CN114069646A - A reactive power compensation optimization method based on substation operation data - Google Patents

A reactive power compensation optimization method based on substation operation data Download PDF

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CN114069646A
CN114069646A CN202111271604.6A CN202111271604A CN114069646A CN 114069646 A CN114069646 A CN 114069646A CN 202111271604 A CN202111271604 A CN 202111271604A CN 114069646 A CN114069646 A CN 114069646A
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reactive power
compensation
power compensation
switching
data
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朱明星
文一
潘丽珠
徐斌
程石
仇茹嘉
郑国强
赵瀚
葛江红
纪陈云
彭锦
曹薇薇
胡文超
刘锋
郑浩
张征凯
倪静怡
彭涛
高敏
倪正
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Anhui Anda Qingneng Electric Technology Co ltd
Electric Power Research Institute of State Grid Anhui Electric Power Co Ltd
Anhui University
Anhui Xinli Electric Technology Consulting Co Ltd
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Anhui Anda Qingneng Electric Technology Co ltd
Electric Power Research Institute of State Grid Anhui Electric Power Co Ltd
Anhui University
Anhui Xinli Electric Technology Consulting Co Ltd
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Abstract

本发明公开了一种基于变电站运行数据的无功补偿优化方法，首先根据设备厂商或者现场测试得到的数据，获得10kV母线侧的电压、有功功率和无功功率数据；按照季度选取母线电压、有功功率和无功功率的典型数据；以剩余无功电量最小为目标函数，以无功不倒送、无功补偿器投切次数和投切间隔作为约束条件，采用改进的粒子群算法进行优化求解，确定无功补偿装置分组和容量的最佳方案，建立综合损耗、投资、位置三因素的加权综合评估系数，比较各个优化方案下的综合优化评估系数，选取综合优化评估系数最小的方案作为最佳方案，实现无功补偿优化。上述方法能够提高功率因数与电压水平，在保证供用电设备安全稳定运行的同时，提高电网运行经济性和可靠性。

Figure 202111271604

The invention discloses a reactive power compensation optimization method based on substation operation data. Firstly, according to the data obtained by equipment manufacturers or field tests, the voltage, active power and reactive power data of the 10kV busbar side are obtained; Typical data of power and reactive power; take the minimum remaining reactive power as the objective function, and use the improved particle swarm algorithm to optimize and solve the problem of reactive power not reverse, reactive power compensator switching times and switching interval as constraints , determine the optimal scheme for the grouping and capacity of reactive power compensation devices, establish a weighted comprehensive evaluation coefficient for the three factors of comprehensive loss, investment and location, compare the comprehensive optimization evaluation coefficients under each optimization scheme, and select the scheme with the smallest comprehensive optimization evaluation coefficient as the most comprehensive evaluation coefficient. The best solution to realize the optimization of reactive power compensation. The above method can improve the power factor and the voltage level, and at the same time ensure the safe and stable operation of the power supply and consumption equipment, and improve the operation economy and reliability of the power grid.

Figure 202111271604

Description

Reactive compensation optimization method based on transformer substation operation data
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:
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.
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:
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;
in this step, the calculation formula of the remaining reactive power is as follows:
Figure BDA0003328163060000031
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:
Figure BDA0003328163060000041
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:
Figure BDA0003328163060000042
the d-dimension position updating formula of the i particle is expressed as follows:
Figure BDA0003328163060000043
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:
Figure BDA0003328163060000044
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:
Figure BDA0003328163060000045
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:
Figure BDA0003328163060000051
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
Figure BDA0003328163060000052
Figure BDA0003328163060000061
(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
Figure BDA0003328163060000062
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)

