CN107658889A - A kind of low-pressure reactive compensation computational methods based on modified particle swarm optiziation - Google Patents
A kind of low-pressure reactive compensation computational methods based on modified particle swarm optiziation Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/18—Arrangements for adjusting, eliminating or compensating reactive power in networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/30—Reactive power compensation
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Abstract
The present invention relates to reactive power compensation technology field, specifically a kind of low-pressure reactive compensation computational methods based on modified particle swarm optiziation, based on the optimization to inertia weight ω, Studying factors c parameters in multi-objective particle swarm algorithm, and by power factorWith voltage distortion rate THD as object function, the compensation capacity Q after optimization is obtainedc, then the compensation capacity Q that will be obtainedcPut into reactive power compensator, can not only reduce amplification of the reactive-load compensation to harmonic wave, reduce the influence to electrical network parameter, so as to improve the effect of reactive-load compensation.
Description
Technical Field
The invention relates to the technical field of reactive compensation, in particular to a low-voltage reactive compensation calculation method based on an improved particle swarm algorithm.
Background
The reactive power is an integral part of ensuring the quality of electric energy and the operation of the power system, as well as the active power. The reactive power can increase the current in the line in the transmission process of the line, so that the loss of equipment and the line is increased, a large amount of loss of active power is caused, meanwhile, the power factor is low, the terminal voltage of a load is reduced, even the terminal voltage of a user cannot reach a specified value, the power equipment cannot fully play the role of the load, and the great waste of energy is caused. The power grid constructed in China, particularly the vast rural power grid, generally has the conditions of low power factor and large power grid loss, and the main reason of the phenomenon is that the power factor is low and the terminal voltage is low due to the fact that the circuit design of numerous inductive loads and the like is lagged behind.
Disclosure of Invention
Aiming at the technical problems that the power factor is low and the power equipment cannot effectively play the role, the invention provides a low-voltage reactive power compensation calculation method based on an improved particle swarm algorithm.
In order to solve the technical problems, the invention adopts the following technical scheme:
a low-voltage reactive compensation calculation method based on an improved particle swarm algorithm comprises the following steps:
s1, initializing the position and speed of a population, and optimizing parameters in a multi-target particle swarm algorithm;
s2, calculating fromToRequired compensation capacity Q c1 ；
S3, calculating fromToThe required compensation capacity is selected as the compensation capacity Q c2 ；
S4, according to the compensation capacity Q c1 Calculating power factorAnd a voltage distortion rate THD;
s5, calculating the power factorAnd the sum voltage distortion rate THD is used as an objective function, the multi-objective evaluation function value is calculated and stored in an array Q c(i) The preparation method comprises the following steps of (1) performing;
s6, combining the array Q c(i) Q obtained in (1) c1 Plus the installed capacitance Q in the reactive power compensator 0 To obtain the compensation capacity Q c1 ′；
S7, compensating the capacity Q c1 ' AND Compensation Capacity Q c2 By comparison, if Q c1 ′>Q c2 Output the optimal compensation capacity Q c1 ', if Q c1 ′<Q c2 And returning to the step S4 for recalculation until the optimal compensation capacity Q is obtained c1 ' and the obtained compensation capacity Q c1 ' putting into a reactive power compensation device.
Further, the step S1 specifically includes:
s1-1, initializing the population size of a particle swarm to be N, setting an inertia factor to be omega, and setting learning factors to be c respectively 1 And c 2 The maximum iteration number of the algorithm is T max ；
S1-2. Speed v of random initialization search point i And position p thereof i Wherein i =1,2 \ 8230n;
s1-3, calculating each particle x i If the fitness value is higher than the current individual extremum of the particle, the position of the particle is assigned to p i And updating the individual extremum;
s1-4, if the highest individual extreme value of all the particles is higher than the current global extreme value of the particles, assigning the position of the particle to p x And proceeding to the next iteration until reaching the preset maximum iteration time T max 。
Further, in the process of carrying out optimization calculation on parameters in the multi-target particle swarm optimization, dynamically updating the changing inertia weight omega and the acceleration factor c.
