CN110021966A - A kind of active distribution network Optimization Scheduling considering dynamic network reconfiguration - Google Patents

Abstract

The invention discloses a kind of active distribution network Optimization Schedulings for considering dynamic network reconfiguration, comprising: (1) obtains active distribution network parameter, obtain active distribution network power flow equation constraint condition；(2) consider dynamic network reconfiguration, correct active distribution network power flow equation constraint condition；(3) active distribution network irradiation structure constraint condition is obtained according to active distribution network irradiation structure；(4) with the minimum objective function of active distribution network integrated operation cost, active distribution network Optimal Operation Model is constructed according to every constraint condition；(5) constraint condition non-convex in master mould is subjected to convex relaxationization, Nonlinear Constraints are linearized；(6) model after conversion is solved, obtains active distribution network Optimized Operation scheme.The present invention fully considers the controllable resources of active distribution network, improves the performance driving economy of active distribution network, thus solves the problems, such as that large-scale distributed plant-grid connection active distribution network is difficult to dissolve and increases with voltage.

Description

An optimal scheduling method for active distribution network considering dynamic network reconfiguration

technical field

The invention belongs to the technical field of active distribution network optimization operation, and more particularly, relates to an active distribution network optimization scheduling method considering dynamic network reconfiguration.

Background technique

In recent years, in order to cope with climate change, solve the energy crisis and promote energy conservation and emission reduction, vigorously developing renewable energy sources such as wind power and solar power generation has become a consensus and an important means at home and abroad. The country will continue to vigorously develop wind power and solar power generation, and achieve distributed development and local consumption of renewable energy through various measures. With the large-scale access of renewable energy to the distribution network in the form of distributed power generation, in some parts of the local distribution network, the penetration rate of distributed power generation even exceeds 100%, while some are connected to the active distribution network. The distributed power supply at the end of the power grid will bring serious overvoltage problems and affect the ability of the active distribution network to absorb renewable energy.

In order to solve the problems caused by the large-scale distributed power supply connecting to the distribution network, the concept of "active distribution network" came into being. Some research institutions and scholars have studied the coordinated operation mechanism of active distribution network from different perspectives such as economy and safety. control resources. As a flexible and variable scheduling resource of network topology, dynamic network reconfiguration can effectively improve the economic operation level of distribution network and the consumption rate of distributed power. my country's distribution network is developing in the direction of intelligence. The "Action Plan for the Construction and Transformation of Distribution Networks (2015-2020)" clearly will accelerate the construction and transformation of modern distribution networks in an all-round way to meet the development of new energy, distributed power and access requirements. Among them, the application of intelligent remote control switch provides conditions for the implementation of dynamic network reconfiguration.

Since most of the existing research focuses on the coordination of "source-load-storage", such as the access control of distributed power, the coordinated optimization of resources such as energy storage and flexible loads, and the coordinated operation of microgrids and active distribution networks, etc. There are few studies on the network structure adjustment of active distribution network, and the potential of active distribution network to absorb distributed power sources has not been fully utilized. However, the research on active distribution network network reconfiguration is mostly limited to the long-term scale optimization of active distribution network, and the dynamic network reconfiguration that regards network structure adjustment as an intraday dispatch resource has received little attention. In addition, most of the existing literatures on the radiation structure constraints of active distribution network use the exhaustive method, and do not give a strict mathematical expression.

SUMMARY OF THE INVENTION

In view of the above defects or improvement needs of the prior art, the present invention proposes an active distribution network optimization scheduling method considering dynamic network reconfiguration, the purpose of which is to fully consider the controllable resources of the active distribution network and improve the active distribution network. Therefore, it solves the technical problems that the large-scale distributed power is connected to the active distribution network, which is difficult to accommodate and the voltage rises.

