CN109494750B - Hierarchical distributed voltage optimization control method for high and medium voltage distribution network - Google Patents
Hierarchical distributed voltage optimization control method for high and medium voltage distribution network Download PDFInfo
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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
Technical Field
The application relates to the technical field of electric power safety, in particular to a layered distributed voltage optimization control method for a high-medium voltage distribution network.
Background
With the improvement of the permeability of distributed photovoltaic in a power distribution network, the power distribution network is changed from a passive unidirectional power distribution network to an active network with power flowing in two directions, and running challenges such as power flow dumping and voltage out-of-limit are faced. This not only limits the acceptance of the distribution network for distributed photovoltaics, but also severely threatens the safe and stable operation of the distribution network. Therefore, the control and management of reactive voltage regulating equipment and distributed photovoltaics in a high and medium voltage distribution network becomes an important task for the optimal operation of the system.
Currently, voltage optimization control of high and medium voltage distribution networks is generally independently implemented. In the medium-voltage distribution network, boundary points of two-stage distribution networks are balance nodes, voltage optimization control of the medium-voltage distribution network is generally realized by a distribution automation system, and optimization scheduling of the medium-voltage distribution network is realized through reactive power optimization or active-reactive power combined optimization. In the high-voltage power distribution network, boundary transmission power of the two-stage power distribution network is load power of boundary nodes, voltage optimization control of the high-voltage power distribution network is achieved through three-stage voltage control of a ground-control AVC system, and economic optimization operation of the high-voltage power distribution network is achieved through reactive power optimization under voltage safety operation constraint. Reactive power optimization is to realize distributed iterative computation of a reactive power optimization model under voltage constraint through decomposition coordination among power distribution network subareas, micro-grids and nodes so as to minimize network active loss. The active-reactive combined optimization is to realize the optimization target of minimizing the active loss and the photovoltaic power generation loss of the power distribution network through distributed optimization calculation among clusters.
According to the voltage optimization control method for the high-voltage distribution network and the medium-voltage distribution network, the operation optimization of the high-voltage distribution network is only based on the voltage of the outlet bus of the individual transformer substation, the integral voltage level of the medium-voltage distribution network cannot be considered, so that the voltage adjustment capability of the medium-voltage distribution network cannot be exerted, the high-permeability distributed photovoltaic is connected, the medium-voltage distribution network can only solve the problem of overvoltage of a line by utilizing the distributed photovoltaic, and partial photovoltaic is easy to force off-grid, so that photovoltaic power generation loss is caused. In addition, the distributed voltage optimization control method of the power distribution network is limited by the convergence of a distributed optimization algorithm, and only the output power of continuous voltage regulating equipment such as a distributed photovoltaic device, an energy storage device and a static reactive compensator can be optimized, and the optimization scheduling of discrete equipment such as an on-load voltage regulating transformer and a feeder switch cannot be considered.
Disclosure of Invention
The application provides a layered distributed voltage optimization control method for a high-voltage and medium-voltage power distribution network, which aims to solve the technical problems that in the prior art, the high-voltage power distribution network cannot perform voltage regulation on the medium-voltage power distribution network and discrete equipment in the power distribution network cannot be optimally scheduled.
In order to solve the technical problems, the embodiment of the application discloses the following technical scheme:
the embodiment of the application discloses a hierarchical distributed voltage optimization control method of a high-medium voltage distribution network, which comprises the following steps:
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: the optimization models in the upper power distribution network and the lower power distribution network are subjected to salifying to obtain global optimization models;
step S300: decomposing the global optimization model into a main problem and a plurality of sub-problems;
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.
Optionally, in the above method for optimizing and controlling the hierarchical distributed voltage of the high-medium voltage power distribution network, the dividing the high-medium voltage power distribution network into an upper power distribution network and a lower power distribution network includes: 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.
Optionally, in the above method for hierarchical distributed voltage optimization control of a high-medium voltage power distribution network, the step of performing a salifying on the optimization models in the upper power distribution network and the lower power distribution network to obtain a global optimization model includes:
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.
Optionally, in the above method for controlling the hierarchical distributed voltage optimization of the high-medium voltage distribution network, the reactive power optimization model and the active-reactive power combined optimization model are subjected to salifying by adopting a second order cone relaxation and LinDistFlow constraint equation.
