CN117713089A - Method and device for calculating bearing capacity of distributed power supply of AC/DC power distribution network - Google Patents
Method and device for calculating bearing capacity of distributed power supply of AC/DC power distribution network Download PDFInfo
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Abstract
The invention relates to a method and a device for calculating the bearing capacity of a distributed power supply of an alternating current/direct current power distribution network, wherein the method comprises the following steps: taking the total capacity of intelligent soft switch access in an AC/DC power distribution network as an optimization decision variable, and constructing an outer SOP planning layer calculation model by taking the minimum weighted value of the construction cost of the intelligent soft switch and the total distributed power supply access amount as a target; taking the number and the positions of nodes connected with the distributed power supply in the AC/DC power distribution network and variables in the running control of the power distribution network as decision variables, and constructing an inner-layer AC/DC power distribution network optimized running model with the minimum running network loss of the AC/DC power distribution network and the maximum total access amount of the distributed power supply as targets; and solving the outer SOP planning layer calculation model and the inner alternating current/direct current power distribution network optimization operation model to obtain the bearing capacity of the distributed power supply of the alternating current/direct current power distribution network. The invention can make up for the shortages of the current other distributed power bearing capacity calculation methods.
Description
Technical Field
The invention relates to the technical field of power distribution network planning and optimal configuration, in particular to a method and a device for calculating the bearing capacity of a distributed power supply of an alternating current/direct current power distribution network.
Background
In recent years, the development of 5G technology, electric vehicles and intelligent building technology is rapid, and the construction requirements of novel infrastructures such as 5G base stations, electric vehicle charging facilities and intelligent buildings are driven, and meanwhile, large-scale new electricity utilization requirements are brought to a power distribution network. The power consumption demand distribution is wide, the direct current proportion is high, the time sequence characteristic and the reliability difference are obvious, meanwhile, the energy use efficiency is more concerned, the power consumption demand distribution system is difficult to be efficiently applied to a traditional alternating current power distribution system, and the power distribution system is required and challenged to be built. The alternating current-direct current flexible power distribution system has direct current power supply capacity and strong power grid structure control capacity, and the energy storage device convenient to configure has good load adjustment capacity, so that the change of the load pattern can be well adapted; meanwhile, compared with an alternating current power distribution system, the alternating current-direct current flexible power distribution system can better adapt to the characteristic of a distributed power supply and bear high-proportion distributed energy access.
At present, for a calculation model for calculating the bearing capacity of a distributed power supply in a power distribution network, the calculation is mostly carried out in a traditional alternating current power distribution system, the calculation model is built based on an alternating current-direct current power distribution network which can adapt to high-proportion distributed energy access, and the calculated distributed power supply access quantity is smaller. The calculation method for establishing the model in the AC/DC power distribution network is not considered for a small part, and the improvement effect of the intelligent soft Switch (SOP) which is a novel power electronic device on the distributed power supply bearing capacity of the power distribution network is not considered, so that the calculated bearing capacity still has the possibility of continuously improving.
Disclosure of Invention
The invention aims to solve the technical problem of providing a method and a device for calculating the bearing capacity of a distributed power supply of an alternating current/direct current power distribution network, which can make up for the defects of the conventional distributed power supply planning and designing methods of other power distribution networks.
The technical scheme adopted for solving the technical problems is as follows: the utility model provides a distributed power bearing capacity calculation method of an AC/DC power distribution network, which comprises the following steps:
taking the total capacity of intelligent soft switch access in an AC/DC power distribution network as an optimization decision variable, and constructing an outer SOP planning layer calculation model by taking the minimum weighted value of the construction cost of the intelligent soft switch and the total distributed power supply access amount as a target;
taking the number and the positions of nodes connected with the distributed power supply in the AC/DC power distribution network and variables in the running control of the power distribution network as decision variables, and constructing an inner-layer AC/DC power distribution network optimized running model with the minimum running network loss of the AC/DC power distribution network and the maximum total access amount of the distributed power supply as targets;
and solving the outer SOP planning layer calculation model and the inner alternating current/direct current power distribution network optimization operation model to obtain the bearing capacity of the distributed power supply of the alternating current/direct current power distribution network.
The objective function of the outer SOP planning layer calculation model is as follows: f (f) Outer part ＝min(λ 1 E SOP -λ 2 S PV ) Wherein E is SOP The construction cost of the intelligent soft switch in the AC/DC power distribution network is expressed as:C SOP the total capacity of the intelligent soft switch connected into the AC/DC power distribution network is expressed as: />N SOP For the quantity of intelligent soft switch in AC/DC distribution network, < >>Intelligent soft switch capacity for node i of intelligent soft switch access, < >>Installation costs for the purchase of units of intelligent soft switches, < >>Follow-up maintenance costs for intelligent soft switch units, < >>For the unit loss cost of the intelligent soft switch, +.>The loss rate of the intelligent soft switch; s is S PV The total capacity of the distributed power supply connected into the AC/DC power distribution network is expressed as: />N is the number of nodes in the AC/DC power distribution network, S i The distributed power capacity accessed for the node i; lambda (lambda) 1 And lambda (lambda) 2 Is a weighting coefficient.
Constraint conditions of the outer SOP planning layer calculation model are as follows:wherein (1)>Intelligent soft switch capacity for node i of intelligent soft switch access, < >>The maximum intelligent soft switching capacity which can be accessed by the node i which can be accessed by the soft switch.
The objective function of the inner-layer alternating-current and direct-current power distribution network optimization operation model is as follows:wherein F is ij,t Is the square of the current in branch ij during time t, r ij For the resistance of branch ij, N L For the number of branches in an AC/DC power distribution network, S PV The total capacity of the distributed power supply connected into the AC/DC power distribution network is expressed as: />N is the number of nodes in the AC/DC power distribution network, S i The distributed power capacity accessed for the node i; lambda (lambda) 3 And lambda (lambda) 4 Is a weighting coefficient.