Further, the formula for the dynamically updated change of the inertial weight ω is:
where T is the number of iterations, ω i Is an initial value of the inertial weight ω, ω f The final value of the inertial weight ω.
Further, the formula for the dynamic update change of the acceleration factor c is:
where T is the number of iterations, c i1 And c i2 As a learning factor c 1 And c 2 Initial value of c f1 And c f2 For learning the factor c 1 And c 2 The final value of (c).
Further, in the process that the particles mutually learn and adjust the flight directions, perturbation is carried out on non-inferior solutions to generate parent particles for the cross operation, and the expression of the non-inferior solution perturbation is as follows:
wherein, the first and the second end of the pipe are connected with each other,andrespectively representing non-inferior solutions x with sparse portions ij Generated by a perturbation factor qTwo particles, which are represented as the jth dimension of the ith particle, wherein r represents Gaussian white noise with the mean value of 0 and the variance of 1;represents the mean of the distances between all neighboring non-inferior solutions.
Further, in step S2 and step S3, use is made of, respectively:
calculating to obtain compensation capacity Q c1 And Q c2 Where P is the effective power, Q c1 And Q c2 In order to have the required compensation capacity,in order to compensate for the power factor before the compensation,andin order to compensate for the power factor after the compensation,
further, in step S4, a compensated power factor is calculatedIncludes calculating the compensation capacity Q c1 Substituting into a formula:
determining compensated power factorWherein, P is the effective power,is the power factor before compensation.
Further, in step S4, the compensated grid harmonic distortion rate THD is calculated according to the following formula,
wherein h is the highest harmonic order, k is the harmonic order, | v 1 L is the effective value of the fundamental voltage, | v k And | is the effective value of the k-th harmonic voltage.
Further, the step S5 specifically includes:
s5-1, establishing power factorThe objective function of (a) is:
in the formulaFor power factor before compensation, Q c For required compensation capacity, P is the system effective power;
s5-2, establishing an objective function of the voltage harmonic distortion rate THD as follows:
wherein h is the highest harmonic frequency, k is the harmonic frequency, | v 1 L is the effective value of the fundamental voltage, | v k And | is the effective value of the k-th harmonic voltage.
S5-3, judging the value of the voltage harmonic distortion rate THD, and if the THD obtained by calculation is less than or equal to 5 percent, obtaining all Q meeting the conditions c1 Calculating an evaluation function value; if the THD obtained by calculation is more than 5%, multiplying the THD by 1000 and then calculating an evaluation function value;
s5-4, adjusting a target function through an evaluation function, namely the proportion of the medium weight coefficient according to the condition that the reactive power compensation device mainly improves the power factor or mainly improves the THD (total harmonic distortion) minimum, and obtaining the compensation capacity Q c1 There is an array Q c(i) In (1).
Compared with the prior art, the method has the following advantages and positive effects:
the low-voltage reactive compensation calculation method provided by the invention aims at the reactive compensation problem of the low-voltage side power grid, can effectively improve the power factor and the reactive compensation effect, and reduces the amplification effect of the reactive compensation on harmonic waves, namely the influence on the power grid parameters.
Drawings
FIG. 1 is a flow chart of the present invention;
fig. 2 is a schematic diagram of the equivalent circuit principle of the present invention.
Detailed Description
The technical solution proposed by the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments. Advantages and features of the present invention will become apparent from the following description and from the claims. It is to be noted that the drawings are in a very simplified form and are each provided with a non-precision ratio for the purpose of convenience and clarity in assisting in describing the embodiments of the present invention.
The invention relates to a low-voltage reactive power compensation calculation method based on an improved particle swarm algorithm, which is mainly based on the optimization of parameters such as inertia weight omega, learning factor c and the like in a multi-target particle swarm algorithm and the combination of power factorsThe sum voltage distortion rate THD is used as an objective function to calculate the optimized compensation capacity Q c The calculated compensation capacity Q c When the reactive power compensation device is put into the reactive power compensation device, the influence on the parameters of the power grid can be reduced, and the reactive power compensation effect is improved.