In order to achieve the above object, the present invention provides an active distribution network optimization scheduling method considering dynamic network reconfiguration, including:

(1) Obtain the parameters of the active distribution network, and construct the constraints of the power flow equation of the active distribution network;

(2) Considering the dynamic network reconstruction, modify the constraints of the power flow equation of the active distribution network, and obtain the modified constraints of the power flow equation of the active distribution network;

(3) According to the radiation structure of the active distribution network, the constraint conditions of the radiation structure of the active distribution network are obtained;

(4) Taking the lowest comprehensive operation cost of the active distribution network as the objective function, according to the revised active distribution network power flow equation constraints, the active distribution network radiation structure constraints and the active distribution network safe operation constraints, construct the active distribution network. Grid optimization scheduling model;

(5) Perform convex relaxation of the non-convex constraints in the model, and linearize the nonlinear constraints in the model;

(6) Solve the converted model to obtain the optimal dispatching scheme of the active distribution network.

Further, active distribution network parameters include distributed power supply parameters, 24h output data of distributed power supply, active distribution network grid parameters, active distribution network node load data, active distribution network port power limit, reactive power compensation Device parameters, upper limit of switching actions, various cost coefficients;

The parameters of the distributed power supply include the maximum active power output P _i,max of the distributed power supply, the power factor limit of the limited power factor range operation

The 24h output data of distributed power supply is the predicted value

The parameters of the active distribution network frame include the conductance g _ij , the susceptance b _ij and the current upper limit I _ij,max of the active distribution network branch ij , the active distribution network initial topology and tie line configuration information, and the active distribution network nodes Voltage upper and lower limits V _i,max and V _i,min ;

The active distribution network node load data includes active load _PL,i,t and reactive load QL,i,t at node i at time _t ;

The active power distribution gateway port power limit includes the active power exchange power upper and lower limits P _T,min , P _T,max and the reactive power exchange power upper and lower limits Q _T,min and Q _T,max ;

The parameters of the reactive power compensation device include the minimum value Q _SVC,i,min and the maximum value Q _SVC,i,max of the SVC reactive power compensation at the node i;

The upper limit of the number of switching actions is SW _max ;

Various cost coefficients include network loss cost coefficient η _L , curtailment wind/light unit power penalty cost coefficient η _RDG , cost coefficient η _S for one switching action.

Further, the constraints of the power flow equation of the active distribution network are:

Among them, _PG,i,t is the active power injection of the distributed power source or the transmission network at the node i at time t, _PL,i,t is the active load at the node i at time t, and N(i) is the power supply connected to the node i Node set, P _ij,t is the active power flowing on branch ij at time t, and the outflow from node i is positive; Q _G,i,t is the reactive power injection of power supply at node i at time t, Q _{L,i, t} is the reactive power load at node i at time t, Q _SVC,i,t is the SVC reactive power compensation power at node i at time t, and Q _ij,t is the reactive power flowing on branch ij at time t, which is calculated from node i outflow is positive;

P _ij,t and Q _ij,t can be derived from the branch apparent power expression:

Among them, S _ij,t is the apparent power of branch ij at time t, is the conjugate phasor of the current of branch ij at time t, g _ij and b _ij are the conductance and susceptance of branch ij respectively, V _i,t is the voltage amplitude of node i at time t, θ _ij,t =θ _{i ,t} -θ _j,t is the voltage phase angle difference between nodes i and j at time t;

After separating the real and imaginary parts, we can get:

Further, the revised constraints of the power flow equation of the active distribution network are:

Wherein, Z _ij,t is the disconnection state variable of branch ij at time t. When branch ij is disconnected, Z _ij,t =0, and corresponding branch power Z _ij,t ·P _ij,t =0.

Further, the constraints of the active distribution network radiation structure are:

Among them, E _ij,t and Z _ij,t are both Boolean variables, E _ij,t is the flow direction variable of branch ij at time t, E _ij,t =1 indicates that node j at time t is the parent node of node i, and the power flow The flow direction is from node j to node i; Z _ij,t is the connected state of branch ij at time t, and Z _ij,t =1 indicates that branch ij is connected at time t.

