CN104809543B - Power system operating mode generation method based on monthly power transmission and transforming equipment repair schedule - Google Patents

Abstract

The invention discloses a method for generating a power grid operation mode based on a monthly power transmission and transformation equipment maintenance plan, and belongs to the technical field of power systems and automation thereof. The invention obtains the original data of the operation mode in the power grid control center, and according to the monthly power transmission and transformation equipment maintenance plan, distributes the monthly power forecast data according to the load rate of different periods in the same period of history, and generates the monthly peak load mode and the power transmission and transformation equipment maintenance plan for each day. There are two operation modes in low valley load mode. In the process of generating these two modes, the influence of system network loss, spinning reserve requirements, and planned outage units are considered, and finally the maintenance of power transmission and transformation equipment according to the "date, load mode" mode is obtained. Data on grid operation mode under the plan. The operation mode of the maintenance plan generated according to the above method is in line with the production needs and habits of the power system, and can provide a data basis for the risk assessment of power grid operation and the readjustment of the maintenance plan under the maintenance plan of power transmission and transformation equipment in the power system.

Description

Generation method of power grid operation mode based on monthly power transmission and transformation equipment maintenance plan

technical field

The invention belongs to the technical field of electric power systems and automation thereof. More precisely, the invention relates to a method for generating a power grid operation mode based on a monthly power transmission and transformation equipment maintenance plan.

Background technique

Power transmission and transformation equipment is the backbone of the power network. Once there is a problem with the equipment, it may cause local and global system equipment to stop running, resulting in power supply interruption accidents. Therefore, the safe and reliable operation of power transmission and transformation equipment is particularly important. With the development of the power system towards high voltage, large capacity, and interconnection, the requirements for the safety and reliability indicators of the power system are getting higher and higher. The maintenance investment of power companies has increased significantly, and the current maintenance system has increasingly exposed its defect. Therefore, implement a more advanced and scientific management and maintenance system for the equipment, form an objective and practical operation mode for the maintenance plan in line with the scheduling operation, and conduct rolling safety and stability checks, regardless of the interests of the power company itself or the requirements of the society It is imperative to set off.

When considering the maintenance plan for safety and stability check, it is first necessary to generate the grid operation mode taking into account the maintenance plan. The planning methods include maintenance plan, power generation plan, load forecasting and other methods under one or a combination of plans. The maintenance plan may include generator maintenance plan, transmission and substation maintenance plan and power distribution equipment maintenance plan, etc. In addition, the basic data conditions of the plan mode data of different time scales are different, and the requirements for the accuracy of the generated operation mode are also different.

The current generation technology of operation mode under the maintenance plan includes the generation of maintenance plans with different time scales. The type of plan considered may be a combination of one or more plans. The goal is to make the planning method more in line with the actual scheduling operation. Or make the arrangement more economical and reasonable. However, it has not been able to comprehensively and effectively utilize the historical load data information and the existing mode data information, which makes it difficult to generate the planning mode, and it is difficult to achieve the actual effect of scheduling operation. In addition, in the process of generating the operation mode, the existing technology only considers some of the factors affecting the maintenance plan of the power transmission and transformation equipment, the outage plan of the unit, the system backup constraint, and the actual network loss of the system, and fails to comprehensively coordinate. consider.

Contents of the invention

The object of the present invention is to provide a method for generating a power grid operation mode based on a monthly power transmission and transformation equipment maintenance plan in view of the deficiencies in the prior art. According to the monthly power transmission and transformation equipment maintenance plan, monthly electricity forecast data and other information, and referring to the actual situation of electricity and load in the same period of the previous year, the method generates two peak load modes and low valley load modes for each day with a monthly power transmission and transformation equipment maintenance plan. mode of operation. In the process of generating these two modes, the network loss of the system, the requirement of spinning reserve, and the influence of planned outage units are considered, and finally the data of the power grid operation mode under the maintenance plan of power transmission and transformation equipment in the mode of "date, load mode" are obtained. The operation mode of the maintenance plan generated according to the above method is in line with the production needs and habits of the power system, and can provide a data basis for the risk assessment of power grid operation and the readjustment of the maintenance plan under the maintenance plan of power transmission and transformation equipment in the power system.

