CN108599168B - Method and system for carrying out rationality evaluation on planned power flow of large power grid - Google Patents
Method and system for carrying out rationality evaluation on planned power flow of large power grid Download PDFInfo
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- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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Abstract
The invention discloses a method and a system for evaluating the reasonability of a planning flow of a large power grid, which comprises the following steps: establishing a first evaluation index set with reasonable data of a single-time-period operation mode; establishing a second evaluation index set with reasonable data of a plurality of time period operation modes; acquiring a data quality score of each evaluation index in a first evaluation index set at any time interval; acquiring average data quality scores of all evaluation indexes in a first evaluation index set at any time period; acquiring a data quality score of each evaluation index in a second evaluation index set of a plurality of time periods; acquiring average data quality scores of all evaluation indexes in a second evaluation index set of a plurality of time periods; and determining the overall average data quality scores of the first evaluation index set and the second evaluation index set based on the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set.
Description
Technical Field
The invention relates to the field of on-line safety and stability calculation and analysis of power systems, in particular to a method and a system for evaluating reasonability of a planned power flow of a large power grid.
Background
The day-ahead scheduling plan of the power system is an important link of power grid scheduling operation, and reasonable scheduling plan arrangement is a premise and basis for ensuring safe and stable operation of a power grid. With the advance of extra-high voltage construction and large-area power grid interconnection, the scale of an alternating current-direct current hybrid power grid is continuously enlarged, new energy such as wind power and photovoltaic is accessed in a large scale, the operation mode of the power grid is more and more complex, and a power grid dispatching department needs to be more refined and accurate when making a dispatching plan. Safety and stability checking is carried out on the dispatching plan, so that the safety and stability problems existing in the day-ahead plan can be found, the reasonable dispatching plan and the corresponding preventive control measures can be made, and the method has extremely important significance on the safe and stable operation of the power grid.
The basis of the safety check of the dispatching plan is to generate plan flow data meeting the safety and stability analysis requirements. Because the operation of the power grid in China adopts a hierarchical management principle, the planning load flow calculation of the large power grid needs to utilize the scheduling plan data of the power grids at different levels of China, networks and provinces, and due to the compactness of the electrical connection of the power grids, the poor data of individual areas can influence the convergence of the overall calculation and the reasonability of results. In addition, certain deviation generally exists in scheduling plan data, wherein the accuracy of system load prediction and bus load prediction is greatly influenced by weather change and user randomness, and certain deviation also exists in a power generation plan, a tie line plan and a total provincial exchange plan which are derived from an economic scheduling algorithm based on direct current power flow, and the deviation is superposed to inevitably influence the convergence and the reasonability of a scheduling plan power flow. In addition, the scheduling plan lacks reactive planning data, which may cause low reactive voltage result precision in the generated planning load flow data, thereby affecting the rationality of the safety check result.
The planning load flow calculation has many data sources, large input data amount and uneven data quality, in order to continuously improve the calculation accuracy of the planning load flow from the management and the technology, key factors influencing the calculation accuracy of the planning load flow need to be researched, and the quantitative evaluation of the rationality influence factors of the planning load flow data is realized, so that the root tracing is facilitated, and the problems are solved from the data source and the model source.
Therefore, a technique is needed to achieve rationality assessment of large grid planned flows.
Disclosure of Invention
The invention provides a method and a system for evaluating the reasonability of a large power grid planning flow, which are used for solving the problem of how to evaluate the reasonability of the large power grid planning flow.
In order to solve the above problem, the present invention provides a method for rationality evaluation of a planned power flow of a large power grid, the method comprising:
establishing a first evaluation index set with reasonable data of a single-time-period operation mode;
establishing a second evaluation index set with reasonable data of a plurality of time period operation modes;
acquiring a data quality score of each evaluation index in the first evaluation index set at any time interval; acquiring average data quality scores of all evaluation indexes in the first evaluation index set at any time period;
acquiring a data quality score of each evaluation index in the second evaluation index set of the plurality of time periods; acquiring average data quality scores of all evaluation indexes in the second evaluation index set in multiple time periods;
determining an overall average data quality score of the first evaluation index set and the second evaluation index set based on the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set.
