CN113013869B - Active power distribution network four-terminal soft switch planning method based on reliability evaluation - Google Patents
Active power distribution network four-terminal soft switch planning method based on reliability evaluation Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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- H—ELECTRICITY
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- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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Abstract
A method for planning four-end soft switches of an active power distribution network based on reliability evaluation is characterized in that a four-end soft switch location and volume planning model of the active power distribution network is established by taking the minimum annual comprehensive cost of the power distribution network as a first objective function and taking access capacity constraint as a constraint condition; the method comprises the steps of establishing an active power distribution network four-end soft switch site selection constant volume normal operation optimization model by taking the minimum power distribution network normal operation total loss as a second objective function and taking power flow constraint, node voltage constraint, line current-carrying capacity constraint and four-end soft switch operation constraint as constraint conditions, solving to obtain the power distribution network normal operation loss, and evaluating the reliability of the active power distribution network containing the four-end soft switch through a reliability evaluation algorithm to obtain the annual average power failure time of each load point of each scene and the annual average transfer power of the four-end soft switch. And substituting the obtained data into the first objective function, solving by utilizing a particle swarm algorithm to obtain an optimal solution, and taking the optimal solution as a site selection and volume fixing scheme of the four-terminal soft switch, thereby greatly improving the system reliability of the power distribution network.
Description
Technical Field
The invention relates to the technical field of site selection and volume fixing planning of four-end soft switches, in particular to a method for planning four-end soft switches of an active power distribution network based on reliability evaluation.
Background
The power distribution network in China generally adopts a power supply mode of ring network design and open-loop operation, when a fault occurs in the power supply process, the problem of continuous power supply of important users cannot be effectively and timely solved, and the reliability of the power distribution network system is greatly reduced. In the actual operation process of the power distribution network, a plurality of factors can cause the occurrence of short-time power supply interruption phenomenon, the influence is generated on the power supply reliability, and the main factors comprise the faults of power distribution equipment and a power distribution line, lower automation level of the equipment, low automation degree of accident processing, long time consumption, slow power supply recovery and the like. The soft switch can change the radial running mode of the existing power distribution network, realizes the flexible closed-loop running of the power distribution network, and hopefully solves the problems of prominent short-time power supply interruption, limited reliability improvement and the like.
A power supply reliability improving method of a power distribution network based on an intelligent soft switch is provided in Chinese patent with publication number 109698500A of 30 days in 4 months and 4 months in 2019, reliability parameters of each load node of the power distribution network containing the intelligent soft switch are analyzed and calculated to obtain reliability indexes of the whole power distribution system, but the method only verifies the reliability improving effect of the power distribution network system of the soft switch, does not consider the effect of the position and capacity of the soft switch connected to the power distribution network system on improving the reliability of the power distribution network, and is limited in reliability improvement.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, provides an active power distribution network four-end soft switch planning method based on reliability evaluation, and solves the problem that the reliability of a power distribution network is improved to a limited extent.
The purpose of the invention is realized by the following technical scheme:
a method for planning four-end soft switches of an active power distribution network based on reliability evaluation comprises the following steps:
the method comprises the following steps: establishing an active power distribution network four-end soft switch location and volume planning model by taking the minimum annual comprehensive cost of the power distribution network as a first objective function and taking access capacity constraint as a constraint condition;
step two: establishing an active power distribution network four-end soft switch location constant volume normal operation optimization model by taking the minimum power distribution network normal operation total loss as a second objective function and taking power flow constraint, node voltage constraint, line current-carrying capacity constraint and four-end soft switch operation constraint as constraint conditions;
step three: evaluating the reliability of the active power distribution network with the four-terminal soft switch through a reliability evaluation algorithm to obtain the annual average power failure time of each load point of each scene and the annual average transfer power of the four-terminal soft switch;
step four: solving a site selection constant-volume normal optimization model of four-end soft switches of the active power distribution network to obtain normal operation loss of the power distribution network;
step five: and substituting the annual average power failure time, the annual average transfer power of the four-terminal soft switch and the normal running loss of the power distribution network of each load point of each scene into a first objective function, solving an active power distribution network four-terminal soft switch constant-volume location planning model by adopting a particle swarm algorithm, and taking the optimal solution obtained by the solution as the installation position and the capacity of the four-terminal soft switch.
Reliability index data of the active power distribution network are obtained through a reliability evaluation algorithm, and the installation position and the capacity of the four-end soft switch are calculated through the obtained reliability index data so as to improve the reliability of the active power distribution network system to the maximum.
Further, the reliability evaluation algorithm in the third step is a quasi-sequential monte carlo simulation method.
Further, the reliability evaluation of the quasi-sequential monte carlo simulation method on the active power distribution network with the four-terminal soft switch comprises the following steps:
3.1: setting the output and load conditions of the distributed power supply in each scene;
3.2: setting the simulation years and all elements at the simulation initial moment to work in a normal state;
3.3: setting a total of X in an active power distribution networkmAn element for randomly generating XmRandom number between 0 and 1, and determining X according to the failure transfer rate and the exponential distributionmFault-free operating time T of individual elementsTTF；
3.4: finding the minimum fault-free operating time TTTFminSaid minimum fault-free running time TTTFminThe corresponding element is a fault element, a random number is generated for the fault element, and the fault repairing time T of the fault element is determined according to the repairing transfer rateTTRAccording to the minimum fault-free running time TTTFminAnd time to failover TTTRDetermining fault isolation and load transfer time, and advancing analog clock to TTTFmin+TTTR；
3.5: determining the power failure time of each load point fault in each subarea in the network, and if the load is supplied by the four-terminal soft switch in each subarea, calculating the power failure time of each load point and the supply power of the four-terminal soft switch in the island period according to the load reduction condition; otherwise, determining the power failure time of each partition load point in the network by combining a feeder partition method, wherein the load reduction conditional expression is as follows:
in the formula: psop(t) the four-terminal soft switch port connected with the fault feeder line at the moment t can supply power; pl,linerem(t) the remaining capacity of the first feeder line connected by the four-terminal soft switch except the fault feeder line; pDG(t) is the total distributed power supply output in the island at the moment t; n is a radical ofLThe total number of the downstream island load points of the fault area is; l isa(t) the load at the a-th load point at time t; epsilona(t) is the reduction state of the a-th load point at time t;
3.6: setting a new operating time T for a defective componentTTFnewUpdating the fault-free running time of the active power distribution network to TTTFmin+TTTR+TTTFnew；
3.7: judging whether the set simulation years are reached or not, if the set simulation years are reached, counting the power failure time of the load point of each simulation year and the conversion power of the four-terminal soft switch, and further calculating the annual average power failure time of each load point of each scene and the annual average conversion power of the four-terminal soft switch; if not, returning to execute the step 3.3;
3.8: judging whether the reliability evaluation of all scenes is finished or not, and if the reliability evaluation is not finished, returning to execute the step 3.2; otherwise, the simulation process ends.
The reliability of the system is evaluated by a Monte Carlo simulation method, and the required annual average power failure time and the annual average transfer power of the four-terminal soft switch are obtained and are used as reliability indexes to be applied to the solving process of the locating and sizing scheme of the four-terminal soft switch. And the Monte Carlo simulation method can directly solve the problem with statistical property, does not need discretization treatment on the continuity problem, simplifies the calculation process and improves the calculation efficiency.
Further, in the second step, the second objective function expression is as follows:
in the formula: ploss,kNormal operation loss of the power distribution network is set for the kth scene; n is a radical ofnThe number of nodes of the power distribution network is; n is a radical ofsopThe number of the four-end soft switches is the access number; pp,kInjecting active power for the node p in the kth scene; beta is asopThe loss coefficient of the four-terminal soft switch; pi,sop,kIs the transmission power of the ith soft switch in the kth scene.
Further, in the constraint condition in the second step, the power flow constraint expression is as follows:
in the formula: pp、QpActive power and reactive power injected into the node p respectively; u shapepIs the voltage amplitude of node p; gpq、BpqRespectively a real part and an imaginary part of the node admittance matrix; thetapqIs the phase angle difference between the nodes p and q; i ispqIs the current of branch pq; q ∈ p denotes a node set connected to the node p;
in the second step, the node voltage constraint expression in the constraint condition is as follows:
Up,min<Up<Up,max
in the formula: u shapep,minIs the lower limit of the voltage amplitude of the node p; u shapep,maxIs the upper voltage amplitude limit of node p;
in the second step, the line current-carrying constraint condition expression in the constraint condition is as follows:
Im<Im,max
in the formula: i ismThe current amplitude of the mth line; i ism,maxThe current amplitude upper limit of the mth line;
in the second step, the four-terminal soft switch operation constraint expression in the constraint condition is as follows:
Pd,soploss＝βsop·|Pd,sop|
in the formula: pd,sopAnd a group of Q's, each of which,dsopactive power and reactive power flowing into the d-th port of the four-terminal soft switch respectively; sd,sopThe rated capacity of the d-th port of the four-end soft switch is obtained; pd,soplossThe transmission loss of the d-th port of the four-terminal soft switch; beta is asopThe loss factor of the four-terminal soft switch.
Under the condition that the voltage amplitude and the current amplitude of a node in the power distribution network are normal, electric energy loss caused by the operation of the four-terminal soft switch is calculated, the loss is considered in the selection of the site selection and volume fixing scheme of the four-terminal soft switch, and the site selection and volume fixing scheme of the four-terminal soft switch is further optimized.
Further, the solution of the four-end soft switch site selection constant volume normal optimization model of the active power distribution network in the fourth step is obtained through a second-order cone programming algorithm.
Further, the solving steps of the second-order cone planning algorithm on the active power distribution network four-end soft switch location constant volume normal optimization model are as follows:
4.1: converting the nonlinear power flow constraint into the linear power flow constraint through variable substitution, wherein the substitution expression is as follows:
in the formula: xp、Xq、Ypq、ZpqRespectively, are alternative variables; u shapepIs the voltage amplitude of node p; thetapqIs the phase angle difference between the nodes p and q; i ispqIs the current of branch pq;
the linear power flow constraint expression obtained by conversion after variable replacement is as follows:
in the formula: pp、QpActive power and reactive power injected into the node p respectively; gpq、BpqRespectively a real part and an imaginary part of the node admittance matrix; thetapqIs the phase angle difference between the nodes p and q; i ispqIs the current of branch pq; q ∈ p denotes a node set connected with the node p; xp、Xq、Ypq、ZpqRespectively, are alternative variables;
4.2: a rotating cone constraint condition is introduced in the conversion process, so that the annual loss calculation model of the power distribution network is in the constraint range of the pointed convex cone, and meanwhile, the solving result of the annual loss calculation model of the power distribution network cannot be influenced, and the rotating cone constraint condition expression is as follows:
in the formula, Xp、Xq、Ypq、ZpqAre respectively asA variable for replacement;
4.3: converting four-terminal soft switch nonlinear operation constraint in a power distribution network annual loss calculation model into a second-order cone constraint condition, wherein the second-order cone constraint condition expression is as follows:
in the formula: pd,sopAnd Qd,dsopRespectively the active power and the reactive power S flowing into the d-th port of the four-end soft switchd,sopThe rated capacity of the d-th port of the four-terminal SOP.
4.4: and solving the converted active power distribution network four-end soft switch site selection constant volume normal operation optimization model by adopting optimization software.
The second-order cone programming is a very special nonlinear optimization, is a very efficient solving algorithm, further improves the solving speed, and reduces the solving time.
Further, the particle swarm algorithm in the fifth step is used for encoding and solving in a real number encoding mode, and the encoding of the installation position and the capacity of the four-terminal soft switch is as follows:
X＝[c1,c2,...,cs]
in the formula: x is a matrix with a row and s columns and represents a site selection and volume fixing scheme of the four-end soft switch, the column number of the matrix represents the sequence number of the installation position of the four-end soft switch, and the matrix element represents the installation capacity of the four-end soft switch; and s is the number of four-end soft switches installed in the power distribution network.
When real number coding is adopted, the variable number of the problem solution is directly used as the dimension of the particle, and the solving efficiency is improved.
Further, in the first step, the first objective function expression is:
in the formula: f is the annual comprehensive cost of the power distribution network; cinvIs a four-end soft switchThe equal annual cost of the construction investment cost is concerned, and d is the discount rate; y is the full life cycle of the four-terminal soft switch; n is a radical ofsopThe number of the four-end soft switches is the number of the four-end soft switches; c. CsopInvestment cost per unit capacity for soft switching; si,sopThe installation capacity of the ith soft switch; cmainThe annual operation and maintenance cost of the soft switch is mu, and the mu is the annual operation and maintenance cost coefficient of the soft switch; cnormalFor the normal running cost of the distribution network, NsObtaining the number of the operation scenes of the power distribution network for clustering; p is a radical ofkProbability of the kth scene; c. C0Is the electricity price; ploss,kNormal operation loss of the power distribution network is set for the kth scene; cfaultReliability cost, P, calculated for reliability assessment of the distribution networksoptransThe annual average transfer loss of the soft switch obtained for reliability evaluation; n is a radical oflThe number of load points; poutage,jThe annual average outage at load point j.
Further, in the step one, the access capacity constraint condition expression is as follows:
Si,sop＝mi·sunit
Si,sop≤Si,sopmax
in the formula: si,sopThe mounting capacity of the ith four-terminal soft switch; m isiIs a positive integer; sunitThe unit installation capacity of the four-end soft switch; si,sopmaxThe maximum installation capacity of the ith four-terminal soft switch.
When the four-terminal soft switch location and volume scheme is selected, the access position and the volume of the four-terminal soft switch are considered, and the economic cost generated in the operation process is also considered comprehensively, so that the economical efficiency of the four-terminal soft switch location and volume scheme is improved.
The invention has the beneficial effects that:
the invention provides an active power distribution network four-end soft switch planning method based on reliability evaluation, wherein a four-end soft switch is selected for system reconstruction, and compared with a common intelligent soft switch four-end soft switch, the active power distribution network four-end soft switch is suitable for reconstructing various complex wiring including a double-loop network, 4-1 main and standby wiring and the like, the expansibility is higher, the power supply requirement under more complex wiring can be met, the multi-feeder flexible interconnection and the power flow regulation and control are realized, and the reliability of a power distribution network is improved more remarkably. In order to further improve the reliability of the system, the optimal scheme is further selected by further screening the locating and sizing scheme of the four-terminal soft switch so as to carry out system reconstruction. According to the method, a sequential Monte Carlo simulation method is utilized to evaluate the reliability of the system, the obtained annual average power failure time and annual average power transfer of the four-terminal soft switches of each load point of each scene are used as reliability index data to be substituted into an active power distribution network four-terminal soft switch location constant volume planning model which takes the minimum power distribution network annual comprehensive cost as a first objective function and takes access capacity constraint as constraint conditions, an optimal solution is obtained through solving by a particle swarm algorithm, and the obtained optimal solution is the optimal scheme of the four-terminal soft switch location constant volume. The invention screens out the optimal site selection and volume fixing scheme of the four-end soft switch so as to ensure the economic and safe operation of the system and simultaneously improve the reliability of the system.
Drawings
FIG. 1 is a flow chart of a reliability-based active power distribution network four-terminal soft switch planning method of the present invention;
fig. 2 is a flowchart of reliability evaluation of an active power distribution network including a four-terminal soft switch by using a quasi-sequential monte carlo simulation method according to an embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the figures and examples.
Example (b):
as shown in fig. 1, the present invention provides a reliability-based active power distribution network four-terminal soft switch planning method, which includes the following steps:
the method comprises the following steps: and establishing an active power distribution network four-end soft switch location and volume planning model by taking the minimum annual comprehensive cost of the power distribution network as a first objective function and taking access capacity constraint as a constraint condition.
The first objective function expression is:
in the formula: f is the annual comprehensive cost of the power distribution network; cinvEqual annual cost of investment cost for four-terminal soft switch construction, and d is the discount rate; y is the full life cycle of the four-terminal soft switch; n is a radical ofsopThe number of the four-end soft switches is the number of the four-end soft switches; c. CsopInvestment cost per unit capacity for soft switching; si,sopThe installation capacity of the ith soft switch; cmainThe annual operation and maintenance cost of the soft switch is mu, and the mu is the annual operation and maintenance cost coefficient of the soft switch; cnormalFor the normal running cost of the distribution network, NsObtaining the number of the operation scenes of the power distribution network for clustering; p is a radical ofkProbability of the kth scene; c. C0Is the electricity price; ploss,kNormal operation loss of the power distribution network is set for the kth scene; cfaultReliability cost, P, calculated for reliability assessment of the distribution networksoptransThe annual average transfer loss of the soft switch obtained for reliability evaluation; n is a radical oflThe number of load points; poutage,jThe annual average outage at load point j.
The access capacity constraint conditional expression is as follows:
Si,sop＝mi·sunit
Si,sop≤Si,sopmax
in the formula: si,sopThe mounting capacity of the ith four-terminal soft switch; m isiIs a positive integer; sunitThe unit installation capacity of the four-end soft switch; si,sopmaxThe maximum installation capacity of the ith four-terminal soft switch.
Step two: and establishing an active power distribution network four-end soft switch location constant volume normal operation optimization model by taking the minimum power distribution network normal operation total loss as a second objective function and taking power flow constraint, node voltage constraint, line current-carrying capacity constraint and four-end soft switch operation constraint as constraint conditions.
The second objective function expression is as follows:
in the formula: ploss,kNormal operation loss of the power distribution network is set for the kth scene; n is a radical ofnThe number of nodes of the power distribution network is; n is a radical ofsopThe number of the four-end soft switches is the access number; pp,kInjecting active power for the node p in the kth scene; beta is asopThe loss coefficient of the four-terminal soft switch; pi,sop,kIs the transmission power of the ith soft switch in the kth scene.
The power flow constraint expression is as follows:
in the formula: pp、QpActive power and reactive power injected into the node p respectively; u shapepIs the voltage amplitude of node p; gpq、BpqRespectively a real part and an imaginary part of the node admittance matrix; thetapqIs the phase angle difference between the nodes p and q; i ispqIs the current of branch pq; q ∈ p denotes a node set connected to the node p;
the node voltage constraint expression is as follows:
Up,min<Up<Up,max
in the formula: u shapep,minIs the lower limit of the voltage amplitude of the node p; u shapep,maxIs the upper voltage amplitude limit of node p;
the line current-carrying constraint conditional expression is as follows:
Im<Im,max
in the formula: i ismThe current amplitude of the mth line; i ism,maxThe current amplitude upper limit of the mth line;
the four-terminal soft switch operation constraint expression is as follows:
Pd,soploss＝βsop·|Pd,sop|
in the formula: pd,sopAnd a group of Q's, each of which,dsopactive power and reactive power flowing into the d-th port of the four-terminal soft switch respectively; sd,sopThe rated capacity of the d-th port of the four-end soft switch is obtained; pd,soplossThe transmission loss of the d-th port of the four-terminal soft switch; beta is asopThe loss factor of the four-terminal soft switch.
Step three: and evaluating the reliability of the active power distribution network with the four-terminal soft switch through a reliability evaluation algorithm to obtain the annual average power failure time of each load point of each scene and the annual average transfer power of the four-terminal soft switch.
As shown in fig. 2, the reliability evaluation algorithm adopts a quasi-sequential monte carlo simulation method, and the reliability evaluation of the active power distribution network including the four-terminal soft switch includes the following steps:
3.1: setting the output and load conditions of the distributed power supply in each scene;
3.2: setting the simulation years and all elements at the simulation initial moment to work in a normal state;
3.3: setting a total of X in an active power distribution networkmAn element for randomly generating XmRandom number between 0 and 1, and determining X according to the failure transfer rate and the exponential distributionmFault-free operating time T of individual elementsTTF；
3.4: finding the minimum fault-free operating time TTTFminSaid minimum fault-free running time TTTFminThe corresponding element is a fault element, a random number is generated for the fault element, and the fault repairing time T of the fault element is determined according to the repairing transfer rateTTRAccording to the minimum fault-free running time TTTFminAnd time to failover TTTRDetermining fault isolation and load transfer time, and advancing analog clock to TTTFmin+TTTR；
3.5: determining the power failure time of each load point fault in each subarea in the network, and if the load is supplied by the four-terminal soft switch in each subarea, calculating the power failure time of each load point and the supply power of the four-terminal soft switch in the island period according to the load reduction condition; otherwise, determining the power failure time of each partition load point in the network by combining a feeder partition method, wherein the load reduction conditional expression is as follows:
in the formula: psop(t) the four-terminal soft switch port connected with the fault feeder line at the moment t can supply power; pl,linerem(t) the remaining capacity of the first feeder line connected by the four-terminal soft switch except the fault feeder line; pDG(t) is the total distributed power supply output in the island at the moment t; n is a radical ofLThe total number of the downstream island load points of the fault area is; l isa(t) the load at the a-th load point at time t; epsilona(t) is the reduction state of the a-th load point at time t;
3.6: setting a new operating time T for a defective componentTTFnewUpdating the fault-free running time of the active power distribution network to TTTFmin+TTTR+TTTFnew；
3.7: judging whether the set simulation years are reached or not, if the set simulation years are reached, counting the power failure time of the load point of each simulation year and the conversion power of the four-terminal soft switch, and further calculating the annual average power failure time of each load point of each scene and the annual average conversion power of the four-terminal soft switch; if not, returning to execute the step 3.3;
3.8: judging whether the reliability evaluation of all scenes is finished or not, and if the reliability evaluation is not finished, returning to execute the step 3.2; otherwise, the simulation process ends.
Step four: and solving a site selection constant volume normal optimization model of four-end soft switches of the active power distribution network to obtain the normal operation loss of the power distribution network.
And in the fourth step, the solution of the four-end soft switch site selection constant volume normal optimization model of the active power distribution network is obtained through a second-order cone programming algorithm.
The solving steps of the second-order cone planning algorithm for the four-end soft switch location and volume fixing normal optimization model of the active power distribution network are as follows:
4.1: converting the nonlinear power flow constraint into the linear power flow constraint through variable substitution, wherein the substitution expression is as follows:
in the formula: xp、Xq、Ypq、ZpqRespectively, are alternative variables; u shapepIs the voltage amplitude of node p; thetapqIs the phase angle difference between the nodes p and q; i ispqIs the current of branch pq;
the linear power flow constraint expression obtained by conversion after variable replacement is as follows:
in the formula: pp、QpActive power and reactive power injected into the node p respectively; gpq、BpqRespectively a real part and an imaginary part of the node admittance matrix; thetapqIs the phase angle difference between the nodes p and q; i ispqIs the current of branch pq; q ∈ p denotes a node set connected with the node p; xp、Xq、Ypq、ZpqRespectively, are alternative variables;
4.2: a rotating cone constraint condition is introduced in the conversion process, so that the annual loss calculation model of the power distribution network is in the constraint range of the pointed convex cone, and meanwhile, the solving result of the annual loss calculation model of the power distribution network cannot be influenced, and the rotating cone constraint condition expression is as follows:
in the formula, Xp、Xq、Ypq、ZpqRespectively, are alternative variables;
4.3: converting four-terminal soft switch nonlinear operation constraint in a power distribution network annual loss calculation model into a second-order cone constraint condition, wherein the second-order cone constraint condition expression is as follows:
in the formula: pd,sopAnd Qd,dsopRespectively the active power and the reactive power S flowing into the d-th port of the four-end soft switchd,sopThe rated capacity of the d-th port of the four-terminal SOP.
4.4: and solving the converted four-end soft switch site selection constant volume normal operation optimization model of the active power distribution network by adopting optimization software CPLEX.
Step five: substituting the annual average power failure time, the annual average transfer power of the four-terminal soft switch and the normal running loss of the power distribution network of each load point of each scene into a first objective function, and performing coding solution on the active power distribution network four-terminal soft switch constant-volume addressing planning model by adopting a particle swarm algorithm in a real number coding mode to obtain the following codes of the installation position and the capacity of the four-terminal soft switch:
X＝[c1,c2,...,cs]
in the formula: x is a matrix with a row and s columns and represents a site selection and volume fixing scheme of the four-end soft switch, the column number of the matrix represents the sequence number of the installation position of the four-end soft switch, and the matrix element represents the installation capacity of the four-end soft switch; and s is the number of four-end soft switches installed in the power distribution network.
And taking the optimal solution obtained by solving by using the particle swarm algorithm as a site selection and volume fixing scheme of the four-terminal soft switch.
The above-described embodiments are only preferred embodiments of the present invention, and are not intended to limit the present invention in any way, and other variations and modifications may be made without departing from the spirit of the invention as set forth in the claims.
Claims (10)
1. A method for planning four-terminal soft switches of an active power distribution network based on reliability evaluation is characterized by comprising the following steps:
the method comprises the following steps: establishing an active power distribution network four-end soft switch location and volume planning model by taking the minimum annual comprehensive cost of the power distribution network as a first objective function and taking access capacity constraint as a constraint condition;
step two: establishing an active power distribution network four-end soft switch location constant volume normal operation optimization model by taking the minimum power distribution network normal operation total loss as a second objective function and taking power flow constraint, node voltage constraint, line current-carrying capacity constraint and four-end soft switch operation constraint as constraint conditions;
step three: evaluating the reliability of the active power distribution network with the four-terminal soft switch through a reliability evaluation algorithm to obtain the annual average power failure time of each load point of each scene and the annual average transfer power of the four-terminal soft switch;
step four: solving a site selection constant-volume normal optimization model of four-end soft switches of the active power distribution network to obtain normal operation loss of the power distribution network;
step five: and substituting the annual average power failure time, the annual average transfer power of the four-terminal soft switch and the normal running loss of the power distribution network of each load point of each scene into a first objective function, solving an active power distribution network four-terminal soft switch constant-volume location planning model by adopting a particle swarm algorithm, and taking the optimal solution obtained by the solution as the installation position and the capacity of the four-terminal soft switch.
2. The active power distribution network four-terminal soft switch planning method based on reliability evaluation according to claim 1, wherein the reliability evaluation algorithm in step three is a quasi-sequential monte carlo simulation method.
3. The active power distribution network four-terminal soft switch planning method based on reliability evaluation according to claim 2, wherein the reliability evaluation of the active power distribution network with the four-terminal soft switch by the quasi-sequential Monte Carlo simulation method comprises the following steps:
3.1: setting the output and load conditions of the distributed power supply in each scene;
3.2: setting the simulation years and all elements at the simulation initial moment to work in a normal state;
3.3: setting active power distribution networkHas a total of XmAn element for randomly generating XmRandom number between 0 and 1, and determining X according to the failure transfer rate and the exponential distributionmFault-free operating time T of individual elementsTTF；
3.4: finding the minimum fault-free operating time TTTFminSaid minimum fault-free running time TTTFminThe corresponding element is a fault element, a random number is generated for the fault element, and the fault repairing time T of the fault element is determined according to the repairing transfer rateTTRAccording to the minimum fault-free running time TTTFminAnd time to failover TTTRDetermining fault isolation and load transfer time, and advancing analog clock to TTTFmin+TTTR；
3.5: determining the power failure time of each load point fault in each subarea in the network, and if the load is supplied by the four-terminal soft switch in each subarea, calculating the power failure time of each load point and the supply power of the four-terminal soft switch in the island period according to the load reduction condition; otherwise, determining the power failure time of each partition load point in the network by combining a feeder partition method, wherein the load reduction conditional expression is as follows:
in the formula: psop(t) the four-terminal soft switch port connected with the fault feeder line at the moment t can supply power; pl,linerem(t) the remaining capacity of the first feeder line connected by the four-terminal soft switch except the fault feeder line; pDG(t) is the total distributed power supply output in the island at the moment t; n is a radical ofLThe total number of the downstream island load points of the fault area is; l isa(t) the load at the a-th load point at time t; epsilona(t) is the reduction state of the a-th load point at time t;
3.6: setting a new operating time T for a defective componentTTFnewUpdating the fault-free running time of the active power distribution network to TTTFmin+TTTR+TTTFnew；
3.7: judging whether the set simulation years are reached or not, if the set simulation years are reached, counting the power failure time of the load point of each simulation year and the conversion power of the four-terminal soft switch, and further calculating the annual average power failure time of each load point of each scene and the annual average conversion power of the four-terminal soft switch; if not, returning to execute the step 3.3;
3.8: judging whether the reliability evaluation of all scenes is finished or not, and if the reliability evaluation is not finished, returning to execute the step 3.2; otherwise, the simulation process ends.
4. The active power distribution network four-terminal soft switch planning method based on reliability evaluation according to claim 1, wherein in the second step, the second objective function expression is as follows:
in the formula: ploss,kNormal operation loss of the power distribution network is set for the kth scene; n is a radical ofnThe number of nodes of the power distribution network is; n is a radical ofsopThe number of the four-end soft switches is the access number; pp,kInjecting active power for the node p in the kth scene; beta is asopThe loss coefficient of the four-terminal soft switch; pi,sop,kIs the transmission power of the ith soft switch in the kth scene.
5. The active power distribution network four-terminal soft switch planning method based on reliability evaluation according to claim 1, wherein in the constraint condition of the second step, a power flow constraint expression is as follows:
in the formula: pp、QpActive power and reactive power injected into the node p respectively; u shapepIs the voltage amplitude of node p; gpq、BpqRespectively a real part and an imaginary part of the node admittance matrix; thetapqIs the phase angle between nodes p, qA difference; i ispqIs the current of branch pq; q ∈ p denotes a node set connected to the node p;
in the second step, the node voltage constraint expression in the constraint condition is as follows:
Up,min<Up<Up,max
in the formula: u shapep,minIs the lower limit of the voltage amplitude of the node p; u shapep,maxIs the upper voltage amplitude limit of node p;
in the second step, the line current-carrying constraint condition expression in the constraint condition is as follows:
Im<Im,max
in the formula: i ismThe current amplitude of the mth line; i ism,maxThe current amplitude upper limit of the mth line;
in the second step, the four-terminal soft switch operation constraint expression in the constraint condition is as follows:
Pd,soploss＝βsop·|Pd,sop|
in the formula: pd,sopAnd a group of Q's, each of which,dsopactive power and reactive power flowing into the d-th port of the four-terminal soft switch respectively; sd,sopThe rated capacity of the d-th port of the four-end soft switch is obtained; pd,soplossThe transmission loss of the d-th port of the four-terminal soft switch; beta is asopThe loss factor of the four-terminal soft switch.
6. The active power distribution network four-terminal soft switch planning method based on reliability evaluation according to claim 1, wherein the solution of the active power distribution network four-terminal soft switch location constant-volume normal optimization model in the fourth step is obtained through a second-order cone planning algorithm.
7. The active power distribution network four-terminal soft switch planning method based on reliability evaluation according to claim 6, wherein the solving steps of the second-order cone planning algorithm on the active power distribution network four-terminal soft switch location constant normal optimization model are as follows:
4.1: converting the nonlinear power flow constraint into the linear power flow constraint through variable substitution, wherein the substitution expression is as follows:
in the formula: xp、Xq、Ypq、ZpqRespectively, are alternative variables; u shapepIs the voltage amplitude of node p; thetapqIs the phase angle difference between the nodes p and q; i ispqIs the current of branch pq;
the linear power flow constraint expression obtained by conversion after variable replacement is as follows:
in the formula: pp、QpActive power and reactive power injected into the node p respectively; gpq、BpqRespectively a real part and an imaginary part of the node admittance matrix; thetapqIs the phase angle difference between the nodes p and q; i ispqIs the current of branch pq; q ∈ p denotes a node set connected with the node p; xp、Xq、Ypq、ZpqRespectively, are alternative variables;
4.2: a rotating cone constraint condition is introduced in the conversion process, so that the annual loss calculation model of the power distribution network is in the constraint range of the pointed convex cone, and meanwhile, the solving result of the annual loss calculation model of the power distribution network cannot be influenced, and the rotating cone constraint condition expression is as follows:
in the formula, Xp、Xq、Ypq、ZpqRespectively, are alternative variables;
4.3: converting four-terminal soft switch nonlinear operation constraint in a power distribution network annual loss calculation model into a second-order cone constraint condition, wherein the second-order cone constraint condition expression is as follows:
in the formula: pd,sopAnd Qd,dsopRespectively the active power and the reactive power S flowing into the d-th port of the four-end soft switchd,sopRated capacity of the d-th port of the four-terminal SOP;
4.4: and solving the converted four-end soft switch site selection constant volume normal operation optimization model of the active power distribution network by adopting optimization software CPLEX.
8. The active power distribution network four-terminal soft switch planning method based on reliability assessment according to claim 1, wherein the particle swarm algorithm in step five is encoded and solved by a real number encoding mode, and the encoding of the installation position and the capacity of the four-terminal soft switch is as follows:
X＝[c1,c2,...,cs]
in the formula: x is a matrix with a row and s columns and represents a site selection and volume fixing scheme of the four-end soft switch, the column number of the matrix represents the sequence number of the installation position of the four-end soft switch, and the matrix element represents the installation capacity of the four-end soft switch; and s is the number of four-end soft switches installed in the power distribution network.
9. The active power distribution network four-terminal soft switch planning method based on reliability evaluation according to claim 1, wherein the first objective function expression in step one is:
in the formula: f is the annual comprehensive cost of the power distribution network; cinvEqual annual cost of investment cost for four-terminal soft switch construction, and d is the discount rate; y is the full life cycle of the four-terminal soft switch; n is a radical ofsopThe number of the four-end soft switches is the number of the four-end soft switches; c. CsopInvestment cost per unit capacity for soft switching; si,sopThe installation capacity of the ith soft switch; cmainThe annual operation and maintenance cost of the soft switch is mu, and the mu is the annual operation and maintenance cost coefficient of the soft switch; cnormalFor the normal running cost of the distribution network, NsObtaining the number of the operation scenes of the power distribution network for clustering; p is a radical ofkProbability of the kth scene; c. C0Is the electricity price; ploss,kNormal operation loss of the power distribution network is set for the kth scene; cfaultReliability cost, P, calculated for reliability assessment of the distribution networksoptransThe annual average transfer loss of the soft switch obtained for reliability evaluation; n is a radical oflThe number of load points; poutage,jThe annual average outage at load point j.
10. The active power distribution network four-terminal soft switch planning method based on reliability evaluation according to claim 1, wherein in the first step, the access capacity constraint condition expression is as follows:
Si,sop＝mi·sunit
Si,sop≤Si,sopmax
in the formula: si,sopThe mounting capacity of the ith four-terminal soft switch; m isiIs a positive integer; sunitThe unit installation capacity of the four-end soft switch; si,sopmaxThe maximum installation capacity of the ith four-terminal soft switch.
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