Specifically, the present invention is realized by adopting the following technical solutions, including the following steps:

1) Obtain the next month's power transmission and transformation equipment maintenance plan and unit outage plan, the next month's forecast power data, the monthly load statistics data of the same month in the previous year and the next month, and their daily load statistics in the power grid control center. The actual load curve, the data of the typical offline mode of the power grid in this month, the rated capacity data of all units and the system spinning reserve coefficient, among which the actual load curve of each month in the same month in the previous year and the next month divides 24 hours a day into N _points Time period, each point of data corresponds to the power grid load power value of a period;

2) The full wiring mode data in the grid offline typical mode data of the control center this month is used as the basic mode data;

3) Allocate the predicted power of the next month to each day of the next month, and estimate the peak load and valley load of each day of the next month;

4) Determine in turn whether there is a maintenance plan for each day of the next month, if not, skip it, otherwise, for each day of the next month with a maintenance plan task, generate two operating modes under peak load and low load for each day;

5) Number the data of the final operation mode and send it to the corresponding data directory of the dispatch management system or other automation systems for its application.

The above technical solution further lies in that said step 3) specifically includes the following steps:

3-1) According to the monthly load statistical data of the same month in the previous year and the next month, calculate the forecasted electricity for each day of the next month according to formulas (1) and (2):

Among them, d is the number of days in the month; WP is the predicted power of the next month; W _i is the predicted power of the i-th day of the next month; The actual power consumption of the same month in a year; W _i ′ is the actual power consumption of the same month and day in the previous year in the same month as the next month in the previous year;

3-2) According to the actual load curve of each month in the same month in the previous year and the next month, the same proportion is distributed according to formula (3), and the predicted load power of each day and time period of the next month is obtained:

Among them, P _{i,j is} the predicted load power of the power grid at the jth time period on the i-th day of the next month; Actual load power at the same time period on the same day;

3-3) Calculate peak load P _i ^max and valley load P _i ^min on the i-th day of the next month according to formulas (4) and (5):

P _i ^max ＝k·max{P _i,j }(i=1～d,j=1～N _point ) (4)

Among them, k is a constant coefficient.

The above-mentioned technical solution is further in that, in the step 4), the steps of generating the two operating modes under the peak load and the valley load of each day are as follows:

4-1) According to the power transmission and transformation equipment maintenance plan arranged on that day, delete the power transmission and transformation equipment for each planned maintenance from the basic mode data one by one to obtain intermediate data;

4-2) Based on the intermediate data, the unit outage plan of the day, and the peak load and valley load of the day obtained in step 3), consider the system spinning reserve and network loss, adjust the unit output and load, so that the system power is basically balanced, and generate Raw data of operation mode;

4-3) Perform power flow calculation on the rough data of the operation mode. If the power flow converges, obtain the mode data. If the power flow reports an error or the calculation diverges, adjust according to the prompt information and recalculate the power flow. Iterate until the power flow converges or the number of iterations exceeds The preset value (according to engineering experience, generally 5 to 10 times) is terminated, and the power flow data calculated and converged is taken as the final mode data.

The above technical solution further lies in that said step 4-2) specifically includes the following steps:

4-2-1) The total output of the generator and the total load in the statistics of the basic mode data, the total output of the generator is P _gorg , and the total load is P _lorg ;

4-2-2) Find the units that are planned to be out of service on that day in the intermediate data, and count the total output of these units as P _gstop , and then delete these units in the intermediate data;

4-2-3) Calculate the difference ΔP _l between the peak load or trough load and P _lorg of the day according to formula (6), and adjust the load of each node in the whole network so that the total load of the whole network is P _llim :

ΔP _l =P _llim -P _lorg (6)

Among them, when calculating the peak load mode, P _llim is the peak load of the day; when calculating the low-valley load mode, P _llim is the low-valley load of the day;

If ΔP _l > 0, then increase the load in the same proportion on each load node in the whole network; if ΔP _l < 0, then decrease the load in the same proportion in each load node in the whole network, so that the total load of the whole network is P _llim ;

4-2-4) Taking into account the units that are planned to be shut down, and considering the size of the network loss according to the proportion of the power generation load in the original data, calculate the total output or decrease of the system generator output ΔP _g , as shown in formula (7):

A) If ΔP _g ≥ 0, increase the output of all generators in the intermediate data of the planned outage units deleted in step 4-2-2), so that the total amount of increased output is ΔP _g :

