load demand of node i in the distribution network at the tth moment of the control period, G i,t is the equivalent conductance of the load demand of node i in the distribution network at the tth moment of the control period, B i,t is the equivalent susceptance of the load demand at node i in the distribution network at the tth moment of the control period, is the equivalent current of the reactive load demand of node i in the distribution network at the tth moment of the control period, j∈(1~n), n is the total number of nodes in the distribution network except node i;

[0057] in, is the real part of the voltage at node j in the distribution network at the tth moment of the control period, The maximum value of the real part of the voltage at node j in the distribution network is preset. The preset minimum value for the real part of the voltage at node j in the distribution network, is the imaginary part of the voltage at node j in the distribution network at the tth moment of the control period, The maximum value of the imaginary part of the voltage at node j in the distribution network is preset. Preset the minimum value for the imaginary part of the voltage at node j in the distribution network;

[0058] The branch current constraint of the objective function of the optimal operation scheduling model is determined as follows:

[0059]

[0060] Where, is the real current of line ij in the distribution network at the tth moment of the control period, is the imaginary current of line ij in the distribution network at the tth moment of the control cycle, is the maximum current allowed on line ij in the distribution network;

[0061] The voltage constraint condition of the objective function of the optimal operation and dispatching model of the distribution network is determined as follows:

[0062]

[0063] Where, is the real part of the voltage at node i in the distribution network at the tth moment of the control cycle, V i max is the maximum voltage of node i in the distribution network, V i min is the minimum voltage of node i in the distribution network;

[0064] The distributed power constraints of the objective function of the optimal operation scheduling model are determined as follows:

[0065]

[0066] Where, is the equivalent current of the active output of the distributed generation input to node i in the distribution network at the tth moment of the control period, is the minimum value of the equivalent current of the active output of the distributed generation input to node i in the distribution network, is the maximum value of the equivalent current of the active output of the distributed generation input to node i in the distribution network;

[0067] The network radial constraint condition of the objective function of the optimal operation scheduling model is determined as follows:

[0068]

[0069] Where, τ ij is the output flow state variable of line ij in the distribution network, τ ji is the output flow state variable of line ji in the distribution network, μ ij is the switching state of line ij in the distribution network, N i is the set of parent nodes with node i in the distribution network as child node, and N1 is the set of line head nodes in the distribution network;

[0070] Among them, when node i in the distribution network is the parent node of node j, then τ ij =1, otherwise, τ ij =0; when node j in the distribution network is the parent node of node i, then τ ji =1, otherwise, τ ji =0.

[0071] In the best embodiment of the present invention, the traditional optimization scheduling model adopts a nonlinear power flow model. Compared with the linear model, it is difficult to ensure the globality of the solution and the solution is more difficult. The optimization scheduling model of the present invention is an output-type linear power flow model established by converting the load node equivalently into a linearized load model in which the node admittance is connected in parallel with the current source, and converting the output of the new energy / distributed power source into an injected current source model.

[0072] Furthermore, the equivalent current of the active power output provided by the large power grid to the node i in the distribution network at the tth moment of the control cycle is determined as follows:

[0073]

[0074] The equivalent current of the reactive power output provided by the large power grid to the node i in the distribution network at the tth moment of the control cycle is determined by the following formula:

[0075]

[0076] The equivalent current of the distributed power source active output input at node i in the distribution network at the tth moment of the control cycle is determined by the following formula:

[0077]

[0078] The equivalent current of the reactive output of the distributed generation input to node i in the distribution network at the tth moment of the control cycle is determined by the following formula:

[0079]

[0080] The equivalent current of the renewable energy active output input at node u in the distribution network at the tth moment of the control cycle is determined by the following formula:

[0081]

[0082] The equivalent current of the renewable energy reactive power input at node i in the distribution network at the tth moment of the control cycle is determined by the following formula:

[0083]

[0084] The equivalent current of the active load demand of node i in the distribution network at the tth moment of the control period is determined by the following formula:

[0085]

[0086] The equivalent current of the reactive load demand of node i in the distribution network at the tth moment of the control period is determined by the following formula:

[0087]

[0088] The equivalent conductance G of the load demand of node i in the distribution network at the tth moment of the control period is determined by the following formula: i，t :

[0089]

[0090] The equivalent susceptance B of the load demand of node i in the distribution network at the tth moment of the control period is determined as follows: i,t :

[0091]

[0092] Where V i 0 is the reference voltage of node i in the distribution network, is the active power output provided by the large power grid to node i in the distribution network at the tth moment of the control cycle, is the reactive power output provided by the large power grid to node i in the distribution network at the tth moment of the control cycle, is the active power output of the distributed generation input to node i in the distribution network at the tth moment of the control period, Z i,t is the inverse of the voltage at node u in the distribution network at the tth moment of the control cycle, is the reactive power output of the distributed generation input to node i in the distribution network at the tth moment of the control period, is the active power output of renewable energy input to node u in the distribution network at the tth moment of the control period, is the reactive power output of renewable energy input to node i in the distribution network at the tth moment of the control period, is the active load demand of node i in the distribution network at the tth moment of the control period, C I is the proportionality coefficient between the reactive load demand of node i in the distribution network and the quadratic term of the voltage at node i in the distribution network, is the reactive load demand of node i in the distribution network at the tth moment of the control period, C′ I is the proportionality coefficient between the reactive load demand of node i in the distribution network and the first-order term of the voltage at node i in the distribution network, C' Z is the proportional coefficient between the active load demand of node i in the distribution network and the first-order term of the voltage at node i in the distribution network, C Z is the proportional coefficient between the active load demand of node i in the distribution network and the quadratic term of the voltage of node i in the distribution network; is the preset maximum value of the inverse of the voltage at node u in the distribution network, It is the preset minimum value of the inverse of the voltage at node u in the distribution network.

[0093] In the best embodiment of the present invention, for loads, their actual operating conditions are mostly related to the actual voltage level of the node, so the impact of voltage level fluctuations on node loads should be considered during the optimization scheduling process.

