CN109494750B - Hierarchical distributed voltage optimization control method for high and medium voltage distribution network - Google Patents

Abstract

The application discloses a hierarchical distributed voltage optimization control method of a high-medium voltage distribution network, which comprises the following steps: dividing a high-medium voltage power distribution network into an upper power distribution network and a lower power distribution network; the optimization models in the upper and lower power distribution networks are subjected to salifying to obtain global optimization models; decomposing the global optimization model into a main problem and a plurality of sub-problems; respectively calculating optimization parameters of boundary variables of mutual transmission between an upper power distribution network and a lower power distribution network; repeating the previous step until the upper and lower bound deviations of the global optimization target are smaller than a preset value. The double-layer power distribution network with the mutual master-slave structure remarkably reduces the complexity of global optimization calculation through a small amount of data exchange and distributed alternate calculation, fully exerts the mutual voltage supporting capability between high and medium voltage power distribution networks and avoids the power generation loss of distributed photovoltaic. And carrying out hierarchical distributed optimization calculation on the model, and issuing control instructions to continuous voltage regulating equipment, discrete equipment and the like in the power distribution network based on the obtained optimization calculation result.

Description

A Hierarchical Distributed Voltage Optimal Control Method for Medium and High Voltage Distribution Networks

technical field

The present application relates to the technical field of electric power security, in particular to a layered distributed voltage optimization control method for a medium and high voltage distribution network.

Background technique

With the increasing penetration of distributed photovoltaics in the distribution network, the distribution network has changed from a passive one-way distribution network to an active network with two-way power flow, and is facing operational challenges such as power flow reversal and voltage over-limit. This not only limits the ability of the distribution network to accept distributed photovoltaics, but also seriously threatens the safe and stable operation of the distribution network. Therefore, the control and management of reactive power regulation equipment and distributed photovoltaics in the high and medium voltage distribution network has become an important task for the optimal operation of the system.

Currently, voltage optimization control for high and medium voltage distribution networks is usually implemented independently. In the medium-voltage distribution network, the boundary point of the two-level distribution network is the balance node. The voltage optimization control of the medium-voltage distribution network is generally realized by the distribution automation system through reactive power optimization or active-reactive power joint optimization. Optimal dispatching of medium voltage distribution networks. In the high-voltage distribution network, the boundary transmission power of the two-level distribution network is the load power of the boundary node, and the voltage optimization control of the high-voltage distribution network is realized by the three-level voltage control of the local AVC system. Under the constraints of voltage safety operation Realize the economically optimal operation of high-voltage distribution network through reactive power optimization. Reactive power optimization is to realize the distributed iterative calculation of the reactive power optimization model under voltage constraints through the decomposition and coordination between distribution network sub-regions, micro-grids and nodes, so as to minimize the network active power loss. The active-reactive power joint optimization is to achieve the optimization goal of minimizing the active power loss and photovoltaic power generation loss of the distribution network through the distributed optimization calculation among the clusters.

For the above-mentioned voltage optimization control methods of high-voltage and medium-voltage distribution networks, the operation optimization of high-voltage distribution networks is only based on the voltage of individual substation outlet busbars, and cannot consider the overall voltage level of medium-voltage distribution networks, so it cannot play its role in the distribution of medium-voltage distribution networks. In the face of the access of distributed photovoltaics with high penetration rate, the medium-voltage distribution network can only use distributed photovoltaics to solve the line overvoltage, which will easily force some photovoltaics to leave the grid, resulting in the loss of photovoltaic power generation. In addition, the distribution network distributed voltage optimization control method is limited by the convergence of distributed optimization algorithms, and can only optimize the output power of continuous voltage regulation equipment such as distributed photovoltaics, energy storage devices, and static var compensators, and cannot consider Optimal scheduling of discrete equipment such as on-load tap changer transformers and feeder switches.

Contents of the invention

This application provides a layered distributed voltage optimization control method for medium and high voltage distribution networks to solve the problem that the medium and high voltage distribution networks in the prior art cannot regulate the voltage of the medium voltage distribution network and cannot control the discrete voltage in the distribution network. Technical problems of optimal scheduling of equipment.