Optionally, in the above method for hierarchical distributed voltage optimization control of a high-medium voltage power distribution network, 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: x is x m The optimization variable of the lower power distribution network m is y, and the optimization variable of the upper power distribution network N is y MV G for the number of lower distribution networks MV,m (x m ) Is the operation constraint of the lower distribution network and is x m Function of G HV (y) is an operation constraint of the upper distribution network and is a function of y, H m (x m Y) =0 is the boundary equation constraint of the lower distribution network m and the upper distribution network.
Optionally, in the above method for hierarchical distributed voltage optimization control of a high-medium voltage power distribution network, decomposing the global optimization model into a main problem and a plurality of sub-problems includes: 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.
Optionally, in the above method for hierarchical distributed voltage optimization control of a high-medium voltage power distribution network, the main problem and the sub-problem are calculated respectively to obtain an optimization solution, and optimization parameters of boundary variables transmitted between the upper power distribution network and the lower power distribution network include:
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,
min f MV,m (x m )
s.t.x m ∈X m ,G 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:
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:
step S403: the upper-layer distribution network solves the main problem,
optionally, in the above method for optimizing and controlling the layered distributed voltage of the high-medium voltage distribution network, the expression of optimizing the cutting plane constraint is introduced
The expression for optimizing the cut plane constraint is expressed as:
optionally, in the above method for optimizing and controlling the layered distributed voltage of the high-medium voltage distribution network, the expression of the feasible cutting plane constraint is introduced
The expression of the viable cut plane constraint is expressed as:
optionally, in the above method for controlling hierarchical distributed voltage optimization of a high-medium voltage power distribution network, the upper and lower bound deviations up to the global optimization target are smaller than a preset value, including: the preset value delta is set to 0.01.
Compared with the prior art, the beneficial effects of this application are:
the application provides 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, wherein a master-slave control structure is arranged between the upper power distribution network and the lower power distribution network; the optimization models in the upper power distribution network and the lower power distribution network 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 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; repeating the previous step until the upper and lower bound deviations of the global optimization target are smaller than a preset value. In the method, the high-medium voltage distribution network is divided into an upper distribution network and a lower distribution network, the double-layer distribution network which are in a master-slave structure is alternately calculated through a small amount of data exchange and distribution, the network loss and the voltage regulation cost are minimized, the complexity of global optimization calculation is remarkably reduced, the mutual voltage supporting capacity between the high-medium voltage distribution networks is fully exerted, and the power generation loss of distributed photovoltaics is avoided. In addition, through the global optimization model in the application, hierarchical distributed optimization calculation is carried out, an optimization scheduling strategy of each control device is obtained, and control instructions are issued to continuous voltage regulating devices, discrete devices and the like in the power distribution network based on the obtained optimization calculation result, so that network reconstruction is realized.
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.
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In order to more clearly illustrate the technical solutions of the present application, the drawings that are needed in the embodiments will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
Fig. 1 is a schematic flow chart of a hierarchical distributed voltage optimization control method for a high-medium voltage distribution network according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a basic structure of a hierarchical distributed voltage optimization control system of a high-medium voltage distribution network according to an embodiment of the present invention;
fig. 3 is a network topology of a high-voltage power distribution network according to an embodiment of the present invention.
Detailed Description
In order to better understand the technical solutions in the present application, the following description will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present application.
Referring to fig. 1, a flow chart of a hierarchical distributed voltage optimization control method for a high-medium voltage distribution network is provided in an embodiment of the present invention. As can be seen in connection with fig. 1, the method comprises the 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;
the method takes a 35kV outlet bus as a boundary, and divides the Gao Zhongya power distribution network into an upper power distribution network and a lower power distribution network based on a master-slave decomposition idea of a generalized Benders decomposition algorithm. Referring to fig. 2, a basic structure diagram of a hierarchical distributed voltage optimization control system of a high-medium voltage distribution network according to an embodiment of the present invention is provided. The high-voltage distribution network is shown in fig. 2, and is composed of one 220kV transformer substation, a plurality of 110kV transformer substations, a 35kV transformer substation and a plurality of medium-voltage distribution networks. The method is to realize the distributed voltage optimization control of the high-medium voltage distribution network by adopting the master-slave control structure shown in fig. 2, wherein the control system of the upper distribution network is a ground-control AVC system, the control system of the lower distribution network is a substation, and the hierarchical distributed computation of the global optimization model is realized based on a small amount of data communication and decomposition coordination algorithm between the double-layer distribution networks.