[0094] Currently commonly used load models include the ZI model, the ZIP model, the exponential model, etc. The ZI model is adopted in the present invention.

[0095]

[0096] Where, P(V i ) and Q(V i ) are the actual operating active power demand and reactive power demand of node i; P0 and Q0 are the initial active power demand and reactive power demand of the load node respectively; V i and V0 are the actual operating voltage and initial reference voltage of the node respectively; and are the current phasor, load phasor and voltage phasor of node i respectively; V i re and V i im are the real and imaginary parts of the voltage at node i, respectively. The load in this invention mainly requires power. This current is outflowing from the node, and its direction is from the node to the load:

[0097]

[0098] Combining the above two formulas, we can get the equivalent calculation formula for current:

[0099]

[0100] In the distribution network, the phase angle of the node voltage is generally small, which means that the imaginary part of the node voltage V i im Small. In fact, the real part of the node voltage is often hundreds of times larger than the imaginary part. Mathematically speaking, this means that the imaginary part of the node voltage can be ignored.

[0101]

[0102]

[0103] Decomposing the current phasor into real and imaginary parts, we can get the current calculation formula: and represent the real and imaginary parts of the current at node i respectively.

[0104]

[0105] The current phasor is decomposed into real and imaginary parts and can be expressed as:

[0106]

[0107] According to the corresponding equality of the real and imaginary parts, we can make equivalent substitutions and obtain:

[0108]

[0109] Where, P i L and are the active and reactive power demands of node i respectively; and are the equivalent branch conductance and equivalent branch susceptance of node i respectively; and are the real part and imaginary part of the equivalent injection current source required by the load at node i; V i 0 is the reference node voltage value of node i, which is generally set to the rated voltage.

[0110] The equivalent model of the output injected from the large power grid to the active distribution network node is:

[0111]

[0112] Where, P i G and are the active and reactive power injected from the large power grid to the distribution network node i; and are the real and imaginary parts of the equivalent current injected from the large power grid into the distribution network node i:

[0113] Considering that the imaginary part of the node voltage can be approximately ignored and the substation node will be selected as the balancing node in the distribution network, the substation node voltage is approximated to the balancing node voltage, and the injection current of the power supply equivalent current source can be approximately obtained as:

[0114]

[0115] The node voltage of the substation can be approximated to the voltage of the balancing node. Generally, the balancing node is set to a voltage value of 1.0 pu. Except for the node voltage of the transformer, other nodes will not meet this setting.

[0116] For some nodes connected to distributed power sources, new energy sources or other power sources, the following transformations must be performed, namely:

[0117]

[0118]

[0119] Where, is the real part of the equivalent injection current of the distributed power / new energy output at node i, is the imaginary part of the equivalent injection current of the distributed power / new energy output at node i, P i is the active power output injected by distributed power / new energy at node i, Q i is the reactive power injected by distributed power / new energy at node i, Z i The parameter introduced is actually the derivative of the voltage at node i, is the minimum value of the inverse of the voltage at node i, is the maximum value of the inverse of the voltage at node i.

[0120] The current scheduling cannot fully take into account a large number of external uncertainties in the operation of the distribution network. These factors will cause safety hazards in the operation of the system. Therefore, while considering the maximum utilization rate of new energy and the minimum operation of the interconnection line switches in the scheduling, the power supply capacity of the system should also be considered.

[0121] The power supply capacity is mainly reflected in the ability to meet the load. Different load levels determine different distribution network power supply capacities. When the load level is low, the distribution network power supply capacity is relatively strong, otherwise it is relatively small. To measure the power supply capacity of the distribution network, it is necessary to plan the changes in the load. The evaluation results of different load growth methods are also different, including but not limited to the following two growth modes: one is that the current total actual load increases proportionally; the other is that the local area load increases in positive proportion, and other loads remain unchanged. In order to ensure the reliability of power supply, the present invention designs a verification model, in which the objective function of the verification model is determined by the following formula:

[0122] Furthermore, the objective function of the verification model is determined as follows:

[0123]

[0124] Where, t∈(1~N T ), N T is the total number of control cycle moments, Z t The change in the sum of the actual injected currents of each node in the distribution network after the load demand of each node in the distribution network is amplified at the t-th moment of the control period compared with the previous value;

[0125] Among them, the change Z of the sum of the actual injected current of each node in the distribution network after the load demand of each node in the distribution network is amplified at the tth moment of the control cycle is calculated as follows: t :

[0126]

[0127] Where, is the real part increase of the actual injected current of node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the reduction in the real part of the actual injected current at node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the increase in the imaginary part of the actual injected current of node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the reduction in the imaginary part of the actual injected current of node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, i∈(1~N), N is the total number of nodes in the distribution network, and All are not less than 0;

[0128] The interactive output constraints of the active distribution network and the large power grid in the objective function of the test model are determined as follows:

[0129]

[0130]

[0131] Where, is the equivalent current of active power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the preset minimum value of the equivalent current of the active power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the preset maximum value of the equivalent current of the active power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the equivalent current of reactive power provided to node i by the large power grid after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the preset minimum value of the equivalent current of the reactive power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, The preset maximum value of the equivalent current of the reactive power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle;

[0132] The output linear power flow constraint condition of the objective function of the test model is determined as follows:

[0133]

[0134] Where G ij is the conductance of line ij in the distribution network, B ij is the susceptance of line ij in the distribution network, χ ij,t To test the switching state of line ij in the distribution network at the tth moment of the control cycle in the model, The real part of the voltage at node j after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: The real part of the voltage at node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: The imaginary part of the voltage at node j after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: The imaginary part of the voltage at node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: is the equivalent current of active power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, The equivalent current of the distributed generation active output input by node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: is the equivalent current corresponding to the active output of renewable energy input to node i in the distribution network at the tth moment of the control cycle in the verification model, is the equivalent current of reactive power provided to node i by the large power grid after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, The equivalent current of the reactive output of the distributed generation input by node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: The equivalent current of the renewable energy reactive power input by node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: is the equivalent current of the active load demand of node i after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the equivalent conductance of the load demand of node i after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the equivalent susceptance of the load demand of node i after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the equivalent current of the reactive power demand of node i after amplifying the load demand of each node in the distribution network at the tth moment of the control period, j∈(1~n), n is the total number of nodes in the distribution network except node i, where, is the optimal switching state of line ij in the distribution network at the tth moment of the control cycle, is the optimal renewable energy active power output of node i in the distribution network at the tth moment of the control period;