In order to solve the above technical problems, the embodiment of the present application discloses the following technical solutions:

The embodiment of the present application discloses a hierarchical distributed voltage optimization control method for a medium and high voltage distribution network, the method comprising:

Step S100: dividing the high and medium voltage distribution network into an upper-level distribution network and a lower-level distribution network, and the upper-level distribution network and the lower-level distribution network have a master-slave control structure;

Step S200: Convexize the optimization models in the upper distribution network and the lower distribution network to obtain a global optimization model;

Step S300: decomposing the global optimization model into a main problem and multiple sub-problems;

Step S400: Calculating the main problem and the sub-problem respectively to obtain an optimized solution, and the upper distribution network and the lower distribution network transmit optimal parameters of boundary variables to each other;

Step S500: Repeat step S400 until the deviation between the upper and lower bounds of the global optimization objective is less than a preset value.

Optionally, in the above-mentioned layered distributed voltage optimization control method for the high and medium voltage distribution network, the division of the high and medium voltage distribution network into the upper distribution network and the lower distribution network includes: taking the 35kV outlet bus as the boundary , dividing the high and medium voltage distribution network into the upper distribution network and the lower distribution network.

Optionally, in the above-mentioned layered distributed voltage optimization control method for high and medium voltage distribution networks, the optimization models in the upper distribution network and the lower distribution network are convexized to obtain a global optimization model, including :

The optimization model of the upper distribution network is a reactive power optimization model, the optimization model of the lower distribution network is an active-reactive power joint optimization model, and the reactive power optimization model and the active-reactive power joint optimization model are combined Carry out convexization to obtain the global optimization model.

Optionally, in the above-mentioned hierarchical distributed voltage optimization control method for high and medium voltage distribution networks, the reactive power optimization model and the active-reactive power joint optimization model are performed using second-order cone relaxation and LinDistFlow reduction equations Convex.

Optionally, in the above-mentioned layered distributed voltage optimization control method for high and medium voltage distribution networks, the global optimization model is expressed as:

stm=1,...,N _MV

x _m ∈ X _m ,G _MV,m (x _m )≤0

y∈Y,G _HV (y)≤0

H _m (x _m ,y) = 0

In the formula: x _m is the optimization variable of the lower distribution network m, y is the optimization variable of the upper distribution network, N _MV is the number of the lower distribution network, G _MV,m (x _m ) is the The operation constraint of the lower distribution network is a function of x _m , G _HV (y) is the operation constraint of the upper distribution network and a function of y, H _m (x _m ,y)=0 is the Boundary equation constraints of the lower distribution network m and the upper distribution network.

Optionally, in the above-mentioned hierarchical distributed voltage optimization control method for high and medium voltage distribution networks, the global optimization model is decomposed into a master problem and multiple sub-problems, including: adopting the master-slave decomposition method of the GBD algorithm, decomposing The global optimization model is decomposed into a main problem and multiple sub-problems.

Optionally, in the above-mentioned layered distributed voltage optimization control method for high and medium voltage distribution networks, the main problem and the sub-problems are calculated respectively to obtain an optimal solution, the upper distribution network and the lower distribution network The optimized parameters for transferring boundary variables between networks, including:

Step S401: Initialize parameters, initialize iteration algebra k=1, optimize cut plane number p _m =0, feasible cut plane number q _m =0, global optimization model objective function lower bound LB=-∞, objective function upper bound UB=∞ ;

Step S402: The lower distribution network solves the sub-problem,

min f _MV,m (x _m )

stx _m ∈ X _m ,G _MV,m (x _m )≤0

If the sub-problem has a feasible solution, then p _m is increased by 1, and the optimized cut plane backfilling main problem is constructed, and the expression of the optimized cut plane constraint is:

If the sub-problem has no feasible solution, then _qm is increased by 1, and a feasible cutting plane is constructed to supplement the main problem. The expression of the feasible cutting plane constraint is:

Step S403: The upper distribution network solves the main problem,

Optionally, in the above-mentioned layered distributed voltage optimization control method for high and medium voltage distribution networks, the expression of the optimization cut plane constraint is introduced

Then the expression of the optimization cut plane constraint is expressed as:

Optionally, in the above-mentioned layered distributed voltage optimization control method for high and medium voltage distribution networks, the expression of the feasible cut plane constraint is introduced

Then the expression of the feasible cut plane constraint is expressed as:

Optionally, in the above-mentioned layered distributed voltage optimization control method for high and medium voltage distribution networks, the deviation up to the upper and lower bounds of the global optimization target is less than a preset value, including: the preset value δ is set to 0.01.