Preferably, the first evaluation index set includes:
the method comprises the steps of consistency of unit output and planned power, consistency of load active power and a predicted value, consistency of sub-province section active power flow and a sub-province total exchange plan, consistency of line state and a maintenance plan, planned non-networking of units, planned non-networking of loads, predicted value non-networking of loads, active power of balance nodes, reactive power of balance nodes, generator terminal voltage, bus node voltage and generator PQ node power factor.
Preferably, the second evaluation index set includes:
the active power change of the generator, the active power change of the load, the reactive power change of the generator, the reactive power change of the load and the on-off state change of the capacitive reactance device.
Preferably, the determining the overall average data quality score of the first evaluation index set and the second evaluation index set based on the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set comprises:
and determining the overall average data quality scores of the first evaluation index set and the second evaluation index set based on the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set, and setting different weights for the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set respectively.
Preferably, the higher the overall average data quality score is, the higher the rationality of the large grid plan power flow plan is.
According to another aspect of the present invention, there is provided a system for rationality assessment of a planned power flow of a large power grid, the system comprising:
the first establishing unit is used for establishing a first evaluation index set with reasonable single-time-period operation mode data;
the second establishing unit is used for establishing a second evaluation index set with reasonable data of the multiple time interval operation modes;
the first acquisition unit is used for acquiring the data quality score of each evaluation index in the first evaluation index set in any time period; acquiring average data quality scores of all evaluation indexes in the first evaluation index set at any time period;
a second obtaining unit configured to obtain a data quality score of each evaluation index in the second evaluation index set of the plurality of time periods; acquiring average data quality scores of all evaluation indexes in the second evaluation index set in multiple time periods;
a scoring unit configured to determine an overall average data quality score of the first evaluation index set and the second evaluation index set based on the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set.
Preferably, the first evaluation index set includes:
the method comprises the steps of consistency of unit output and planned power, consistency of load active power and a predicted value, consistency of sub-province section active power flow and a sub-province total exchange plan, consistency of line state and a maintenance plan, planned non-networking of units, planned non-networking of loads, predicted value non-networking of loads, active power of balance nodes, reactive power of balance nodes, generator terminal voltage, bus node voltage and generator PQ node power factor.
Preferably, the second evaluation index set includes:
the active power change of the generator, the active power change of the load, the reactive power change of the generator, the reactive power change of the load and the on-off state change of the capacitive reactance device.
Preferably, the scoring unit is configured to: determining an overall average data quality score of the first evaluation index set and the second evaluation index set based on the average data quality scores of all evaluation indexes in the first evaluation index set and the average data quality scores of all evaluation indexes in the second evaluation index set, including:
and determining the overall average data quality scores of the first evaluation index set and the second evaluation index set based on the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set, and setting different weights for the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set respectively.
Preferably, the scoring unit is configured to: the higher the overall average data quality score is, the higher the rationality of the large power grid planned power flow plan is.
The technical scheme of the invention provides a method and a system for evaluating the reasonability of a large power grid planning flow, and an index system for evaluating the reasonability of the large power grid planning flow is established. The technical scheme of the invention establishes a series of evaluation indexes aiming at the planning flow data of a single planning moment and a plurality of continuous planning moments and evaluates the rationality of the planning flow data. And then, establishing a calculation precision evaluation index respectively aiming at the active voltage result and the reactive voltage result of the planned power flow, analyzing and calculating the influence factors of the deviation, and carrying out quantitative evaluation on the influence factors.
Drawings
A more complete understanding of exemplary embodiments of the present invention may be had by reference to the following drawings in which:
FIG. 1 is a flow chart of a method for rationality assessment of a large grid planned power flow according to a preferred embodiment of the present invention;
FIG. 2 is a flow chart of a method for rationality assessment of a large grid planned power flow according to a preferred embodiment of the present invention;
fig. 3 is a flow chart of the line active power flow deviation calculation according to the preferred embodiment of the invention;
FIG. 4 is a flow chart of voltage deviation calculation according to a preferred embodiment of the present invention;
FIG. 5 is a graph illustrating the evaluation of average data quality at time 96 for each indicator in accordance with a preferred embodiment of the present invention;
FIG. 6 is a diagram illustrating average data quality scores at time 96 according to a preferred embodiment of the present invention;
FIG. 7 is a schematic diagram of a continuous multi-temporal average data quality score according to a preferred embodiment of the present invention;
FIG. 8 is a graph of mean deviation power at various times versus planned tidal flow yield in accordance with a preferred embodiment of the present invention;
FIG. 9 is a schematic diagram of daily deviation accumulation of line active power flow according to the preferred embodiment of the present invention; and
fig. 10 is a diagram of a system for rationality evaluation of a planned power flow of a large power grid according to a preferred embodiment of the present invention.
