CN112350347B - Power control method, system, device and medium for rail transit vehicle-mounted power grid - Google Patents
Power control method, system, device and medium for rail transit vehicle-mounted power grid Download PDFInfo
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- H—ELECTRICITY
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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- H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
- H02M5/00—Conversion of ac power input into ac power output, e.g. for change of voltage, for change of frequency, for change of number of phases
- H02M5/40—Conversion of ac power input into ac power output, e.g. for change of voltage, for change of frequency, for change of number of phases with intermediate conversion into dc
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- H02J2310/40—The network being an on-board power network, i.e. within a vehicle
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- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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Abstract
A power control method, system, device and medium for a rail transit on-board power grid. The invention discloses a power control method of a rail transit vehicle-mounted power grid, which is characterized in that the power control of the conventional rail transit vehicle-mounted power grid is limited by the power control defect of an alternating current-alternating current matrix converter, the global optimal switch state combination of the matrix converter cannot be quickly obtained, and the stability control of the power of the vehicle-mounted power grid cannot be realized.
Description
Technical Field
The invention relates to the field of power control of a rail transit vehicle-mounted power grid.
Background
With the development of power electronic technology, the requirement for the stability of the vehicle-mounted power grid suitable for rail transit is increasingly urgent, the power supply of the vehicle-mounted power grid can be provided by a large power grid in China and also can be provided by an independent power supply, and the independent power supply can be an independent power supply of various power sources, such as an independent power supply taking solar energy, wind energy and photoelectric complementary forms as an energy source and an independent power supply based on diesel/gasoline engine power generation. The vehicle-mounted power grid of the rail transit needs to be matched with various power supplies to provide stable power for the vehicle, and the power control technology of the vehicle-mounted power grid becomes a research focus.
A matrix converter is needed in a rail transit vehicle-mounted power grid to achieve stable alternating current output, and constant frequency indexes of a power generation system are achieved. In the past decades, ac-ac matrix converters have been used due to their unique characteristics: the input power factor is controllable, the input current harmonic is small, the power density is high, the energy flows in two directions, and the like, and the device is greatly developed, and particularly applied to rail transit.
Since the ac-ac matrix converter has no dc energy storage element, the influence of external disturbances on the converter is very prominent. Therefore, there is a need for a control method, system, device and storage medium with simple principle and good performance, which can improve the noise immunity of the matrix converter to ensure its safe and stable operation.
Generally, the collected voltage and current and a discrete mathematical model of the converter are utilized to circularly calculate the predicted power error, and the optimal vector of the matrix converter is selected by finding the minimum predicted power error to realize the power control of the converter. Because the collected voltage and current information has time delay, the prediction result is influenced, the sampling period is shortened, the prediction precision is favorably improved, but the calculation capability of the chip is higher, therefore, the power prediction error value of the matrix converter is calculated by adopting a particle swarm optimization method in the prior art, although the calculation load of the chip is reduced by the method, the optimal solution cannot be found.
In the power control of the rail transit vehicle-mounted power grid, the ant colony algorithm is introduced into the calculation of the power prediction error of the matrix converter, so that the optimal solution can be found, meanwhile, at the beginning of the ant colony algorithm calculation, the distance value between the switch states is set according to the switch mutual exclusion relation in the alternating current-alternating current matrix converter, the global optimal switch state combination can be rapidly obtained, the obtained optimal switch state combination is applied to the matrix converter, and the vehicle-mounted power grid is ensured to provide stable alternating current. By the power control method, the system, the device and the medium for the rail transit vehicle-mounted power grid, provided by the invention, the global minimum predicted power error can be quickly found, the global optimal switch state combination is obtained, the quick and accurate power control of the alternating current-alternating current matrix converter is realized, the running stability of a rail vehicle which is connected with the output end of the alternating current-alternating current matrix converter and serves as a load is further ensured, and the vehicle-mounted power grid is realized to provide stable alternating current output.
Disclosure of Invention
The invention aims to provide a power control method, a system, a medium and a device for a vehicle-mounted power grid, and the method, the system, the medium and the device can provide stable alternating current for a vehicle and ensure the running stability of the vehicle.