Further, the constraints on the safe operation of the active distribution network also include:

Voltage amplitude upper and lower limit constraints:

V _i,min ≤V _i,t ≤V _i,max

Among them, V _i,max and V _i,min are the upper and lower limits of the voltage amplitude at node i, respectively.

Branch current upper limit constraint:

Among them, I _ij,t is the amplitude of the branch current, and I _ij,max is the upper limit of the amplitude of the branch current.

Distributed power output constraints:

Among them, P _RDG,i,t and Q _RDG,i,t are the active and reactive real power of distributed power generation at node i at time t, respectively, is the predicted output value of the distributed power supply at node i at time t; the distributed power supply is operated with a limited power factor range, is the power factor limit value of the distributed power supply at node i.

Active power distribution gateway port power constraints:

Among them, P _T,t is the active power flowing into the distribution network at the current level from the root node of the distribution network at time t, and P _T,min and P _T,max are the upper and lower limits of active power exchange power at the active distribution gateway interface respectively; Q _{T , t} is the reactive power flowing into the distribution network at this level from the root node of the distribution network at time t, and Q _T,min and Q _T,max are the upper and lower limits of the reactive power exchange power at the active distribution gateway interface, respectively.

SVC constraints of static var compensation device:

Q _SVC,i,min ≤Q _SVC,i,t ≤Q _SVC,i,max

Among them, Q _SVC,i,t is the reactive power compensation power of node i at time t, and Q _SVC,i,min and Q _SVC,i,max are the minimum and maximum value of SVC reactive power compensation at node i, respectively.

The number of switching actions is limited:

ΔZ _ij,t represents the number of switching changes at time t relative to time t-1, and SW _max is the upper limit of the number of switching actions.

Further, the expression of the objective function is:

Among them, _{PL, t} is the network loss of active distribution network at time t, and η _L is the cost coefficient of network loss; is the abandonment of the distributed power generation of node i at time t, η _RDG is the penalty cost coefficient of abandoning wind/light per unit of electricity; ΔZ _ij,t is the number of network switching actions at time t relative to the previous time, η _S is the cost coefficient of one switching action , Ω _RDG is the set of distributed power access points, and Ω _E is the set of power grid branches.

Further, the non-convex constraints include the constraints of the power flow equation, and the nonlinear constraints include the product term of the modified constraints of the power flow equation, the upper limit constraints of the branch currents and the absolute value expressions of the switching action times constraints,

The convex relaxation of the constraints of the power flow equation is:

Its standard second-order conical form is:

where U _i,t , W _ij,t and T _ij,t satisfy:

Linearize the product term of the modified power flow equation constraints:

in, are the node voltage variables U _i,t and U _j,t related to nodes i and j, respectively, correspond to the branch voltage variables related to the branch “ij”, and satisfy the following constraints:

The upper limit constraint condition of the branch current is linearized as:

For the absolute value expression of the number of switching action constraints, it can be replaced by the following expression:

In this way, the original optimization model is transformed into a mixed integer second-order cone programming model, which can be well solved. Among them, the optimization software is the existing optimization problem solving software, such as CPLEX, yalmip toolbox in Matlab, Gurobi and so on.

The invention proposes an active distribution network optimization scheduling strategy considering dynamic network reconfiguration, aiming to make full use of the active distribution network schedulable resources and further improve the consumption of distributed power sources. Correspondingly, the strict mathematical expression and the solution method of the model for the radiation structure constraints of the distribution network are given. It makes up for the deficiencies of the existing technical solutions well.