[0135] The branch current constraint conditions of the objective function of the test model are determined as follows:

[0136]

[0137] Where, is the real part of the current on line ij in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the imaginary part of the current on line ij in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the maximum current allowed on line ij in the distribution network;

[0138] The voltage constraint of the objective function of the test model is determined as follows:

[0139]

[0140] Where, is the real part of the voltage at node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, To amplify the load demand of each node in the distribution network, the maximum voltage of node i is: The minimum voltage value of node i after amplifying the load demand of each node in the distribution network;

[0141] The distributed generation constraints of the objective function of the distribution network test model are determined as follows:

[0142]

[0143] Where, The equivalent current of the distributed generation active output input to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: To amplify the load demand of each node in the distribution network, the minimum equivalent current of the distributed generation active output input to node i is: The maximum value of the equivalent current of the distributed generation active output input to node i after amplifying the load demand of each node in the distribution network;

[0144] The renewable energy reactive output constraint condition of the objective function of the distribution network test model is determined as follows:

[0145]

[0146] Where, The minimum value of the equivalent current of the renewable energy reactive output input by node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, It is the maximum value of the equivalent current of the renewable energy reactive output input by node i after amplifying the load demand of each node in the distribution network at the tth moment of the control period.

[0147] In a specific example of the present invention, if the objective function value solved by the test model is 0, that is, the test model can converge, indicating that when the load demand of each node increases proportionally (for example: the load demand of each node is proportionally amplified to K times the original), the system can still operate stably; on the contrary, the power supply capacity cannot meet the power supply capacity requirements, and it is necessary to add a set of test constraints to the optimal operation scheduling model and re-solve it. Because the load fluctuation in the actual power supply process is within a certain range, the load fluctuation generally does not exceed 30% of the load, so K can be taken as 1.3.

[0148] Furthermore, the inspection constraint condition is determined as follows:

[0149]

[0150] Where λ ij,t For the formula The dual variable, μ ij,t is the switching state of line ij in the distribution network at the tth moment of the control cycle, ρ ij,t for The dual variable of is the renewable energy active power output of node i in the distribution network at the tth moment of the control period, ij∈(1~N B ), N B is the total number of lines in the distribution network.

[0151] The present invention provides a distribution network optimization scheduling system considering power supply capacity, such as Figure 2 As shown, the system includes:

[0152] A determination module is used to determine the optimal output of each power node in the distribution network and the optimal switching state of each line in the distribution network according to the load demand of each load node in the distribution network;

[0153] A control module, configured to control the output of each power node in the distribution network and the switch state of each line in the distribution network to be the optimal output and optimal switch state respectively;

[0154] Wherein, the power supply node is a new energy node or a distributed power supply node.

[0155] Specifically, the determination module includes:

[0156] A first substitution unit is used to substitute the load demand of each load node in the distribution network into a pre-built optimal operation scheduling model, solve the pre-built optimal operation scheduling model, and obtain the optimal output of each power node in the distribution network and the optimal switching state of each line in the distribution network;

[0157] a second substitution unit, configured to amplify the load demand of each load node in the distribution network, substitute the amplified load demand of each load node in the distribution network, the optimal active output of each new energy node in the power supply node in the distribution network, and the optimal switching state of each line in the distribution network into a pre-established verification model, solve the pre-established verification model, and obtain an objective function value output by the verification model;

[0158] The judgment unit judges whether the objective function value output by the test model is 0. If so, the optimal active output and optimal reactive output of each power node in the distribution network and the optimal switching state of each line in the distribution network are output. Otherwise, the test constraint conditions are added to the pre-built optimal operation scheduling model, and the process returns to step a.

[0159] Furthermore, the objective function of the optimal operation scheduling model is determined as follows:

[0160] minF=w1·f1+w2·f2

[0161] Where F is the objective function value of the optimal operation scheduling model, w1 is the weight corresponding to the utilization rate of renewable energy, f1 is the inverse of the utilization rate of renewable energy in the distribution network during the control period, w2 is the weight corresponding to the number of line switch operations in the distribution network, and f2 is the number of line switch operations in the distribution network during the control period.

[0162] Among them, the new energy utilization rate f1 of the distribution network during the control period is determined by the following formula:

[0163]

[0164] Where, is the output of the xth new energy node in the power supply node of the distribution network consumed at the tth moment of the control cycle, P NE,x (t) is the actual output of the xth new energy node in the power node of the distribution network at the tth moment of the control period, t∈(1~N T ), N T is the total number of control cycle moments, x∈(1~N J ), N J is the total number of new energy nodes in the power nodes of the distribution network;

[0165] The number of line switch operations f2 of the distribution network in the control cycle is determined by the following formula:

[0166]

[0167] Where μ ij,t is the switching state of line ij in the distribution network at the tth moment of the control cycle, μ ij,t-1 is the switch state of line ij in the distribution network at the t-1th moment of the control cycle, ij∈(1~N B ), N B is the total number of lines in the distribution network;

[0168] Among them, at the tth moment of the control cycle, the switch state of line ij in the distribution network is open, then μ ij,t =1, otherwise, μ ij,t =0;

[0169] At the t-1th moment of the control cycle, the switch state of line ij in the distribution network is open, then μ ij,t-1 =1, otherwise, μ ij,t-1 =0.

