CN111079972A - Method, device and medium for planning reliability of active power distribution network - Google Patents
Method, device and medium for planning reliability of active power distribution network Download PDFInfo
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Abstract
The invention discloses a method, a device and a medium for planning the reliability of an active power distribution network, wherein the method comprises the following steps: step S1, dividing the ADN reliability planning into a main item and a sub item, wherein the main item is ADN planning cost optimization, and the sub item is reliability verification under the power grid planning of the main item; step S2, constructing a cost optimization objective function taking the minimum annual average comprehensive cost value as a standard; s3, respectively carrying out relevant constraints on the radialization of the power distribution network, the construction of power distribution network equipment, the operation flow of the power distribution network, the capacity of a feeder line and the voltage amplitude to obtain constraint formulas of each item; step S4, constructing a reliability cost objective function taking the minimum annual power supply cost as a standard; and step S5, solving the cost optimization objective function and the reliability cost objective function by using the generalized Benders decomposition algorithm. By implementing the method, the power distribution network reliability verification, the power distribution network frame planning construction and the DG planning construction are cooperatively solved, and the mixed integer linear planning is used for carrying out the maximum power supply capability evaluation on the power distribution network.
Description
Technical Field
The invention belongs to the field of communication, and relates to a method, equipment and medium for planning the reliability of an active power distribution network.
Background
In recent years, Distributed power Generation (DG), namely Distributed Generation, is widely applied to the construction of power distribution networks, not only meets the power consumption requirement, but also provides clean energy for users.
However, a severe test is generated on the operation and planning of the traditional power distribution Network, and the active power distribution Network, namely the active distribution Network, referred to as ADN for short, can realize active control and active management of distributed energy in the power distribution Network and improve the power flow distribution. The ADN relies on high-reliability protection equipment, a high-efficiency power electronic controller, a bidirectional high-speed communication network, a flexible topological structure, a perfect intelligent measurement system and other infrastructure equipment to actively adjust and control various types of DER in the jurisdiction range of the ADN, so that the ADN actively participates in the system response process to realize the optimized operation of a power distribution network and even the whole power system.
The reasonable development of ADN planning can not only improve the power supply quality, but also save the investment, and also achieve the purpose of consuming large-scale intermittent renewable energy sources, and the reliability and the economy are two important indexes considering the ADN planning, but the two indexes are usually opposite.
In order to improve the reliability of the power distribution network, the contact relationship of the power grid is inevitably strengthened, and the construction cost is increased; on the other hand, controlling the construction investment of the power grid may affect the reliability and the power supply quality, so that considering the establishment of the balance relationship between the investment and the reliability is the key point of planning and research of the active power distribution network. The active power distribution network reliability planning comprises the contents of power grid network frame planning, substation planning, DG constant volume site selection, reactive compensation device configuration and the like, and factors involved in the planning simultaneously comprise continuous variables and integer variables, so that the active power distribution network reliability planning belongs to a complex mixed integer nonlinear programming (MINLP) problem, and an objective function and constraint conditions thereof are nonlinear, so that local optimization is easily formed in the solving process.
At present, the solution methods for the MINLP problem involved in the reliability planning of the active power distribution network can be classified into 2 types, namely a deterministic method and a stochastic method. The deterministic method mainly comprises a branch-and-bound method, an external approximation method, an extended cutting plane method and the like; the randomness method mainly comprises a simulated annealing algorithm, tabu search, an evolutionary algorithm and the like.
Summarizing the MINLP problem solving method related to the current active power distribution network reliability planning, for deterministic methods such as a branch-and-bound method, an external approximation method, an extended secant plane method and the like, the deterministic methods can only solve the global optimum for convex MINLP, but can hardly find the global optimum for non-convex MINLP, and the calculation time is increased sharply along with the increase of integer variables. In recent years, stochastic methods such as simulated annealing algorithm, tabu search, evolutionary algorithm, etc. which can process integer variables and continuous variables simultaneously are adopted, but these stochastic methods usually take much time and sometimes fall into local optimality.
Disclosure of Invention
The technical problem to be solved by the embodiment of the invention is to provide a method, equipment and a medium for planning the reliability of an active power distribution network, and solve the problems of large scale, nonlinearity, multiple constraints, easy formation of local optimum, low feasibility and high cost caused by multiple factors in the conventional planning method.
The invention provides a reliability planning method for an active power distribution network, which specifically comprises the following steps:
step S1, dividing the ADN reliability planning into a main item and a sub item, wherein the main item is the ADN planning cost optimization until the annual average comprehensive cost value reaches the minimum, and the sub item is the reliability verification under the power grid planning of the main item until the annual average lack power supply cost value reaches the minimum;
step S2, constructing a cost optimization objective function taking the minimum annual average comprehensive cost value as a standard;
s3, respectively carrying out relevant constraints on the radialization of the power distribution network, the construction of power distribution network equipment, the operation flow of the power distribution network, the capacity of a feeder line and the voltage amplitude to obtain constraint formulas of each item;
step S4, constructing a reliability cost objective function taking the minimum annual power supply cost as a standard;
and step S5, solving the cost optimization objective function and the reliability cost objective function by using the generalized Benders decomposition algorithm.
Further, in step S2, the cost optimization objective function is specifically the following formula:
minT＝Iv+Mv+Sv+Lv
wherein T represents the total cost of the investment; mvRepresenting equipment operation and maintenance cost; svIndicating the compensation cost of power failure; i isvRepresenting investment cost of the net rack construction and the DG construction; l isvRepresenting reliability costs of ADN planning; r represents a discount rate; n is a radical oftRepresenting the planning age of the power distribution network; n is a radical ofkRepresenting the number of returns of the planned construction line; n is a radical ofgRepresenting the number of nodes of the planned grid-connected DG; c. C1Representing a line construction fee; c. C2Representing a DG construction fee; c. C3Representing equipment operation and maintenance cost; c. C4Indicating the cost of the unit price for power failure compensation, i indicating the node number, αij，t、γij,t、δij,tRepresenting a 01 variable, αij，t1 means that the tth planned inter-year line ij is connected; gamma rayij,t1 means that DG is accessed at node i during the tth planned year; deltaij,t1 represents that the load of the node i is put into operation in the t planning year αij，t-1、γij,t-1The corresponding situation in t-1 year.
Further, in step S3, the radial constraint of the distribution network is specifically performed by the following formula, where the node where the substation is located is set as a root node, the grid planning is gradually extended from the root node,
wherein N isrFor number of nodes of substation, omegarIs a root node set when βij＝1，βjiWhen the value is 0, the node i is a parent node of the node j; when both are 0, it means that the ij nodes are not connected.
Further, in step S3, the equipment construction constraint of the power distribution network is specifically performed by the following formula,
wherein, αij，t、γij,t、δij,tRepresenting a 01 variable αij，tRepresenting the communication of the t-th planned inter-year line ij; gamma rayij,tRepresenting that a DG is accessed at a node i during the t planning year; deltaij,tIndicating that the node i load is put into operation in the t planning year.
Further, in step S3, the power flow constraint of the power distribution network is specifically performed by the following formula,
further, variables α are combinedij，t、γij,t、δij,tAnd obtaining a final power flow model:
wherein, ViIs the voltage amplitude of node i; vjIs the voltage amplitude of node j; pijAs a lineij active power flowing; qijReactive power circulating for line ij; rijIs the resistance of line ij; xijIs the reactance of line ij; pGi,tThe active power output of the ith DG in the t planning year; qGi,tThe reactive power output of the ith DG in the t planning year; pLi,tThe active load of the node i in the t planning year is obtained; qLi,tPlanning the reactive load of the node i in the year for the t;
representing the direction of the flow of the line flow of the t planning year flowing into the node i;
representing the direction of the flow of the line flow flowing out of the node i in the t planning year; pij,tActive power circulating for the t-th planned year line ij; qij,tThe reactive power for the t-th planned year line ij; m1Is a sufficiently large constant; vi,tThe voltage amplitude of the node i in the t planning year is obtained; vj,tThe voltage magnitude of node j in the t-th planned year.
Further, in step S3, the constructing the feeder capacity and voltage amplitude constraints is specifically performed by the following formula,
wherein, Vi,maxIs the upper limit of the voltage amplitude of the node i; vi,minIs the lower limit of the voltage amplitude of the node i; i isij,maxIs the upper limit of the current amplitude of the line ij; i isij,minThe lower current amplitude limit for line ij.
Further, in step S4, the reliability cost objective function is specifically the following formula:
the constraint is the following calculation:
wherein L isvThe annual power supply fee is lacking; c5Unit price of electricity for the amount of power supply lacking; n is a radical ofSFor the number of scenes, the corresponding S section branch is disconnected; sigmai,s,3、μij,s,tIs a 01 variable, σi,s,3Showing the cutting-off condition of the ith load node in the S scene of the 3 rd planning year when sigma isi,s,3When the value is 0, the load is removed; mu.sij,s,tRepresents the switching state of the circuit for forming island under the S-th scene when muij,s,t0, indicating line disconnection; lambda [ alpha ]sRepresenting the fault probability of the branch in the S section; pGi,s,tThe active output of the ith DG in the scene of S of the tth planning year; qGi,s,tThe reactive power output of the ith DG under the scene of the Tth planning year S; pLi,tThe active load of the node i in the t planning year is obtained; qLi,tPlanning the reactive load of the node i in the year for the t;
representing the direction of the flow of the line flow of the t planning year flowing into the node i;
representing the direction of the flow of the line flow flowing out of the node i in the t planning year; pij,s,tActive power flowing through the circuit ij under the scene of the t planning year S; qij,s,tThe reactive power of the circuit ij in the scenario of the t planning year S is provided; m1Is a sufficiently large constant; vi,s,tThe voltage amplitude of the node i under the scene of the Tth planning year S is obtained; vj,s,tAnd the voltage amplitude of the node j under the scenario of the t-th planned year S is obtained.
Further, in step S4, the specific process of solving by using the generalized Benders decomposition algorithm is as follows:
regarding the calculation of the main terms, under the framework of the generalized Benders decomposition algorithm, the cost optimization objective function is rewritten into the following compact form,
minT＝C(αij,t,γi,t,δi,t)+ω(n)
s.t.αij,t (n),γi,t (n),δi,t (n)∈f(αij,t,γi,t,δi,t)
ω(n)≥ω-
wherein, C (α)ij,t,γi,t,δi,t) Representing the construction cost, equipment maintenance cost and power failure compensation cost of the grid and DG, omega representing the optimization result of the subproblems, f (α)ij,t,γi,t,δi,t) Representing variables α determined by the constraints of the main questionij,t,γi,t,δi,tThe value range of (a); n is the number of iterations,
representing the function value of the subproblem after the nth iteration;
is the dual variable obtained from the nth iteration sub-problem,
respectively, the nth iteration yields a variable αij,s,t,γi,t,δi,tA value of (d); omega-Is the lower limit value of the omega initialization,
further, the sub-term is solved on the basis of the main term by the following formula,
minD(σi,s,t)
s.t.σi,s,t∈g(σi,s,t),
wherein g (σ)i,s,t) Is a constraint of the child item.
In another aspect, the present invention provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the following method when executing the computer program:
dividing the ADN reliability planning into a main item and a sub item, wherein the main item is ADN planning cost optimization until the annual average comprehensive cost value reaches the minimum, and the sub item is reliability verification under the power grid planning of the main item until the annual average lack power supply cost value reaches the minimum;
constructing a cost optimization objective function taking the minimum annual average comprehensive cost value as a standard;
respectively carrying out relevant constraints on the radiation of the power distribution network, the construction of power distribution network equipment, the operation flow of the power distribution network, the capacity of a feeder line and the voltage amplitude, and solving constraint formulas of all items;
constructing a reliability cost objective function taking the minimum annual power supply cost as a standard;
and solving the cost optimization objective function and the reliability cost objective function by utilizing the generalized Benders decomposition algorithm.
In another aspect, the present invention also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of:
dividing the ADN reliability planning into a main item and a sub item, wherein the main item is ADN planning cost optimization until the annual average comprehensive cost value reaches the minimum, and the sub item is reliability verification under the power grid planning of the main item until the annual average lack power supply cost value reaches the minimum;
constructing a cost optimization objective function taking the minimum annual average comprehensive cost value as a standard;
respectively carrying out relevant constraints on the radiation of the power distribution network, the construction of power distribution network equipment, the operation flow of the power distribution network, the capacity of a feeder line and the voltage amplitude, and solving constraint formulas of all items;
constructing a reliability cost objective function taking the minimum annual power supply cost as a standard;
and solving the cost optimization objective function and the reliability cost objective function by utilizing the generalized Benders decomposition algorithm.
The embodiment of the invention has the following beneficial effects:
the method, the device and the medium for planning the reliability of the active power distribution network, provided by the embodiment of the invention, realize the cooperative solution of the reliability verification of the power distribution network, the planning construction of the network frame of the power distribution network and the planning construction of the DG, thereby obtaining the optimal scheme of the reliability planning of the active power distribution network;
the new model solving method can better converge to the optimal planning scheme of the active power distribution network, and the solving speed is higher on the basis of ensuring the solving accuracy;
analysis simulation under multiple scenes is introduced, and influence of DG site selection planning, net rack planning and DG access positions on ADN planning is cooperatively considered, so that an overall optimal active power distribution network planning scheme is obtained;
on the basis of the maximum power supply capacity evaluation of the power distribution network, the fast reconstruction, the N-1 safety constraint and the power flow constraint of the power distribution network are considered, the idea of optimization solution is adopted, and the maximum power supply capacity evaluation is carried out on the power distribution network by using a mixed integer linear programming.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is within the scope of the present invention for those skilled in the art to obtain other drawings based on the drawings without inventive exercise.
Fig. 1 is a main flow diagram of a reliability planning method for an active power distribution network according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings.
As shown in fig. 1, a schematic diagram of an embodiment of the method for planning reliability of an active power distribution network provided by the present invention is shown, and in this embodiment, the method specifically includes the steps of:
step S1, dividing the ADN reliability planning into a main item and a sub item, wherein the main item is the ADN planning cost optimization until the annual average comprehensive cost value reaches the minimum, and the sub item is the reliability verification under the power grid planning of the main item until the annual average lack power supply cost value reaches the minimum;
in the specific embodiment, the ADN reliability planning is divided into a main problem and a sub-problem, the main problem is an ADN planning cost optimization problem, and the minimum annual average comprehensive cost is taken as a target, wherein the target comprises the construction cost of a distribution network rack and a distributed power supply, the operation and maintenance cost and the power failure compensation of a non-power supply load node; the sub-problem is the N-1 safety check carried out under the distribution network planning related to the main problem, and the minimum annual power supply cost is taken as a target.
Step S2, constructing a cost optimization objective function taking the minimum annual average comprehensive cost value as a standard;
in a specific embodiment, the cost optimization objective function is specifically the following formula:
minT＝Iv+Mv+Sv+Lv
wherein T represents the total cost of the investment; mvRepresenting equipment operation and maintenance cost; svIndicating the compensation cost of power failure;Ivrepresenting investment cost of the net rack construction and the DG construction; l isvRepresenting reliability costs of ADN planning; r represents the reduction rate, and is taken as 8%; n is a radical oftRepresenting the planning years of the power distribution network, and taking the planning years as 3 years; n is a radical ofkRepresenting the number of returns of the planned construction line; n is a radical ofgRepresenting the number of nodes of the planned grid-connected DG; c. C1Representing a line construction fee; c. C2Representing a DG construction fee; c. C3Representing equipment operation and maintenance cost; c. C4Indicating the cost of the unit price for power failure compensation, i indicating the node number, αij，t、γij,t、δij,tRepresenting a 01 variable, αij，t1 means that the tth planned inter-year line ij is connected; gamma rayij,t1 means that DG is accessed at node i during the tth planned year; deltaij,t1 represents that the load of the node i is put into operation in the t planning year αij，t＝1、γij,t-1The corresponding situation in t-1 year.
S3, respectively carrying out relevant constraints on the radialization of the power distribution network, the construction of power distribution network equipment, the operation flow of the power distribution network, the capacity of a feeder line and the voltage amplitude to obtain constraint formulas of each item;
in a specific embodiment, the radial constraint of the power distribution network is specifically performed by the following formula, a node where a transformer substation is located is set as a root node, the network frame planning is gradually extended from the root node,
wherein N isrFor number of nodes of substation, omegarIs a root node set when βij＝1，βjiWhen the value is 0, the node i is a parent node of the node j; when both are 0, it means that the ij nodes are not connected.
Specifically, the equipment construction constraint of the power distribution network is specifically performed by the following formula,
wherein, αij，t、γij,t、δij,tRepresenting a 01 variable αij，tRepresenting the communication of the t-th planned inter-year line ij; gamma rayij,tRepresenting that a DG is accessed at a node i during the t planning year; deltaij,tThe load of the node i is put into operation in the t planning year, and the investment construction of feeder lines, DGs and other equipment is irreversible.
More specifically, the power flow constraint of the power distribution network is specifically carried out by the following formula, and V is setiIs the voltage amplitude of node i; vjIs the voltage amplitude of node j; pijActive power circulating for line ij; qijReactive power circulating for line ij; rijIs the resistance of line ij; xijFor the reactance of line ij, and to provide convergence of the algorithm, the simplification is as follows:
further, variables α are combinedij，t、γij,t、δij,tAnd obtaining a final power flow model:
wherein, PGi,tThe active power output of the ith DG in the t planning year; qGi,tThe reactive power output of the ith DG in the t planning year; pLi,tThe active load of the node i in the t planning year is obtained; qLi,tPlanning the reactive load of the node i in the year for the t;
representing the direction of the flow of the line flow of the t planning year flowing into the node i;
representing the direction of the flow of the line flow flowing out of the node i in the t planning year; pij,tActive power circulating for the t-th planned year line ij; qij,tThe reactive power for the t-th planned year line ij; m1Is a sufficiently large constant; vi,tIs as followsVoltage amplitude of node i in t planning years; vj,tThe voltage magnitude of node j in the t-th planned year.
More specifically, the construction of the feeder capacity and voltage amplitude constraints is specifically performed by the following formula,
wherein, Vi,maxIs the upper limit of the voltage amplitude of the node i; vi,minIs the lower limit of the voltage amplitude of the node i; i isij,maxIs the upper limit of the current amplitude of the line ij; i isij,minThe lower current amplitude limit for line ij.
Step S4, constructing a reliability cost objective function taking the minimum annual power supply cost as a standard;
in the specific embodiment, after the active power distribution network planning scheme is obtained, N-1 safety verification is carried out to verify the reliability of the planning scheme. The sub-problem is reliability cost, and the minimum power shortage amount is taken as a target, and the reliability cost target function is specifically the following formula:
the constraint is the following calculation:
wherein L isvThe annual power supply fee is lacking; c5Unit price of electricity for the amount of power supply lacking; n is a radical ofSFor the number of scenes, the corresponding S section branch is disconnected; sigmai,s,3、μij,s,tIs a 01 variable, σi,s,3Showing the cutting-off condition of the ith load node in the S scene of the 3 rd planning year when sigma isi,s,3When the value is 0, the load is removed; mu.sij,s,tIndicating the offline of the Sth sceneSwitching state of road island formation when muij,s,t0, indicating line disconnection; lambda [ alpha ]sRepresenting the fault probability of the branch in the S section; pGi,s,tThe active output of the ith DG in the scene of S of the tth planning year; qGi,s,tThe reactive power output of the ith DG under the scene of the Tth planning year S; pLi,tThe active load of the node i in the t planning year is obtained; qLi,tPlanning the reactive load of the node i in the year for the t;
representing the direction of the flow of the line flow of the t planning year flowing into the node i;
representing the direction of the flow of the line flow flowing out of the node i in the t planning year; pij,s,tActive power flowing through the circuit ij under the scene of the t planning year S; qij,s,tThe reactive power of the circuit ij in the scenario of the t planning year S is provided; m1Is a sufficiently large constant; vi,s,tThe voltage amplitude of the node i under the scene of the Tth planning year S is obtained; vj,s,tAnd the voltage amplitude of the node j under the scenario of the t-th planned year S is obtained.
Step S5, solving the cost optimization objective function and the reliability expense objective function by using the generalized Benders decomposition algorithm,
in a specific embodiment, the specific process of solving by using the generalized Benders decomposition algorithm is as follows:
regarding the calculation of the main terms, under the framework of the generalized Benders decomposition algorithm, the cost optimization objective function is rewritten into the following compact form,
minT＝C(αij,t,γi,t,δi,t)+ω(n)
s.t.αij,t (n),γi,t (n),δi,t (n)∈f(αij,t,γi,t,δi,t)
ω(n)≥ω-
wherein, C (α)ij,t,γi,t,δi,t) Including the construction cost, the equipment maintenance cost and the power failure compensation cost of the grid frame and the DG, omega represents the optimization result of the subproblem and is a continuous variable, f (α)ij,t,γi,t,δi,t) Representing variables α determined by the constraints of the main questionij,t,γi,t,δi,tThe value range of (a); n represents the number of iterations and,
representing the function value of the subproblem after the nth iteration;
is the dual variable obtained from the nth iteration sub-problem,
respectively, the nth iteration yields a variable αij,s,t,γi,t,δi,tA value of (d); omega-Is the lower limit of ω initialization; omega(n)≥ω-The set of cuts for the Benders is,
further, the sub-term is to solve the minimum cost of annual power supply shortage on the basis of the main term through the following formula,
minD(σi,s,t)
s.t.σi,s,t∈g(σi,s,t),
wherein g (σ)i,s,t) Is a constraint of a sub-term, and σ is determined from the above constrainti,s,tThe value range of (a).
In another aspect, the present invention provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the following method when executing the computer program:
dividing the ADN reliability planning into a main item and a sub item, wherein the main item is ADN planning cost optimization until the annual average comprehensive cost value reaches the minimum, and the sub item is reliability verification under the power grid planning of the main item until the annual average lack power supply cost value reaches the minimum;
constructing a cost optimization objective function taking the minimum annual average comprehensive cost value as a standard;
respectively carrying out relevant constraints on the radiation of the power distribution network, the construction of power distribution network equipment, the operation flow of the power distribution network, the capacity of a feeder line and the voltage amplitude, and solving constraint formulas of all items;
constructing a reliability cost objective function taking the minimum annual power supply cost as a standard;
and solving the cost optimization objective function and the reliability cost objective function by utilizing the generalized Benders decomposition algorithm.
In another aspect, the present invention also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of:
dividing the ADN reliability planning into a main item and a sub item, wherein the main item is ADN planning cost optimization until the annual average comprehensive cost value reaches the minimum, and the sub item is reliability verification under the power grid planning of the main item until the annual average lack power supply cost value reaches the minimum;
constructing a cost optimization objective function taking the minimum annual average comprehensive cost value as a standard;
respectively carrying out relevant constraints on the radiation of the power distribution network, the construction of power distribution network equipment, the operation flow of the power distribution network, the capacity of a feeder line and the voltage amplitude, and solving constraint formulas of all items;
constructing a reliability cost objective function taking the minimum annual power supply cost as a standard;
and solving the cost optimization objective function and the reliability cost objective function by utilizing the generalized Benders decomposition algorithm.
For further details, reference may be made to the preceding description of the drawings, which are not described in detail herein.
The embodiment of the invention has the following beneficial effects:
the embodiment of the invention provides a method, equipment and medium for planning the reliability of an active power distribution network,
the power distribution network reliability verification, the power distribution network frame planning construction and the DG planning construction are cooperatively solved, so that an optimal scheme of the active power distribution network reliability planning is obtained;
the new model solving method can better converge to the optimal planning scheme of the active power distribution network, and the solving speed is higher on the basis of ensuring the solving accuracy;
analysis simulation under multiple scenes is introduced, and influence of DG site selection planning, net rack planning and DG access positions on ADN planning is cooperatively considered, so that an overall optimal active power distribution network planning scheme is obtained;
on the basis of the maximum power supply capacity evaluation of the power distribution network, the fast reconstruction, the N-1 safety constraint and the power flow constraint of the power distribution network are considered, the idea of optimization solution is adopted, and the maximum power supply capacity evaluation is carried out on the power distribution network by using a mixed integer linear programming.
While the invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not to be limited to the disclosed embodiment, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.
Claims (10)
1. A reliability planning method for an active power distribution network is characterized by comprising the following steps:
step S1, dividing the ADN reliability planning into a main item and a sub item, wherein the main item is the ADN planning cost optimization until the annual average comprehensive cost value reaches the minimum, and the sub item is the reliability verification under the power grid planning of the main item until the annual average lack power supply cost value reaches the minimum;
step S2, constructing a cost optimization objective function taking the minimum annual average comprehensive cost value as a standard;
s3, respectively carrying out relevant constraints on the radialization of the power distribution network, the construction of power distribution network equipment, the operation flow of the power distribution network, the capacity of a feeder line and the voltage amplitude to obtain constraint formulas of each item;
step S4, constructing a reliability cost objective function taking the minimum annual power supply cost as a standard;
and step S5, solving the cost optimization objective function and the reliability cost objective function by using the generalized Benders decomposition algorithm.
2. The method according to claim 1, wherein in step S2, the cost optimization objective function is embodied by the following formula:
minT＝Iv+Mv+Sv+Lv
wherein T represents the total cost of the investment; mvRepresenting equipment operation and maintenance cost; svIndicating the compensation cost of power failure; i isvRepresenting investment cost of the net rack construction and the DG construction; l isvRepresenting reliability costs of ADN planning; r represents a discount rate; n is a radical oftRepresenting the planning age of the power distribution network; n is a radical ofkRepresenting the number of returns of the planned construction line; n is a radical ofgRepresenting the number of nodes of the planned grid-connected DG; c. C1Representing a line construction fee; c. C2Representing a DG construction fee; c. C3Representing equipment operation and maintenance cost; c. C4Indicating the cost of the unit price for power failure compensation, i indicating the node number, αij，t、γij，t、δij，tRepresenting a 01 variable, αij，t1 means that the tth planned inter-year line ij is connected; gamma rayij，t1 means that DG is accessed at node i during the tth planned year; deltaij，t1 represents that the load of the node i is put into operation in the t planning year αij，t-1、γij，t-1The corresponding situation in t-1 year.
3. The method of claim 2, wherein in step S3, the radial constraint of the distribution network is performed by setting the node where the substation is located as a root node, and the grid planning is extended gradually from the root node,
wherein N isrFor number of nodes of substation, omegarIs a root node set when βij＝1，βjiWhen the value is 0, the node i is a parent node of the node j; when both are 0, it means that the ij nodes are not connected.
4. The method of claim 3, wherein in step S3, the equipment construction constraints of the power distribution network are specifically formulated by the following formula,
wherein, αij，t、γij，t、δij，tRepresenting a 01 variable αij，tRepresenting the communication of the t-th planned inter-year line ij; gamma rayij，tRepresenting that a DG is accessed at a node i during the t planning year; deltaij，tIndicating that the node i load is put into operation in the t planning year.
5. The method according to claim 4, wherein in step S3, the power flow constraint of the distribution network is performed by the following formula,
further, variables α are combinedij，t、γij，t、δij，tAnd obtaining a final power flow model:
wherein, ViIs the voltage amplitude of node i; vjIs the voltage amplitude of node j; pijActive power circulating for line ij; qijReactive power circulating for line ij; rijIs the resistance of line ij; xijIs the reactance of line ij; pGi，tThe active power output of the ith DG in the t planning year; qGi，tThe reactive power output of the ith DG in the t planning year; pLi，tThe active load of the node i in the t planning year is obtained; qLi，tPlanning the reactive load of the node i in the year for the t;
representing the direction of the flow of the line flow of the t planning year flowing into the node i;
representing the direction of the flow of the line flow flowing out of the node i in the t planning year; pij，tActive power circulating for the t-th planned year line ij; qij，tThe reactive power for the t-th planned year line ij; m1Is a sufficiently large constant; vi，tThe voltage amplitude of the node i in the t planning year is obtained; vj，tThe voltage magnitude of node j in the t-th planned year.
6. The method of claim 5, wherein in step S3, the constructing feeder line capacity and voltage magnitude constraints is performed by the following equations,
wherein, Vi，maxIs the upper limit of the amplitude of the voltage at node i；Vi，minIs the lower limit of the voltage amplitude of the node i; i isij，maxIs the upper limit of the current amplitude of the line ij; i isij，minThe lower current amplitude limit for line ij.
7. The method according to claim 6, wherein in step S4, the reliability cost objective function is specified by the following formula:
the constraint is the following calculation:
wherein L isvThe annual power supply fee is lacking; c5Unit price of electricity for the amount of power supply lacking; n is a radical ofSFor the number of scenes, the corresponding S section branch is disconnected; sigmai，s，3、μij，s，tIs a 01 variable, σi，s，3Showing the cutting-off condition of the ith load node in the S scene of the 3 rd planning year when sigma isi，s，3When the value is 0, the load is removed; mu.sij，s，tRepresents the switching state of the circuit for forming island under the S-th scene when muij，s，t0, indicating line disconnection; lambda [ alpha ]sRepresenting the fault probability of the branch in the S section; pGi，s，tThe active output of the ith DG in the scene of S of the tth planning year; qGi，s，tThe reactive power output of the ith DG under the scene of the Tth planning year S; pLi，tThe active load of the node i in the t planning year is obtained; qLi，tPlanning the reactive load of the node i in the year for the t;
representing the flow inflow of the line current of the t planning yearThe direction of node i;
representing the direction of the flow of the line flow flowing out of the node i in the t planning year; pij，s，tActive power flowing through the circuit ij under the scene of the t planning year S; qij，s，tThe reactive power of the circuit ij in the scenario of the t planning year S is provided; m1Is a sufficiently large constant; vi，s，tThe voltage amplitude of the node i under the scene of the Tth planning year S is obtained; vj，s，tAnd the voltage amplitude of the node j under the scenario of the t-th planned year S is obtained.
8. The method as claimed in claim 7, wherein in step S5, the specific process of solving using the generalized Benders decomposition algorithm is as follows:
under the framework of the generalized Benders decomposition algorithm, the cost optimization objective function is rewritten into the following compact form,
minT＝C(αij，t，γi，t，δi，t)+ω(n)
s.t.αij，t (n)，γi，t (n)，δi，t (n)∈f(αij，t，γi，t，δi，t)
ω(n)≥ω-
wherein, C (α)ij，t，γi，t，δi，t) Representing construction cost, equipment maintenance cost and power failure compensation cost of the grid and the DG, omega representing the optimization result of the sub-items, f (α)ij，t，γi，t，δi，t) Representing variables α determined by the constraints of the primary termij，t，γi，t，δi，tThe value range of (a); n represents the number of iterations and,
representing the function value of the subproblem after the nth iteration;
is the dual variable obtained from the nth iteration sub-problem,
respectively, the nth iteration yields a variable αij，s，t，γi，t，δi，tA value of (d); omega-Is the lower limit value of the omega initialization,
further, the sub-term is solved on the basis of the main term by the following formula,
minD(σi，s，t)
s.t.σi，s，t∈g(σi，s，t)，
wherein g (σ)i，s，t) Is a constraint of the child item.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 8 are implemented when the computer program is executed by the processor.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 8.
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