Through the above technical solutions conceived by the present invention, compared with the prior art, the following can be achieved

Beneficial effects:

1. The present invention aims at the lowest comprehensive operation cost of the distribution network, takes into account the constraints of the power flow equation and the number of switching actions, and at the same time integrates adjustable resources such as distributed power sources and reactive power compensation devices, and establishes a dynamic network that considers This model can accurately describe the operation requirements of active distribution network considering the access of large-scale distributed power sources;

2. The model transformation method based on second-order cone relaxation and variable product linearization proposed in the present invention can perform convex processing on the non-convex power flow equation and variable product term, and then convert the original model into an easy-to-solve mixed integer two. The order cone problem greatly reduces the difficulty of solving;

3. The active distribution network optimization scheduling strategy considering dynamic network reconfiguration proposed by the present invention can make full use of the active distribution network schedulable resources, and further improve the distributed power consumption capacity of the active distribution network; at the same time, the reactive power compensation device can be used. Coordination with dynamic network reconfiguration can better solve the problem of voltage rise caused by the access of large-scale distributed power sources to the distribution network, and has good economy and applicability.

Description of drawings

Fig. 1 is the 24h distribution curve of distributed power source and load of a kind of active distribution network optimization scheduling method considering dynamic network reconfiguration provided by the present invention;

Fig. 2 is a topological structure diagram of an active distribution network system of an active distribution network optimization scheduling method considering dynamic network reconfiguration provided by the present invention.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

An active distribution network optimization scheduling strategy considering dynamic network reconfiguration according to an embodiment of the present invention, its calculation includes the following steps:

(1) Obtain the parameters of all distributed power sources in the active distribution network as shown in Table 1, the 24h distribution curve of distributed power sources and loads as shown in Figure 1, and the parameters of the active distribution network grid as shown in Table 2. The topology structure As shown in Figure 2, the active distribution network node load data is shown in Table 3, the active distribution network port power limit is shown in Table 4, the parameters of the reactive power compensation device are -100 ~ 300kVar, and the upper limit of the number of switching operations is 24 times and various cost coefficients are shown in Table 5;

Table 1

Distributed Power access node Rated power/MW power factor PV 6 0.5 0 Wind 7 0.6 0.9 Wind 13 1 0.9 Wind 18 1 0.9 Wind 28 0.6 0.9 PV 33 0.5 0

Table 2

head node tail node Resistance/Ω Reactance/Ω head node tail node Resistance/Ω Reactance/Ω 1 2 0.0922 0.047 20 twenty one 0.4095 0.4784 2 3 0.493 0.2511 twenty one twenty two 0.7089 0.9373 3 4 0.366 0.1864 3 twenty three 0.4512 0.3083 4 5 0.3811 0.1941 twenty three twenty four 0.898 0.7091 5 6 0.819 0.707 twenty four 25 0.896 0.7011 6 7 0.1872 0.6188 6 26 0.203 0.1034 7 8 0.7114 0.2351 26 27 0.2842 0.1447 8 9 1.03 0.74 27 28 1.059 0.9337 9 10 1.044 0.74 28 29 0.8042 0.7006 10 11 0.1966 0.065 29 30 0.5075 0.2585 11 12 0.3744 0.1238 30 31 0.9744 0.963 12 13 1.468 1.155 31 32 0.3105 0.3619 13 14 0.5416 0.7129 32 33 0.341 0.5302 14 15 0.591 0.526 8 twenty one 2 2 15 16 0.7463 0.545 9 15 2 2 16 17 1.289 1.721 12 twenty two 2 2 17 18 0.732 0.574 18 33 0.5 0.5 2 19 0.164 0.1565 25 29 0.5 0.5 19 20 1.5042 1.3554 - - - -

table 3

Table 4

parameter name Active power lower limit/MW Active power upper limit/MW Lower reactive power limit/MVar Reactive power ceiling/MVar power limit -5 10 -2 8

table 5

parameter name Relative value network loss cost 50 Wind/Light penalty cost 1 Switching action cost 2

(2) Establish the node constraints of the power flow equation of the active distribution network and the correction constraints considering the dynamic network reconfiguration:

Among them, _PG,i,t is the active power injection of the power source (distributed power supply or transmission network) at node i at time t, _PL,i,t is the active load at node i at time t, N(i) is the connection with node i The set of connected nodes, P _ij,t is the active power flowing on branch ij at time t, and the outflow from node i is positive; Q _G,i,t is the reactive power injection of power supply at node i at time t, Q _{L, i,t} is the reactive load at node i at time t, Q _SVC,i,t is the SVC reactive power compensation power at node i at time t, and Q _ij,t is the reactive power flowing on branch ij at time t, from Node i outflow is positive. The right side of the equation represents the sum of the total active/reactive outflow power of all lines connected to node i at time t. In addition, P _ij,t and Q _ij,t can be derived from the branch apparent power expression:

The constraints of the modified active distribution network power flow equation considering dynamic network reconfiguration are:

Wherein, Z _ij,t is the disconnection state variable of branch ij at time t. When branch ij is disconnected, Z _ij,t =0, and corresponding branch power Z _ij,t ·P _ij,t =0.

(3) Constraints for establishing the radial structure of active distribution network:

Among them, E _ij,t and Z _ij,t are both Boolean variables. E _ij,t is the flow direction variable of branch ij at time t, E _ij,t =1 indicates that node j is the parent node of node i at time t, and the flow direction is from node j to node i; Z _ij,t is time t The connected state of the branch ij, Z _ij,t =1 indicates that the branch ij is connected at time t. The first term in the constraints restricts that E _ij,t and E _ji,t can only be 1 at most and maintains the bidirectionality of the branch ij power flow; the second formula indicates that all nodes except the substation node have only one parent node; the third Item indicates that the substation node has no parent node.

(4) Establish an active distribution network optimization scheduling model considering dynamic network reconfiguration, including objective functions and related constraints;

Among them, the objective function of the active distribution network optimization scheduling model considering dynamic network reconfiguration is:

Specifically, the constraints on the safe operation of the radiation structure of the active distribution network also include:

Voltage amplitude upper and lower limit constraints

V _i,min ≤V _i,t ≤V _i,max

Among them, V _i,max and V _i,min are the upper and lower limits of the voltage amplitude at node i, respectively.

Branch Current Upper Limit Constraint

In the formula, I _ij,t is the branch current amplitude, and I _ij,max is the upper limit of the branch current amplitude.

Distributed power output constraints

In the formula, P _RDG,i,t and Q _RDG,i,t are the active and reactive real power of distributed power generation at node i at time t, respectively, is the predicted output value of the distributed power supply at node i at time t; the distributed power supply is operated with a limited power factor range, is the power factor limit value of the distributed power supply at node i.

Active Power Distribution Gateway Port Power Constraints

In order to suppress the influence of the power fluctuation of the active distribution network on the transmission network, it is necessary to take into account the gate exchange power constraints of the root node of the active distribution network, namely:

In the formula, P _T,t is the active power flowing into the distribution network at this level from the root node of the distribution network at time t, and P _T,min and P _T,max are the upper and lower limits of the active power exchange power at the active distribution gateway interface; Q _T,t is the reactive power flowing into the distribution network at this level from the root node of the distribution network at time t, and Q _T,min and Q _T,max are the upper and lower limits of the reactive power exchange power at the active distribution gateway interface, respectively.

SVC constraint of static var compensation device

Q _SVC,i,min ≤Q _SVC,i,t ≤Q _SVC,i,max

In the formula, Q _SVC,i,t is the reactive power compensation power of node i at time t, and Q _SVC,i,min and Q _SVC,i,max are the minimum and maximum value of SVC reactive power compensation at node i, respectively.