[0170] Furthermore, the interactive output constraints of the active distribution network and the large power grid in the objective function of the optimal operation scheduling model are determined as follows:

[0171]

[0172]

[0173] Where, is the equivalent current of active power output provided by the large power grid to node i in the distribution network at the tth moment of the control cycle, is the preset minimum value of the equivalent current of the active power output provided by the large power grid to node i in the distribution network, is the preset maximum value of the equivalent current of the active power output provided by the large power grid to node i in the distribution network, is the equivalent current of reactive power output provided by the large power grid to node i in the distribution network at the tth moment of the control period, is the preset minimum value of the equivalent current of the reactive power output provided by the large power grid to node i in the distribution network, is the preset maximum value of the equivalent current of the reactive power output provided by the large power grid to node i in the distribution network;

[0174] The output linear power flow constraint condition of the objective function of the optimal operation scheduling model is determined as follows:

[0175]

[0176]

[0177] Where G ij is the conductance of line ij in the distribution network, B ijis the susceptance of line ij in the distribution network, β ij,t is the product of the switch state of line ij in the distribution network and the imaginary part of the voltage at node j in the distribution network at the tth moment of the control cycle, β ji,t is the product of the switch state of line ij in the distribution network and the imaginary part of the voltage of node i in the distribution network at the tth moment of the control period, α ij,t is the product of the switch state of line ij in the distribution network and the real part of the voltage of node j in the distribution network at the tth moment of the control period, α ji,t is the product of the switch state of line ij in the distribution network and the real part of the voltage of node i in the distribution network at the tth moment of the control period, is the equivalent current of active power output provided by the large power grid to node i in the distribution network at the tth moment of the control cycle, is the equivalent current of the active output of the distributed generation input to node i in the distribution network at the tth moment of the control period, is the real part of the voltage at node i in the distribution network at the tth moment of the control cycle, is the equivalent current of the renewable energy active power input to node i in the distribution network at the tth moment of the control period, is the imaginary part of the voltage at node i in the distribution network at the tth moment of the control cycle, is the equivalent current of reactive power output provided by the large power grid to node i in the distribution network at the tth moment of the control period, is the equivalent current of the reactive output of the distributed generation input to node i in the distribution network at the tth moment of the control period, is the equivalent current of the renewable energy reactive power input to node i in the distribution network at the tth moment of the control period, is the equivalent current of the active load demand of node i in the distribution network at the tth moment of the control period, G i,t is the equivalent conductance of the load demand of node i in the distribution network at the tth moment of the control period, B i,t is the equivalent susceptance of the load demand at node i in the distribution network at the tth moment of the control period, is the equivalent current of the reactive load demand of node i in the distribution network at the tth moment of the control period, j∈(1~n), n is the total number of nodes in the distribution network except node i;

[0178] in, is the real part of the voltage at node j in the distribution network at the tth moment of the control period, The maximum value of the real part of the voltage at node j in the distribution network is preset. The preset minimum value for the real part of the voltage at node j in the distribution network, is the imaginary part of the voltage at node j in the distribution network at the tth moment of the control period, The maximum value of the imaginary part of the voltage at node j in the distribution network is preset. Preset the minimum value for the imaginary part of the voltage at node j in the distribution network;

[0179] The branch current constraint of the objective function of the optimal operation scheduling model is determined as follows:

[0180]

[0181] Where, is the real current of line ij in the distribution network at the tth moment of the control period, is the imaginary current of line ij in the distribution network at the tth moment of the control cycle, is the maximum current allowed on line ij in the distribution network;

[0182] The voltage constraint condition of the objective function of the optimal operation and dispatching model of the distribution network is determined as follows:

[0183]

[0184] Where, is the real part of the voltage at node i in the distribution network at the tth moment of the control cycle, V i max is the maximum voltage of node i in the distribution network, V i min is the minimum voltage of node i in the distribution network;

[0185] The distributed power constraints of the objective function of the optimal operation scheduling model are determined as follows:

[0186]

[0187] Where, is the equivalent current of the active output of the distributed generation input to node i in the distribution network at the tth moment of the control period, is the minimum value of the equivalent current of the active output of the distributed generation input to node i in the distribution network, is the maximum value of the equivalent current of the active output of the distributed generation input to node i in the distribution network;

[0188] The network radial constraint condition of the objective function of the optimal operation scheduling model is determined as follows:

[0189]

[0190] Where, τ ij is the output flow state variable of line ij in the distribution network, τ ji is the output flow state variable of line ji in the distribution network, μ ijis the switching state of line ij in the distribution network, N i is the set of parent nodes with node i in the distribution network as child node, and N1 is the set of line head nodes in the distribution network;

[0191] Among them, when node i in the distribution network is the parent node of node j, then τ ij =1, otherwise, τ ij =0; when node j in the distribution network is the parent node of node i, then τ ji =1, otherwise, τ ji =0.

[0192] Furthermore, the equivalent current of the active power output provided by the large power grid to the node i in the distribution network at the tth moment of the control cycle is determined as follows:

[0193]

[0194] The equivalent current of the reactive power output provided by the large power grid to the node i in the distribution network at the tth moment of the control cycle is determined by the following formula:

[0195]

[0196] The equivalent current of the distributed power source active output input at node i in the distribution network at the tth moment of the control cycle is determined by the following formula:

[0197]

[0198] The equivalent current of the reactive output of the distributed generation input to node i in the distribution network at the tth moment of the control cycle is determined by the following formula:

[0199]

[0200] The equivalent current of the renewable energy active output input at node u in the distribution network at the tth moment of the control cycle is determined by the following formula:

[0201]

[0202] The equivalent current of the renewable energy reactive power input at node i in the distribution network at the tth moment of the control cycle is determined by the following formula:

[0203]

[0204] The equivalent current of the active load demand of node i in the distribution network at the tth moment of the control period is determined by the following formula:

[0205]

[0206] The equivalent current of the reactive load demand of node i in the distribution network at the tth moment of the control period is determined by the following formula:

[0207]

[0208] The equivalent conductance G of the load demand of node i in the distribution network at the tth moment of the control period is determined by the following formula: i,t :

[0209]

[0210] The equivalent susceptance B of the load demand of node i in the distribution network at the tth moment of the control period is determined as follows: i,t：

[0211]