The constraints of the inner-layer alternating-current and direct-current power distribution network optimization operation model comprise:
ac branch active constraints, expressed as:
reactive power constraint of the alternating current branch is expressed as:
ac branch voltage constraints, expressed as:
ac branch current constraints, expressed as:
the second order cone constraint of the alternating current branch is expressed as:
the dc branch active constraint is expressed as:
the dc branch voltage constraint is expressed as:
direct current branch current constraints, expressed as:
the second order cone constraint of the direct current branch is expressed as:
the voltage square constraint, expressed as: v (V) min ≤V≤V max ；
The current square constraint, expressed as: f (F) min ≤F≤F max ；
Intelligent soft switch ac side capacity constraints, expressed as:
intelligent soft switch dc side capacity constraints, expressed as:
wherein P is i′j′,t For the active power flowing in the alternating current branch i 'j' in the t time period, P j′k′,t For the active power, r, flowing in the ac branch j 'k' during the period t i′j′ For the resistance of the ac branch i 'j', F i′j′,t Is the square of the current in ac branch j 'k' during time t, For the output of the distributed power supply connected to the AC branch node j' in the t time period, +.>Active power consumed by the load at the alternating current branch node j' in the t time period; q (Q) i′j′,t For reactive power flowing in the ac branch i 'j' during the period t, Q j′k′,t For reactive power, x flowing in the ac branch j 'k' during the period t i′j′ Reactance of ac branch i' j +.>Reactive power of distributed power supply connected to AC branch node j' in t time period, +.>Reactive power consumed by the load at the alternating current branch node j' in the t time period; v (V) j′,t Is the square of the voltage of the alternating current branch node j' in the t time period, V i′,t Is the square of the voltage of the alternating current branch node i' in the t time period, F i′j′,t Is the square of the current in the ac branch i 'j' during the t period; p (P) i″j″,t The active power flowing in the direct current branch i 'j' in the t time period; p (P) j″k″,t For the active power flowing in the direct current branch j 'k' in the t time period, r i″j″ Resistance of the direct current branch i "j", F i″j″,t Is the square of the current in the direct current branch i "j" in the t period,/i->For the output of the distributed power supply connected at the direct current branch node j″ in the t period, < +.>Active power consumed by the load at the direct current branch node j″ in the t time period; v (V) j″,t Is the square of the voltage of the direct current branch node j' in the t time period, V i″,t Is the square of the voltage of the direct current branch node i' in the t time period, F i″j″,t The square of the current in the direct current branch i 'j' in the t time period; v represents the square of the voltage at the node, V min Representing the minimum voltage square of the node, V max Representing the maximum voltage square of the node; f represents the square of the branch current, F min Representing the least squares of the currents of the branches, F max Representing the maximum current square of the branch;for the active power transmitted by the intelligent soft switch at node i' where the t time period is connected to the ac side of the intelligent soft switch,for the reactive power transmitted by the intelligent soft switch at node i' where the t time period is connected to the ac side of the intelligent soft switch,the capacity of the intelligent soft switch is accessed to the node i' accessed to the intelligent soft switch; />Active power transmitted by the intelligent soft switch at node j″ connected to the DC side of the intelligent soft switch for time period t, +.>The capacity of the intelligent soft switch accessed for the node i' accessed by the intelligent soft switch.
Solving the outer SOP planning layer calculation model and the inner alternating current/direct current power distribution network optimization operation model to obtain the bearing capacity of the distributed power supply of the alternating current/direct current power distribution network, wherein the method specifically comprises the following steps:
Optimizing the capacity of the intelligent soft switch accessed by each point by adopting a particle swarm algorithm, and solving an outer SOP planning layer calculation model to obtain an intelligent soft switch initial capacity configuration scheme and a first distributed power supply access maximum capacity;
the intelligent soft switch initial capacity configuration scheme is imported into the inner-layer AC/DC power distribution network optimization operation model, and a preset solver is adopted to solve the inner-layer AC/DC power distribution network optimization operation model, so that a second distributed power supply access maximum capacity is obtained;
comparing the first distributed power supply access maximum capacity with the second distributed power supply access maximum capacity, ending iteration if the difference between the first distributed power supply access maximum capacity and the second distributed power supply access maximum capacity is within an error range, otherwise repeating the steps.
The technical scheme adopted for solving the technical problems is as follows: the utility model provides a distributed power bearing capacity calculation device of alternating current-direct current distribution network, includes:
the first construction module is used for taking the total capacity of the intelligent soft switch access in the AC/DC power distribution network as an optimization decision variable, and constructing an outer SOP planning layer calculation model by taking the minimum weighted value of the construction cost of the intelligent soft switch and the total distributed power supply access amount as a target;
The second construction module is used for taking the number and the positions of nodes connected with the distributed power supply in the AC/DC power distribution network and variables in the running control of the power distribution network as decision variables, and constructing an inner-layer AC/DC power distribution network optimized running model with the minimum running network loss of the AC/DC power distribution network and the maximum total access amount of the distributed power supply as targets;
and the solving module is used for solving the outer SOP planning layer calculation model and the inner alternating current/direct current power distribution network optimization operation model to obtain the bearing capacity of the distributed power supply of the alternating current/direct current power distribution network.
The objective function of the outer SOP planning layer calculation model is as follows: f (f) Outer part ＝min(λ 1 E SOP -λ 2 S PV ) Wherein E is SOP The construction cost of the intelligent soft switch in the AC/DC power distribution network is expressed as:C SOP the total capacity of the intelligent soft switch connected into the AC/DC power distribution network is expressed as: />N SOP For the quantity of intelligent soft switch in AC/DC distribution network, < >>Intelligent soft switch capacity for node i of intelligent soft switch access, < >>Installation costs for the purchase of units of intelligent soft switches, < >>Follow-up maintenance costs for intelligent soft switch units, < >>For the unit loss cost of the intelligent soft switch, +.>For intelligent soft switchingLoss rate; s is S PV The total capacity of the distributed power supply connected into the AC/DC power distribution network is expressed as: / >N is the number of nodes in the AC/DC power distribution network, S i The distributed power capacity accessed for the node i; lambda (lambda) 1 And lambda (lambda) 2 Is a weighting coefficient.
Constraint conditions of the outer SOP planning layer calculation model are as follows:wherein (1)>Intelligent soft switch capacity for node i of intelligent soft switch access, < >>The maximum intelligent soft switching capacity which can be accessed by the node i which can be accessed by the soft switch.
The objective function of the inner-layer alternating-current and direct-current power distribution network optimization operation model is as follows:wherein F is ij,t Is the square of the current in branch ij during time t, r ij For the resistance of branch ij, N L For the number of branches in an AC/DC power distribution network, S PV The total capacity of the distributed power supply connected into the AC/DC power distribution network is expressed as: />N is the number of nodes in the AC/DC power distribution network, S i The distributed power capacity accessed for the node i; lambda (lambda) 3 And lambda (lambda) 4 Is a weighting coefficient.