1.一种基于变电站运行数据的无功补偿优化方法，其特征在于，所述方法包括：1. A reactive power compensation optimization method based on substation operation data, characterized in that the method comprises: 步骤1、根据设备厂商或者现场测试得到的数据，获得10kV母线侧的电压、有功功率和无功功率数据；Step 1. Obtain the voltage, active power and reactive power data of the 10kV bus side according to the data obtained by the equipment manufacturer or field test; 步骤2、选取一年中母线电压、有功功率和无功功率的典型数据，数据选取按照每个季度最少选择一周时间长度的数据序列；Step 2. Select the typical data of bus voltage, active power and reactive power in one year, and select the data sequence of at least one week length of each quarter; 步骤3、以剩余无功电量最小为目标函数，以无功不倒送、无功补偿装置投切次数和投切时间间隔作为约束条件，采用改进的粒子群算法进行优化求解，获得无功补偿装置分组和容量的优化方案；Step 3. Taking the minimum remaining reactive power as the objective function, and taking the reactive power non-reverse, the switching times of the reactive power compensation device and the switching time interval as the constraints, the improved particle swarm algorithm is used to optimize the solution to obtain reactive power compensation. Optimization scheme of device grouping and capacity; 步骤4、建立综合损耗、投资、位置三因素的加权综合评估系数，比较各个优化方案下的综合优化评估系数，选取系数最小的方案作为最佳方案，实现无功补偿优化。Step 4: Establish a weighted comprehensive evaluation coefficient for the three factors of comprehensive loss, investment and location, compare the comprehensive optimization evaluation coefficients under each optimization scheme, and select the scheme with the smallest coefficient as the best scheme to realize reactive power compensation optimization. 2.根据权利要求1所述基于变电站运行数据的无功补偿优化方法，其特征在于，在步骤3中，剩余无功电量的计算公式为：2. The reactive power compensation optimization method based on the operation data of the substation according to claim 1, is characterized in that, in step 3, the calculation formula of remaining reactive power is:
Figure FDA0003328163050000011
Figure FDA0003328163050000011
 式中，kvarh1为补偿后剩余的无功电量；N为采样点数；Q1为补偿后的无功功率；tinter为采样时间间隔；In the formula, kvarh1 is the remaining reactive power after compensation; N is the number of sampling points; Q1 is the reactive power after compensation; t inter is the sampling time interval; 无功补偿装置的无功补偿投切按照如下原则进行：The reactive power compensation switching of the reactive power compensation device is carried out according to the following principles: (1)无功不倒送(1) No reversal 无功不倒送要求无功补偿装置补偿的无功功率不超过变电站原始的无功功率数据，且变电站无功功率为负时不补偿，所以若变电站原始的无功功率数据大于等于无功补偿装置补偿的最大容量，则对这些数据采取最大容量进行补偿；筛选之后，若变电站原始的无功功率数据大于等于无功补偿装置补偿的次大容量，则对这些数据采取次大容量进行补偿；依次筛选……；最后，若变电站无功功率为负时，则无功补偿装置进行补偿；Non-reverse reactive power transmission requires that the reactive power compensated by the reactive power compensation device does not exceed the original reactive power data of the substation, and no compensation is made when the reactive power of the substation is negative, so if the original reactive power data of the substation is greater than or equal to the reactive power compensation If the original reactive power data of the substation is greater than or equal to the second largest capacity compensated by the reactive power compensation device, the second largest capacity will be used to compensate these data; Screen in turn...; Finally, if the reactive power of the substation is negative, the reactive power compensation device will compensate; (2)投切时间间隔至少30min(2) The switching time interval is at least 30min 因为切除的无功补偿装置要在30min之后才能完成充放电的过程，才不会对下一次投入产生影响；所以要求每组无功补偿装置在30min之内不能连续投切，30min内，若无功补偿装置在第一数据采样点处于投入状态、在下一数据采样点处于切除状态且在此后的剩余时间内有处于投入的状态，则在此后的剩余时间内使无功补偿装置均处于切除状态，故投切时间间隔应满足如下条件：Because the removed reactive power compensation device can only complete the charging and discharging process after 30 minutes, it will not affect the next input; therefore, it is required that each group of reactive power compensation devices cannot be switched continuously within 30 minutes. If the power compensation device is in the ON state at the first data sampling point, is in the OFF state at the next data sampling point, and is in the ON state in the remaining time thereafter, the reactive power compensation device is in the OFF state in the remaining time thereafter. , so the switching time interval should meet the following conditions: Tinterval≥30minT interval ≥30min 式中，Tinterval为无功补偿器投切时间间隔；In the formula, T interval is the switching time interval of the reactive power compensator; (3)无功补偿装置投切次数小于上限原则(3) The principle that the switching times of the reactive power compensation device is less than the upper limit 无功补偿装置频繁投切会损坏投切开关，降低电容器使用寿命，因此需要对每组无功补偿装置每天的最大投切次数进行约束，假设次数为b，投入和切除均为无功补偿装置的投切动作，首先找到无功补偿装置每天投入的次数，若该次数小于等于b/2-1，则保持原有投切策略，否则找到无功补偿装置每天状态变化点的下标；再基于此找到无功补偿装置每天的工作区间，对这些工作区间的长度进行排序；最后因为有的工作区间可能会贯穿两天，所以要筛选出每天最长的b/2-1个区间，并且令其余的时间均不工作，即切除状态；因此无功补偿装置投切次数应满足如下条件：Frequent switching of the reactive power compensation device will damage the switching switch and reduce the service life of the capacitor. Therefore, it is necessary to restrict the maximum switching times of each group of reactive power compensation devices per day. Suppose the number of times is b, and the switching and cutting are both reactive power compensation devices. For the switching action, first find the number of times the reactive power compensation device is put into every day, if the number of times is less than or equal to b/2-1, keep the original switching strategy, otherwise find the subscript of the daily state change point of the reactive power compensation device; then Based on this, find the working interval of the reactive power compensation device every day, and sort the length of these working intervals; finally, because some working intervals may last for two days, the longest b/2-1 interval per day should be screened out, and Make the rest of the time not work, that is, the cut-off state; therefore, the switching times of the reactive power compensation device should meet the following conditions:
Figure FDA0003328163050000021
Figure FDA0003328163050000021
 式中，swi d为第i组无功补偿器第d天的投切次数；swmax为无功补偿器每天的最大投切次数，根据实际需要自行设定。In the formula, sw i d is the switching times of the ith group of reactive power compensators on the d day; sw max is the maximum switching times of the reactive power compensators per day, which can be set according to actual needs. 3.根据权利要求1所述基于变电站运行数据的无功补偿优化方法，其特征在于，在步骤4中，损耗最小的评估方法为：3. the reactive power compensation optimization method based on substation operation data according to claim 1, is characterized in that, in step 4, the evaluation method with the least loss is:
Figure FDA0003328163050000022
Figure FDA0003328163050000022
 式中，kvarh1为补偿后剩余的无功电量；kvarh为补偿前的无功电量；In the formula, kvarh1 is the remaining reactive power after compensation; kvarh is the reactive power before compensation; 投资最小的评估方法为：The minimum investment evaluation method is:
Figure FDA0003328163050000023
Figure FDA0003328163050000023
 式中，Qc为无功补偿总容量；Qmax为补偿前最大无功需量；In the formula, Q c is the total reactive power compensation capacity; Q max is the maximum reactive power demand before compensation; 位置最优的评估方法为：The optimal evaluation method for the location is: Z＝0.8代表位置选取最优；Z＝1代表位置选取适中；Z＝1.2代表位置选取不合适；Z=0.8 represents the best location selection; Z=1 represents the moderate location selection; Z=1.2 represents the inappropriate location selection; 则结合损耗、投资、位置三因素的加权综合优化评估系数F表示为：Then the weighted comprehensive optimization evaluation coefficient F combining the three factors of loss, investment and location is expressed as: F＝α*X+β*Y+γ*ZF=α*X+β*Y+γ*Z 式中，α、β、γ为权重系数，α越大说明补偿效果占比越大；β越大说明经济效益占比越大；γ越大说明位置的选取占比越大；α、β、γ值根据具体情况进行设置；In the formula, α, β, and γ are the weight coefficients. The larger the α, the larger the proportion of the compensation effect; the larger the β, the larger the proportion of economic benefits; the larger the γ, the larger the proportion of location selection; α, β, The γ value is set according to the specific situation; 加权综合评估系数F值越小则越优；因为补偿容量越大，则投资越大；分组越多，则投切开关多，经济性差；位置选取不合适，则安全程度越低。The smaller the weighted comprehensive evaluation coefficient F value, the better; because the larger the compensation capacity, the larger the investment; the more groups, the more switching switches, the poorer the economy; the less suitable the location is, the lower the safety level.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117220356A (en) * 2023-11-09 2023-12-12 国网四川省电力公司电力科学研究院 Multi-time-scale-based annual loss reduction operation optimization method and system for power transmission network
CN118054426A (en) * 2024-03-19 2024-05-17 江苏能呈电气有限公司 Reactive power compensation device and energy storage coordination optimization configuration method and system