First, it is judged whether the space for increasing the force is sufficient considering whether the system has a certain reserve according to whether the formula (8) is satisfied:

Among them, N is the total number of generators in the whole network in the intermediate data; p _k is the initial output of the kth generator in the original data; p _cap,k is the rated capacity of the kth generator; λ is the system spinning reserve coefficient , its value is different under the mode of peak load and low load, and is determined according to the relevant standards or specifications of the industry or enterprise;

If formula (8) is satisfied, then increase the output of each generator in the intermediate data, and the output of each generator needs to be increased according to formula (9):

Among them, Δp _k is the need to increase the output of the kth generator;

If Equation (8) is not satisfied, add units in the intermediate data one by one except for the units that are scheduled to be out of service, and make the initial output of the additional units be 0 until Equation (8) is satisfied; when the units are added one by one, the entire network The total number N of generators is also updated accordingly, and the value of N increases by 1 for each additional unit;

In the intermediate data, adjust the output of the additional unit to its minimum output value; on this basis, increase the output of each generator according to formula (9), and modify it into the intermediate data;

B) If ΔP _g <0, reduce the output of all generators in the entire network in the intermediate data, and the total amount of reduced output is ΔP _g ; each generator needs to reduce the output according to formula (10):

At this time, Δp _k is the required output power of the kth generator, and α _k is the minimum output proportional coefficient of the kth generator;

4-2-5) After the above adjustments, the intermediate data is defined as rough data.

A further feature of the above technical solution is that the value of the constant coefficient k is 1.0-1.1.

A further feature of the above technical solution is that the minimum output proportional coefficient α _k of the kth generator takes a value of 0.5-0.6.

The further feature of the above technical solution is that the N _point is 96, and the monthly actual load curve of each month in the same month in the previous year and the next month divides 24 hours a day into 96 time periods, each time period is 15 minutes, and each time period is 15 minutes. The point data corresponds to the grid load power value for 15 minutes.

The beneficial effects of the present invention are as follows: the present invention proposes a method for generating the power grid operation mode under the monthly power transmission and transformation equipment maintenance plan, which can provide the mode data under the maintenance plan for the power system operation mode personnel, and provide related automation for the maintenance plan checking system, etc. The system provides the data basis; in the process of generating the operation mode under the maintenance plan of power transmission and transformation equipment, the influence factors such as system network loss, spinning reserve requirements, and planned outage units are considered, making the result data more reasonable and practical, and providing a basis for the power system. The risk assessment of power grid operation under the maintenance plan of power transmission and transformation equipment and the readjustment of the maintenance plan provide a data basis.

Description of drawings

Fig. 1 is the flowchart of the method of the present invention.

Detailed ways

The present invention will be described in further detail below with reference to the accompanying drawings.

Step 1 in Figure 1 describes that the power grid control center obtains the next month’s power transmission and transformation equipment maintenance plan and unit outage plan, the next month’s forecast power data, and the monthly data of the same month in the previous year as the next month Load statistical data and its daily actual load curve, data of the typical offline mode of the power grid this month, data of all unit rated capacity and system spinning reserve coefficient, among which the monthly actual load curve of each month in the same month in the previous year and the next month will be one day 24 hours are divided into N _point periods, and each point of data corresponds to the grid load power value of a period. In practice, N _point generally takes 96, that is, the actual load curve of each month in the same month in the previous year and the next month divides 24 hours a day into 96 time periods, each time period is 15 minutes, and each point of data corresponds to 15 minutes grid load power value.

Step 2 in Figure 1 describes that the full wiring mode data in the grid offline typical mode data of the control center this month is used as the basic mode data.

Step 3 in Figure 1 describes that the forecasted power of the next month is allocated to each day of the next month, and the peak load and trough load of each day of the next month are estimated. The calculation process specifically includes the following steps.

3-1) According to the monthly load statistical data of the same month in the previous year and the next month, calculate the forecast electricity of each day according to formula (1) and (2):

Among them, d is the number of days in the month; WP is the predicted power of the next month; W _i is the predicted power of the i-th day of the next month; Actual power consumption of the same month in a year; W _i ′ is the actual power consumption of the same month and day in the previous year in the monthly load statistics data of the same month in the previous year and the next month.

3-2) According to the actual load curve of each month in the same month in the previous year and the next month, the same proportion is distributed according to formula (3), and the predicted load power of each day and time period of the next month is obtained:

Among them, P _{i,j is} the predicted load power of the power grid at the jth time period on the i-th day of the next month; Actual load power at the same time period on the same day.

In particular, when the N _point is 96, formula (3) is:

3-3) Calculate peak load P _i ^max and valley load P _i ^min on the i-th day of the next month according to formulas (4) and (5):

P _i ^max ＝k·max{P _i,j }(i=1～d,j=1～N _point ) (4)

Among them, k is a constant coefficient, determined according to engineering experience, and generally takes a value of 1.0 to 1.1.

Step 4 in Figure 1 describes that it is necessary to sequentially judge whether there is a maintenance plan for each day of the next month, and skip it if there is no maintenance plan. Two modes of operation. Its calculation process includes the following steps.

4-1) According to the power transmission and transformation equipment maintenance plan arranged on that day, delete the power transmission and transformation equipment for each planned maintenance from the basic mode data one by one to obtain intermediate data;

4-2) Based on the intermediate data, the unit outage plan of the day, and the peak load and valley load of the day obtained in step 3), consider the system spinning reserve and network loss, adjust the unit output and load, so that the system power is basically balanced, and generate Run mode coarse data. Its calculation process includes the following steps.

4-2-1) The total output of the generator and the total load in the statistics of the basic mode data, the total output of the generator is P _gorg , and the total load is P _lorg ;

4-2-2) Find the units that are planned to be out of service on that day in the intermediate data, and count the total output of these units as P _gstop , and then delete these units in the intermediate data;

4-2-3) Calculate the difference ΔP _l between the peak load or trough load and P _lorg of the day according to formula (6), and adjust the load of each node in the whole network so that the total load of the whole network is P _llim :

ΔP _l =P _llim -P _lorg (6)

Among them, P _llim is the peak load of the day when calculating the peak load mode; P _llim is the low valley load of the day when calculating the valley load mode.

If ΔP _l >0, then increase the load in the same proportion on each load node in the whole network, if ΔP _l <0, then decrease the load in the same proportion in each load node in the whole network, so that the total load of the whole network is P _llim .

4-2-4) Taking into account the units that are planned to be shut down, and considering the size of the network loss according to the proportion of the power generation load in the original data, calculate the total output or decrease of the system generator output ΔP _g , as shown in formula (7):

A) If ΔP _g ≥ 0, increase the output of all generators in the intermediate data of the planned outage units deleted in step 4-2-2), so that the total amount of increased output is ΔP _g :

First of all, judge whether there is enough space for increasing the force under the condition that the system has a certain reserve, that is, judge whether the formula (8) is satisfied:

Among them, N is the total number of generators in the whole network in the intermediate data; p _k is the initial output of the kth generator in the original data; p _cap,k is the rated capacity of the kth generator; λ is the system spinning reserve coefficient , its value is different under peak load and low load mode, and it is determined according to relevant industry or enterprise standards or norms.

If formula (8) is satisfied, then increase the output of each generator in the intermediate data. Each generator needs to increase output according to formula (9):

Among them, Δp _k is the need to increase the output of the kth generator;

If Equation (8) is not satisfied, start-up units one by one in the intermediate data (except the units that are planned to be out of service), and set the initial output p _k of the additional units to be 0, until Equation (8) is satisfied. It should be noted that when the units are added one by one, the total number N of generators in the whole network will also be updated accordingly, and the value of N will increase by 1 for each additional unit.

In the intermediate data, the output of the additional unit is adjusted to its minimum output value. On this basis, increase the output of each generator according to formula (9), and modify it into the intermediate data.

B) If ΔP _g <0, reduce the output of all generators in the entire network in the intermediate data, and the total amount of output reduction is ΔP _g . The output power of each generator needs to be reduced according to formula (10):

At this time, Δp _k is the required output power of the kth generator, and α _k is the minimum output proportional coefficient of generator k, which generally takes a value of 0.5 to 0.6.

4-2-5) After the above adjustments, the intermediate data is defined as rough data.

4-3) Perform power flow calculation on rough data, which can be completed by existing mature commercial software. If the power flow converges, obtain the mode data. If the power flow reports an error or the calculation diverges, adjust according to the prompt information and recalculate the power flow. Iterate until the power flow converges or the number of iterations exceeds the preset value (according to engineering experience, generally 5 to 10 times) then stop. The power flow data calculated for convergence is used as the final mode data.

Step 5 in Figure 1 describes that the final operating mode data is numbered and sent to the corresponding data directory of the dispatch management system or other automation systems for its application. Numbering can be done using the "date and load method".

Although the present invention has been disclosed above with preferred embodiments, the embodiments are not intended to limit the present invention. Any equivalent changes or modifications made without departing from the spirit and scope of the present invention also belong to the protection scope of the present invention. Therefore, the scope of protection of the present invention should be based on the content defined by the claims of this application.

Claims (4)

1. the power system operating mode generation method based on monthly power transmission and transforming equipment repair schedule, which is characterized in that including walking as follows Suddenly：

1) next monthly power transmission and transforming equipment repair schedule and unit outage plan, next monthly are obtained at power grid regulation center It predicts bent with next monthly identical monthly monthly load statistics and its each day actual load in electricity data, previous year The offline typical way data of line, this month power grid, all unit rated capacity data and system spinning reserve coefficient, wherein upper one year In degree with next monthly identical monthly monthly each day realized load curve by one day 24 it is small when be divided into N_pointA period, every point Data correspond to the network load performance number of a period；

2) mode data based on the full mode of connection data that will regulate and control in the offline typical way data of center this month power grid；

3) next monthly prediction electricity is shared into each day of next month, and estimates the peak load and low ebb of next month each day Load comprises the following steps：

3-1) according in previous year with next monthly identical monthly monthly load statistics, by formula (1), (2) calculate under The prediction electricity of a month each day：

<mrow> <msub> <mi>W</mi> <mi>i</mi> </msub> <mo>=</mo> <mfrac> <msubsup> <mi>W</mi> <mi>i</mi> <mo>&amp;prime;</mo> </msubsup> <mrow> <msup> <mi>WP</mi> <mo>&amp;prime;</mo> </msup> </mrow> </mfrac> <mo>&amp;times;</mo> <mi>W</mi> <mi>P</mi> <mo>,</mo> <mrow> <mo>(</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>~</mo> <mi>d</mi> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow>

<mrow> <msup> <mi>WP</mi> <mo>&amp;prime;</mo> </msup> <mo>=</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>d</mi> </munderover> <msubsup> <mi>W</mi> <mi>i</mi> <mo>&amp;prime;</mo> </msubsup> <mo>,</mo> <mrow> <mo>(</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>~</mo> <mi>d</mi> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow>

Wherein, d is monthly number of days；WP is next monthly prediction electricity；W_iFor the prediction electricity on next month 1；WP ' is upper In one year with the previous year same month actual electricity in next monthly identical monthly monthly load statistics；W_i' it is upper In one year with the actual electricity on the same day of the previous year same month in next monthly identical monthly monthly load statistics；

3-2) according to, with next monthly identical monthly monthly each day realized load curve, being carried out in previous year by formula (3) same Pro rate obtains the prediction load power of each day day part next month：

<mrow> <msub> <mi>P</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo>=</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <msub> <mi>N</mi> <mrow> <mi>p</mi> <mi>o</mi> <mi>int</mi> </mrow> </msub> </munderover> <mrow> <mo>(</mo> <mfrac> <msub> <mi>W</mi> <mi>i</mi> </msub> <msubsup> <mi>W</mi> <mi>i</mi> <mo>&amp;prime;</mo> </msubsup> </mfrac> <mo>&amp;CenterDot;</mo> <msubsup> <mi>P</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> <mo>&amp;prime;</mo> </msubsup> <mo>)</mo> </mrow> <mo>,</mo> <mrow> <mo>(</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>~</mo> <mi>d</mi> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1</mn> <mo>~</mo> <msub> <mi>N</mi> <mrow> <mi>p</mi> <mi>o</mi> <mi>int</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </mrow>

Wherein, P_i,jLoad power is predicted for the power grid of jth period next month 1；P_i,′_jFor in previous year with it is next monthly Same month prior year in identical monthly monthly each day realized load curve is on the same day the same as the actual load power of period；

3-3) peak load P on next month 1 is calculated by formula (4), (5)_i ^maxWith low ebb load P_i ^min：

P_i ^max=Kmax { P_i,j(i=1~d, j=1~N_point) (4)