The constraints of the inner-layer alternating-current and direct-current power distribution network optimization operation model comprise:
ac branch active constraints, expressed as:
reactive power constraint of the alternating current branch is expressed as:
ac branch voltage constraints, expressed as:
ac branch current constraints, expressed as:
the second order cone constraint of the alternating current branch is expressed as:
the dc branch active constraint is expressed as:
The dc branch voltage constraint is expressed as:
direct current branch current constraints, expressed as:
the second order cone constraint of the direct current branch is expressed as:
the voltage square constraint, expressed as: v (V) min ≤V≤V max ；
The current square constraint, expressed as: f (F) min ≤F≤F max ；
Intelligent soft switch ac side capacity constraint, representationThe method comprises the following steps:
intelligent soft switch dc side capacity constraints, expressed as:
wherein P is i′j′,t For the active power flowing in the alternating current branch i 'j' in the t time period, P j′k′,t For the active power, r, flowing in the ac branch j 'k' during the period t i′j′ For the resistance of the ac branch i 'j', F i′j′,t Is the square of the current in ac branch j 'k' during time t,for the output of the distributed power supply connected to the AC branch node j' in the t time period, +.>Active power consumed by the load at the alternating current branch node j' in the t time period; q (Q) i′j′,t For reactive power flowing in the ac branch i 'j' during the period t, Q j′k′,t For reactive power, x flowing in the ac branch j 'k' during the period t i′j′ Reactance of ac branch i' j +.>Reactive power of distributed power supply connected to AC branch node j' in t time period, +.>Reactive power consumed by the load at the alternating current branch node j' in the t time period; v (V) j′,t Is the square of the voltage of the alternating current branch node j' in the t time period, V i′,t Is the square of the voltage of the alternating current branch node i' in the t time period, F i′j′,t Is the square of the current in the ac branch i 'j' during the t period; p (P) i″j″,t For a period of tActive power flowing through the direct current branch i 'j'; p (P) j″k″,t For the active power flowing in the direct current branch j 'k' in the t time period, r i″j″ Resistance of the direct current branch i "j", F i″j″,t Is the square of the current in the direct current branch i "j" in the t period,/i->For the output of the distributed power supply connected at the direct current branch node j″ in the t period, < +.>Active power consumed by the load at the direct current branch node j″ in the t time period; v (V) j″,t Is the square of the voltage of the direct current branch node j' in the t time period, V i″,t Is the square of the voltage of the direct current branch node i' in the t time period, F i″j″,t The square of the current in the direct current branch i 'j' in the t time period; v represents the square of the voltage at the node, V min Representing the minimum voltage square of the node, V max Representing the maximum voltage square of the node; f represents the square of the branch current, F min Representing the least squares of the currents of the branches, F max Representing the maximum current square of the branch; />Active power transmitted by the intelligent soft switch at node i' connected to the ac side of the intelligent soft switch for time period t, +.>Reactive power transmitted by the intelligent soft switch at node i' connected to the ac side of the intelligent soft switch for time period t,/- >The capacity of the intelligent soft switch is accessed to the node i' accessed to the intelligent soft switch; />For t time period and intelligent soft switch direct currentActive power transmitted by the intelligent soft switch at node j″ connected to the side, +.>The capacity of the intelligent soft switch accessed for the node i' accessed by the intelligent soft switch.
The solving module comprises:
the first solving unit is used for optimizing the capacity of the intelligent soft switch accessed by each point by adopting a particle swarm algorithm, and solving an outer SOP planning layer calculation model to obtain an intelligent soft switch initial capacity configuration scheme and a first distributed power supply access maximum capacity;
the second solving unit is used for importing the intelligent soft switch initial capacity configuration scheme into the inner-layer AC/DC power distribution network optimization operation model, and solving the inner-layer AC/DC power distribution network optimization operation model by adopting a preset solver to obtain a second distributed power supply access maximum capacity;
and the comparison unit is used for comparing the first distributed power supply access maximum capacity with the second distributed power supply access maximum capacity, ending iteration if the difference between the first distributed power supply access maximum capacity and the second distributed power supply access maximum capacity is within an error range, and repeating the operation of the first solving unit and the second solving unit if the difference between the first distributed power supply access maximum capacity and the second distributed power supply access maximum capacity is within the error range.
The technical scheme adopted for solving the technical problems is as follows: an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the steps of the method for calculating the distributed power bearing capacity of the ac/dc power distribution network are implemented when the processor executes the computer program.
The technical scheme adopted for solving the technical problems is as follows: there is provided a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the above method for calculating the distributed power carrying capacity of an ac/dc distribution network.
Advantageous effects
Due to the adoption of the technical scheme, compared with the prior art, the invention has the following advantages and positive effects: the invention establishes the optimization calculation model based on the AC/DC power distribution network, is more in line with the development trend of the future power distribution network, and has larger capacity of the distributed power supply which can be carried compared with the traditional AC power distribution network. On the basis of the novel AC/DC power distribution network, the invention considers the effect of SOP in the power distribution network, and the SOP can replace the traditional tie switch to control the flow of tide, thereby not only remarkably reducing the network loss of the power distribution network, but also realizing the source-load mutual aid between lines and providing more choices for the scheme of distributed power supply access. The method can make up for the shortages of the current other methods for calculating the bearing capacity of the distributed power supply, is favorable for more deeply and comprehensively excavating the bearing potential of the power distribution network to the distributed power supply, is suitable for the development trend of the power distribution network in the future, and has foreseeability and advancement.
Drawings
Fig. 1 is a flowchart of a method for calculating a distributed power supply bearing capacity of an ac/dc power distribution network according to a first embodiment of the present invention;
fig. 2 is a topological diagram of a system structure of an ac/dc power distribution network according to a first embodiment of the present invention;
fig. 3 is a schematic diagram of a solution process in the first embodiment of the present invention.
Detailed Description
The invention will be further illustrated with reference to specific examples. It is to be understood that these examples are illustrative of the present invention and are not intended to limit the scope of the present invention. Further, it is understood that various changes and modifications may be made by those skilled in the art after reading the teachings of the present invention, and such equivalents are intended to fall within the scope of the claims appended hereto.
