CN107808256B - Regional high-voltage distribution network supply transfer method based on opportunity constraint planning - Google Patents
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Abstract
The invention discloses a regional high-voltage distribution network power transfer method based on opportunity constraint planning, which is characterized in that based on the topology reconstruction capability of a high-voltage distribution network, a high-voltage distribution network opportunity constraint power transfer model taking a feasible topological state of a 110kV power transformation unit group as a control object is provided, a multi-state modeling is carried out on random variables by utilizing a probability density function of wind power-load errors, and a high-voltage power network operation optimization technology taking topological reconstruction as a means under an uncertain condition is constructed by taking source load power balanced distribution as a target. The method can effectively relieve the consumption contradiction of the high-voltage power grid in the area after the high-permeability wind power is accessed in the non-uniform mode, and is favorable for improving the flexible utilization efficiency of the high-voltage power grid assets to stabilize the blocking risk.
Description
Technical Field
The invention belongs to the technical field of power system automation, and particularly relates to a design of a regional high-voltage distribution network power supply transfer method based on opportunity constraint planning.
Background
After the national energy agency publishes 'notice about distributed access wind power development' of new national energy [2011]226 and 'notice about issuing distributed access wind power project development construction guidance suggestion' of new national energy [2011]374 in 2011, medium-scale wind power is directly merged into regional power grids for rapid development of local consumption technology. Due to the limitation of randomness and fluctuation of wind energy resources, wind power access is non-uniform, and local consumption of regional power grids is difficult. Meanwhile, the regional power grid construction is difficult to ensure the adaptability to the increase of each local load, and the local region is easy to have heavy load. Therefore, the high-voltage power grid in the high-permeability area is easy to have the coexistence situation of blocking risk and consumption predicament. In order to ensure power supply reliability, a plurality of standby supply lines are often built in a regional high-voltage power distribution network, so that potential power supply paths of the regional high-voltage power distribution network are extremely large, the coexistence of a looped network and a radial network is realized, and the balanced distribution of power can be realized by utilizing the characteristic of high flexibility and transferability of the regional high-voltage power distribution network, but the conventional research on the transfer operation of a Distributed Generation (DG) in the power distribution network mainly focuses on a 10kV medium-voltage level. Due to the lack of a clear model of the high voltage distribution network considering DG, existing research is mainly focused on a single layer, such as the problem of consumption brought by only reconstructing the high voltage distribution network or only by DG. Meanwhile, due to the randomness of wind power, a power transfer algorithm under a deterministic condition is not completely applicable, and a medium-scale wind power deterministic representation method of a high-voltage distribution network is lacked in the prior art. In conclusion, the uncertainty of wind power control is difficult to be controlled by the prior art and the model, and the consumption difficulty and the load overload of the regional high-voltage distribution network cannot be considered.
Disclosure of Invention
The invention aims to solve the defect that a high-voltage distribution network in a high-permeability area is difficult to take into account of consumption difficulty and load overload under medium-scale wind power access, and provides a regional high-voltage distribution network power supply method based on opportunity constraint planning.
The technical scheme of the invention is as follows: a regional high-voltage distribution network supply method based on opportunity constraint planning comprises the following steps:
and S1, constructing a high-voltage distribution network opportunity constraint transfer model.
S2, searching a feasible topological structure of the power supply unit group in the high-voltage distribution network opportunity constraint transfer model to obtain a feasible topological state of the power supply unit group.
The rule for searching the feasible topological structure of the power supply unit group is as follows:
the action of the circuit breaker needs to be matched in any switching operation, namely the number of the circuit breakers in a closed state is constant;
and for the situation that a plurality of 220kV transformer substations are selected in the transfer process, only one transfer direction can be selected.
And S3, solving the high-voltage distribution network opportunity constraint transfer model by adopting a decimal genetic algorithm according to the feasible topological state of the power supply unit group, and realizing load dispersion and wind power consumption optimization of the regional high-voltage power network after the high-permeability wind power is accessed non-uniformly.