Compared with the prior art, the beneficial effects of the present application are:

The present application provides a hierarchical distributed voltage optimization control method for a high- and medium-voltage distribution network. The method includes: dividing the high- and medium-voltage distribution network into an upper-level distribution network and a lower-level distribution network, and the upper-level distribution network and the master-slave control structure between the lower-level distribution network; the optimization model in the upper-level distribution network and the lower-level distribution network is convexized to obtain a global optimization model; the global optimization model is decomposed into A main problem and a plurality of sub-problems; respectively calculate the main problem and the sub-problems to obtain an optimized solution, and the optimized parameters of the boundary variables are transmitted between the upper distribution network and the lower distribution network; repeat the previous step , until the upper and lower bound deviations of the global optimization objective are less than the preset value. In this application, the high and medium voltage distribution network is divided into upper and lower distribution networks. The two-layer distribution network with a master-slave structure minimizes network loss and voltage regulation costs through a small amount of data exchange and distributed alternate calculations, significantly reducing The complexity of the global optimization calculation is reduced, and the mutual voltage support ability between the high and medium voltage distribution networks is fully utilized to avoid the loss of distributed photovoltaic power generation. In addition, through the global optimization model in this application, the layered distributed optimization calculation is carried out to obtain the optimal scheduling strategy of each control equipment, and based on the obtained optimization calculation results, the control of continuous voltage regulation equipment and discrete equipment in the distribution network is issued. Instructions to implement network reconfiguration.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.

Description of drawings

In order to illustrate the technical solution of the present application more clearly, the accompanying drawings that need to be used in the embodiments will be briefly introduced below. Obviously, for those of ordinary skill in the art, on the premise of not paying creative work, there are also Additional figures can be derived from these figures.

Fig. 1 is a schematic flow diagram of a layered distributed voltage optimization control method for a high and medium voltage distribution network provided by an embodiment of the present invention;

FIG. 2 is a schematic diagram of the basic structure of a layered distributed voltage optimization control system for a high and medium voltage distribution network provided by an embodiment of the present invention;

Fig. 3 is a network topology of a high-voltage distribution network provided by an embodiment of the present invention.

Detailed ways

In order to enable those skilled in the art to better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described The embodiments are only some of the embodiments of the present application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

Referring to FIG. 1 , it is a schematic flowchart of a hierarchical distributed voltage optimization control method for a medium and high voltage distribution network provided by an embodiment of the present invention. As can be seen in conjunction with Figure 1, the method includes the following steps:

Step S100: dividing the high and medium voltage distribution network into an upper-level distribution network and a lower-level distribution network, and the upper-level distribution network and the lower-level distribution network have a master-slave control structure;

This application takes the 35kV outlet bus as the boundary, and divides the high and medium voltage distribution network into the upper distribution network and the lower distribution network based on the master-slave decomposition idea of the generalized Benders decomposition algorithm. Referring to FIG. 2 , it is a schematic diagram of a basic structure of a layered distributed voltage optimization control system for a medium and high voltage distribution network provided by an embodiment of the present invention. As shown in Figure 2, the high-voltage distribution network in the figure consists of a 220kV substation, multiple 110kV substations and 35kV substations, and multiple medium-voltage distribution networks. This application intends to use the master-slave control structure shown in Figure 2 to realize the distributed voltage optimization control of the high and medium voltage distribution network. Based on a small amount of data communication and decomposition coordination algorithm between the substation and the double-layer distribution network, the hierarchical distributed computing of the global optimization model is realized.

Step S200: Convexize the optimization models in the upper distribution network and the lower distribution network to obtain a global optimization model;

The optimization model of the upper distribution network is a reactive power optimization model, and the optimization model of the lower distribution network is an active-reactive power joint optimization model. In order to reduce the difficulty of solving the optimization model and ensure the convergence of the GBD algorithm, this application The reactive power optimization model and the active-reactive power joint optimization model are convexized by using second-order cone relaxation and the LinDistFlow reduction equation to obtain the global optimization model.