The first embodiment of the invention relates to a method for calculating the distributed power supply bearing capacity of an alternating current/direct current power distribution network, which aims at the problem of calculating the distributed power supply bearing capacity in the alternating current/direct current power distribution network containing multiple SOPs as shown in fig. 2, and provides a double-layer calculation model, wherein the outer layer is an SOP planning layer, and the inner layer is an optimal operation layer. As shown in fig. 1, the method specifically comprises the following steps:
and step 1, taking the total capacity of intelligent soft switch access in the AC/DC power distribution network as an optimization decision variable, and constructing an outer SOP planning layer calculation model by taking the minimum weighted value of the construction cost of the intelligent soft switch and the total distributed power supply access amount as a target.
The objective of the outer layer SOP planning layer calculation model constructed in the step is to adjust the SOP capacity of each point access on the premise that the SOP access node determines and the single point access capacity is limited, and the objective is to minimize the subtraction weighted value of the SOP construction cost and the total distributed power access amount, so as to attempt to accommodate the most distributed power with the minimum SOP configuration, and the expression of the objective function is as follows: f (f) Outer part ＝min(λ 1 E SOP -λ 2 S PV )。
Wherein E is SOP The construction cost for the intelligent soft switch in the AC/DC power distribution network comprises the following steps: the acquisition and installation cost, the subsequent maintenance cost and the loss cost of the SOP in the power conversion process of the SOP can be expressed as follows:C SOP for the intelligent soft switch total capacity of inserting in the AC/DC distribution network, < >>Installation costs for the purchase of units of intelligent soft switches, < >>The unit subsequent maintenance cost for the intelligent soft switch,for the unit loss cost of the intelligent soft switch, +.>Is the loss rate of the intelligent soft switch.
C SOP The total capacity of the intelligent soft switch connected into the AC/DC power distribution network can be expressed as:N SOP for the quantity of intelligent soft switch in AC/DC distribution network, < >>And the intelligent soft switch capacity is accessed for the node i accessed by the intelligent soft switch.
S PV The total capacity of the distributed power supply connected into the AC/DC power distribution network is expressed as: N is the number of nodes in the AC/DC power distribution network, S i And the distributed power capacity accessed for the node i.
λ 1 And lambda (lambda) 2 The weight coefficients are respectively the SOP construction cost and the total distributed power supply access amount.
And 2, taking the number and the positions of nodes connected with the distributed power supply in the AC/DC power distribution network and variables during operation control of the power distribution network as decision variables, and constructing an inner-layer AC/DC power distribution network optimization operation model by taking the minimum operation network loss of the AC/DC power distribution network and the maximum total connection amount of the distributed power supply as targets.
Decision variables in this step include: node voltage square:branch current square: />Branch active power flow:branch reactive power flow: />Distributed energy access location->Distributed energy access capacity->
N represents the total node number of the AC/DC power distribution network; i represents a node number of the power distribution network; n (N) L Representing the total branch number of the power distribution network; ij represents the ij-th branch; t represents the running time point. V (V) i,t Is the square of the voltage at node i, v, over a period of t i,t Representing the actual voltage of node i during time t, F ij,t Is the square of the current in branch ij during time t, f ij,t Representing the actual current on branch ij during time t. P (P) ij,t For the active power flowing in branch ij in t time period, Q ij,t For the reactive power flowing in the branch ij during the period t,accessing node locations for distributed energy, < >>Is the access capacity of the distributed energy source at the node i.
The optimization operation objective of the inner-layer alternating-current and direct-current power distribution network is that on the basis of an outer-layer SOP planning layer calculation model, after the capacity of each SOP is determined, the minimum operation network loss of the alternating-current and direct-current power distribution network and the maximum distributed power supply access capacity are considered, so that an objective function of the optimization operation model of the inner-layer alternating-current and direct-current power distribution network is expressed as:
wherein lambda is 3 And lambda (lambda) 4 The weight coefficients of the total network loss and the total distributed power access amount in a typical day are respectively given.
Constraints of the inner-layer alternating-current and direct-current power distribution network optimization operation model comprise:
ac branch active constraints, expressed as:
reactive power constraint of the alternating current branch is expressed as:
ac branch voltage constraints, expressed as:
ac branch current constraints, expressed as:
the dc branch active constraint is expressed as:
the dc branch voltage constraint is expressed as:
direct current branch current constraints, expressed as:
the voltage square constraint, expressed as: v (V) min ≤V≤V max ；
The current square constraint, expressed as: f (F) min ≤F≤F max ；
Wherein P is i′j′,t For the active power flowing in the alternating current branch i 'j' in the t time period, P j′k′,t For the active power, r, flowing in the ac branch j 'k' during the period t i′j′ For the resistance of the ac branch i 'j', F i′j′,t Is the square of the current in ac branch j 'k' during time t,for the output of the distributed power supply connected to the AC branch node j' in the t time period, +.>For a period of tActive power consumed by the load at the ac branch node j'; q (Q) i′j′,t For reactive power flowing in the ac branch i 'j' during the period t, Q j′k′,t For reactive power, x flowing in the ac branch j 'k' during the period t i′j′ Reactance of ac branch i' j +.>Reactive power of distributed power supply connected to AC branch node j' in t time period, +.>Reactive power consumed by the load at the alternating current branch node j' in the t time period; v (V) j′,t Is the square of the voltage of the alternating current branch node j' in the t time period, V i′,t Is the square of the voltage of the alternating current branch node i' in the t time period, F i′j′,t Is the square of the current in the ac branch i 'j' during the t period; p (P) i″j″,t The active power flowing in the direct current branch i 'j' in the t time period; p (P) j″k″,t For the active power flowing in the direct current branch j 'k' in the t time period, r i″j″ Resistance of the direct current branch i "j", F i″j″,t Is the square of the current in the direct current branch i "j" in the t period,/i- >For the output of the distributed power supply connected at the direct current branch node j″ in the t period, < +.>Active power consumed by the load at the direct current branch node j″ in the t time period; v (V) j″,t Is the square of the voltage of the direct current branch node j' in the t time period, V i″,t Is the square of the voltage of the direct current branch node i' in the t time period, F i″j″,t The square of the current in the direct current branch i 'j' in the t time period; v represents the square of the voltage at the node, V min Representing the minimum voltage square of the node, V max Representing the maximum voltage square of the node; f represents branch current levelSquare F min Representing the least squares of the currents of the branches, F max Representing the maximum current square of the branch.