Step S3 specifically includes the following substeps:
and S31, generating an initial population of the decimal genetic algorithm according to the feasible topological state of the power supply unit group.
And S32, calculating an objective function of the high-voltage distribution network opportunity constraint transfer model, and calculating the individual fitness of the current population.
And S33, judging whether an algorithm termination condition is met (the iteration number reaches a preset maximum iteration number), if so, entering a step S34, and otherwise, entering a step S36.
And S34, outputting the feasible topological state of the power supply unit group as an algorithm result.
And S35, judging whether the algorithm result meets the opportunity constraint condition, if so, ending the solving, otherwise, returning to the step S31.
And S36, judging whether the iteration process falls into local optimum (when the iteration number h is greater than a preset iteration number threshold K, the optimum fitness of continuous n iterations is the fitness of the same individual in the population), if so, entering a step S37, and otherwise, entering a step S38.
S37, calculating the optimal individual fitness according to the individual fitness of the current population, and entering the step S38.
S38, generating next generation individuals by genetic operation, and returning to step S32.
The invention has the beneficial effects that: the invention provides a high-voltage distribution network opportunity constraint transfer model taking a feasible topological state of a 110kV power transformation unit group as a control object based on the topological reconstruction capability of a high-voltage distribution network, performs multi-state modeling on random variables by using a probability density function of wind power-load errors, and constructs a high-voltage power network operation optimization technology taking topological reconstruction as a means under an uncertain condition by taking source load power balanced distribution as a target. The method can effectively relieve the consumption contradiction of the high-voltage power grid in the area after the high-permeability wind power is accessed in the non-uniform mode, and is favorable for improving the flexible utilization efficiency of the high-voltage power grid assets to stabilize the blocking risk.
Drawings
Fig. 1 is a flowchart of a regional high-voltage distribution network power supply method based on opportunity constraint planning according to an embodiment of the present invention.
Fig. 2 is a schematic diagram illustrating a regional high-voltage power grid transformation unit and a connection relationship thereof according to an embodiment of the present invention.
Fig. 3 is a schematic representation diagram of a topology structure of a regional high-voltage power grid according to an embodiment of the present invention.
Fig. 4 is a flowchart illustrating a substep of step S3 according to an embodiment of the present invention.
Fig. 5 is a local system wiring diagram of a regional high-voltage power grid according to an embodiment of the present invention.
Fig. 6 is a schematic diagram illustrating a ratio of a wind power and load power certainty prediction value provided by an embodiment of the present invention.
Fig. 7 is a schematic diagram illustrating comparison of system states before and after optimization according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It is to be understood that the embodiments shown and described in the drawings are merely exemplary and are intended to illustrate the principles and spirit of the invention, not to limit the scope of the invention.
The embodiment of the invention provides a regional high-voltage distribution network switching method based on opportunity constraint planning, which comprises the following steps of S1-S3 as shown in figure 1:
and S1, constructing a high-voltage distribution network opportunity constraint transfer model.
Based on the topology reconstruction capability of the high-voltage distribution network, the invention provides an opportunity constraint transfer model of the high-voltage distribution network, which takes a 110kV power supply unit as a control object. The high-voltage distribution network transfer operation is realized by changing the connection relation among all power supply units, so the meaning of the power supply units and the connection relation among the power supply units are firstly clarified by the model. The 110kV substation is usually provided with 2-3 two-coil transformers, which are generally a single bus section, an inner bridge and a T-connection combination of the single bus section and the inner bridge and a line transformer set, as shown in fig. 2. In order to ensure the power supply reliability, a large number of standby supply lines are built in the 110kV network of the regional high-voltage power grid according to the design standard of a ring network, the longest standby supply distance can reach 10 kilometers, at least 1 standby supply line exists in each 110kV transformer substation, and the topological structure expression of the regional power grid high-voltage power grid is shown in fig. 3.
S2, searching a feasible topological structure of the power supply unit group in the high-voltage distribution network opportunity constraint transfer model to obtain a feasible topological state of the power supply unit group.