The number of switching actions is limited

In the formula, ΔZ _ij,t represents the number of switching changes at time t relative to time t-1, and SW _max is the upper limit of the number of switching actions. where ΔZ _ij,t is expressed as follows:

ΔZ _ij,t =|Z _ij,t -Z _ij,t-1 |

(5) Convert non-convex expressions such as negative quadratic and trigonometric functions in the original model to convex relaxation, and convert them into standard second-order conical expressions, including the power flow equation constrained convex relaxation and the current upper limit constraint convex relaxation;

The convex relaxation of the constraints of the power flow equation is:

Its standard second-order conical form is:

Among them, U _i,t , W _ij,t and T _ij,t satisfy the following formula;

(6) Linearize the nonlinear constraints through the linearization of the variable product, and use the optimization software to solve the converted optimization model, and obtain the optimal dispatching strategy of the active distribution network considering the dynamic network reconfiguration.

The linearized power flow equation is:

Among them, in the formula, are the node voltage variables U _i,t , U _j,t related to nodes i and j, respectively, correspond to the "branch voltage" variables related to the branch "ij", and satisfy the following constraints:

The upper current limit constraint is replaced by:

For the absolute value expression of the number of switching actions constraints, replace it with the following expression:

In this way, the original optimization model is converted into a mixed integer second-order cone programming model, which is solved by using the yalmip toolbox in CPLEX and Matlab in this embodiment.

The example sets 5 scenarios to analyze the effectiveness of the proposed method.

Scenario 1: At a single point in time, only RDG active and reactive power can be controlled in the network;

Scenario 2: Consider static network reconfiguration based on scenario 1;

Scenario 3: Consider hourly DNR for 24-hour load and RDG output;

Scenario 4: On the basis of Scenario 3, further consider the constraints on the number of switch actions proposed in this paper and the selected key switches;

Scenario 5: On the basis of Scenario 4, further explore the influence of reactive power compensation device on DNR.

Table 6

Table 6 shows the comparison of the results of Scenario 1 and Scenario 2. From the comparison of the results in Table 6, it can be seen that the economic operation level of the system is significantly improved after considering the network reconstruction, and the overall RDG consumption of the active distribution network increases by 0.6515MWh. The network loss of the distribution network has been reduced by 29.72%, and the minimum voltage level of the active distribution network has been raised. From the comparison between Scenario 1 and Scenario 2, it can be seen that distribution network reconfiguration has great potential to improve the economic operation level of active distribution network, and the calculation example results provide data support for the study of hour-level dynamic reconfiguration.

Table 7

Analysis of the results of the third part of the time period in Scenario 7 in Table 7 shows that when the RDG output is not large, compared with the optimal static reconfiguration strategy, the DNR has no obvious effect on reducing the network loss of the active distribution network, because the RDG can be completely eliminated at this time. When the RDG output is large enough (penetration rate ≥ 100%), compared with the optimal static strategy, the dynamic reconfiguration has a significant effect on reducing the network loss of the active distribution network. , RDG consumption also increased significantly. It can be seen that DNR can optimize the network structure of the active distribution network by adjusting the network switch during the period when the RDG output is relatively large, and can better cope with the changes in the load and RDG output.

Table 8

Table 9

Table 8 shows the switching state results of scenarios 4 and 5, and Table 9 shows the voltage levels of scenarios 4 and 5. As can be seen from Table 8, compared with Scenario 4, the switch state has changed in Scenario 5, and the RDG consumption has also increased. As can be seen from Table 9, in scenario 4, the highest voltage of the network is at node 13, which reaches the upper limit of the voltage amplitude; while in scenario 5, the voltage distribution of the network is optimized by the reactive power compensation device, and the highest voltage does not reach the upper limit of the amplitude. Comprehensive analysis shows that there is no reactive power compensation device in scenario 4, and the consumption of RDG is limited by the voltage constraints of the active distribution network, while in scenario 5, the reactive power compensation device can be flexibly invoked through dynamic network reconfiguration to improve the active distribution network voltage. level, so in Scenario 5, the active distribution grid can absorb more RDG.