SOP is used as a flexible multi-state switch, can flexibly control power flow and adjust node voltage, and can also be used for fault recovery when a power distribution network breaks down. The power loss of SOP is expressed as:wherein,for the loss of SOP at node i' connected to the SOP ac side in time t, < ->Is the loss of SOP at node j' connected to the DC side of SOP during time t,/and>active power transmitted by the intelligent soft switch at node i' connected to the ac side of the intelligent soft switch for time period t, +.>Reactive power transmitted by the intelligent soft switch at node i' connected to the ac side of the intelligent soft switch for time period t,/- >Active power transmitted by the intelligent soft switch at node j″ connected to the DC side of the intelligent soft switch for time period t, +.>SOP converter loss factor for node i' access,/->And the SOP converter loss coefficient accessed at the node j'.
Each port of the SOP is isolated by the DC link, becauseThe ports only need to meet respective capacity constraints, and the capacity constraints of the SOP alternating current side are expressed as:SOP dc side capacity constraint, expressed as: />
Because the inner layer model problem belongs to a mixed integer nonlinear programming problem (mixed integer non-linear programming, MINLP), the constraint condition has quadratic terms and integer terms, and the conventional solving method has poor solving effect, so that the problem is converted into a programming problem which is convenient to solve by utilizing second-order cone relaxation, and the constraint of the second-order cone of the alternating current branch is expressed as:the second order cone constraint of the direct current branch is expressed as: />
And step 3, solving the outer SOP planning layer calculation model and the inner AC/DC power distribution network optimization operation model to obtain the bearing capacity of the distributed power supply of the AC/DC power distribution network. As shown in fig. 3, the solution process is as follows:
(1) On the basis of an outer SOP planning layer, on the premise that SOP access nodes determine and single-point access capacity is limited, the SOP capacity of each point access is optimized through a particle swarm algorithm, and a calculation model of the outer SOP planning layer is solved, so that an intelligent soft switch initial capacity configuration scheme and a first distributed power supply access maximum capacity are obtained.
(2) And leading the inner-layer alternating-current and direct-current power distribution network optimization operation model into an SOP configuration scheme sent by the outer layer, and solving the inner-layer alternating-current and direct-current power distribution network optimization operation model by adopting a commercial solver according to load information of the SOP configuration scheme, system voltage and power flow constraint conditions to obtain the maximum capacity of the second distributed power supply access.
(3) Comparing the first distributed power supply access maximum capacity with the second distributed power supply access maximum capacity, and ending iteration if the difference between the first distributed power supply access maximum capacity and the second distributed power supply access maximum capacity is within an error range; if the error range is exceeded, returning to the step (1), updating the SOP capacity allocation scheme by the outer layer model through a particle swarm algorithm, sending the SOP capacity allocation scheme to the inner layer model, and turning to the step (2).
It is easy to find that the invention establishes an optimization calculation model based on the AC/DC power distribution network, more accords with the development trend of the future power distribution network, and has larger capacity of the distributed power supply which can be carried compared with the traditional AC power distribution network. On the basis of the novel AC/DC power distribution network, the invention considers the effect of SOP in the power distribution network, and the SOP can replace the traditional tie switch to control the flow of tide, thereby not only remarkably reducing the network loss of the power distribution network, but also realizing the source-load mutual aid between lines and providing more choices for the scheme of distributed power supply access. The method can make up for the shortages of the current other methods for calculating the bearing capacity of the distributed power supply, is favorable for more deeply and comprehensively excavating the bearing potential of the power distribution network to the distributed power supply, is suitable for the development trend of the power distribution network in the future, and has foreseeability and advancement.
A second embodiment of the present invention relates to an apparatus for calculating a distributed power supply capacity of an ac/dc power distribution network, including:
the first construction module is used for taking the total capacity of the intelligent soft switch access in the AC/DC power distribution network as an optimization decision variable, and constructing an outer SOP planning layer calculation model by taking the minimum weighted value of the construction cost of the intelligent soft switch and the total distributed power supply access amount as a target;
the second construction module is used for taking the number and the positions of nodes connected with the distributed power supply in the AC/DC power distribution network and variables in the running control of the power distribution network as decision variables, and constructing an inner-layer AC/DC power distribution network optimized running model with the minimum running network loss of the AC/DC power distribution network and the maximum total access amount of the distributed power supply as targets;
and the solving module is used for solving the outer SOP planning layer calculation model and the inner alternating current/direct current power distribution network optimization operation model to obtain the bearing capacity of the distributed power supply of the alternating current/direct current power distribution network.
The outer layer SOThe objective function of the calculation model of the P planning layer is as follows: f (f) Outer part ＝min(λ 1 E SOP -λ 2 S PV ) Wherein E is SOP The construction cost of the intelligent soft switch in the AC/DC power distribution network is expressed as:C SOP the total capacity of the intelligent soft switch connected into the AC/DC power distribution network is expressed as: / >N SOP For the quantity of intelligent soft switch in AC/DC distribution network, < >>Intelligent soft switch capacity for node i of intelligent soft switch access, < >>Installation costs for the purchase of units of intelligent soft switches, < >>Follow-up maintenance costs for intelligent soft switch units, < >>For the unit loss cost of the intelligent soft switch, +.>The loss rate of the intelligent soft switch; s is S PV The total capacity of the distributed power supply connected into the AC/DC power distribution network is expressed as: />N is the number of nodes in the AC/DC power distribution network, S i The distributed power capacity accessed for the node i; lambda (lambda) 1 And lambda (lambda) 2 Is a weighting coefficient.
Constraint conditions of the outer SOP planning layer calculation model are as follows:wherein (1)>Intelligent soft switch capacity for node i of intelligent soft switch access, < >>The maximum intelligent soft switching capacity which can be accessed by the node i which can be accessed by the soft switch.
The objective function of the inner-layer alternating-current and direct-current power distribution network optimization operation model is as follows:wherein F is ij,t Is the square of the current in branch ij during time t, r ij For the resistance of branch ij, N L For the number of branches in an AC/DC power distribution network, S PV The total capacity of the distributed power supply connected into the AC/DC power distribution network is expressed as: />N is the number of nodes in the AC/DC power distribution network, S i The distributed power capacity accessed for the node i; lambda (lambda) 3 And lambda (lambda) 4 Is a weighting coefficient.