Aiming at power supply units in the high-voltage distribution network opportunity constraint transfer model, the power supply units are divided into groups according to the following rules:
(1) any two power supply units with electrical connection belong to the same power supply unit group a as well as all power supply units between them if there is no 220kV substation in this connection.
(2) The unit group is supplied with power by fixed 220kV substations, which are in direct electrical contact with a certain power supply unit of the unit group (without passing through other intra-group units).
(3) The 220kV transformer substation can simultaneously supply power to a plurality of unit groups, and the load size of the transformer substation is equal to the power of the power supply unit carried at the moment.
The power supply unit switching operation is realized through a 110kV network topological state, the state of a 110kV line breaker is also changed, the feasible topological state of the power supply unit group is determined in advance by utilizing a search algorithm, the algorithm efficiency can be improved, and the rule is as follows:
(1) the action of the circuit breaker needs to be matched in any switching operation, namely the number of the circuit breakers in a closed state is constant.
(2) And for the situation that a plurality of 220kV transformer substations are selected in the transfer process, only one transfer direction can be selected.
And S3, solving the high-voltage distribution network opportunity constraint transfer model by adopting a decimal genetic algorithm according to the feasible topological state of the power supply unit group, and realizing load dispersion and wind power consumption optimization of the regional high-voltage power network after the high-permeability wind power is accessed non-uniformly.
As shown in fig. 4, step S3 specifically includes the following substeps S31-S38:
s31, coding genes according to the feasible topological state of the power supply unit group to generate an initial population of the decimal genetic algorithm, wherein the calculation formula is as follows:
wherein xiRepresenting a feasible topological state of the ith power supply unit group, hiRepresents the controllable DG power adjustment of the ith power supply unit group, Pi ENSIndicating the load shedding of the ith power supply unit group, BGroFor a set of power supply units, giIndicates the gene corresponding to the i-th power supply unit group, GtRepresents the total set of coding genes at time t.
And S32, calculating an objective function of the high-voltage distribution network opportunity constraint transfer model, and calculating the individual fitness of the current population.
The objective function f is calculated as:
f＝min(f1+a1f2+a2f3) (2)
wherein f is1Area power grid power equilibrium distribution coefficient expected value, f under opportunity constraint planning2For the number of times the circuit breaker can be operated during the switching operation, f3For the adjustment of the controllable DG power, i.e. for the adjustment of the controllable DG power in local areas during the supply process to improve the wind power absorption capacity and balance the load, a1、a2Is the penalty factor of the corresponding operation.
The formula (2) ensures that the action times of the circuit breaker and the controllable DG power are adjusted within a safety threshold value, so that the network power distribution is balanced, the wind power consumption capability is improved, and the heavy load of a transformer substation is eliminated.
f1The calculation formula of (2) is as follows:
f1＝exp{||kn-kavg||2}，n＝1，2，...，NT (3)
wherein k isnRepresents the load factor, k, of the nth 220kV substationavgRepresents the mean load factor, N, of a 220kV transformer substationTThe number of the transformer substations is 220 kV.
The formula (3) represents the load factor k of each 220kV transformer substationnAbout its mean value kavg2-norm of f1The smaller the value is, the more balanced the system power distribution under the opportunity constraint planning is, and the consumption spear is effectively solvedAnd heavy load phenomena of a shield and a transformer substation. k is a radical ofnThe calculation formula of (2) is as follows:
wherein
The load power and the fan power of the power supply unit of the nth 220kV transformer substation in the ith power supply unit group at the moment t respectively,
rated capacity of the nth 220kV transformer substation, T is a time set, phi is a 220kV transformer substation set, BGroIs a power supply unit group set.
f2The calculation formula of (2) is as follows:
wherein
Respectively the topological states before and after the optimization of the jth operable circuit breaker at the moment t under the ith feasible topology,
for a feasible set of topologies, BBroIs a set of operable circuit breakers.
f3The calculation formula of (2) is as follows:
wherein h isi，jRepresents the controllable DG power adjustment of the jth power transformation unit in the ith power supply unit group, BBroFor a set of operable circuit breakers, BUniIs a power transformation unit set.