The invention provides a power control method for a rail transit vehicle-mounted power grid, which is characterized by comprising the following steps of 1: initializing an ant colony algorithm according to the number of switches of the AC-AC matrix converter; step 2: determining the distance between the switch states according to the on-off rule of the switch in the AC-AC matrix converter, and placing ants in different switch states; and step 3: the global optimal switch state combination module calculates the predicted power error of the alternating current-alternating current matrix converter every time the ants complete traversal; and 4, step 4: after the maximum iteration times are finished, obtaining the optimal switching state combination of the current AC-AC matrix converter according to the obtained minimum global prediction power error of the AC-AC matrix converter; and 5: and (5) adjusting the alternating current-alternating current matrix converter according to the optimal switching state combination obtained in the step (4) to ensure that the vehicle-mounted power grid provides stable alternating current.
The step 1 specifically comprises the following steps: the number of ants in the ant colony is m, the number of switches in the AC-AC matrix converter is n, and each switch is represented by SW 1 ,SW 2 ,…,SW n Each switch has two states, on and off, expressed as SW 1-1 /SW 1-0 ，SW 2-1 /SW 2-0 ,…,SW n-1 /SW n-0 The ant needs to traverse n switches and 2n switch states, and finally finds the optimal solution of the on-off condition of the n switches.
M is 1.5 times of 2n, namely m =3n, and the distance from the switch state i to the switch state j is d ij (i, j =1,2, \8230;, 2 n), in particular, the distance between the different states of one and the same switch is set to a maximum value, thereby expressing that one and the same switch can only have one state, either on or off, preferably the distance between the different states of one and the same switch is set to infinity.
the concentration of pheromone on a connecting path between the switch state i and the switch state j at the time tc is tau ij (tc). At the initial time, the pheromone concentration on each switch state connecting path is the same and is tau ij (tc)＝τ 0 . Then the ants will select the circuit according to a certain probability,
representing the probability of ant q transitioning from switch state i to switch state j at time tc.
Wherein,
representing the desired degree of ant transfer from switch state i to switch state j for a heuristic function,
allow com for ants to access the set of switch states, if switch state j belongs to allow com Then, then
If the switch state j does not belong to all com Then->
Mu represents a pheromone importance factor, and a larger value indicates that the pheromone concentration has a larger effect in metastasis; theta is an important degree factor of the heuristic function, and the larger the value of theta indicates that the heuristic function has larger effect in transfer, ants can be transferred to a short-distance switch state with higher probability;
the step 2 specifically comprises the following steps: and calculating the distance value between the switch states according to the mutual exclusion relation of on-off of the switches.
First, d ij The calculation method of (A) is as follows:
then, in order to further improve the calculation efficiency and accuracy of the ant colony algorithm, d is calculated ij Making a correction when j is equal to
When any switch state is not the same, judging whether the switches respectively corresponding to the switch state i and the switch state j are in a mutual exclusion relationship:
if the two are mutually exclusive, continuously judging whether the current switch state i and the switch state j have the same state indication, namely, both are on or both are off, if the indication states are the same, d ij = ∞; if the indication states are different, it indicates that the switch state i and the switch state j meet the mutual exclusion requirement, and if one switch is on, the two states are necessarily simultaneously existed, so that the distance between the switch state i and the switch state j at the moment is set as the minimum value, which can be 1.
If the switches corresponding to the switch states i and j are not in an exclusive relationship, the distance between the switch states i and j is γ, and γ is a constant greater than 1.
Thus, d ij The final calculation method of (c) is:
ants were randomly placed on the switch state.
Initially, allow com 2n-1 elements in the tree, representing all but the ant q-initiated switch state, all over time com The number of elements in (1) is continuously reduced until the number is null, which indicates that all switch states are completely accessed. When the ants release the pheromone, the pheromone on each switch state connecting path gradually disappears, and after all the ants finish one-time circulation, the concentration of the pheromone on each switch state connecting path is updated in real time, which specifically comprises the following steps:
in the formula,
releasing pheromone concentration for the qth ant on a connection path between a switch state i and a switch state j; delta tau ij The sum of the concentration of pheromones released by all ants on the connection path of the switch state i and the switch state j; the parameter epsilon represents the volatilization degree of the pheromone, and epsilon is more than 0 and less than 1; />
Wherein Q is a constant, typically having a value of [20, 2000%]L represents the total amount of pheromone released by ants in one cycle q The length of the path passed by the qth ant is represented by the number of nodes.