The constraints of the inner-layer alternating-current and direct-current power distribution network optimization operation model comprise:
ac branch active constraints, expressed as:
reactive power constraint of the alternating current branch is expressed as:
ac branch voltage constraints, expressed as:/>
ac branch current constraints, expressed as:
the second order cone constraint of the alternating current branch is expressed as:
the dc branch active constraint is expressed as:
the dc branch voltage constraint is expressed as:
direct current branch current constraints, expressed as:
the second order cone constraint of the direct current branch is expressed as:
the voltage square constraint, expressed as: v (V) min ≤V≤V max ；
The current square constraint, expressed as: f (F) min ≤F≤F max ；
Intelligent soft switch ac side capacity constraints, expressed as:
intelligent soft switch dc side capacity constraints, expressed as:
wherein P is i′j′,t For the active power flowing in the alternating current branch i 'j' in the t time period, P j′k′,t For the active power, r, flowing in the ac branch j 'k' during the period t i′j′ For the resistance of the ac branch i 'j', F i′j′,t Is the square of the current in ac branch j 'k' during time t,for the output of the distributed power supply connected to the AC branch node j' in the t time period, +.>Active power consumed by the load at the alternating current branch node j' in the t time period; q (Q) i′j′,t For reactive power flowing in the ac branch i 'j' during the period t, Q j′k′,t For reactive power, x flowing in the ac branch j 'k' during the period t i′j′ Reactance of ac branch i' j +.>Reactive power of distributed power supply connected to AC branch node j' in t time period, +.>Reactive power consumed by the load at the alternating current branch node j' in the t time period; v (V) j′,t Is the square of the voltage of the alternating current branch node j' in the t time period, V i′,t Is the square of the voltage of the alternating current branch node i' in the t time period, F i′j′,t Is the square of the current in the ac branch i 'j' during the t period; p (P) i″j″,t The active power flowing in the direct current branch i 'j' in the t time period; p (P) j″k″,t For the active power flowing in the direct current branch j 'k' in the t time period, r i″j″ Resistance of the direct current branch i "j", F i″j″,t Is the square of the current in the direct current branch i "j" in the t period,/i->For the output of the distributed power supply connected at the direct current branch node j″ in the t period, < +.>Active power consumed by the load at the direct current branch node j″ in the t time period; v (V) j″,t Is the square of the voltage of the direct current branch node j' in the t time period, V i″,t Is the square of the voltage of the direct current branch node i' in the t time period, F i″j″,t The square of the current in the direct current branch i 'j' in the t time period; v represents the square of the voltage at the node, V min Representing the minimum voltage square of the node, V max Representing the maximum voltage square of the node; f represents the square of the branch current, F min Representing the least squares of the currents of the branches, F max Representing the maximum current square of the branch;for the active power transmitted by the intelligent soft switch at node i' where the t time period is connected to the ac side of the intelligent soft switch,reactive power transmitted by the intelligent soft switch at node i' connected to the ac side of the intelligent soft switch for time period t,/->The capacity of the intelligent soft switch is accessed to the node i' accessed to the intelligent soft switch; />Active power transmitted by the intelligent soft switch at node j″ connected to the DC side of the intelligent soft switch for time period t, +.>The capacity of the intelligent soft switch accessed for the node i' accessed by the intelligent soft switch.
The solving module comprises:
the first solving unit is used for optimizing the capacity of the intelligent soft switch accessed by each point by adopting a particle swarm algorithm, and solving an outer SOP planning layer calculation model to obtain an intelligent soft switch initial capacity configuration scheme and a first distributed power supply access maximum capacity;
the second solving unit is used for importing the intelligent soft switch initial capacity configuration scheme into the inner-layer AC/DC power distribution network optimization operation model, and solving the inner-layer AC/DC power distribution network optimization operation model by adopting a preset solver to obtain a second distributed power supply access maximum capacity;
And the comparison unit is used for comparing the first distributed power supply access maximum capacity with the second distributed power supply access maximum capacity, ending iteration if the difference between the first distributed power supply access maximum capacity and the second distributed power supply access maximum capacity is within an error range, and repeating the operation of the first solving unit and the second solving unit if the difference between the first distributed power supply access maximum capacity and the second distributed power supply access maximum capacity is within the error range.
A third embodiment of the present invention relates to an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the steps of the method for calculating the distributed power bearing capacity of an ac/dc power distribution network according to the first embodiment are implemented when the processor executes the computer program.
A fourth embodiment of the invention relates to a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the method for calculating the load bearing capacity of a distributed power supply of an ac/dc power distribution network of the first embodiment.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, magnetic disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (14)
1. The method for calculating the distributed power supply bearing capacity of the AC/DC power distribution network is characterized by comprising the following steps of:
taking the total capacity of intelligent soft switch access in an AC/DC power distribution network as an optimization decision variable, and constructing an outer SOP planning layer calculation model by taking the minimum weighted value of the construction cost of the intelligent soft switch and the total distributed power supply access amount as a target;
Taking the number and the positions of nodes connected with the distributed power supply in the AC/DC power distribution network and variables in the running control of the power distribution network as decision variables, and constructing an inner-layer AC/DC power distribution network optimized running model with the minimum running network loss of the AC/DC power distribution network and the maximum total access amount of the distributed power supply as targets;
and solving the outer SOP planning layer calculation model and the inner alternating current/direct current power distribution network optimization operation model to obtain the bearing capacity of the distributed power supply of the alternating current/direct current power distribution network.
2. The method for calculating the distributed power supply bearing capacity of the ac/dc power distribution network according to claim 1, wherein the objective function of the calculation model of the outer SOP planning layer is: f (f) Outer part ＝min(λ 1 E SOP -λ 2 S PV ) Wherein E is SOP The construction cost of the intelligent soft switch in the AC/DC power distribution network is expressed as:
C SOP the total capacity of the intelligent soft switch connected into the AC/DC power distribution network is expressed as: />N SOP For the quantity of intelligent soft switch in AC/DC distribution network, < >>Intelligent soft switch capacity for node i of intelligent soft switch access, < >>Installation costs for the purchase of units of intelligent soft switches, < >>Follow-up maintenance costs for intelligent soft switch units, < >>For the unit loss cost of the intelligent soft switch, +.>The loss rate of the intelligent soft switch; s is S PV The total capacity of the distributed power supply connected into the AC/DC power distribution network is expressed as:
n is the number of nodes in the AC/DC power distribution network, S i The distributed power capacity accessed for the node i; lambda (lambda) 1 And lambda (lambda) 2 Is a weighting coefficient.