Detailed Description
The exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, however, the present invention may be embodied in many different forms and is not limited to the embodiments described herein, which are provided for complete and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention. In the drawings, the same units/elements are denoted by the same reference numerals.
Unless otherwise defined, terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Further, it will be understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense.
Fig. 1 is a flow chart of a method for rationality evaluation of a planned power flow of a large power grid according to a preferred embodiment of the invention. The embodiment of the application provides an evaluation index system for the rationality of the planned power flow of the large power grid aiming at the day-ahead scheduling plan of the power system, and solves the problem that the rationality of the planned power flow is not considered in the existing safety check method for the day-ahead scheduling plan. The technical problem to be solved by the application is an index system for evaluating the reasonability of the planned power flow of the large power grid. Specifically, a series of evaluation indexes are established for the planned power flow data of a single planning time and a plurality of continuous planning times, and the rationality of the planned power flow data is evaluated. And then, establishing a calculation precision evaluation index respectively aiming at the active voltage result and the reactive voltage result of the planned power flow, analyzing and calculating the influence factors of the deviation, and carrying out quantitative evaluation on the influence factors.
As shown in fig. 1, a method for rationality evaluation of a planned power flow of a large power grid, the method comprising:
preferably, in step 101: and establishing a first reasonable evaluation index set of the single-time-period operation mode data. Preferably, the first evaluation index set includes: the method comprises the steps of consistency of unit output and planned power, consistency of load active power and a predicted value, consistency of sub-province section active power flow and a sub-province total exchange plan, consistency of line state and a maintenance plan, planned non-networking of units, planned non-networking of loads, predicted value non-networking of loads, active power of balance nodes, reactive power of balance nodes, generator terminal voltage, bus node voltage and generator PQ node power factor.
Preferably, at step 102: and establishing a second evaluation index set with reasonable operation mode data in a plurality of time periods. Preferably, the second evaluation index set includes: the active power change of the generator, the active power change of the load, the reactive power change of the generator, the reactive power change of the load and the on-off state change of the capacitive reactance device.
Preferably, in step 103: acquiring a data quality score of each evaluation index in a first evaluation index set at any time interval; and acquiring the average data quality scores of all the evaluation indexes in the first evaluation index set in any time period.
Preferably, at step 104: acquiring a data quality score of each evaluation index in a second evaluation index set of a plurality of time periods; and acquiring the average data quality scores of all the evaluation indexes in the second evaluation index set of a plurality of time periods.
Preferably, at step 105: and determining the overall average data quality scores of the first evaluation index set and the second evaluation index set based on the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set.
Preferably, determining the overall average data quality score of the first evaluation index set and the second evaluation index set based on the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set comprises: and respectively setting different weights for the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set, and determining the overall average data quality scores of the first evaluation index set and the second evaluation index set.
Preferably, the higher the overall average data quality score, the higher the rationality of the large grid plan flow plan.
The application provides a large power grid plan flow rationality evaluation index system, which comprises the following steps:
1) evaluating the rationality of the data of the operation mode in a single time period;
2) evaluating the quality of the operation mode data in multiple time periods;
3) scheduling plan operation mode data rationality evaluation system;
4) evaluating the active accuracy of the planned power flow;
5) and (4) planning the accuracy evaluation of the tidal current reactive voltage.
And 1) performing reasonability evaluation on the operation mode data in a single time period in the step 1), performing data quality evaluation on the operation mode data at a certain planning moment of the scheduling plan, wherein the evaluation result reflects the data quality at the planning moment.
And 1) evaluating the rationality of the single-time-period operation mode data, namely evaluating the consistency of a planned power flow result and a planned value, the topology rationality, the active power flow rationality, the reactive power and the voltage rationality aiming at the scheduling planned operation mode data of the single time period, and establishing an evaluation index.