The calculation example results show that the method proposed in this patent can make good use of the dynamic reconfiguration of the active distribution network network topology, further improve the distributed power consumption level of the distribution network, and improve the operation state of the active distribution network.

Those skilled in the art can easily understand that the above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention, etc., All should be included within the protection scope of the present invention.

Claims (8)

1. An active power distribution network optimal scheduling method considering dynamic network reconstruction is characterized by comprising the following steps:

(1) acquiring parameters of the active power distribution network to obtain constraint conditions of a power flow equation of the active power distribution network;

(2) considering dynamic network reconstruction, correcting the constraint conditions of the power flow equation of the active power distribution network to obtain the corrected constraint conditions of the power flow equation of the active power distribution network;

(3) obtaining a constraint condition of the radiation structure of the active power distribution network according to the radiation structure of the active power distribution network;

(4) constructing an active power distribution network optimization scheduling model according to the corrected active power distribution network power flow equation constraint condition, the active power distribution network radiation structure constraint condition and the active power distribution network safe operation constraint condition by taking the lowest comprehensive operation cost of the active power distribution network as a target function;

(5) convex relaxation is carried out on the non-convex constraint conditions in the model, and linearization is carried out on the non-linear constraint conditions in the model;

(6) and solving the converted model to obtain an optimized scheduling scheme of the active power distribution network.

2. The method of claim 1, wherein the active power distribution network parameters comprise distributed power source parameters, distributed power source 24h output data, active power distribution network frame parameters, active power distribution network node load data, active power distribution network gateway power limits, reactive compensation device parameters, upper limit on switching times, cost coefficients;

wherein the distributed power parameter comprises a distributed power maximum active power output P_i,maxPower factor limit for operation in a defined power factor range

The 24h output data of the distributed power supply is a predicted value

The active power distribution network frame parameters comprise the conductance g of the active power distribution network branches i-j_ijB.c. susceptance_ijAnd upper current limit I_ij,maxInitial topological structure of active power distribution network and configuration information of tie line, upper and lower limits V of node voltage of active power distribution network_i,maxAnd V_i,min；

The active power distribution network node load data comprise active loads P at a node i at the moment t_L,i,tAnd reactive load Q_L,i,t；

The gateway power of the active power distribution networkThe limit values comprise an upper limit value P and a lower limit value P of active exchange power of the gateway of the active power distribution network_T,min、P_T,maxAnd upper and lower limit values Q of reactive exchange power_T,minAnd Q_T,max；

The parameters of the reactive power compensation device comprise the minimum value Q of SVC reactive power compensation at the node i_SVC,i,minAnd maximum value Q_SVC,i,max；

The upper limit of the number of the switching actions is SW_max；

The cost coefficients include a loss cost coefficient η_LWind abandon or light abandon unit electricity penalty cost coefficient η_RDGCost factor η of one switching event_S。

3. The method of claim 1, wherein the active distribution network power flow equation constraints are:

wherein, P_G,i,tFor active injection, P, of the distributed power supply or grid at node i at time t_L,i,tFor the active load at node i at time t, N (i) is the set of nodes connected to node i, P_ij,tThe active power flowing through the branch i-j at the time t is positive when the active power flows out of the node i; q_G,i,tFor reactive injection, Q, of the power supply at node i at time t_L,i,tFor a reactive load at node i at time t, Q_SVC,i,tFor SVC reactive compensation power, Q, at node i at time t_ij,tThe reactive power flowing through the branch i-j at the time t is positive when the reactive power flows out of the node i;