3. The method for calculating the distributed power supply bearing capacity of the ac/dc power distribution network according to claim 1, wherein the constraint condition of the calculation model of the outer SOP planning layer is:wherein (1)>Intelligent soft switch capacity for node i of intelligent soft switch access, < >>The maximum intelligent soft switching capacity which can be accessed by the node i which can be accessed by the soft switch.
4. The method for calculating the distributed power supply bearing capacity of the ac/dc power distribution network according to claim 1, wherein the objective function of the inner ac/dc power distribution network optimization operation model is:wherein F is ij,t Is the square of the current in branch ij during time t, r ij For the resistance of branch ij, N L For the number of branches in an AC/DC power distribution network, S PV The total capacity of the distributed power supply connected into the AC/DC power distribution network is expressed as: />N is the number of nodes in the AC/DC power distribution network, S i The distributed power capacity accessed for the node i; lambda (lambda) 3 And lambda (lambda) 4 Is a weighting coefficient.
5. The method for calculating the distributed power supply bearing capacity of the ac/dc power distribution network according to claim 1, wherein the constraints of the inner ac/dc power distribution network optimization operation model include:
Ac branch active constraints, expressed as:
reactive power constraint of the alternating current branch is expressed as:
ac branch voltage constraints, expressed as:
ac branch current constraints, expressed as:
the second order cone constraint of the alternating current branch is expressed as:
DC branch active constraint meterThe method is shown as follows:
the dc branch voltage constraint is expressed as:
direct current branch current constraints, expressed as:
the second order cone constraint of the direct current branch is expressed as:
the voltage square constraint, expressed as: v (V) min ≤V≤V max ；
The current square constraint, expressed as: f (F) min ≤F≤F max ；
Intelligent soft switch ac side capacity constraints, expressed as:
intelligent soft switch dc side capacity constraints, expressed as:
wherein P is i′j′,t For the active power flowing in the alternating current branch i 'j' in the t time period, P j′k′,t For the active power, r, flowing in the ac branch j 'k' during the period t i′j′ For the resistance of the ac branch i 'j', F i′j′,t Is the square of the current in ac branch j 'k' during time t,for distributed electric access at ac branch node j' during time tOutput of source->Active power consumed by the load at the alternating current branch node j' in the t time period; q (Q) i′j′,t For reactive power flowing in the ac branch i 'j' during the period t, Q j′k′,t For reactive power, x flowing in the ac branch j 'k' during the period t i′j′ Reactance of ac branch i' j +.>Reactive power of distributed power supply connected to AC branch node j' in t time period, +.>Reactive power consumed by the load at the alternating current branch node j' in the t time period; v (V) j′,t Is the square of the voltage of the alternating current branch node j' in the t time period, V i′,t Is the square of the voltage of the alternating current branch node i' in the t time period, F i′j′,t Is the square of the current in the ac branch i 'j' during the t period; p (P) i″j″,t The active power flowing in the direct current branch i 'j' in the t time period; p (P) j″k″,t For the active power flowing in the direct current branch j 'k' in the t time period, r i″j″ Resistance of the direct current branch i "j", F i″j″,t Is the square of the current in the direct current branch i "j" in the t period,/i->The output of the distributed power supply connected at the direct current branch node j' in the t time period,
active power consumed by the load at the direct current branch node j″ in the t time period; v (V) j″,t Is the square of the voltage of the direct current branch node j' in the t time period, V i″,t Is straight within t time periodSquare of voltage at current branch node i ", F i″j″,t The square of the current in the direct current branch i 'j' in the t time period; v represents the square of the voltage at the node, V min Representing the minimum voltage square of the node, V max Representing the maximum voltage square of the node; f represents the square of the branch current, F min Representing the least squares of the currents of the branches, F max Representing the maximum current square of the branch; />Active power transmitted by the intelligent soft switch at node i' connected to the ac side of the intelligent soft switch for time period t, +.>Reactive power transmitted by the intelligent soft switch at node i' connected to the ac side of the intelligent soft switch for time period t,/->The capacity of the intelligent soft switch is accessed to the node i' accessed to the intelligent soft switch; />Active power transmitted by the intelligent soft switch at node j″ connected to the DC side of the intelligent soft switch for time period t, +.>The capacity of the intelligent soft switch accessed for the node i' accessed by the intelligent soft switch.
6. The method for calculating the bearing capacity of the distributed power supply of the ac/dc power distribution network according to claim 1, wherein the solving the outer layer SOP planning layer calculation model and the inner layer ac/dc power distribution network optimization operation model to obtain the bearing capacity of the distributed power supply of the ac/dc power distribution network specifically comprises:
optimizing the capacity of the intelligent soft switch accessed by each point by adopting a particle swarm algorithm, and solving an outer SOP planning layer calculation model to obtain an intelligent soft switch initial capacity configuration scheme and a first distributed power supply access maximum capacity; the intelligent soft switch initial capacity configuration scheme is imported into the inner-layer AC/DC power distribution network optimization operation model, and a preset solver is adopted to solve the inner-layer AC/DC power distribution network optimization operation model, so that a second distributed power supply access maximum capacity is obtained;
Comparing the first distributed power supply access maximum capacity with the second distributed power supply access maximum capacity, ending iteration if the difference between the first distributed power supply access maximum capacity and the second distributed power supply access maximum capacity is within an error range, otherwise repeating the steps.
7. An ac/dc distribution network distributed power bearing capacity calculating device, comprising:
the first construction module is used for taking the total capacity of the intelligent soft switch access in the AC/DC power distribution network as an optimization decision variable, and constructing an outer SOP planning layer calculation model by taking the minimum weighted value of the construction cost of the intelligent soft switch and the total distributed power supply access amount as a target;
the second construction module is used for taking the number and the positions of nodes connected with the distributed power supply in the AC/DC power distribution network and variables in the running control of the power distribution network as decision variables, and constructing an inner-layer AC/DC power distribution network optimized running model with the minimum running network loss of the AC/DC power distribution network and the maximum total access amount of the distributed power supply as targets;
and the solving module is used for solving the outer SOP planning layer calculation model and the inner alternating current/direct current power distribution network optimization operation model to obtain the bearing capacity of the distributed power supply of the alternating current/direct current power distribution network.
8. The ac/dc distribution network distributed power load capacity calculation apparatus according to claim 7, wherein the objective function of the outer SOP planning layer calculation model is: f (f) Outer part ＝min(λ 1 E SOP -λ 2 S PV ) Wherein E is SOP The construction cost of the intelligent soft switch in the AC/DC power distribution network is expressed as:
C SOP the total capacity of the intelligent soft switch connected into the AC/DC power distribution network is expressed as: />N SOP For the quantity of intelligent soft switch in AC/DC distribution network, < >>Intelligent soft switch capacity for node i of intelligent soft switch access, < >>Installation costs for the purchase of units of intelligent soft switches, < >>Follow-up maintenance costs for intelligent soft switch units, < >>For the unit loss cost of the intelligent soft switch, +.>The loss rate of the intelligent soft switch; s is S PV The total capacity of the distributed power supply connected into the AC/DC power distribution network is expressed as:
n is the number of nodes in the AC/DC power distribution network, S i The distributed power capacity accessed for the node i; lambda (lambda) 1 And lambda (lambda) 2 Is a weighting coefficient.
9. An ac/dc distribution network distributed power supply according to claim 7The bearing capacity calculating device is characterized in that the constraint conditions of the outer SOP planning layer calculating model are as follows:wherein (1)>Intelligent soft switch capacity for node i of intelligent soft switch access, < >>The maximum intelligent soft switching capacity which can be accessed by the node i which can be accessed by the soft switch.
10. The distributed power bearing capacity computing device of an ac/dc power distribution network according to claim 7, wherein the objective function of the inner ac/dc power distribution network optimization operation model is: Wherein F is ij,t Is the square of the current in branch ij during time t, r ij For the resistance of branch ij, N L For the number of branches in an AC/DC power distribution network, S PV The total capacity of the distributed power supply connected into the AC/DC power distribution network is expressed as: />N is the number of nodes in the AC/DC power distribution network, S i The distributed power capacity accessed for the node i; lambda (lambda) 3 And lambda (lambda) 4 Is a weighting coefficient.
11. The ac/dc distribution network distributed power load capacity calculation apparatus according to claim 7, wherein the constraints of the inner ac/dc distribution network optimization operation model include:
ac branch active constraints, expressed as:
reactive power constraint of the alternating current branch is expressed as:
ac branch voltage constraints, expressed as:
ac branch current constraints, expressed as:
the second order cone constraint of the alternating current branch is expressed as:
the dc branch active constraint is expressed as:
the dc branch voltage constraint is expressed as:
direct current branch current constraints, expressed as:
the second order cone constraint of the direct current branch is expressed as:
the voltage square constraint, expressed as: v (V) min ≤V≤V max ；
The current square constraint, expressed as: f (F) min ≤F≤F max ；
Intelligent soft switch ac side capacity constraints, expressed as:
intelligent soft switch dc side capacity constraints, expressed as: Wherein P is i′j′,t For the active power flowing in the alternating current branch i 'j' in the t time period, P j′k′,t For the active power, r, flowing in the ac branch j 'k' during the period t i′j′ For the resistance of the ac branch i 'j', F i′j′,t Is the square of the current in the ac branch j 'k' during the t period,/v%>For the output of the distributed power supply connected to the AC branch node j' in the t time period, +.>Active power consumed by the load at the alternating current branch node j' in the t time period; q (Q) i′j′,t For reactive power flowing in the ac branch i 'j' during the period t, Q j′k′,t For reactive power, x flowing in the ac branch j 'k' during the period t i′j′ Reactance of ac branch i' j +.>Reactive power of distributed power supply connected to AC branch node j' in t time period, +.>Reactive power consumed by the load at the alternating current branch node j' in the t time period; v (V) j′,t Is the square of the voltage of the alternating current branch node j' in the t time period, V i′,t For the voltage of the ac branch node i' in the t periodSquaring, F i′j′,t Is the square of the current in the ac branch i 'j' during the t period; p (P) i″j″,t The active power flowing in the direct current branch i 'j' in the t time period; p (P) j″k″,t For the active power flowing in the direct current branch j 'k' in the t time period, r i″j″ Resistance of the direct current branch i "j", F i″j″,t Is the square of the current in the direct current branch i "j" in the t period,/i->For the output of the distributed power supply connected at the direct current branch node j″ in the t period, < +.>Active power consumed by the load at the direct current branch node j″ in the t time period; v (V) j″,t Is the square of the voltage of the direct current branch node j' in the t time period, V i″,t Is the square of the voltage of the direct current branch node i' in the t time period, F i″j″,t The square of the current in the direct current branch i 'j' in the t time period; v represents the square of the voltage at the node, V min Representing the minimum voltage square of the node, V max Representing the maximum voltage square of the node; f represents the square of the branch current, F min Representing the least squares of the currents of the branches, F max Representing the maximum current square of the branch; />Active power transmitted by the intelligent soft switch at node i' connected to the ac side of the intelligent soft switch for time period t, +.>Reactive power transmitted by the intelligent soft switch at node i' connected to the ac side of the intelligent soft switch for time period t,/->Intelligent for node i' access of intelligent soft switchSoft switching capacity; />Active power transmitted by the intelligent soft switch at node j″ connected to the DC side of the intelligent soft switch for time period t, +. >The capacity of the intelligent soft switch accessed for the node i' accessed by the intelligent soft switch.
12. The ac/dc distribution network distributed power bearing capacity calculation device of claim 7, wherein said solution module comprises:
the first solving unit is used for optimizing the capacity of the intelligent soft switch accessed by each point by adopting a particle swarm algorithm, and solving an outer SOP planning layer calculation model to obtain an intelligent soft switch initial capacity configuration scheme and a first distributed power supply access maximum capacity;
the second solving unit is used for importing the intelligent soft switch initial capacity configuration scheme into the inner-layer AC/DC power distribution network optimization operation model, and solving the inner-layer AC/DC power distribution network optimization operation model by adopting a preset solver to obtain a second distributed power supply access maximum capacity;
and the comparison unit is used for comparing the first distributed power supply access maximum capacity with the second distributed power supply access maximum capacity, ending iteration if the difference between the first distributed power supply access maximum capacity and the second distributed power supply access maximum capacity is within an error range, and repeating the operation of the first solving unit and the second solving unit if the difference between the first distributed power supply access maximum capacity and the second distributed power supply access maximum capacity is within the error range.
13. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor, when executing the computer program, implements the steps of the method for calculating the distributed power load capacity of an ac/dc distribution network according to any one of claims 1-6.
14. A computer readable storage medium having stored thereon a computer program, which when executed by a processor performs the steps of the method for calculating the load capacity of a distributed power supply of an ac/dc distribution network according to any of claims 1-6.
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