The step 3 specifically comprises the following steps:
step 3.1: collecting corresponding voltage and current at the input end of the matrix converter, and transmitting the corresponding voltage and current to the global optimal switch state combination module; step 3.2: the global optimal switching state combination module calculates the next beat of the kth beat sampling point, namely the output power of the kth +1 beat matrix converter according to the power prediction model of the alternating current-alternating current matrix converter; step 3.3: transmitting the voltage and the current of the k +1 th beat output end of the AC-AC matrix converter to a global optimal switch state combination module; step 3.4: the global optimal switch state combination module calculates the actual power of the output end of the alternating current-alternating current matrix converter; step 3.5: and the global optimal switch state combination module calculates the predicted power error of the alternating current-alternating current matrix converter according to the calculation results of the step 3.2 and the step 3.4.
Specifically, the predicted power calculation formula is:
wherein it is present>
And &>
Is the predicted value of the current at the kth +1 th beat at the lower input end of the alpha _ beta coordinate system, and is judged according to the predicted value>
And &>
Is the k-th beat sampling voltage value of the input end under the alpha-beta coordinate system. The k +1 th beat power at the output end of the AC-AC matrix converter is calculated by the formula
Wherein it is present>
And &>
Is the voltage value of the (k + 1) th beat at the input end under an alpha _ beta coordinate system, and is combined with the circuit>
And &>
Is the current value of the (k + 1) th beat of the input end under the alpha _ beta coordinate system.
When the AC-AC matrix converter takes a beat of k +1, the predicted value of the output power of the matrix converter at the input end is subtracted from the output power of the matrix converter and then squared to obtain the power prediction error variance err of the AC-AC matrix converter, namely
The step 4 specifically comprises the following steps: and setting the objective function as min (err), namely solving the minimum value of the predicted power error, and selecting the optimal switch state combination according to the obtained minimum value of the predicted power error.
The step 5 specifically comprises the following steps: and transmitting the optimal switch state combination to an alternating current-alternating current matrix converter to control the normal operation of the alternating current-alternating current matrix converter, so as to ensure stable alternating current of a rail transit vehicle-mounted power grid.
The power control method for the rail transit vehicle-mounted power grid provided by the first aspect of the invention can ensure that the vehicle-mounted power grid provides stable alternating current to rail vehicles and ensures the running stability of the rail vehicles.
The device can realize the power control method for the rail transit vehicle-mounted power grid provided by the first aspect of the invention, ensure that the vehicle-mounted network provides stable alternating current for rail vehicles and ensure the running stability of the rail vehicles.
Another aspect of the present invention is to provide a computer for power control of a rail transit vehicle-mounted power grid, where the program may implement the power control method for a rail transit vehicle-mounted power grid provided by the first aspect of the present invention, so as to ensure that a vehicle-mounted power grid provides a stable alternating current to a rail vehicle, and ensure the stability of operation of the rail vehicle.
Another aspect of the present invention is to provide a storage medium, where a computer program for executing the power control method for a rail transit vehicle electrical system is stored, so as to ensure that a vehicle electrical system provides stable alternating current to a rail vehicle, and ensure the stability of operation of the rail vehicle.
Has the advantages that: in the power control of the rail transit vehicle-mounted power grid, the improved ant colony algorithm is applied to the control of the matrix converter, the distance factor between the switch states is determined according to the mutual exclusion relation between the switches in the AC-AC matrix converter, then the global optimal solution can be obtained in a short time, the optimal switch state combination of the AC-AC matrix converter is found, the accurate control of the power prediction of the matrix converter is realized, the power control accuracy of the rail transit vehicle-mounted power grid is finally realized, the vehicle-mounted power grid is ensured to provide stable AC, and the running stability of rail vehicles is ensured.