The current population individual fitness fit (f (d)) is calculated by the formula:
wherein N isdAnd d is the position of the individual in the population determined according to the size of the objective function, sp is the selection pressure, and sp is more than or equal to 1 and less than or equal to 2 in the embodiment of the invention.
And S33, judging whether the algorithm termination condition is met, if so, entering a step S34, and otherwise, entering a step S36.
In the embodiment of the invention, the algorithm termination condition is as follows: the iteration times reach the preset maximum iteration times.
And S34, outputting the feasible topological state of the power supply unit group as an algorithm result.
And S35, judging whether the algorithm result meets the opportunity constraint condition, if so, ending the solving, otherwise, returning to the step S31.
Opportunity constraints include node voltage constraints, load rate constraints, and wind power constraints.
The formula of the node voltage constraint condition is as follows:
equation (8) is the voltage amplitude chance constraint of the 220kV node and the 110kV node, wherein
Respectively represent the ith 110kV node voltage and the jth 220kV node voltage,
respectively a lower limit and an upper limit of the voltage amplitude of the 110kV node,
the lower limit and the upper limit of the voltage amplitude of the 220kV node are respectively, alpha is a confidence level, and Pr {. is a reliability function.
The formula of the load rate constraint is:
equation (9) is the 220kV substation and 220kV line load rate opportunity constraint, where knIs the load factor, k, of the nth 220kV transformer substationn，maxIs the upper limit of the load factor k of the 220kV transformer substationlIs the load factor, k, of the l 220kV linel，maxThe load factor of the 220kV line is the upper limit.
The formula of the wind power constraint condition is as follows:
wherein
Respectively the load active power and the wind power active power of the nth 220kV transformer substation at the time t,
load reactive power and wind power reactive power of the nth 220kV transformer substation at the time t respectively,
the threshold value of the wind power active power reverse transmission quantity is shown, T is a time set, and phi is a 220kV transformer substation set.
Equation (10) represents wind power active power constraints, in general
That is, the reverse transmission amount of 110kV wind power active power to the 220kV main network is allowed to be within a certain threshold, and the formula (11) represents wind power reactive power constraint, that is, 110kV wind power reactive power is not allowedAnd (5) sending the data to a 220kV main network.
And S36, judging whether the iteration process falls into local optimum, if so, entering a step S37, and otherwise, entering a step S38.
In the embodiment of the invention, the conditions for the iteration process to fall into the local optimum are as follows: and when the iteration times h are larger than a preset iteration time threshold value K, the optimal fitness of the continuous n iterations is the fitness of the same individual in the population.
S37, calculating the optimal individual fitness according to the individual fitness of the current population, and entering the step S38.
The decimal genetic algorithm optimizing range adopted by the embodiment of the invention is the product of feasible topological states in each unit group, and the scale is large, so that the local optimization is easy to fall into in the iteration process. For this case, the individual fitness fit (d) is dynamically adjusted: i.e. the number of iterations h>And K, if the fact that the local optimum is possibly involved is detected, adjusting the optimum individual fitness, and the optimum individual fitness fit is fitm(d) The calculation formula of (2) is as follows:
wherein
And f, as a fitness adjustment coefficient, fit (d) as the individual fitness of the current population, h as the iteration number, and K as a preset iteration number threshold.
S38, generating next generation individuals by genetic operation, and returning to step S32.
In the embodiment of the invention, the specific method for generating the next generation of individuals by using genetic manipulation is as follows:
and (3) sequencing the individuals of the generation according to the individual fitness (if the population consists of 50 individuals, the sequencing serial number is 1-50), removing 2 individuals (1-48) with the minimum fitness, copying 2 individuals (1, 2) with the maximum fitness to directly enter the next generation, dividing 1-48 into 24 pairs, carrying out specific position exchange genes between each pair (for example, aec and dbf are new individuals after the gene exchange of the abc and the def second stage), and forming the newly generated 48 individuals and the previous generation 1 and 2 individuals into the next generation 50 individuals.