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103595135A (en) * 2013-11-21 2014-02-19 国家电网公司 Intelligent reactive power optimization and coordinated control system of middle-and-low-voltage regional power grid
CN105244889A (en) * 2015-07-21 2016-01-13 河南行知专利服务有限公司 Power distribution network reactive power compensation planning method
CN108695859A (en) * 2018-06-04 2018-10-23 南京工程学院 A kind of capacitor group addressing constant volume method of access active distribution network

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103595135A (en) * 2013-11-21 2014-02-19 国家电网公司 Intelligent reactive power optimization and coordinated control system of middle-and-low-voltage regional power grid
CN105244889A (en) * 2015-07-21 2016-01-13 河南行知专利服务有限公司 Power distribution network reactive power compensation planning method
CN108695859A (en) * 2018-06-04 2018-10-23 南京工程学院 A kind of capacitor group addressing constant volume method of access active distribution network

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
MINGXING ZHU等: "Study on Power Quality Characteristics of Electric Kiln Based on Energy Balance Model", 《2019 IEEE INTERNATIONAL CONFERENCE ON POWER DATA SCIENCE (ICPDS)》, 2 March 2020 (2020-03-02), pages 122 - 125 *
段国泉 等: "基于改进最优覆盖法的智能变电站无功优化配置", 《电力建设》, vol. 35, no. 07, 31 July 2014 (2014-07-31), pages 20 - 25 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117220356A (en) * 2023-11-09 2023-12-12 国网四川省电力公司电力科学研究院 Multi-time-scale-based annual loss reduction operation optimization method and system for power transmission network
CN117220356B (en) * 2023-11-09 2024-01-16 国网四川省电力公司电力科学研究院 Multi-time-scale-based annual loss reduction operation optimization method and system for power transmission network
CN118054426A (en) * 2024-03-19 2024-05-17 江苏能呈电气有限公司 Reactive power compensation device and energy storage coordination optimization configuration method and system

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