Referring to fig. 1, the low-voltage reactive compensation calculation method based on the improved particle swarm optimization comprises the following steps:
initializing the position and speed of a population, and optimizing parameters in a multi-target particle swarm algorithm;
the process specifically comprises the following steps:
s1-1, initializing the population scale of a particle swarm to be N, setting an inertia factor to be omega, and setting learning factors to be c respectively 1 And c 2 The maximum iteration number of the algorithm is T max ；
S1-2. Velocity v of random initialization search point i And position p thereof i Wherein i =1,2 \ 8230n;
s1-3, calculating each particle x i If the fitness value is higher than the current individual extremum of the particle, the position of the particle is assigned to p i And updating the individual extremum;
s1-4, if the highest individual extreme value of all the particles is higher than the current global extreme value of the particles, assigning the position of the particle to p x And proceeding to the next iteration until reaching the preset maximum iteration time T max 。
In the iterative process of the algorithm, in order to better balance the global optimization capability and the local optimization capability of the algorithm and improve the convergence rate, the dynamically updated and changed inertial weight omega and the acceleration factor c are adopted in the process of carrying out optimization calculation on parameters in the multi-target particle swarm optimization.
The formula for the dynamically updated change of the inertial weight ω is:
where T is the number of iterations, ω i Is an initial value of the inertial weight ω, ω f The final value of the inertial weight ω.
The formula for the dynamic update change of the acceleration factor c is:
wherein T is the number of iterations, c i1 And c i2 For learning the factor c 1 And c 2 Initial value of c f1 And c f2 For learning the factor c 1 And c 2 The final value of (c).
In the process of mutually learning and adjusting the flight direction, a large number of particles are possibly gathered together, so that Pareto front sparse parts appear in uneven distribution, for this reason, parent particles used for cross operation are generated by disturbing non-inferior solutions, and the expression of the non-inferior solution disturbance is as follows:
wherein the content of the first and second substances,andrespectively representing non-inferior solutions x with sparse portions ij Two particles generated by a perturbation factor q representing the jth dimension of the ith particle, r representing bothGaussian white noise with value 0 and variance 1;represents the mean of the distances between all neighboring non-inferior solutions.
Step two, calculating the slaveToRequired compensation capacity Q c1 ；
Step three, calculating the slaveToThe required compensation capacity is selected as the compensation capacity Q c2 ；
When calculating the compensation capacity, referring to the schematic diagram of the equivalent circuit of fig. 2, the relationship between the power factor before and after compensation and the compensation capacity is:where P is the effective power of the system, Q c In order to have the required compensation capacity,in order to compensate for the power factor before the compensation,is the compensated power factor.
And for calculating the compensation capacity Q in step two and step three c1 And Q c2 Respectively utilizing:
where P is the effective power, measurable, Q c1 And Q c2 In order to have the required compensation capacity,in order to compensate for the power factor before the compensation,andin order to compensate for the power factor after the compensation,the compensation method refers to the power factor (namely the power factor before compensation, which can be measured in actual conditions) when a compensation device is not installed in a low-voltage power grid, and switched capacitance is discrete due to the limitation of the actual conditions, so that the optimal compensation capacity Q is difficult to obtain c So according to the standards stipulated by the state: the power factor is randomly selected from 0.9-1, i.e.
Step four, according to the compensation capacity Q c1 Calculating power factorAnd a voltage distortion rate THD.
Calculating compensated power factor
The obtained compensation capacity Q c1 Substituting into a formula:
determining compensated power factorWherein, P is the effective power,is the power factor before compensation.
Calculating the compensated power grid harmonic distortion rate THD according to the following formula:
wherein h is the highest harmonic frequency, k is the harmonic frequency, | v 1 L is the effective value of the fundamental voltage, | v k And | is the effective value of the k-th harmonic voltage.
Step five, using power factorAnd the sum voltage distortion rate THD is used as an objective function, the multi-objective evaluation function value is calculated and stored in an array Q c(i) Performing the following steps;
further, the process specifically comprises:
s5-1, establishing a power factorThe objective function of (a) is:
in the formulaTo compensate for the power factor, Q c For the required compensation capacity, P is the system effective power;
s5-2, establishing an objective function of the voltage harmonic distortion rate THD as follows:
wherein h is the highest harmonic frequency, k is the harmonic frequency, | v 1 L is effective value of fundamental voltage, | v k And | is the effective value of the k-th harmonic voltage.
S5-3, judging the value of the voltage harmonic distortion rate THD, and according to the regulation of national standard 'harmonic of electric energy quality public power grid GB/T14549-93', judging that the harmonic standard in 400V is not more than 5%, so if the THD obtained by calculation is less than or equal to 5%, obtaining all Q meeting the conditions c1 Calculating an evaluation function value; if the THD obtained by calculation is more than 5%, multiplying the THD by 1000 and then calculating an evaluation function value;
s5-4, adjusting a target function through an evaluation function, namely the proportion of the medium weight coefficient according to the principle that the reactive power compensation device mainly improves the power factor or mainly improves the THD minimum, and obtaining the compensation capacity Q c1 All exist array Q c(i) In (1).
Step six, the array Q is processed c(i) Q obtained in (1) c1 Plus capacitance Q installed in reactive power compensation device 0 To obtain a new compensation capacity Q c1 ′；
Step seven, compensating the capacity Q c1 ' AND Compensation Capacity Q c2 Comparison, if Q c1 ′>Q c2 Output the optimal compensation capacity Q c1 ', if Q c1 ′<Q c2 And returning to the step four to recalculate until the optimal compensation capacity Q is obtained c1 ', and finally, the obtained compensation capacity Q is again used c1 ' is put into a reactive power compensation device, thereby reducing the amplification effect of reactive power compensation on harmonic waves.
It should be understood by those skilled in the art that the present invention may be embodied in many other specific forms without departing from the spirit or scope of the invention, and that the foregoing disclosure only represents a preferred embodiment of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise embodiments disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents, and one skilled in the art can make variations and modifications within the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A low-voltage reactive compensation calculation method based on an improved particle swarm algorithm is characterized in that,
the calculation method comprises the following steps:
s1, initializing the position and speed of a population, and optimizing parameters in a multi-target particle swarm algorithm;
s2, calculating fromToRequired compensation capacity Q c1 ；
S3, calculating fromToThe required compensation capacity is selected as the compensation capacity Q c2 ；
S4, according to the compensation capacity Q c1 Calculating power factorAnd a voltage distortion rate THD;
s5, calculating power factorThe sum voltage distortion rate THD is used as an objective function, the multi-objective evaluation function value is calculated and stored in an array Q c(i) Performing the following steps;
s6, combining the array Q c(i) Q obtained in (1) c1 Plus the installed capacitance Q in the reactive compensation means 0 Obtaining compensated capacity Q' c1 ；
S7, compensating the capacity Q c1 ' AND Compensation Capacity Q c2 By comparison, if Q c1 ′>Q c2 Output the optimal compensation capacity Q c1 ', if Q c1 ′<Q c2 Returning to the step S4 for recalculation until the optimal compensation capacity Q 'is obtained' c1 And the obtained compensation capacity Q' c1 And putting the reactive power compensation device into a reactive power compensation device.
2. The low-voltage reactive compensation calculation method based on the improved particle swarm algorithm according to claim 1, wherein the step S1 specifically comprises:
s1-1, initializing the population size of a particle swarm to be N, setting an inertia factor to be omega, and setting learning factors to be c respectively 1 And c 2 The maximum iteration number of the algorithm is T max ；
S1-2. Velocity v of random initialization search point i And position p thereof i Wherein i =1,2 8230;
s1-3, calculating each particle x i If the fitness value is higher than the current individual extremum of the particle, the position of the particle is assigned to p i And updating the individual extremum;
s1-4, if the highest individual extreme value of all the particles is higher than the current global extreme value of the particles, assigning the position of the particle to p x And performing the next iteration until the preset maximum iteration time T is reached max 。
3. The method for calculating the low-voltage reactive power compensation based on the improved particle swarm optimization according to claim 2, wherein the inertia weight ω and the acceleration factor c which are dynamically updated and changed are adopted in the process of performing the optimization calculation on the parameters in the multi-target particle swarm optimization.
4. The low-voltage reactive compensation calculation method based on the improved particle swarm optimization algorithm is characterized in that the formula of the dynamic update change of the inertia weight omega is as follows:
wherein T is the number of iterations, ω i Is an initial value of the inertial weight ω, ω f The final value of the inertial weight ω.
5. The low-voltage reactive compensation calculation method based on the improved particle swarm optimization algorithm is characterized in that the formula of the dynamic update change of the acceleration factor c is as follows:
wherein T is the number of iterations, c i1 And c i2 For learning the factor c 1 And c 2 Initial value of c f1 And c f2 For learning the factor c 1 And c 2 The final value of (c).
6. The method for calculating the low-voltage reactive compensation based on the improved particle swarm optimization algorithm according to claim 1 or 2, wherein in the process of mutually learning and adjusting the flight directions of the particles, the non-inferior solution disturbance is disturbed to generate parent particles for the cross operation, and the expression of the non-inferior solution disturbance is as follows:
wherein the content of the first and second substances,andrespectively representing non-inferior solutions x with sparse portions ij Two particles generated by the perturbation factor q are expressed as the jth dimension of the ith particle, r represents Gaussian white noise with the mean value of 0 and the variance of 1;represents the mean of the distances between all neighboring non-inferior solutions.
7. The improved particle swarm algorithm-based low-voltage reactive compensation calculation method according to claim 1, characterized in that in step S2 and step S3, use is respectively made of:
calculating to obtain the compensation capacity Q c1 And Q c2 Where P is the effective power, Q c1 And Q c2 In order to have the required compensation capacity,in order to compensate for the power factor before the compensation,andin order to compensate for the power factor after the compensation,
8. the method for calculating the low-voltage reactive power compensation based on the improved particle swarm optimization according to claim 1, wherein in step S4, the compensated power factor is calculatedIncludes calculating the compensation capacity Q c1 Substituting into a formula:
determining compensated power factorWherein, P is the effective power,is the power factor before compensation.
9. The low-voltage reactive power compensation calculation method based on the improved particle swarm optimization algorithm is characterized in that in the step S4, the compensated grid harmonic distortion rate THD is calculated according to the following formula,
wherein h is the highest harmonic order, k is the harmonic order, | v 1 L is the effective value of the fundamental voltage, | v k And | is the effective value of the k-th harmonic voltage.
10. The low-voltage reactive compensation calculation method based on the improved particle swarm algorithm according to claim 1, wherein the step S5 specifically comprises:
s5-1, establishing a power factorThe objective function of (a) is:
in the formulaTo compensate for the power factor, Q c For required compensation capacity, P is the system effective power;
s5-2, establishing an objective function of the voltage harmonic distortion rate THD as follows:
in the formula, h is the highest harmonic order, k is the harmonic order, | v 1 L is effective value of fundamental voltage, | v k And | is the effective value of the k-th harmonic voltage.
S5-3, judging the value of the voltage harmonic distortion rate THD, and if the THD obtained by calculation is less than or equal to 5 percent, obtaining all Q meeting the conditions c1 Calculating an evaluation function value; if the THD obtained by calculation is more than 5%, multiplying the THD by 1000 and then calculating an evaluation function value;
s5-4, according to the reactive power compensation device, the power factor is improvedMainly based on the THD minimum, adjusting the objective function by evaluating the function, namely the proportion of the medium weight coefficient, and obtaining the compensation capacity Q c1 There is an array Q c(i) In (1).
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109038564A (en) * | 2018-08-16 | 2018-12-18 | 东北大学 | It is a kind of that system and method is inhibited based on the sub-synchronous oscillation for improving particle swarm algorithm |
| CN110518597A (en) * | 2019-05-16 | 2019-11-29 | 北京千驷驭电气有限公司 | Reactive-load compensation method, equipment and the computer readable storage medium of middle-voltage network |
| CN110518597B (en) * | 2019-05-16 | 2022-01-11 | 北京千驷驭电气有限公司 | Reactive compensation method and equipment for medium voltage network and computer readable storage medium |
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| CN117543706A (en) * | 2024-01-08 | 2024-02-09 | 国网江西省电力有限公司经济技术研究院 | Hybrid energy storage configuration method and system based on micro-grid wind-solar energy storage system |
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