[0212] Where V i 0 is the reference voltage of node i in the distribution network, is the active power output provided by the large power grid to node i in the distribution network at the tth moment of the control cycle, is the reactive power output provided by the large power grid to node i in the distribution network at the tth moment of the control cycle, is the active power output of the distributed generation input to node i in the distribution network at the tth moment of the control period, Z i,t is the inverse of the voltage at node u in the distribution network at the tth moment of the control cycle, is the reactive power output of the distributed generation input to node i in the distribution network at the tth moment of the control period, is the active power output of renewable energy input to node u in the distribution network at the tth moment of the control period, is the reactive power output of renewable energy input to node i in the distribution network at the tth moment of the control period, is the active load demand of node i in the distribution network at the tth moment of the control period, C I is the proportionality coefficient between the reactive load demand of node i in the distribution network and the quadratic term of the voltage at node i in the distribution network, is the reactive load demand of node i in the distribution network at the tth moment of the control period, C′ I is the proportionality coefficient between the reactive load demand of node i in the distribution network and the first-order term of the voltage at node i in the distribution network, C' Z is the proportional coefficient between the active load demand of node i in the distribution network and the first-order term of the voltage at node i in the distribution network, C Zis the proportional coefficient between the active load demand of node i in the distribution network and the quadratic term of the voltage of node i in the distribution network; is the preset maximum value of the inverse of the voltage at node u in the distribution network, It is the preset minimum value of the inverse of the voltage at node u in the distribution network.

[0213] Furthermore, the objective function of the verification model is determined as follows:

[0214]

[0215] Where, t∈(1~N T ), N T is the total number of control cycle moments, Z t The change in the sum of the actual injected currents of each node in the distribution network after the load demand of each node in the distribution network is amplified at the t-th moment of the control period compared with the previous value;

[0216] Among them, the change Z of the sum of the actual injected current of each node in the distribution network after the load demand of each node in the distribution network is amplified at the tth moment of the control cycle is calculated as follows: t :

[0217]

[0218] Where, is the real part increase of the actual injected current of node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the reduction in the real part of the actual injected current at node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the increase in the imaginary part of the actual injected current of node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the reduction in the imaginary part of the actual injected current of node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, i∈(1~N), N is the total number of nodes in the distribution network, and All are not less than 0;

[0219] The interactive output constraints of the active distribution network and the large power grid in the objective function of the test model are determined as follows:

[0220]

[0221]

[0222] Where, is the equivalent current of active power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the preset minimum value of the equivalent current of the active power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the preset maximum value of the equivalent current of the active power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the equivalent current of reactive power provided to node i by the large power grid after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the preset minimum value of the equivalent current of the reactive power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, The preset maximum value of the equivalent current of the reactive power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle;

[0223] The output linear power flow constraint condition of the objective function of the test model is determined as follows:

[0224]

[0225] Where G ij is the conductance of line ij in the distribution network, B ij is the susceptance of line ij in the distribution network, χ ij,t To test the switching state of line ij in the distribution network at the tth moment of the control cycle in the model, The real part of the voltage at node j after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: The real part of the voltage at node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: The imaginary part of the voltage at node j after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: The imaginary part of the voltage at node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: is the equivalent current of active power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, The equivalent current of the distributed generation active output input by node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: is the equivalent current corresponding to the active output of renewable energy input to node i in the distribution network at the tth moment of the control cycle in the verification model, is the equivalent current of reactive power provided to node i by the large power grid after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, The equivalent current of the reactive output of the distributed generation input by node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: The equivalent current of the renewable energy reactive power input by node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: is the equivalent current of the active load demand of node i after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the equivalent conductance of the load demand of node i after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the equivalent susceptance of the load demand of node i after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the equivalent current of the reactive power demand of node i after amplifying the load demand of each node in the distribution network at the tth moment of the control period, j∈(1~n), n is the total number of nodes in the distribution network except node i, where, is the optimal switching state of line ij in the distribution network at the tth moment of the control cycle, is the optimal renewable energy active power output of node i in the distribution network at the tth moment of the control period;

[0226] The branch current constraint conditions of the objective function of the test model are determined as follows:

[0227]

[0228] Where, is the real part of the current on line ij in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the imaginary part of the current on line ij in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the maximum current allowed on line ij in the distribution network;

[0229] The voltage constraint of the objective function of the test model is determined as follows:

[0230]

[0231] Where, is the real part of the voltage at node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, To amplify the load demand of each node in the distribution network, the maximum voltage of node i is: The minimum voltage value of node i after amplifying the load demand of each node in the distribution network;

[0232] The distributed generation constraints of the objective function of the distribution network test model are determined as follows:

[0233]

[0234] Where, The equivalent current of the distributed generation active output input to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: To amplify the load demand of each node in the distribution network, the minimum equivalent current of the distributed generation active output input to node i is: The maximum value of the equivalent current of the distributed generation active output input to node i after amplifying the load demand of each node in the distribution network;

[0235] The renewable energy reactive output constraint condition of the objective function of the distribution network test model is determined as follows:

[0236]

[0237] Where, The minimum value of the equivalent current of the renewable energy reactive output input by node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, It is the maximum value of the equivalent current of the renewable energy reactive output input by node i after amplifying the load demand of each node in the distribution network at the tth moment of the control period.

[0238] Furthermore, the inspection constraint condition is determined as follows:

[0239]

[0240] Where λ ij,t For the formula The dual variable, μ ij,t is the switching state of line ij in the distribution network at the tth moment of the control cycle, ρ ij,t for The dual variable of is the renewable energy active power output of node i in the distribution network at the tth moment of the control period, ij∈(1~N B ), N B is the total number of lines in the distribution network.

[0241] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can 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 can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0242] 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 produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. 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.

[0243] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work 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 The function specified in one or more boxes.