The feasibility and the effectiveness of the regional high-voltage distribution network power supply transfer method based on opportunity constraint planning provided by the invention are verified by a regional power grid local system:
as shown in fig. 5, the 220kV system has 6 substations and 10 lines; the 110kV system has 38 power supply units and 40 lines, wherein 9 lines are in a standby state, and the system is divided into 6 power supply unit groups (A1-A6) according to the regional high-voltage distribution network power supply transferring method provided by the embodiment of the invention. The installed capacity of a 17-node wind power plant is 150MW, the installed capacity of a 27-node wind power plant is 50MW, and the installed capacity of a 38-node wind power plant is 100 MW; nodes 29 and 37 are connected with 8MW controllable DGs.
The power and load power of each wind power plant in the next 2 hours are shown in table 1 with 30min as a time interval.
TABLE 1
Under the initial working condition, the A3 belt is overloaded with all industrial loads, and the load rate is 120%; at the moment, the wind speed is large, the output of the 38-node wind power plant is close to the rated power and cannot be consumed on site, and the wind power is returned in A6, so that a large transfer space exists in the network. The obtained results are shown in fig. 6 and 7, and it can be seen from the graphs that the load rates of the optimized 220kV substations are relatively balanced, the overload lines return to the rated capacity, and the substations have no heavy load phenomenon and no wind power consumption dilemma. Table 2 shows the operation of each high-voltage circuit breaker in each time period.
TABLE 2
It will be appreciated by those of ordinary skill in the art that the embodiments described herein are intended to assist the reader in understanding the principles of the invention and are to be construed as being without limitation to such specifically recited embodiments and examples. Those skilled in the art can make various other specific changes and combinations based on the teachings of the present invention without departing from the spirit of the invention, and these changes and combinations are within the scope of the invention.
Claims (7)
1. A regional high-voltage distribution network transfer method based on opportunity constraint planning is characterized by comprising the following steps:
s1, constructing a high-voltage distribution network opportunity constraint transfer model;
s2, searching a feasible topological structure of a power supply unit group in the high-voltage distribution network opportunity constraint transfer model to obtain a feasible topological state of the power supply unit group;
s3, solving a high-voltage distribution network opportunity constraint transfer model by adopting a decimal genetic algorithm according to the feasible topological state of the power supply unit group, and realizing load dispersion and wind power consumption optimization of the regional high-voltage power network after the high-permeability wind power is accessed non-uniformly;
the rule for performing feasible topology searching on the power supply unit group in step S2 is as follows:
the action of the circuit breaker needs to be matched in any switching operation, namely the number of the circuit breakers in a closed state is constant;
for the situation that a plurality of 220kV transformer substations are selected in the transfer process, only one transfer direction can be selected;
the step S3 specifically includes the following sub-steps:
s31, generating an initial population of the decimal genetic algorithm according to the feasible topological state of the power supply unit group;
s32, calculating a target function of the high-voltage distribution network opportunity constraint transfer model, and calculating the individual fitness of the current population;
s33, judging whether the algorithm termination condition is met, if so, entering a step S34, otherwise, entering a step S36;
s34, outputting the feasible topological state of the power supply unit group as an algorithm result;
s35, judging whether the algorithm result meets the opportunity constraint condition, if so, ending the solving, otherwise, returning to the step S31;
s36, judging whether the iteration process falls into local optimum or not, if so, entering a step S37, and otherwise, entering a step S38;
s37, calculating the optimal individual fitness according to the individual fitness of the current population, and entering the step S38;
s38, generating next generation individuals by genetic operation, and returning to the step S32;
the calculation formula of the objective function f in step S32 is:
f＝min(f1+a1f2+a2f3)