Drawings
FIG. 1: power control structure diagram of rail transit vehicle-mounted power grid
FIG. 2 is a drawing: topological diagram of two-stage AC-AC matrix converter
FIG. 3 is a drawing: computing flow chart for obtaining optimal switch state combination of alternating current-alternating current matrix converter based on ant colony algorithm
Reference numerals
U a 、U b 、U c Is a three input voltage, L f Representing input terminal equivalent inductance, C f Representing input equivalent electricityC, holding; l represents the equivalent inductance of the output end of the AC-AC matrix converter, and R represents the equivalent capacitance of the output end of the AC-AC matrix converter; s ap 、S an 、S bp 、S bn 、S cp 、S cn ,S Ap 、S An 、S Bp 、S Bn 、…、S Xp 、S Xn Switches, S, both of AC-AC matrix converters ap 、S an 、S bp 、S bn 、S cp 、S cn ,S Ap Are composed of two IGBTs with reverse parallel diodes connected according to a common emitter stage, S Ap 、S An 、S Bp 、S Bn 、…、S Xp 、S Xn Each consisting of one IGBT.
Detailed Description
The present invention is further illustrated by the following examples.
At present, the main rail transportation modes comprise high-speed railways, motor train units, heavy-duty freight locomotives, light rails, subway vehicles, monorail trains and magnetic suspension rail transportation, wherein long-distance and high-power main rail transportation generally adopts an alternating current power supply system. The vehicle-mounted power grid of the rail transit needs to be matched with various power supplies to provide stable power for vehicles, the power supply of the vehicle-mounted power grid can be provided by a large power grid in China, and can also be provided by an independent power supply, and the independent power supply can be an independent power supply of various power sources, such as an independent power supply taking a solar energy, wind energy and photoelectric complementary form as an energy source, and an independent power supply based on diesel/gasoline engine power generation. The on-board electrical system requires power control in order to provide a stable alternating current for the rail vehicle.
The rail vehicle obtains energy from a vehicle-mounted power grid, an alternating current-alternating current matrix converter is needed to ensure that the energy is stable and controllable, and if the matrix converter wants to realize power control more quickly and accurately, an optimal combination mode of internal switch states of the matrix converter needs to be obtained.
According to the invention, as shown in figure 1, in a vehicle-mounted power grid, voltage and current values of an input end in sampling beat are collected and transmitted to a global optimal switch state combination module, and the module calculates the predicted power of an output end in the next beat of the sampling beat; meanwhile, the voltage and the current of the next beat of output end of the AC-AC matrix converter are transmitted to a global optimal switch state combination module, and the module calculates the actual power of the output end; the global optimal switch state combination module calculates a power error based on predicted power and actual power, obtains an optimal switch state combination of the alternating current-alternating current matrix converter by solving a minimum power error, adjusts the setting of the matrix converter by using the combination, realizes accurate control of the matrix converter power prediction, further realizes the stability of energy supply of the rail vehicle, and ensures the running stability of the rail vehicle.
Taking T as a discrete period, based on an instantaneous power calculation mode, the discrete mathematical model of the AC-AC matrix converter is as follows:
u in 、i in respectively representing the sampled input voltage and current; u. u out 、i out Respectively representing the output voltage and current; l is an output end equivalent inductor, R is an output end equivalent resistor, and C is an output end equivalent capacitor; t is a discrete period, T is a time constant, and k represents the kth beat of samples.
Since the sampling frequency is very high, it can be considered that the voltages at the input terminals of two consecutive times are approximately equal,
the predicted power calculation formula is as follows: />
Wherein it is present>
And &>
Is the predicted value of the current at the kth +1 th beat at the lower input end of the alpha _ beta coordinate system, and is judged according to the predicted value>
And &>
Is the k-th beat sampling voltage value of the input end under the alpha-beta coordinate system. The calculation formula of the k +1 th beat power of the output end of the AC-AC matrix converter is->
Wherein +>
And &>
Is the (k + 1) th beat voltage value at the input end under the alpha _ beta coordinate system, is greater than or equal to>
And &>
Is the current value of the (k + 1) th beat of the input end under the alpha _ beta coordinate system.
The predicted value of the output power of the matrix converter from the k +1 th beat input end of the AC-AC matrix converter is subtracted from the output power of the matrix converter and then squared to obtain the power prediction error variance err of the AC-AC matrix converter, namely
And setting the objective function as min (err), namely solving the minimum error value of the predicted power, obtaining the optimal switch state combination according to the minimum error value, and finally transmitting the optimal switch state combination to the AC-AC matrix converter to control the normal operation of the AC-AC matrix converter.