[0244] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0245] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A distribution network optimization scheduling method considering power supply capacity, characterized in that: The method comprises: Determine the optimal output of each power node in the distribution network and the optimal switching state of each line in the distribution network according to the load demand of each load node in the distribution network; Respectively controlling the output of each power node in the distribution network and the switch state of each line in the distribution network to be the optimal output and optimal switch state; Wherein, the power supply node is a new energy node or a distributed power supply node; Wherein, the optimal output includes the optimal active output and the optimal reactive output; The determining of the optimal output of each power node in the distribution network and the optimal switching state of each line in the distribution network according to the load demand of each load node in the distribution network includes: Step a: Substituting the load demand of each load node in the distribution network into a pre-built optimal operation scheduling model, solving the pre-built optimal operation scheduling model, and obtaining the optimal output of each power node in the distribution network and the optimal switching state of each line in the distribution network; Step b: amplifying the load demand of each load node in the distribution network, substituting the amplified load demand of each load node in the distribution network, the optimal active output of each new energy node in the power supply node in the distribution network, and the optimal switching state of each line in the distribution network into a pre-established verification model, solving the pre-established verification model, and obtaining the objective function value output by the verification model; Step c: Determine whether the objective function value output by the test model is 0. If so, output the optimal active power output and optimal reactive power output of each power node in the distribution network and the optimal switching state of each line in the distribution network. Otherwise, add test constraints to the pre-built optimal operation scheduling model and return to step a. The objective function of the optimal operation scheduling model is determined as follows: minF=w1·f1+w2·f2 Where F is the objective function value of the optimal operation scheduling model, w1 is the weight corresponding to the utilization rate of renewable energy, f1 is the inverse of the utilization rate of renewable energy in the distribution network during the control period, w2 is the weight corresponding to the number of line switch operations in the distribution network, and f2 is the number of line switch operations in the distribution network during the control period. Among them, the new energy utilization rate f1 of the distribution network during the control period is determined by the following formula: Where, is the output of the xth new energy node in the power supply node of the distribution network consumed at the tth moment of the control cycle, P NE,x (t) is the actual output of the xth new energy node in the power node of the distribution network at the tth moment of the control period, t∈(1~N T ), N T is the total number of control cycle moments, x∈(1~N J ), N J is the total number of new energy nodes in the power nodes of the distribution network; The number of line switch operations f2 of the distribution network in the control cycle is determined by the following formula: Where μ ij,t is the switching state of line ij in the distribution network at the tth moment of the control cycle, μ ij,t-1 is the switch state of line ij in the distribution network at the t-1th moment of the control cycle, ij∈(1~N B ), N B is the total number of lines in the distribution network; Among them, at the tth moment of the control cycle, the switch state of line ij in the distribution network is open, then μ ij,t =1, otherwise, μ ij,t =0; At the t-1th moment of the control cycle, the switch state of line ij in the distribution network is open, then μ ij,t-1 =1, otherwise, μ ij,t-1 =0.

2. The method according to claim 1, characterized in that The constraints of the objective function of the optimal operation scheduling model include: interactive output constraints of the active distribution network and the large power grid, output-type linear power flow constraints, branch current constraints, voltage constraints, distributed power supply constraints and network radial constraints.

3. The method according to claim 2, wherein The interactive output constraint conditions between the active distribution network and the large power grid are determined as follows: Where, is the equivalent current of active power output provided by the large power grid to node i in the distribution network at the tth moment of the control cycle, is the preset minimum value of the equivalent current of the active power output provided by the large power grid to node i in the distribution network, is the preset maximum value of the equivalent current of the active power output provided by the large power grid to node i in the distribution network, is the equivalent current of reactive power output provided by the large power grid to node i in the distribution network at the tth moment of the control period, is the preset minimum value of the equivalent current of the reactive power output provided by the large power grid to node i in the distribution network, is the preset maximum value of the equivalent current of the reactive power output provided by the large power grid to node i in the distribution network; The output type linear power flow constraint condition is determined as follows: Where G ij is the conductance of line ij in the distribution network, B ij is the susceptance of line ij in the distribution network, β ij,t is the product of the switch state of line ij in the distribution network and the imaginary part of the voltage at node j in the distribution network at the tth moment of the control cycle, β ji,t is the product of the switch state of line ij in the distribution network and the imaginary part of the voltage of node i in the distribution network at the tth moment of the control period, α ij,t is the product of the switch state of line ij in the distribution network and the real part of the voltage of node j in the distribution network at the tth moment of the control period, α ji,t is the product of the switch state of line ij in the distribution network and the real part of the voltage of node i in the distribution network at the tth moment of the control period, is the equivalent current of active power output provided by the large power grid to node i in the distribution network at the tth moment of the control cycle, is the equivalent current of the active output of the distributed generation input to node i in the distribution network at the tth moment of the control period, is the real part of the voltage at node i in the distribution network at the tth moment of the control cycle, is the equivalent current of the renewable energy active power input to node i in the distribution network at the tth moment of the control period, is the imaginary part of the voltage at node i in the distribution network at the tth moment of the control cycle, is the equivalent current of reactive power output provided by the large power grid to node i in the distribution network at the tth moment of the control period, is the equivalent current of the reactive output of the distributed generation input to node i in the distribution network at the tth moment of the control period, is the equivalent current of the renewable energy reactive power input to node i in the distribution network at the tth moment of the control period, is the equivalent current of the active load demand of node i in the distribution network at the tth moment of the control period, G i,t is the equivalent conductance of the load demand of node i in the distribution network at the tth moment of the control period, B i,t is the equivalent susceptance of the load demand at node i in the distribution network at the tth moment of the control period, is the equivalent current of the reactive load demand of node i in the distribution network at the tth moment of the control period, j∈(1~n), n is the total number of nodes in the distribution network except node i; in, is the real part of the voltage at node j in the distribution network at the tth moment of the control period, The maximum value of the real part of the voltage at node j in the distribution network is preset. The preset minimum value for the real part of the voltage at node j in the distribution network, is the imaginary part of the voltage at node j in the distribution network at the tth moment of the control period, The maximum value of the imaginary part of the voltage at node j in the distribution network is preset. Preset the minimum value for the imaginary part of the voltage at node j in the distribution network; The branch current constraint condition is determined as follows: Where, is the real current of line ij in the distribution network at the tth moment of the control period, is the imaginary current of line ij in the distribution network at the tth moment of the control cycle, is the maximum current allowed on line ij in the distribution network; The voltage constraint condition is determined as follows: Where, is the real part of the voltage at node i in the distribution network at the tth moment of the control cycle, V i max is the maximum voltage of node i in the distribution network, V i min is the minimum voltage of node i in the distribution network; The distributed power constraints are determined as follows: Where, is the equivalent current of the active output of the distributed generation input to node i in the distribution network at the tth moment of the control period, is the minimum value of the equivalent current of the active output of the distributed generation input to node i in the distribution network, is the maximum value of the equivalent current of the active output of the distributed generation input to node i in the distribution network; The network radial constraint condition is determined as follows: Where, τ ij is the output flow state variable of line ij in the distribution network, τ ji is the output flow state variable of line ji in the distribution network, μ ij is the switching state of line ij in the distribution network, N i is the set of parent nodes with node i in the distribution network as child node, and N1 is the set of line head nodes in the distribution network; Among them, when node i in the distribution network is the parent node of node j, then τ ij =1, otherwise, τ ij =0; when node j in the distribution network is the parent node of node i, then τ ji =1, otherwise, τ ji =0.