The global optimization model is expressed as:

stm=1,...,N _MV

x _m ∈ X _m ,G _MV,m (x _m )≤0

y∈Y,G _HV (y)≤0

H _m (x _m ,y) = 0

和/>

相关。In the formula: x _m is the optimization variable of the lower distribution network m, y is the optimization variable of the upper distribution network, N _MV is the number of the lower distribution network, G _MV,m (x _m ) is the The operation constraint of the lower distribution network is a function of x _m , G _HV (y) is the operation constraint of the upper distribution network and a function of y, H _m (x _m ,y)=0 is the The boundary equation constraints of the lower distribution network m and the upper distribution network, and only with

and />

relevant.

Step S300: decomposing the global optimization model into a main problem and multiple sub-problems;

This application adopts the master-slave decomposition method of the GBD algorithm to decompose the global optimization model into a master problem and multiple sub-problems.

Step S400: Calculating the main problem and the sub-problem respectively to obtain an optimized solution, and the upper distribution network and the lower distribution network transmit optimal parameters of boundary variables to each other;

In the distributed optimization iterative process of the high and medium voltage distribution network, the interactive data between the upper and lower distribution networks are shown in Table 1:

Table 1:

In order to realize the distributed calculation of the global optimization model of the high-medium voltage distribution network, the present invention decomposes the global optimization model into a master problem and multiple sub-problems for alternate calculation based on the master-slave decomposition idea of the GBD algorithm. The high-voltage distribution network and each medium-voltage distribution network independently solve the main problem and each sub-problem, and after obtaining the optimal solution in each round, transmit the optimal parameters of the boundary variables to each other. In order to reduce the amount of communication data between double-layer distribution networks, the present invention adjusts the solution process of the GBD algorithm, and the specific solution process is as follows:

Step S401: Initialize parameters, initialize iteration algebra k=1, optimize cut plane number p _m =0, feasible cut plane number q _m =0, global optimization model objective function lower bound LB=-∞, objective function upper bound UB=∞ , the feasible initial value of the boundary variable of the high-voltage distribution network

求解如下子优化问题：Step S402: The lower distribution network solves sub-problems. In the objective function of the global optimization model, only f _MV,m (x _m ) is related to the variable x _m , so the distribution network m is based on the boundary variables of the high-voltage distribution network

Solve the following sub-optimization problem:

min f _MV,m (x _m )

stx _m ∈ X _m ,G _MV,m (x _m )≤0

对应的拉格朗日乘子/>

利用目标函数值f_MV,m(x_m)更新中压配电网m的目标函数UB_MV,m，并构建优化割平面回补主问题，优化割平面约束的表达式为：If the subproblem has a feasible solution, p _m is increased by 1 to solve the boundary equality constraints

The corresponding Lagrangian multiplier />

Use the objective function value f _MV,m (x _m ) to update the objective function UB _MV,m of the medium-voltage distribution network m, and construct the main problem of optimal cut plane compensation. The expression of the optimal cut plane constraint is:

In order to reduce the amount of communication data between the upper distribution network and the lower distribution network, it is possible to introduce

Then the expression of the optimization cut plane constraint is expressed as:

If the subproblem has no feasible solution, then _qm is increased by 1, and the slack variable is introduced to construct the following relaxed optimization problem:

stx _m ∈ X _m ,G _MV,m (x _m )≤0

α _i ≥0,i=1,2,...,6

目标函数上界UB_MV,m不变，并构建可行割平面回补给主问题，可行割平面约束的表达式为：Solve the corresponding optimal solution x _root,m and the multipliers λ ₁ ～λ ₆ corresponding to the boundary constraints, and let

The upper bound of the objective function UB _MV,m remains unchanged, and a feasible cutting plane is constructed to supplement the main problem. The expression of the feasible cutting plane constraint is:

In order to reduce the amount of communication data between the upper distribution network and the lower distribution network, it is possible to introduce

Then the expression of the feasible cut plane constraint is expressed as:

和中压配电网的目标函数值，开展上层配电网最优潮流计算，以更新全局优化目标的上界UB。然后，基于所有中压配电网的可行割和优化割平面参数，上层配电网求解主问题：Step S403: The upper distribution network solves the main problem. First, the HV distribution network is based on all boundary variables

and the objective function value of the medium-voltage distribution network, carry out the optimal power flow calculation of the upper distribution network to update the upper bound UB of the global optimization objective. Then, based on the feasible cuts of all medium-voltage distribution networks and the optimized cut plane parameters, the upper distribution network solves the main problem:

赋值，用于下轮迭代计算。Use the obtained objective function value to update the lower bound LB of the global optimization objective, and use the optimal solution as

Assignment, used for the next round of iterative calculation.

Step S500: Repeat step S400 until the deviation between the upper and lower bounds of the global optimization objective is less than a preset value.

In this application, the preset value is set manually. When the difference between LB and UB is less than a certain value, the distributed optimization is considered to be converged. Generally, it is about 1% of the objective function value, and its value is set to 0.01 in the calculation example of this application.

Referring to FIG. 3 , it is a network topology of a high-voltage distribution network provided by an embodiment of the present invention. Combined with Figure 3, only the medium-voltage distribution network with 80, 81, and 82 busbars connected to the grid is connected to a distributed photovoltaic power generation system, which are defined as DN1, DN2, and DN3 respectively. These three medium-voltage distribution networks contain 81, 61 and 97 nodes respectively. The network topology and distributed photovoltaic access locations are shown in Figure 2. The present invention selects the high-voltage distribution network shown in Figure 3 and three medium-voltage distribution networks containing distributed photovoltaics to verify the proposed hierarchical distributed optimization method, and uses historical operating data at a certain moment to carry out simulation calculations.

边界传输有功/>

和无功/>

功率(MW)以及各子问题的目标函数值UB_MV,m(￥)。Table 2 is the boundary variable and objective function of DN2 in the hierarchical distributed iterative process provided by the embodiment of the present invention, and Table 2 shows the square of the DN2 boundary voltage for solving the main problem in the hierarchical distributed optimization process

Boundary transmission active power/>

and var/>

Power (MW) and the objective function value UB _MV,m (￥) of each sub-problem.

Table 2:

As shown in Table 2, when iterating to the 12th generation, the difference between the upper bound UB and the lower bound LB of the global optimization objective is only 0.0099￥. The number of iterations required to converge is much less than distributed optimization methods based on the method of alternating direction multipliers. The latter requires hundreds of iterations to achieve better convergence.

Table 3 shows the optimal cut and feasible cut parameters of DN2 in the layered distributed iterative process of the embodiment of the present invention.

table 3:

反之，配网m在本次迭代中不存在可行解，后四列对应为子问题的可行割平面参数/>

In Table 3, the parameters in the p _m column are specific values, while the parameters in the q _m column are "-", indicating that there is a feasible solution for the distribution network m in k iterations, and the parameters in the last four columns correspond to the optimized cutting plane parameters of the subproblem m

On the contrary, there is no feasible solution for the distribution network m in this iteration, and the last four columns correspond to the feasible cutting plane parameters of the subproblem/>

In order to verify the accuracy of the proposed hierarchical distributed optimization method, the present invention further builds the global centralized optimization and independent optimization simulation models of the high-voltage distribution network in Figure 3, and performs optimization calculations.

Table 4 is a comparison of objective function values of different optimization calculation methods in the embodiment of the present invention.

Table 4:

Table 4 compares the objective function values of global centralized optimization, layered distributed optimization in this application, and independent optimization, including parameters such as network loss, number of discrete device actions, and photovoltaic active power reduction. From Table 4, it can be seen that under the global centralized optimization and hierarchical distributed optimization methods, the network losses of the high-voltage distribution network and the three medium-voltage distribution networks are slightly different; The on-load voltage regulation variable tap of the 33 bus is raised by one level, the capacitor bank of the 34 bus is put into one group, and the feeder switch does not operate; the photovoltaic active power reduction of each medium-voltage distribution network is zero; the global objective function value differs by 0.21￥, and the deviation The rate is 0.063%. Under the independent optimization method, the active power loss of the upper distribution network is reduced; the taps of the on-load tap changer do not operate, the 7 sets of capacitor banks in the 5 35kV substations are put into operation, and the feeder switches do not operate; DN1 and DN2 reduce the PV The active power is 0.7563MW to solve the overvoltage in the distribution network; because the photovoltaic active power is greatly reduced, the global objective function value rises to 828.92￥.

The simulation results show that the calculation results of the layered distributed optimization method in this application are very close to the global centralized optimization method. Although the independent optimization method can effectively reduce the network loss of the high and medium voltage distribution network and solve the overvoltage problem, it will cause a large loss of photovoltaic power generation due to the neglect of the voltage support capacity between distribution networks of different voltage levels. The hierarchical distributed optimization method in this application realizes the distributed calculation of the global optimization goal through the decomposition and coordination between the high and medium voltage distribution networks, and effectively reduces the loss of photovoltaic power generation and the network operation cost.

Since the above implementation methods are described in conjunction with reference to other methods, different embodiments have the same parts, and the same and similar parts of the various embodiments in this specification can be referred to each other. No further elaboration here.

It should be noted that in this specification, relative terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply No such actual relationship or order exists between these entities or operations. Furthermore, the term "comprises", "comprises" or any other variation thereof is intended to cover a non-exclusive inclusion such that a circuit arrangement, article or apparatus comprising a set of elements includes not only those elements but also elements not expressly listed Other elements, or also include elements inherent in such circuit structures, articles or equipment. Without further limitations, the presence of an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in a circuit arrangement, article or device comprising said element.

Other embodiments of the present application will be readily apparent to those skilled in the art from consideration of the specification and practice of the inventive disclosure herein. This application is intended to cover any modification, use or adaptation of the present invention, these modifications, uses or adaptations follow the general principles of the application and include common knowledge or conventional technical means in the technical field not disclosed in the application . The specification and examples are to be considered exemplary only, with the true scope and spirit of the application indicated by the contents of the appended claims.

The embodiments of the present application described above are not intended to limit the scope of protection of the present application.

Claims (9)

1. The hierarchical distributed voltage optimization control method for the high and medium voltage distribution network is characterized by comprising the following steps of:

step S100: dividing a high-medium voltage power distribution network into an upper power distribution network and a lower power distribution network, wherein a master-slave control structure is arranged between the upper power distribution network and the lower power distribution network;

step S200: and carrying out salifying on the optimization models in the upper power distribution network and the lower power distribution network to obtain a global optimization model, wherein the global optimization model is expressed as:

s.t.m＝1，...，N _MV

x _m ∈X _m ，G _MV，m (x _m )≤0

y∈Y，G _HV (y)≤0

H _m (x _m ，y)＝0

wherein: f (f) _MV，m (x _m ) As an objective function of the lower distribution network m, x _m Is the optimization variable f of the lower distribution network m _HV (y) is an objective function of the upper distribution network, y is the upper distribution networkOptimization variables, N, of layer distribution network _MV X is the number of the lower distribution network _m Is x _m Feasible region of G _MV，m (x _m ) Constraining the operation of the lower distribution network and being x only _m Y is the feasible region of Y, G _HV (y) is an operation constraint of the upper distribution network and is only a function of y, H _m (x _m Y) =0 is the boundary equation constraint of the lower-layer power distribution network m and the upper-layer power distribution network;

step S300: decomposing the global optimization model into a main problem and a plurality of sub-problems, wherein the main problem is expressed as:

s.t.y∈Y，G _HV (y)≤0

m＝1，...，N _MV

the sub-problem is expressed as:

min f _MV，m (x _m )

s.t.x _m ∈X _m ，G _MV，m (x _m )≤0

wherein: x is X _root，m And (3) optimizing variables y for boundary nodes of the lower-layer power distribution network m _τ(m) As an optimization variable of boundary nodes of the upper-layer power distribution network,

is y _τ(m) Is set at a given value of H _m (x _root，m ，y _τ(m) ) =0 is the boundary equation constraint of the lower distribution network m and the upper distribution network;

step S400: respectively calculating the main problem and the sub-problem to obtain an optimization solution, wherein the optimization parameters of the mutual transmission boundary variables between the upper-layer power distribution network and the lower-layer power distribution network are obtained;

step S500: and repeating the step S400 until the upper and lower bound deviations of the global optimization target are smaller than a preset value.