FIG. 2 shows a topology of a two-stage AC-AC matrix converter, U a 、U b 、U c Is a three input voltage, L f Represents the input terminal equivalent inductance, C f Representing the input terminal equivalent capacitance; l represents AC-AC matrix changeThe equivalent inductance of the output end of the converter, R represents the equivalent capacitance of the output end of the AC-AC matrix converter; s ap 、S an 、S bp 、S bn 、S cp 、S cn ,S Ap 、S An 、S Bp 、S Bn 、…、S Xp 、S Xn Switches, S, both of AC-AC matrix converters ap 、S an 、S bp 、S bn 、S cp 、S cn ,S Ap Composed of two IGBTs with reverse parallel diodes connected in a common emitter stage, S Ap 、S An 、S Bp 、S Bn 、…、S Xp 、S Xn Each consisting of one IGBT. Fig. 2 a-c matrix converter has a common combination of switching states (2) 6 +2 2X ) And (2) carrying out switching state, wherein X represents the last Xth switching group of the inverter stage, and total number of (2X + 6) switches. The switch state combinations are shown in the following table:
| serial number | S ap | S an | S bp | S bn | S cp | S cn | S Ap | S An | S Bp | S Bn | … | S Xp | S Xn |
| 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | … | 0 | 1 |
| 2 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | … | 0 | 0 |
| 3 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | … | 1 | 0 |
| 4 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | … | 0 | 0 |
| 5 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | … | 1 | 0 |
| 6 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 1 | 1 | … | 1 | 1 |
| 7 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 1 | 0 | … | 0 | 1 |
| 8 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | … | 0 | 0 |
| 9 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | … | 1 | 0 |
| 10 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | … | 0 | 0 |
| … | … | … | … | … | … | … | 0 | 1 | 1 | 1 | … | 1 | 0 |
| 2 6 -2 2X -1 | — | — | — | — | — | — | — | — | — | — | … | — | — |
In order to quickly obtain a global optimal solution of an objective function min (err), an ant colony algorithm is introduced into the calculation of a predicted power minimum error of the AC-AC matrix converter, and in order to better obtain the global optimal solution, the distance between the switch states is set according to a mutual exclusion relation between the switches, and if the switches have a mutual exclusion requirement, namely two switches are inevitably kept in an open (conducting) state and a closed (disconnecting) state when the AC-AC matrix converter is actually applied, the distance value between the switch states needs to be determined according to the switch states.
For example, the two-stage AC-AC matrix converter of FIG. 2 of the present invention may have S at the inverter stage Ap 、S An Are a group S Bp 、S Bn The control is performed for one group, and the driving pulse meets the principle that one group is turned on and the other group is turned off. Meanwhile, the on-off of the rectifier stage and the inverter stage switching tube also needs to ensure the synchronism.
Fig. 3 shows a calculation flow chart of the ant colony algorithm-based ac-ac matrix converter for obtaining the optimal switch state combination. Firstly, initializing an ant colony algorithm; then, determining the distance between the switch states according to the switch on-off rule; randomly placing ants to any on-off state; selecting the switching state of the next alternating current-alternating current matrix converter for each ant, and calculating the concentration of the pheromone; then judging whether all the switch states are traversed, if the traversal is finished, updating the pheromone table, and if not, continuously selecting the next switch state until all the switch states are traversed; and then, judging whether the maximum iteration times of the ant colony algorithm are finished or not, if so, obtaining a global optimal switch combination state, otherwise, executing the ant colony algorithm again until the maximum iteration times are finished.