P_ij,tand Q_ij,tThe following can be derived from the branch apparent power expression:

wherein S is_ij,tFor the apparent power of branch i-j at time t,is the conjugate phasor, g, of the i-j current of the branch at time t_ijAnd b_ijConductance and susceptance, V, of branches i-j, respectively_i,tIs the voltage amplitude, θ, of node i at time t_ij,t＝θ_i,t-θ_j,tIs the voltage phase angle difference between nodes i, j at time t;

and (3) separating a real part from an imaginary part:

to obtain P_ij,tAnd Q_ij,t。

4. The method of claim 1, wherein the modified active distribution network power flow equation constraints are:

wherein Z is_ij,tFor the on-off state variable of branch i-j at time t, when branch i-j is off, Z_ij,t0, corresponding branch power Z_ij,t·P_ij,t＝0。

5. The method of claim 1, wherein the active distribution network radiating structure constraints are:

wherein E is_ij,tAnd Z_ij,tAre all Boolean variables, E_ij,tIs the current direction variable of branch i-j at time t, E_ij,t1 represents that a node j is a parent node of a node i at the time t, and the flow direction is from the node j to the node i; z_ij,tIs the connected state of the branch i-j at time t, Z_ij,tAnd 1 represents that the branch i-j is communicated at the moment t.

6. The method of claim 1, wherein the active power distribution network safe operation constraints comprise:

and (3) limiting the upper limit and the lower limit of the voltage amplitude:

V_i,min≤V_i,t≤V_i,max

and (3) branch current upper limit constraint:

distributed power supply output constraint

Power constraint of active power distribution network gateway

SVC constraint:

Q_SVC,i,min≤Q_SVC,i,t≤Q_SVC,i,max

and (3) restricting the number of switching actions:

wherein, V_i,maxAnd V_i,minRespectively, the upper and lower limits of the voltage amplitude at node I, I_ij,tIs the branch current amplitude, I_ij,maxIs the upper limit value of the branch current amplitude, P_RDG,i,tAnd Q_RDG,i,tRespectively located at node i at time tThe distributed power source has active and reactive real power,a distributed power output predicted value at a node i at the time t is obtained; a limited power factor range of operation is assumed for the distributed power source,for distributed Power factor Limit value, P, at node i_T,tActive power flowing into the primary distribution network from the root node of the distribution network at time t, P_T,minAnd P_T,maxRespectively an upper limit value and a lower limit value of active exchange power of the gateway of the active power distribution network; q_T,tFor the reactive power, Q, flowing from the root node of the distribution network into the distribution network of this stage at time t_T,minAnd Q_T,maxRespectively as the upper and lower limit values of reactive exchange power, Q, of the gateway of the active power distribution network_SVC,i,tFor the reactive power compensation of the node i at the time t, Q_SVC,i,minAnd Q_SVC,i,maxRespectively the minimum value and the maximum value of SVC reactive compensation at the node i, Delta Z_ij,tIndicating the number of switch changes at time t relative to time t-1, SW_maxIs the upper limit of the number of switching operations.

7. The method of claim 1, wherein the objective function is expressed as:

wherein, P_L,tFor active distribution network loss at time t, η_LIs the loss cost coefficient;curtailment of distributed Power for inode at time t, η_RDGPunishment cost coefficient for wind/light unit electric quantity; delta Z_ij,tη for the number of network switching events at time t relative to the last time_SCost factor of once switching action, omega_RDGIs distributed electricitySet of source access points, Ω_EIs a power grid branch set.

8. The method of claim 1, wherein the non-convex constraints comprise power flow equation constraints, the non-linear constraints comprise product terms of the modified power flow equation constraints, branch current upper limit constraints, and absolute value expressions of switching action number constraints,

the convex relaxation of the constraint condition of the power flow equation is as follows:

the standard second order taper form is:

wherein, U_i,t、W_ij,tAnd T_ij,tThe following constraints are satisfied:

and linearizing the product term of the constraint condition of the corrected power flow equation into:

wherein,the following constraints are satisfied:

node voltage variables U associated with nodes i, j, respectively_i,t、U_j,tCorresponding to the branch voltage variable associated with branch "i-j";

the branch current upper limit constraint condition is linearized as:

the absolute value expression of the switch action frequency constraint condition is linearized as: