CN114069646A - Reactive compensation optimization method based on transformer substation operation data - Google Patents
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Abstract
The invention discloses a reactive compensation optimization method based on transformer substation operation data, which comprises the steps of firstly, obtaining voltage, active power and reactive power data of a 10kV bus side according to data obtained by equipment manufacturers or field tests; selecting typical data of bus voltage, active power and reactive power according to the seasons; the method comprises the steps of taking the minimum residual reactive power as a target function, taking the reactive power non-reversal transmission, the reactive power compensator switching times and the switching intervals as constraint conditions, adopting an improved particle swarm algorithm to carry out optimization solution, determining the optimal scheme of reactive power compensation device grouping and capacity, establishing weighted comprehensive evaluation coefficients of three factors of comprehensive loss, investment and position, comparing the comprehensive optimization evaluation coefficients under each optimization scheme, selecting the scheme with the minimum comprehensive optimization evaluation coefficient as the optimal scheme, and realizing reactive power compensation optimization. The method can improve the power factor and the voltage level, and improve the economical efficiency and the reliability of the operation of the power grid while ensuring the safe and stable operation of the power supply and utilization equipment.
Description
Technical Field
The invention relates to the technical field of power quality control of power systems, in particular to a reactive power compensation optimization method based on transformer substation operation data.
Background
The reactive power deficiency of the power system can reduce the power factor of the system, further increase the loss of a power supply line, reduce the utilization rate of power generation and supply equipment, and when the power factor is lower than the national standard, an electric power company can carry out fine payment or even power failure on the power supply line. At present, a method of centralized compensation of a transformer substation is usually selected for a power network, reactive compensation is performed on a 10kV bus side, and compensation equipment comprises a Static Var Compensator (SVC), a parallel capacitor, a synchronous phase modulator, a static synchronous compensator (STATCOM) and the like. The optimization of the reactive compensation of the transformer substation relates to various aspects, including the type of a reactive compensation device, the reactive compensation capacity, an installation site and grouping, so that the voltage of a bus is increased after the compensation is performed, the power factor is increased, the related indexes of the electric energy quality are effectively improved, and the safe operation of a system is ensured.
In the prior art, various problems can be encountered in the process of formulating the reactive power compensation scheme of the transformer substation, firstly, historical data is selected, and the fact that power users generally have seasonality and the load properties and the power consumption of the power users in different seasons are generally different is considered, so that the historical data of the whole year of reactive power operation is required to be used as a basis of reactive power optimization data under strict conditions, but the huge historical data undoubtedly increases the difficulty of reactive power compensation optimization, and the formulating of the reactive power compensation scheme is complicated; secondly, selecting reactive compensation capacity and grouping, wherein the larger the reactive compensation capacity is, the larger the investment is; the more the grouping is, the more the switching switches are, so that the economical efficiency and the safe reliability of the reactive compensation scheme are reduced; the reactive power is ensured not to be transmitted reversely again, when the reactive compensation quantity is larger than the reactive requirement, redundant reactive power can be transmitted to the power grid reversely, but the power factor is calculated to be 'reverse transmission positive memory', so that the power factor is reduced, and a series of hazards are brought; in addition, daily switching frequency limitation of the reactive compensator is also considered, overvoltage, impact current and the like generated in the switching process threaten safe and stable operation of a power grid on one hand, insulation aging and capacity attenuation of the capacitor are accelerated on the other hand, and the service life of the capacitor is shortened.
Disclosure of Invention
The invention aims to provide a reactive compensation optimization method based on transformer substation operation data, which can improve the power factor and the voltage level, ensure the safe and stable operation of power supply and utilization equipment and improve the operation economy and reliability of a power grid.
The purpose of the invention is realized by the following technical scheme:
a reactive compensation optimization method based on substation operation data comprises the following steps:
and 4, establishing weighted comprehensive evaluation coefficients of the three factors of comprehensive loss, investment and position, comparing the comprehensive optimization evaluation coefficients under each optimization scheme, and selecting the scheme with the minimum coefficient as the optimal scheme to realize reactive compensation optimization.
According to the technical scheme provided by the invention, the method can improve the power factor and the voltage level, and improve the economical efficiency and the reliability of the operation of the power grid while ensuring the safe and stable operation of the power supply and utilization equipment.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a reactive compensation optimization method based on substation operation data according to an embodiment of the present invention;
FIG. 2 is a typical data operating curve of voltage, active power and reactive power in an embodiment of the present invention;
FIG. 3 is a schematic diagram of an iterative process of an improved particle swarm algorithm according to an embodiment of the present invention;
FIG. 4 is a diagram showing reactive compensation effect in an example of the present invention;
fig. 5 is a diagram showing the effect of the control strategy of the reactive power compensation device in the illustrated example of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, not all embodiments, and this does not limit the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flow chart of a reactive compensation optimization method based on substation operation data according to an embodiment of the present invention, where the method includes:
in this step, the calculation formula of the remaining reactive power is as follows:
in the formula, kvarh1 is the residual reactive power after compensation; n is the number of sampling points; q1The compensated reactive power is obtained; t is tinterIs the sampling time interval.
In the concrete implementation, the reactive compensation switching of the reactive compensation device is carried out according to the following principle:
(1) non-reversing reactive power transmission
Reactive power non-reverse transmission requires that reactive power compensated by the reactive compensation device does not exceed original reactive power data of the transformer substation, and the reactive power of the transformer substation is not compensated when the reactive power is negative, so that if the original reactive power data of the transformer substation is larger than or equal to the maximum compensation capacity of the reactive compensation device, the maximum compensation capacity is adopted for the data; after screening, if the original reactive power data of the transformer substation are larger than or equal to the secondary large capacity compensated by the reactive compensation device, compensating the data by adopting the secondary large capacity; sequentially screening … …; finally, if the reactive power of the transformer substation is negative, the reactive power compensation device carries out compensation;
(2) the switching time interval is at least 30min
The cut reactive compensation device can complete the charging and discharging process after 30min, so that the next investment is not influenced; therefore, each group of reactive compensation devices is required to be incapable of being switched continuously within 30min, and within 30min, if the reactive compensation devices are in a switching state at a first data sampling point, in a cutting state at a next data sampling point and in a switching state within the remaining time, the reactive compensation devices are all in the cutting state within the remaining time, so that the switching time interval should meet the following conditions:
Tinterval≥30min
in the formula, TintervalSwitching time intervals for the reactive compensator;
(3) principle that switching times of reactive compensation device is less than upper limit
The switching switch can be damaged by frequent switching of the reactive compensation device, the service life of the capacitor is reduced, the maximum switching times of each group of reactive compensation devices per day needs to be restrained, if the times is b, switching-in and switching-off are both switching actions of the reactive compensation devices, firstly, the times of each day switching-in of the reactive compensation devices are found, if the times are less than or equal to b/2-1, the original switching strategy is kept, otherwise, subscripts of state change points of each day of the reactive compensation devices are found; then, working intervals of the reactive power compensation device in each day are found based on the working intervals, and the lengths of the working intervals are sequenced; finally, because some working intervals may run through two days, b/2-1 intervals which are longest every day need to be screened out, and the rest time is not working, namely, the cutting state; therefore, the switching times of the reactive power compensation device should meet the following conditions:
in the formula (sw)i dSwitching times of the ith group of reactive compensator on the d day; swmaxThe maximum switching times of the reactive compensator every day are set according to actual needs.
In addition, the improved particle swarm algorithm specifically comprises:
the d-dimension velocity updating formula of the i particle is expressed as:
the d-dimension position updating formula of the i particle is expressed as follows:
wherein v is the velocity of the particle; x is the position of the particle; w is the inertial weight; k is the current iteration number; id is the d dimension of the ith particle; gbest is the individual extremum of the particle; zbest is the global extremum of the population; c. C1、c2Is a learning factor; r is1、r2Is a random number between 0 and 1; and w is the weight of the particle swarm algorithm.
In order to accelerate the convergence speed, the particle swarm algorithm weight w is improved as follows:
in the formula, wmax、wminThe inertia weight is the maximum value and the small value respectively; k is the current iteration number; k is the total number of iterations.
The particle swarm algorithm weight w is larger during initial iteration, the particle speed is also larger, and the global search capability is strong; the continuous iteration reduces the weight w of the particle swarm algorithm, the speed of the particles is reduced, the local searching capability is strong, the operation rate is improved, and the convergence process is accelerated.
And 4, establishing weighted comprehensive evaluation coefficients of the three factors of comprehensive loss, investment and position, comparing the comprehensive optimization evaluation coefficients under each optimization scheme, and selecting the scheme with the minimum coefficient as the optimal scheme to realize reactive compensation optimization.
In this step, the evaluation method for minimizing the loss is:
in the formula, kvarh1 is the residual reactive power after compensation; kvarh is reactive power before compensation;
the evaluation method with the minimum investment comprises the following steps:
in the formula, QcThe total capacity is compensated for reactive power; qmaxThe maximum reactive demand before compensation;
the position optimal evaluation method comprises the following steps:
z is 0.8, and the position is selected to be optimal; the selection of the Z-1 representative position is moderate; z is not proper for position selection as 1.2;
and then the weighted comprehensive optimization evaluation coefficient F combining the loss, investment and position is expressed as:
F＝α*X+β*Y+γ*Z
in the formula, alpha, beta and gamma are weight coefficients, and the larger alpha is, the larger the compensation effect proportion is; the larger beta is, the larger the economic benefit ratio is; the larger the gamma is, the larger the selection proportion of the position is; the values of alpha, beta and gamma are set according to specific conditions.
And comparing the comprehensive optimization evaluation coefficients F under the optimization schemes, wherein the smaller the F value is, the better the F value is.
Because the larger the compensation capacity, the larger the investment; the more the grouping is, the more the switching switches are, and the economical efficiency is poor; the less safe the position selection is inappropriate.
It is noted that those skilled in the art will recognize that embodiments of the present invention are not described in detail herein.
For convenience of understanding, the following description is made with reference to specific examples, it should be noted that the values used in the following examples are only examples, and a user may make corresponding changes according to actual needs, and only a few of the following schemes are referred to for comparison, and the best scheme is selected for description, in this example, the data sampling time interval is 15min, the data source is a certain substation 10kV bus voltage and a 10kV total incoming line power, and the reactive compensation scheme is formulated based on the data:
(1) obtaining the voltage u of the 10kV bus side according to data obtained by equipment manufacturers or field tests0(t) active Power p0(t) and reactive power q0(t)。
(2) Typical data of four weeks are selected according to the quarterly, the typical data comprise voltage u (t), active power p (t) and reactive power q (t) on the 10kV bus side, typical data operation curves of the voltage, the active power and the reactive power are shown in fig. 2, wherein (1) is a voltage data operation curve, and (2) is a power data operation curve, the statistical results of the voltage and the power operation are shown in the following tables 1 and 2, and the maximum reactive demand of the transformer substation is 6.85 Mvar.
Table 1 bus running voltage trend statistical report
| I. Maximum (kV) | I. Minimum (kV) | I. Mean value (kV) | I.95% probability value (kV) |
| II.10.55 | II.9.81 | II.10.24 | II.10.49 |
TABLE 2 running power statistics report
(3) And (3) taking the minimum residual reactive power as an objective function, taking the reactive power non-reversal transmission, the switching times and the switching time interval of the reactive power compensator as constraint conditions, and adopting an improved particle swarm algorithm to carry out optimization solution to obtain an optimization scheme of the grouping and capacity of the reactive power compensation device.
The reactive compensation devices are grouped into 2 groups, 3 groups and 4 groups, the optimal compensation capacity and the comprehensive optimization evaluation coefficient are calculated respectively, the calculation result is shown in the following table 3, 2 groups of reactive compensation devices are installed as an example, fig. 3 is a schematic diagram of an iteration process of an improved particle swarm optimization algorithm in the example provided by the invention, fig. 4 is a diagram showing a reactive compensation effect in the example provided by the invention, the diagram includes (1) a reactive compensation quantity and load reactive comparison diagram and (2) comparison diagrams before and after power factor compensation, fig. 5 is a diagram showing a control strategy effect of the reactive compensation device in the example provided by the invention, and the diagram includes (1) a switching state diagram of each group of reactive compensation devices, (2) the number of switching times per group of reactive compensation devices per group and (3) the accumulated operating time of each group of reactive compensation devices per group.
(4) And establishing weighted comprehensive evaluation coefficients of the three factors of comprehensive loss, investment and position, comparing the comprehensive optimization evaluation coefficients under each optimization scheme, and selecting the scheme with the minimum coefficient as the optimal scheme to realize reactive compensation optimization.
TABLE 3 reactive compensation optimization scheme
The final comprehensive optimization evaluation coefficients obtained by the 3 schemes in the step (3) are respectively F2＝1.5068、F3＝1.8617、F42.1942, the value of the first scheme is the minimum, so the compensation effect of the first scheme is the best.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims. The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
Claims (3)
1. A reactive compensation optimization method based on substation operation data is characterized by comprising the following steps:
step 1, obtaining voltage, active power and reactive power data of a 10kV bus side according to data obtained by equipment manufacturers or field tests;
step 2, selecting typical data of bus voltage, active power and reactive power in one year, and selecting a data sequence with a one-week time length at least according to each quarter;
step 3, taking the minimum residual reactive power as an objective function, taking the reactive power non-reversal transmission, the switching times and the switching time interval of the reactive power compensation device as constraint conditions, and adopting an improved particle swarm algorithm to carry out optimization solution to obtain an optimization scheme of the grouping and capacity of the reactive power compensation device;
and 4, establishing weighted comprehensive evaluation coefficients of the three factors of comprehensive loss, investment and position, comparing the comprehensive optimization evaluation coefficients under each optimization scheme, and selecting the scheme with the minimum coefficient as the optimal scheme to realize reactive compensation optimization.
2. The reactive compensation optimization method based on the substation operation data according to claim 1, wherein in step 3, the calculation formula of the residual reactive power is as follows:
in the formula, kvarh1 is the residual reactive power after compensation; n is the number of sampling points; q1The compensated reactive power is obtained; t is tinterIs a sampling time interval;
the reactive compensation switching of the reactive compensation device is carried out according to the following principle:
(1) non-reversing reactive power transmission
Reactive power non-reverse transmission requires that reactive power compensated by the reactive compensation device does not exceed original reactive power data of the transformer substation, and the reactive power of the transformer substation is not compensated when the reactive power is negative, so that if the original reactive power data of the transformer substation is larger than or equal to the maximum compensation capacity of the reactive compensation device, the maximum compensation capacity is adopted for the data; after screening, if the original reactive power data of the transformer substation are larger than or equal to the secondary large capacity compensated by the reactive compensation device, compensating the data by adopting the secondary large capacity; sequentially screening … …; finally, if the reactive power of the transformer substation is negative, the reactive power compensation device carries out compensation;
(2) the switching time interval is at least 30min
The cut reactive compensation device can complete the charging and discharging process after 30min, so that the next investment is not influenced; therefore, each group of reactive compensation devices is required to be incapable of being switched continuously within 30min, and within 30min, if the reactive compensation devices are in a switching state at a first data sampling point, in a cutting state at a next data sampling point and in a switching state within the remaining time, the reactive compensation devices are all in the cutting state within the remaining time, so that the switching time interval should meet the following conditions:
Tinterval≥30min
in the formula, TintervalSwitching time intervals for the reactive compensator;
(3) principle that switching times of reactive compensation device is less than upper limit
The switching switch can be damaged by frequent switching of the reactive compensation device, the service life of the capacitor is reduced, the maximum switching times of each group of reactive compensation devices per day needs to be restrained, if the times is b, switching-in and switching-off are both switching actions of the reactive compensation devices, firstly, the times of each day switching-in of the reactive compensation devices are found, if the times are less than or equal to b/2-1, the original switching strategy is kept, otherwise, subscripts of state change points of each day of the reactive compensation devices are found; then, working intervals of the reactive power compensation device in each day are found based on the working intervals, and the lengths of the working intervals are sequenced; finally, because some working intervals may run through two days, b/2-1 intervals which are longest every day need to be screened out, and the rest time is not working, namely, the cutting state; therefore, the switching times of the reactive power compensation device should meet the following conditions:
in the formula (sw)i dSwitching times of the ith group of reactive compensator on the d day; swmaxThe maximum switching times of the reactive compensator every day are set according to actual needs.
3. The reactive compensation optimization method based on the substation operation data according to claim 1, wherein in step 4, the evaluation method of the minimum loss is as follows:
in the formula, kvarh1 is the residual reactive power after compensation; kvarh is reactive power before compensation;
the evaluation method with the minimum investment comprises the following steps:
in the formula, QcThe total capacity is compensated for reactive power; qmaxThe maximum reactive demand before compensation;
the position optimal evaluation method comprises the following steps:
z is 0.8, and the position is selected to be optimal; the selection of the Z-1 representative position is moderate; z is not proper for position selection as 1.2;
and then the weighted comprehensive optimization evaluation coefficient F combining the loss, investment and position is expressed as:
F＝α*X+β*Y+γ*Z
in the formula, alpha, beta and gamma are weight coefficients, and the larger alpha is, the larger the compensation effect proportion is; the larger beta is, the larger the economic benefit ratio is; the larger the gamma is, the larger the selection proportion of the position is; the values of alpha, beta and gamma are set according to specific conditions;
the smaller the weighted comprehensive evaluation coefficient F value is, the better the weighted comprehensive evaluation coefficient F value is; because the larger the compensation capacity, the larger the investment; the more the grouping is, the more the switching switches are, and the economical efficiency is poor; the less safe the position selection is inappropriate.
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