2. The method for optimizing and controlling the hierarchical distributed voltage of the high and medium voltage distribution network according to claim 1, wherein the dividing the high and medium voltage distribution network into an upper layer distribution network and a lower layer distribution network comprises the following steps: and dividing the Gao Zhongya power distribution network into an upper power distribution network and a lower power distribution network by taking a 35kV outlet bus as a boundary.

3. The hierarchical distributed voltage optimization control method of a high and medium voltage distribution network according to claim 1, wherein the step of projecting the optimization models in the upper layer distribution network and the lower layer distribution network to obtain a global optimization model comprises the steps of:

the optimization model of the upper power distribution network is a reactive power optimization model, the optimization model of the lower power distribution network is an active-reactive power combined optimization model, and the reactive power optimization model and the active-reactive power combined optimization model are subjected to salifying to obtain the global optimization model.

4. The hierarchical distributed voltage optimization control method of a high and medium voltage distribution network according to claim 3, wherein the reactive power optimization model and the active-reactive power combined optimization model are subjected to convexity by adopting a second order cone relaxation and LinDistFlow reduced equation.

5. The method for hierarchical distributed voltage optimization control of a high and medium voltage distribution network according to claim 1, wherein decomposing the global optimization model into a main problem and a plurality of sub-problems comprises: and decomposing the global optimization model into a main problem and a plurality of sub-problems by adopting a principal-subordinate decomposition method of the GBD algorithm.

6. The hierarchical distributed voltage optimization control method of a high and medium voltage distribution network according to claim 1, wherein the main problem and the sub problem are calculated respectively to obtain an optimization solution, and the optimization parameters of the mutual transmission boundary variables between the upper layer distribution network and the lower layer distribution network comprise:

step S401: initializing parameters, initializing iteration algebra k=1, and optimizing the number p of cutting planes _m Number of feasible cutting planes q =0 _m =0, the objective function lower bound lb= - ≡of the global optimization model, the objective function upper bound ub= ≡;

step S402: the lower-layer distribution network solves the sub-problem,

minf _MV，m (x _m )

s.t.x _m ∈X _m ，GM _MV，m (x _m )≤0

if the sub-problem has a feasible solution, p _m Adding 1, constructing an optimized cutting plane and compensating the main problem, wherein the expression of the constraint of the optimized cutting plane is as follows:

wherein: UB (UB) _MV，m For solving the sub-problem objective function f _MV，m (x _m ) Numerical value of mu ^m，p Optimizing cut parameters, μ for boundary equation constraints ^mp Transpose (mu) ^m，p ) ^T For row vectors

And->

Lagrangian multipliers respectively representing boundary node voltages, boundary transmission active power and reactive power equality constraints;

if the sub-problem has no feasible solution, q _m Adding 1, constructing a feasible cutting plane to supplement the main problem, wherein the expression of the constraint of the feasible cutting plane is as follows:

wherein: lambda (lambda) ^m，q Feasible cut parameters constrained by boundary equations, lambda ^m，q Transpose (lambda) ^m，q ) ^T For row vectors

And->

Lagrangian multipliers respectively representing boundary node voltages, boundary transmission active power and reactive power equality constraints;

step S403: the upper-layer distribution network solves the main problem,

7. the hierarchical distributed voltage optimization control method for the high and medium voltage distribution network according to claim 6, which is characterized in thatCharacterized in that the expression of the optimized cutting plane constraint is introduced

The expression for optimizing the cut plane constraint is expressed as:

wherein: />

And optimizing the cutting parameters for the p-th iteration of the lower power distribution network m.

8. The hierarchical distributed voltage optimization control method for a high and medium voltage distribution network according to claim 6, wherein the expression of the feasible cutting plane constraint is introduced

The expression of the viable cut plane constraint is expressed as:

wherein: />

And (5) the feasible cutting parameter of the q-th iteration of the lower power distribution network m.

9. The method for hierarchical distributed voltage optimization control of a high and medium voltage distribution network according to claim 1, wherein the upper and lower bound deviations up to the global optimization objective are smaller than a preset value, comprising: the preset value delta is set to 0.01.

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