Step S200: the optimization models in the upper power distribution network and the lower power distribution network are subjected to salifying to obtain global optimization models;
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 in order to reduce the solving difficulty of the optimization model and ensure the convergence of a GBD algorithm, 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 constraint equation, so that the global optimization model is obtained.
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: x is x m The optimization variable of the lower power distribution network m is y, and the optimization variable of the upper power distribution network N is y MV G for the number of lower distribution networks MV,m (x m ) Is the operation constraint of the lower distribution network and is x m Function of G HV (y) is an operational constraint of the upper distribution network and is a function of yNumber, H m (x m Y) =0 is the boundary equation constraint of the lower distribution network m and the upper distribution network, and is only related to
And->
And (5) correlation.
Step S300: decomposing the global optimization model into a main problem and a plurality of sub-problems;
the global optimization model is decomposed into a main problem and a plurality of sub-problems by adopting a principal-subordinate decomposition method of the GBD algorithm.
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;
in the distributed optimization iterative process of the high-medium voltage distribution network, interaction data between the upper layer distribution network and the lower layer distribution network are shown in table 1:
table 1:
in order to realize distributed computation of a global optimization model of a high-medium voltage distribution network, the global optimization model is decomposed into a main problem and a plurality of sub-problems for alternate computation based on a principal and subordinate decomposition thought of a GBD algorithm. The high-voltage distribution network and each medium-voltage distribution network respectively and independently solve the main problem and each sub-problem, and after each round of optimization solution is obtained, the optimization parameters of boundary variables are transmitted to the other party. In order to reduce the communication data volume between the two layers of distribution networks, the solving process of the GBD algorithm is adjusted, and the specific solving process is as follows:
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= infinity of the global optimization model, and high-voltage power distributionFeasible initial value of network boundary variable
Step S402: and solving the sub-problem by the lower power distribution network. Only f in objective function of global optimization model MV,m (x m ) And variable x m The distribution network m is based on boundary variables of the high-voltage distribution network
Solving the following sub-optimization problem:
min f MV,m (x m )
s.t.x m ∈X m ,G MV,m (x m )≤0
if the sub-problem has a feasible solution, p m Adding 1, solving the boundary equation constraint
Corresponding Lagrangian multiplier +.>
Using the objective function value f MV,m (x m ) Updating an objective function UB of a medium voltage distribution network m MV,m And constructing an optimized cutting plane back-filling main problem, wherein the expression of the optimized cutting plane constraint is as follows:
to reduce the amount of data communicated between the upper distribution network and the lower distribution network, an introduction can be made
The expression for optimizing the cut plane constraint is expressed as:
if the sub-problem has no feasible solution, q m Increasing 1, introducing a relaxation variable builds the following relaxation optimization problem:
s.t.x m ∈X m ,G MV,m (x m )≤0
α i ≥0,i＝1,2,...,6
solving the corresponding optimal solution x root,m Multiplier lambda corresponding to boundary constraint 1 ～λ 6 And order
Upper bound UB of objective function MV,m The method is unchanged, and constructs a feasible cutting plane recharging main problem, wherein the expression of the constraint of the feasible cutting plane is as follows:
to reduce the amount of data communicated between the upper distribution network and the lower distribution network, an introduction can be made
The expression of the viable cut plane constraint is expressed as:
step S403: and solving a main problem by the upper-layer power distribution network. First, the high voltage distribution network is based on all boundary variables
And the objective function value of the medium-voltage distribution network is used for carrying out the calculation of the optimal power flow of the upper-layer distribution network so as to update the upper bound UB of the global optimization objective. Then, based on feasible cutting and optimized cutting plane parameters of all medium-voltage distribution networks, the upper distribution network solves the main problem:
updating the lower bound LB of the global optimization target by using the obtained objective function value, and using the optimal solution as
And assigning values for the next round of iterative computation.
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.
The preset value is set by people in the application, and when the difference between LB and UB is smaller than a certain value, the distributed optimization is considered to be converged. The objective function value is generally about 1%, and in the present example, the value is set to 0.01.
Referring to fig. 3, a network topology of a high-voltage power distribution network according to an embodiment of the present invention is provided. With reference to fig. 3, only 80, 81, 82 bus-connected medium voltage distribution networks are connected with a distributed photovoltaic power generation system, which is respectively defined as DN1, DN2 and DN3. The three medium voltage distribution networks respectively comprise 81, 61 and 97 nodes, and the network topology and the distributed photovoltaic access location are shown in fig. 2. The method selects the high-voltage distribution network shown in fig. 3 and three medium-voltage distribution networks containing distributed photovoltaics to verify the provided hierarchical distributed optimization method, and adopts historical operation data at a certain moment to carry out simulation calculation.
Table 2 shows the boundary variables and objective functions of DN2 in the hierarchical distributed iterative process, table 2 shows the square of DN2 boundary voltage for solving the main problem in the hierarchical distributed optimization process
Boundary transmission active->
And reactive->
Power (MW) and objective function value UB for each sub-problem MV,m (￥)。
Table 2:
as shown in Table 2, the difference between the upper bound UB and the lower bound LB of the global optimization objective was only 0.0099 th generation from iteration to 12 th generation. The number of iterations required for convergence is much less than for the distributed optimization method based on the alternating direction multiplier method. The latter requires hundreds of iterations to achieve a good convergence.
Table 3 shows the optimized and feasible cut parameters for DN2 in a hierarchical distributed iterative process in accordance with an embodiment of the present invention.
Table 3:
p in Table 3 m The column parameter being a specific value and q m Column parameters are "-" to indicate that the distribution network m has a feasible solution in k iterations, and the last four column parameters correspond to optimized cutting plane parameters of the sub-problem m
On the contrary, the distribution network m has no feasible solution in the iteration, and the last four columns correspond to feasible cutting plane parameters of the sub-problem +.>
In order to verify the accuracy of the provided hierarchical distributed optimization method, the invention further builds a global centralized optimization and independent optimization simulation model of the high-voltage distribution network in fig. 3, and performs optimization calculation.
Table 4 shows comparison of objective function values of different optimization calculation methods according to the embodiments of the present invention.
Table 4:
the objective function values of global centralized optimization, hierarchical distributed optimization and independent optimization in the application are compared in table 4, and specifically include parameters such as network loss, discrete equipment action times, photovoltaic active reduction and the like. Under the global centralized optimization and the layered distributed optimization methods, which can be obtained from table 4, the network losses of the high-voltage distribution network and the three medium-voltage distribution networks are slightly deviated; the discrete reactive voltage regulating equipment has the same action mode, namely the 33-bus on-load voltage regulating variable tap is up-regulated by one grade, the 34-bus capacitor bank is put into one group, and the feeder switch does not act; the photovoltaic active reduction amount of each medium-voltage distribution network is zero; the global objective function value differs by 0.21% and the deviation rate is 0.063%. Under the independent optimization method, the active loss of the upper distribution network is reduced; the on-load voltage regulation variable tap does not act, 7 groups of capacitor banks in the 5-seat 35kV transformer substation are put into, and the feeder switch does not act; DN1 and DN2 are contracted together to reduce the photovoltaic active power 0.7563MW to solve the overvoltage in the distribution network; as the photovoltaic active power is greatly reduced, the global objective function value is increased to 828.92.
Simulation results show that the calculation result of the hierarchical distributed optimization method in the method is very similar to that of the global centralized optimization method. Although the independent optimization method can effectively reduce network loss of the high-medium voltage distribution network and solve the overvoltage problem, larger photovoltaic power generation loss is caused by neglecting voltage supporting capability among distribution networks with different voltage grades. According to the hierarchical distributed optimization method, the distributed calculation of the global optimization target is realized through the decomposition coordination among the high-voltage distribution network and the medium-voltage distribution network, so that the photovoltaic power generation loss and the network operation cost are effectively reduced.
Since the foregoing embodiments are all described in other modes by reference to the above, the same parts are provided between different embodiments, and the same and similar parts are provided between the embodiments in the present specification. And will not be described in detail herein.
It should be noted that in this specification, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a circuit structure, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such circuit structure, article, or apparatus. Without further limitation, the statement "comprises" or "comprising" a … … "does not exclude that an additional identical element is present in a circuit structure, article or apparatus that comprises the element.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure of the invention herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the application pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
The above-described embodiments of the present application are not intended to limit the scope 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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