4. The method according to claim 3, wherein The equivalent current of the active power output provided by the large power grid to the node i in the distribution network at the tth moment of the control cycle is determined by the following formula: : The equivalent current of the reactive power output provided by the large power grid to the node i in the distribution network at the tth moment of the control cycle is determined by the following formula: : The equivalent current of the distributed power source active output input at node i in the distribution network at the tth moment of the control cycle is determined by the following formula: : The equivalent current of the reactive output of the distributed generation input to node i in the distribution network at the tth moment of the control cycle is determined by the following formula: : The equivalent current of the renewable energy active output input at node u in the distribution network at the tth moment of the control cycle is determined by the following formula: : The equivalent current of the renewable energy reactive power input at node i in the distribution network at the tth moment of the control cycle is determined by the following formula: : The equivalent current of the active load demand of node i in the distribution network at the tth moment of the control period is determined by the following formula: : The equivalent current of the reactive load demand of node i in the distribution network at the tth moment of the control period is determined by the following formula: : The equivalent conductance G of the load demand of node i in the distribution network at the tth moment of the control period is determined by the following formula: i,t : The equivalent susceptance B of the load demand of node i in the distribution network at the tth moment of the control period is determined as follows: i,t : Where V i 0 is the reference voltage of node i in the distribution network, is the active power output provided by the large power grid to node i in the distribution network at the tth moment of the control cycle, is the reactive power output provided by the large power grid to node i in the distribution network at the tth moment of the control cycle, is the active power output of the distributed generation input to node i in the distribution network at the tth moment of the control period, Z i,t is the inverse of the voltage at node u in the distribution network at the tth moment of the control cycle, is the reactive power output of the distributed generation input to node i in the distribution network at the tth moment of the control period, is the active power output of renewable energy input to node u in the distribution network at the tth moment of the control period, is the reactive power output of renewable energy input to node i in the distribution network at the tth moment of the control period, is the active load demand of node i in the distribution network at the tth moment of the control period, C I is the proportionality coefficient between the reactive load demand of node i in the distribution network and the quadratic term of the voltage at node i in the distribution network, is the reactive load demand of node i in the distribution network at the tth moment of the control period, C' I is the proportionality coefficient between the reactive load demand of node i in the distribution network and the first-order term of the voltage at node i in the distribution network, C' Z is the proportional coefficient between the active load demand of node i in the distribution network and the first-order term of the voltage at node i in the distribution network, C Z is the proportional coefficient between the active load demand of node i in the distribution network and the quadratic term of the voltage of node i in the distribution network; is the preset maximum value of the inverse of the voltage at node u in the distribution network, It is the preset minimum value of the inverse of the voltage at node u in the distribution network.

5. The method according to claim 1, wherein The objective function of the verification model is determined as follows: Where, t∈(1~N T ), N T is the total number of control cycle moments, Z t The change in the sum of the actual injected currents of each node in the distribution network after the load demand of each node in the distribution network is amplified at the t-th moment of the control period compared with the previous value; Among them, the change Z of the sum of the actual injected current of each node in the distribution network after the load demand of each node in the distribution network is amplified at the tth moment of the control cycle is calculated as follows: t : Where, is the real part increase of the actual injected current of node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the reduction in the real part of the actual injected current at node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the increase in the imaginary part of the actual injected current of node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the reduction in the imaginary part of the actual injected current of node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, i∈(1~N), N is the total number of nodes in the distribution network, and Are not less than 0.

6. The method according to claim 5, wherein The constraints of the objective function of the test model include: interactive output constraints of the active distribution network and the large power grid, output-type linear power flow constraints, branch current constraints, voltage constraints, distributed power supply constraints and new energy reactive output constraints.