The number of ants in the ant colony is m, the number of switches in the AC-AC matrix converter is n, and each switch can be represented as SW 1 ,SW 2 ,…,SW n Each switch has two states, on and off, expressed as SW 1-1 /SW 1-0 ，SW 2-1 /SW 2-0 ,…,SW n-1 /SW n-0 The ant needs to traverse n switches and 2n switch states, and finally finds the optimal solution of the on-off conditions of the n switches. According to the experimental result, m is set to be 1.5 times of 2n, namely m =3n, so that the global optimal solution can be obtained quickly, and local improper convergence is prevented. The distance between the switch state i and the switch state j is set as d ij (i, j =1,2, \8230;, 2 n), in particular, the distance between the different states of one and the same switch is set to a maximum value, thereby expressing that one and the same switch can only have one state, either on or off, preferably the distance between the different states of one and the same switch is set to infinity. the concentration of pheromone on the connection path between the switch state i and the switch state j at the time of tc is tau ij (tc). At the initial time, the pheromone concentration on each switch state connecting path is the same and is tau ij (tc) = τ 0. Then the ants will select the circuit according to a certain probability,
representing the probability of ant q transitioning from switch state i to switch state j at time tc.
Wherein,
representing the desired degree of ant transfer from switch state i to switch state j, as a heuristic function,
allow com for ants to access the set of switch states, if switch state j belongs to allow com Then, then
If the switch state j does not belong to all com Then->
Mu means letterThe larger the value of the pheromone importance factor, the larger the effect of the pheromone concentration in the transfer is; theta is an important degree factor of the heuristic function, the larger the value of theta indicates that the heuristic function has larger effect in transfer, and ants can be transferred to a switch state with short distance with higher probability;
first, d ij The calculation method is as follows:
then, in order to further improve the calculation efficiency and accuracy of the ant colony algorithm, d is calculated ij Making a correction when j and
when any switch state is not the same, judging whether the switches respectively corresponding to the switch state i and the switch state j are in a mutual exclusion relationship:
if the two are mutually exclusive, continuously judging whether the current switch state i and the switch state j have the same state indication, namely, the two states are on or off, and if the indication states are the same, d ij = ∞; if the indication states are different, it indicates that the switch state i and the switch state j meet the mutual exclusion requirement, and if one switch is on, the two states are necessarily simultaneously existed, so that the distance between the switch state i and the switch state j at the moment is set as the minimum value, which can be 1.
If the switches corresponding to the switch states i and j are not mutually exclusive, the distance between the switch states i and j is gamma, and gamma is a constant larger than 1.
Thus, d ij The final calculation method of (a) is as follows:
ants were placed on different switch states.
Initially, allow com There are 2n-1 elements, i.e. all other switch states except the one from ant q, all over time com The elements in (b) are continuously reduced until the elements are empty, which indicates that all switch states are completely accessed. When the ants release the pheromone, the pheromone on each switch state connecting path gradually disappears, and after all the ants finish one-time circulation, the concentration of the pheromone on each switch state connecting path is updated in real time, which specifically comprises the following steps:
in the formula,
releasing pheromone concentration on a connection path of a switch state i and a switch state j for the qth ant; delta tau ij The sum of the concentration of released pheromones of all ants on the connection path of the switch state i and the switch state j; the parameter epsilon represents the volatilization degree of the pheromone, and epsilon is more than 0 and less than 1; />
Wherein Q is a constant, typically having a value of [20, 2000%]L represents the total amount of pheromone released by ants in one cycle q The path length of the q-th ant is expressed by the number of nodes.
The maximum iteration number of the whole ant colony algorithm is set to iter _ max, and the value range of the maximum iteration number is usually [100, 600], so that premature convergence is not easy to occur, and a globally optimal solution can be found, preferably, the value of iter _ max is 220.
While one embodiment of the present invention has been described in detail, the description is only a preferred embodiment of the present invention and should not be taken as limiting the scope of the invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.