<mrow> <msubsup> <mi>P</mi> <mi>i</mi> <mi>min</mi> </msubsup> <mo>=</mo> <mfrac> <mrow> <mi>m</mi> <mi>i</mi> <mi>n</mi> <mo>{</mo> <msub> <mi>P</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mo>}</mo> </mrow> <mi>K</mi> </mfrac> <mo>,</mo> <mrow> <mo>(</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>~</mo> <mi>d</mi> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1</mn> <mo>~</mo> <msub> <mi>N</mi> <mrow> <mi>p</mi> <mi>o</mi> <mi>int</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mo>)</mo> </mrow> </mrow>

Wherein, K is constant coefficient；

4) judge whether next month each day has repair schedule successively, skipped if not, otherwise to there is the next of repair schedule task Each day of the moon, two kinds of methods of operation under each day peak load and low ebb load are generated respectively；

Described the step of generating two kinds of methods of operation under each day peak load and low ebb load, is as follows：

4-1) the power transmission and transforming equipment repair schedule arranged according to this day, deletes each scheduled overhaul one by one in basal profile data Power transmission and transforming equipment obtains intermediate data；

Intermediate data, the peak load of this day that this day unit outage plan, step 3) obtain and low ebb load 4-2) are based on, is examined Worry system spinning reserve and network loss adjust unit output and load, make system power in a basic balance, generating run mode slightly counts According to comprising the following steps：

4-2-1) generator gross capability and load total amount in statistical basis mode data, if generator gross capability is P_gorg, load is total It measures as P_lorg；

The unit of the daily planning stoppage in transit 4-2-2) is searched in intermediate data, and the gross capability for counting these units is P_gstop, so These units are deleted in intermediate data afterwards；

4-2-3) peak load of this day or low ebb load and P are calculated by formula (6)_lorgDifference DELTA P_l, and adjust each node of the whole network Load makes the whole network load total amount be P_llim：

ΔP_l=P_llim-P_lorg (6)

Wherein, the P when calculating peak load mode_llimFor the peak load of this day；The P when calculating low ebb load method_llimFor this The low ebb load of day；

If Δ P_l＞ 0 then increases load at equal pace in each load bus of the whole network, if Δ P_l＜ 0, then in each load bus of the whole network Load shedding at equal pace so that the whole network total load is P_llim；

4-2-4) the unit of meter and planned outage, and consider network loss size in the ratio of generation load in initial data, calculate system System generator need to increase output or subtract output total value Δ P_g, as shown in formula (7)：

<mrow> <msub> <mi>&amp;Delta;P</mi> <mi>g</mi> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>P</mi> <mrow> <mi>g</mi> <mi>o</mi> <mi>r</mi> <mi>g</mi> </mrow> </msub> <mo>&amp;CenterDot;</mo> <msub> <mi>P</mi> <mrow> <mi>l</mi> <mi>lim</mi> </mrow> </msub> </mrow> <msub> <mi>P</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>r</mi> <mi>g</mi> </mrow> </msub> </mfrac> <mo>-</mo> <msub> <mi>P</mi> <mrow> <mi>g</mi> <mi>o</mi> <mi>r</mi> <mi>g</mi> </mrow> </msub> <mo>+</mo> <msub> <mi>P</mi> <mrow> <mi>g</mi> <mi>s</mi> <mi>t</mi> <mi>o</mi> <mi>p</mi> </mrow> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>7</mn> <mo>)</mo> </mrow> </mrow>

A) if Δ P_g>=0, to step 4-2-2) in deleted all generators in the intermediate data of planned outage unit and increased and contributed, So that it is Δ P to increase the total amount contributed_g：

First, according to whether meet formula (8) judge consideration system leave it is certain it is spare in the case of increase output space whether Enough：

<mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <mrow> <mo>(</mo> <msub> <mi>p</mi> <mrow> <mi>c</mi> <mi>a</mi> <mi>p</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>p</mi> <mi>k</mi> </msub> <mo>)</mo> </mrow> <mo>-</mo> <msub> <mi>&amp;Delta;P</mi> <mi>g</mi> </msub> <mo>&amp;GreaterEqual;</mo> <mi>&amp;lambda;</mi> <mo>&amp;CenterDot;</mo> <msub> <mi>P</mi> <mrow> <mi>l</mi> <mi>lim</mi> </mrow> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>8</mn> <mo>)</mo> </mrow> </mrow>

Wherein, N is the whole network generator sum in intermediate data；p_kFor the initial output in initial data of k-th of generator； p_cap,kFor the rated capacity of k-th of generator；λ is system spinning reserve coefficient, its value under peak load and low ebb load method Difference determines respectively according to industry or enterprise's relevant criterion or specification；

If formula (8) meets, increase each generator output in intermediate data, each generator need to increase output and be calculated by (9) formula：

<mrow> <msub> <mi>&amp;Delta;p</mi> <mi>k</mi> </msub> <mo>=</mo> <mfrac> <mrow> <mo>(</mo> <msub> <mi>p</mi> <mrow> <mi>c</mi> <mi>a</mi> <mi>p</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>p</mi> <mi>k</mi> </msub> <mo>)</mo> </mrow> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <mrow> <mo>(</mo> <msub> <mi>p</mi> <mrow> <mi>c</mi> <mi>a</mi> <mi>p</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>p</mi> <mi>k</mi> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>&amp;CenterDot;</mo> <msub> <mi>&amp;Delta;P</mi> <mi>g</mi> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>9</mn> <mo>)</mo> </mrow> </mrow>

Wherein, Δ p_kIt need to increase output for k-th of generator；

If formula (8) is unsatisfactory for, except increasing unit but the unit of planned outage one by one in intermediate data, unit is increased in order Initial contribute is 0, until formula (8) meets；The whole network generator sum N also updates therewith when increasing unit one by one, often increases The numerical value of one unit N adds 1；

The output for increasing unit is adjusted to its minimum load value in intermediate data；Increase again by formula (9) on this basis each Generator output, and be modified in intermediate data；

B) if Δ P_g＜ 0 subtracts output to all generators of the whole network in intermediate data, and the total amount for subtracting output is Δ P_g；Each generator needs Subtract and strength by formula (10) calculating：

<mrow> <msub> <mi>&amp;Delta;p</mi> <mi>k</mi> </msub> <mo>=</mo> <mfrac> <mrow> <mo>(</mo> <msub> <mi>p</mi> <mi>k</mi> </msub> <mo>-</mo> <msub> <mi>&amp;alpha;</mi> <mi>k</mi> </msub> <mo>&amp;CenterDot;</mo> <msub> <mi>p</mi> <mrow> <mi>c</mi> <mi>a</mi> <mi>p</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> <mo>)</mo> </mrow> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <mrow> <mo>(</mo> <msub> <mi>p</mi> <mi>k</mi> </msub> <mo>-</mo> <msub> <mi>&amp;alpha;</mi> <mi>k</mi> </msub> <mo>&amp;CenterDot;</mo> <msub> <mi>p</mi> <mrow> <mi>c</mi> <mi>a</mi> <mi>p</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>&amp;CenterDot;</mo> <msub> <mi>&amp;Delta;P</mi> <mi>g</mi> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>10</mn> <mo>)</mo> </mrow> </mrow>

At this point, Δ p_kIt need to need to subtract for k-th of generator and strength, α_kFor the minimum load proportionality coefficient of k-th of generator；

4-2-5) after above-mentioned adjustment, intermediate data is defined as raw data；

Load flow calculation 4-3) is carried out to method of operation raw data, if trend restrains, acquisition pattern data, if trend reports an error Or calculate diverging, then it is adjusted according to prompt message, and trend is recalculated, such iteration is until trend restrains or iteration time Number is then terminated more than preset value, will calculate convergent flow data as final mode data；

5) by final running mode data by being numbered, and dispatching management information system or other automated system respective counts are sent to It is applied according to catalogue for it.

2. the power system operating mode generation method according to claim 1 based on monthly power transmission and transforming equipment repair schedule, It is characterized in that, the constant coefficient K values are 1.0~1.1.

3. the power system operating mode generation method according to claim 1 based on monthly power transmission and transforming equipment repair schedule, It is characterized in that, the minimum load proportionality coefficient α of k-th of generator_kValue is 0.5~0.6.

4. it is generated according to the arbitrary power system operating mode based on monthly power transmission and transforming equipment repair schedule of claims 1 to 3 Method, which is characterized in that the N_pointIt is bent with next monthly identical monthly monthly each day actual load in previous year for 96 Line by one day 24 it is small when be divided into 96 periods, each period is 15 minutes, and the network load work(of 15 minutes is corresponded to per point data Rate value.