7. The method according to claim 6, wherein The interactive output constraint conditions between the active distribution network and the large power grid are determined as follows: Where, is the equivalent current of active power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the preset minimum value of the equivalent current of the active power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the preset maximum value of the equivalent current of the active power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the equivalent current of reactive power provided to node i by the large power grid after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the preset minimum value of the equivalent current of the reactive power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, The preset maximum value of the equivalent current of the reactive power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle; The output type linear power flow constraint condition is determined as follows: Where G ij is the conductance of line ij in the distribution network, B ij is the susceptance of line ij in the distribution network, χ ij,t To test the switching state of line ij in the distribution network at the tth moment of the control cycle in the model, The real part of the voltage at node j after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: The real part of the voltage at node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: The imaginary part of the voltage at node j after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: The imaginary part of the voltage at node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: is the equivalent current of active power output provided by the large power grid to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, The equivalent current of the distributed generation active output input by node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: is the equivalent current corresponding to the active output of renewable energy input to node i in the distribution network at the tth moment of the control cycle in the verification model, is the equivalent current of reactive power provided to node i by the large power grid after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, The equivalent current of the reactive output of the distributed generation input by node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: The equivalent current of the renewable energy reactive power input by node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: is the equivalent current of the active load demand of node i after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the equivalent conductance of the load demand of node i after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the equivalent susceptance of the load demand of node i after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the equivalent current of the reactive power demand of node i after amplifying the load demand of each node in the distribution network at the tth moment of the control period, j∈(1~n), n is the total number of nodes in the distribution network except node i, where, is the optimal switching state of line ij in the distribution network at the tth moment of the control cycle, is the optimal renewable energy active power output of node i in the distribution network at the tth moment of the control period; The branch current constraint condition is determined as follows: Where, is the real part of the current on line ij in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the imaginary part of the current on line ij in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the maximum current allowed on line ij in the distribution network; The voltage constraint condition is determined as follows: Where, is the real part of the voltage at node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, To amplify the load demand of each node in the distribution network, the maximum voltage of node i is: The minimum voltage value of node i after amplifying the load demand of each node in the distribution network; The distributed power constraints are determined as follows: Where, The equivalent current of the distributed generation active output input to node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle is: To amplify the load demand of each node in the distribution network, the minimum equivalent current of the distributed generation active output input to node i is: The maximum value of the equivalent current of the distributed generation active output input to node i after amplifying the load demand of each node in the distribution network; The reactive power output constraint condition of the new energy source is determined as follows: Where, The minimum value of the equivalent current of the renewable energy reactive output input by node i after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, It is the maximum value of the equivalent current of the renewable energy reactive output input by node i after amplifying the load demand of each node in the distribution network at the tth moment of the control period.

8. The method according to claim 1, wherein The inspection constraint condition is determined as follows: Where λ ij,t For the formula The dual variable, μ ij,t is the switching state of line ij in the distribution network at the tth moment of the control cycle, ρ ij,t for The dual variable of is the renewable energy active power output of node i in the distribution network at the tth moment of the control period, ij∈(1~N B ), N B is the total number of lines in the distribution network.

9. A distribution network optimization scheduling system considering power supply capacity, characterized in that: The system comprises: A determination module is used to determine the optimal output of each power node in the distribution network and the optimal switching state of each line in the distribution network according to the load demand of each load node in the distribution network; A control module, configured to control the output of each power node in the distribution network and the switch state of each line in the distribution network to be the optimal output and optimal switch state respectively; Wherein, the power supply node is a new energy node or a distributed power supply node; Wherein, the determining module includes: A first substitution unit is used to substitute the load demand of each load node in the distribution network into a pre-built optimal operation scheduling model, solve the pre-built optimal operation scheduling model, and obtain the optimal output of each power node in the distribution network and the optimal switching state of each line in the distribution network; a second substitution unit, configured to amplify the load demand of each load node in the distribution network, substitute the amplified load demand of each load node in the distribution network, the optimal active output of each new energy node in the power supply node in the distribution network, and the optimal switching state of each line in the distribution network into a pre-established verification model, solve the pre-established verification model, and obtain an objective function value output by the verification model; A judgment unit determines whether the objective function value output by the test model is 0. If so, the optimal active output and optimal reactive output of each power node in the distribution network and the optimal switching state of each line in the distribution network are output; otherwise, a test constraint condition is added to the pre-built optimal operation scheduling model, and the process returns to step a. The objective function of the optimal operation scheduling model is determined as follows: minF=w1·f1+w2·f2 Where F is the objective function value of the optimal operation scheduling model, w1 is the weight corresponding to the utilization rate of renewable energy, f1 is the inverse of the utilization rate of renewable energy in the distribution network during the control period, w2 is the weight corresponding to the number of line switch operations in the distribution network, and f2 is the number of line switch operations in the distribution network during the control period. Among them, the new energy utilization rate f1 of the distribution network during the control period is determined by the following formula: Where, is the output of the xth new energy node in the power supply node of the distribution network consumed at the tth moment of the control cycle, P NE,x (t) is the actual output of the xth new energy node in the power node of the distribution network at the tth moment of the control period, t∈(1~N T ), N T is the total number of control cycle moments, x∈(1~N J ), N J is the total number of new energy nodes in the power nodes of the distribution network; The number of line switch operations f2 of the distribution network in the control cycle is determined by the following formula: Where μ ij,t is the switching state of line ij in the distribution network at the tth moment of the control cycle, μ ij,t-1 is the switch state of line ij in the distribution network at the t-1th moment of the control cycle, ij∈(1~N B ), N B is the total number of lines in the distribution network; Among them, at the tth moment of the control cycle, the switch state of line ij in the distribution network is open, then μ ij,t =1, otherwise, μ ij,t =0; At the t-1th moment of the control cycle, the switch state of line ij in the distribution network is open, then μ ij,t-1 =1, otherwise, μ ij,t-1 =0.

10. The system according to claim 9, wherein: The objective function of the verification model is determined as follows: Where, t∈(1~N T ), N T is the total number of control cycle moments, Z t The change in the sum of the actual injected currents of each node in the distribution network after the load demand of each node in the distribution network is amplified at the t-th moment of the control period compared with the previous value; Among them, the change Z of the sum of the actual injected current of each node in the distribution network after the load demand of each node in the distribution network is amplified at the tth moment of the control cycle is calculated as follows: t : Where, is the real part increase of the actual injected current of node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the reduction in the real part of the actual injected current at node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control period, is the increase in the imaginary part of the actual injected current of node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, is the reduction in the imaginary part of the actual injected current of node i in the distribution network after amplifying the load demand of each node in the distribution network at the tth moment of the control cycle, i∈(1~N), N is the total number of nodes in the distribution network, and Are not less than 0.

11. The system according to claim 9, wherein The inspection constraint condition is determined as follows: Where λ ij,t For the formula The dual variable, μ ij,t is the switching state of line ij in the distribution network at the tth moment of the control cycle, ρ ij,t for The dual variable of is the renewable energy active power output of node i in the distribution network at the tth moment of the control period, ij∈(1~N B ), N B is the total number of lines in the distribution network.

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