Claims (6)
1. A power control method for a rail transit vehicle-mounted power grid is characterized in that,
step 1: initializing an ant colony algorithm according to the number of switches of the AC-AC matrix converter;
step 2: determining the distance between the switch states according to the on-off rule of the switch in the AC-AC matrix converter, and placing ants on different switch states;
and step 3: the global optimal switch state combination module calculates the predicted power error of the alternating current-alternating current matrix converter every time the ants complete traversal;
and 4, step 4: after the maximum iteration times are finished, obtaining the optimal switching state combination of the current AC-AC matrix converter according to the obtained minimum global prediction power error of the AC-AC matrix converter;
and 5: adjusting the alternating current-alternating current matrix converter according to the optimal switching state combination obtained in the step 4 to ensure that the vehicle-mounted power grid provides stable alternating current;
the step 1 specifically comprises the following steps: the number of ants in the ant colony is m, the number of switches in the AC-AC matrix converter is n, and each switch is represented by SW 1 ，SW 2 ，…，SW n Each switch has two states, on and off, expressed as SW 1-1 /SW 1-0 ，SW 2-1 /SW 2-0 ，…，SW n-1 /SW n-0 The ant needs to traverse n switches and 2n switch states, and finally finds the optimal solution of the on-off conditions of the n switches;
the concentration of pheromone on a connecting path between the switch state i and the switch state j at the time tc is tau ij (tc); at the initial time, the pheromone concentration on each switch state connecting path is the same and is tau ij (tc)＝τ 0 (ii) a Then the ants will select the circuit according to a certain probability,
representing the probability of the ant q transferring from the switch state i to the switch state j at the tc moment;
wherein,
representing the desired degree of ant transfer from switch state i to switch state j for a heuristic function,
allow com for ants to access the set of switch states, if switch state j belongs to allow com Then, then
If the switch state j does not belong to all com Then->
Mu represents a pheromone importance factor, and a larger value indicates that the pheromone concentration has a larger effect in metastasis; theta is a factor of importance degree of the heuristic function, and the larger the value of theta is, the larger the effect of the heuristic function in transfer is; the distance between the switch state i and the switch state j is set as d ij (i，j＝1，2，…，2n)；
The step 2 specifically comprises the following steps: d ij The calculation method of (A) is as follows:
the step 3 specifically comprises the following steps: step 3.1: collecting corresponding voltage and current at the input end of the matrix converter, and transmitting the corresponding voltage and current to the global optimal switch state combination module; step 3.2: the global optimal switch state combination module calculates the next beat of the kth beat sampling point, namely the output power of the kth +1 beat matrix converter according to the power prediction model of the alternating current-alternating current matrix converter; step 3.3: transmitting the voltage and the current of the k +1 th beat output end of the AC-AC matrix converter to a global optimal switch state combination module; step 3.4: the global optimal switch state combination module calculates the actual power of the output end of the alternating current-alternating current matrix converter; step 3.5: the global optimal switch state combination module calculates the predicted power error of the alternating current-alternating current matrix converter according to the calculation results of the step 3.2 and the step 3.4;
step 3 also includes: the predicted power calculation formula is:
2. The method of claim 1, further characterized by initially allowing com 2n-1 elements in the ant represent all the switch states except the switch state from which the ant q starts; all over time com The element in (1) is continuously reduced until the element is empty, which indicates the positionThe access is finished in all the switch states; when the ants release the pheromone, the pheromone on each switch state connecting path gradually disappears, and after all the ants finish one-time circulation, the concentration of the pheromone on each switch state connecting path is updated in real time, which specifically comprises the following steps:
in the formula,
releasing pheromone concentration for the qth ant on a connection path between a switch state i and a switch state j; delta tau ij The sum of the concentration of pheromones released by all ants on the connection path of the switch state i and the switch state j; the parameter epsilon represents the volatilization degree of the pheromone, and epsilon is more than 0 and less than 1;
3. The method according to claim 1, wherein step 4 is specifically: setting an objective function as min (err), wherein err represents the power prediction error variance of the AC-AC matrix converter, solving the minimum value of the prediction power error, and selecting the optimal switch state combination according to the obtained minimum value of the prediction power error.
4. A power control system for a rail transit onboard electrical network, which system is capable of implementing the power control method for a rail transit onboard electrical network according to any of claims 1 to 3.
5. A power device for a rail transit vehicle-mounted power grid, which comprises an input parameter module, an alternating current-alternating current matrix converter and a global optimal switch state combination module, and can realize the power control method for the rail transit vehicle-mounted power grid according to any one of claims 1 to 3.
6. A storage medium, on which a computer program is stored, which is capable of implementing the power control method for a rail transit on-board electrical network of any of claims 1-3.
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| CN107612409A (en) * | 2017-09-27 | 2018-01-19 | 西安理工大学 | Simplify matrix converter model predictive control method with magnetic saturation control |
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| CN109639153A (en) * | 2018-12-26 | 2019-04-16 | 北京航空航天大学 | A kind of model predictive control method of the source Quasi-Z indirect matrix converter |
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