wherein f is1Area power grid power equilibrium distribution coefficient expected value, f under opportunity constraint planning2For the number of times the circuit breaker can be operated during the switching operation, f3For controllable DG power scaling, a1、a2A penalty factor for the corresponding operation;
f1the calculation formula of (2) is as follows:
f1＝exp{||kn-kavg||2},n＝1,2,...,NT
wherein k isnRepresents the load factor, k, of the nth 220kV substationavgRepresents the mean load factor, N, of a 220kV transformer substationTThe number of the transformer substations is 220 kV;
knthe calculation formula of (2) is as follows:
wherein
The load power and the fan power of the power supply unit of the nth 220kV transformer substation in the ith power supply unit group at the moment t respectively,
rated capacity of the nth 220kV transformer substation, T is a time set, phi is a 220kV transformer substation set, BGroA power supply unit set is provided;
f2the calculation formula of (2) is as follows:
wherein
Respectively the topological states before and after the optimization of the jth operable circuit breaker at the moment t under the ith feasible topology,
for a feasible set of topologies, BBroIs a set of operable circuit breakers;
f3the calculation formula of (2) is as follows:
wherein h isi,jRepresents the controllable DG power adjustment of the jth power transformation unit in the ith power supply unit group, BBroFor a set of operable circuit breakers, BUniIs a power transformation unit set.
2. The regional high-voltage distribution network transfer method according to claim 1, wherein the calculation formula for generating the initial population of the decimal genetic algorithm in step S31 is as follows:
wherein xiRepresenting a feasible topological state of the ith power supply unit group,hirepresents the controllable DG power adjustment of the ith power supply unit group, Pi ENSIndicating the load shedding of the ith power supply unit group, BGroFor a set of power supply units, giIndicates the gene corresponding to the i-th power supply unit group, GtRepresents the total set of coding genes at time t.
3. The method for regional high-voltage distribution network transfer according to claim 1, wherein the calculation formula of the current population individual fitness fit (d) in step S32 is as follows:
wherein N isdAnd d is the size of the population, d is the position of the individual in the population determined according to the size of the objective function, and sp is the selection pressure.
4. The method for regional high-voltage distribution network transfer according to claim 1, wherein the algorithm termination condition in step S33 is: the iteration times reach the preset maximum iteration times.
5. The regional high-voltage distribution network trans-supply method according to claim 1, wherein the opportunity constraint conditions in the step S35 include a node voltage constraint condition, a load rate constraint condition and a wind power constraint condition;
the formula of the node voltage constraint condition is as follows:
wherein Vi 110、
Respectively represent the ith 110kV node voltage and the jth 220kV node voltage,
respectively a lower limit and an upper limit of the voltage amplitude of the 110kV node,
respectively setting a lower limit and an upper limit of a voltage amplitude of a 220kV node, wherein alpha is a confidence level, and Pr {. is a reliability function;
the formula of the load rate constraint condition is as follows:
wherein k isnIs the load factor, k, of the nth 220kV transformer substationn,maxIs the upper limit of the load factor k of the 220kV transformer substationlIs the load factor, k, of the l 220kV linel,maxThe load factor upper limit of the 220kV line is set;
the formula of the wind power constraint condition is as follows:
wherein
Respectively the load active power and the wind power active power of the nth 220kV transformer substation at the time t,
load reactive power and wind power reactive power of the nth 220kV transformer substation at the time t respectively,
the threshold value of the wind power active power reverse transmission quantity is shown, T is a time set, and phi is a 220kV transformer substation set.
6. The regional high-voltage distribution network transfer method according to claim 1, wherein the conditions for the iterative process to fall into the local optimum in step S36 are: and when the iteration times h are larger than a preset iteration time threshold value K, the optimal fitness of the continuous n iterations is the fitness of the same individual in the population.
7. The method for regional high-voltage distribution network transfer according to claim 1, wherein the optimal individual fitness fit in step S37 is setm(d) The calculation formula of (2) is as follows:
wherein
And f, as a fitness adjustment coefficient, fit (d) as the individual fitness of the current population, h as the iteration number, and K as a preset iteration number threshold.
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