The single-time-period operation mode data rationality evaluation of the step 1), wherein the indexes of the consistency of the planned power flow result and the planned value comprise: the consistency of the output of the unit and the planned power, the consistency of the load active power and the predicted value, the consistency of the active power flow of the provincial section and the total provincial exchange plan, and the consistency of the line state and the maintenance plan. The detailed index specification, index calculation formula and scoring criteria are as follows:
evaluating the rationality of the operation mode data in a single time period in the step 1), wherein the indexes of the topology rationality comprise: the unit is planned to be not networked, the load is predicted value not networked, and the detailed index specification, the index calculation formula and the scoring standard are as follows:
evaluating the rationality of the operation mode data in a single time period in the step 1), wherein the index of the rationality of the active power flow comprises the following steps: the active power of the balance node is out of limit, and the detailed index specification, the index calculation formula and the scoring standard are as follows:
evaluating the reasonability of the running mode data in a single time period in the step 1), wherein indexes of the reasonability of the reactive voltage comprise: the balance node reactive power is out of limit, generator terminal voltage is out of limit, bus node voltage is out of limit, generator PQ node power factor is reasonable, and detailed index specification, index calculation formula and scoring standard are as follows:
the data quality evaluation of the multi-period operation mode in the step 2), the evaluation result can reflect the current and historical comprehensive level of an evaluation object, and the rationality of the operation mode of the dispatching plan can be more comprehensively evaluated by utilizing the dispatching operation rule and the dispatching plan time sequence characteristics
The multiple-time-interval operation mode data quality evaluation of the step 2) is to evaluate five aspects of unreasonable change of the active power of the generator, unreasonable change of the active power of the load, unreasonable change of the reactive power of the generator, unreasonable change of the reactive power of the load and unreasonable change of the putting-on and putting-off state of the capacitive reactance device aiming at the scheduling plan operation mode data of multiple time intervals, and establish evaluation indexes, wherein detailed index descriptions, index calculation formulas and grading standards are as follows:
the scheduling plan operation mode data rationality evaluation system of the step 3) aims at the scheduling plan operation mode data of a single time period and according to 11 indexes established in the step 1)
To
After the data quality evaluation is carried out, the average data quality score of the time interval is obtained, and the conversion is carried out according to the full score of 100 to obtain the data quality score of the ith time interval
The calculation formula is as follows:
in the formula
The j-th single period evaluation index representing the ith period is 110 full score before conversion.
The scheduling plan operation mode data rationality evaluation system of the step 3) calculates an average evaluation index aiming at the scheduling plan operation mode data of 96 time periods
The calculation formula is as follows:
step 3) of setting a single-period data quality score for the scheduling plan operation mode data rationality evaluation system
The threshold value of (1) is 95, the data quality qualification rate of the scheduling plan operation mode in 96 time periods can be counted
The scheduling plan operation mode data rationality evaluation system of the step 3) aims at the scheduling plan operation mode data of continuous multiple time intervals and according to the 5 indexes established in the step 2)
To
After data quality evaluation is carried out, average data quality scores are obtained, conversion is carried out according to the full score of 100, and data quality scores of multiple time interval angles are obtained
The calculation formula is as follows:
the scheduling plan operation mode data rationality evaluation system in the step 3) comprehensively considers the data rationality of the scheduling operation mode in a single time period and the data rationality of the scheduling operation mode in a plurality of time periods
Carrying out weighted average, and establishing average data quality score index C on the wholeRThe calculation formula is as follows:
according to the experience of lambda1Take 0.7, λ2Take 0.3.
The average data quality score index C can be used for the scheduling plan operation mode data rationality evaluation system in the step 3)RAnd scheduling plan operation mode data quality qualification rate in 96 time period
And evaluating the two indexes, wherein the higher the average data quality score index and the data quality qualified rate is, the higher the data reasonability of the operation mode of the scheduling plan is.
And 4) evaluating the active power accuracy of the plan power flow, wherein the active power flow of the scheduling plan operation mode data comprises line active power flow, generator and load active power, direct current line active power, transformer active power and provincial section active power.
And 4) evaluating the active power accuracy of the planned power flow, wherein the active power flow of the line in the planned power flow result is influenced by various scheduling planning factors such as power generation, load, direct current, provincial sections and the like. Therefore, the calculation accuracy of the planning power flow is mainly evaluated from the aspect of the line active power flow.
And 4) evaluating the active accuracy of the planned power flow, namely evaluating the active accuracy of the planned power flow by comparing the data of the operation mode of the scheduling plan with the measured data of the power grid operation corresponding to the scheduling date after the scheduling plan occurs.
Fig. 3 is a flow chart of the line active power flow deviation calculation according to the preferred embodiment of the present invention, as shown in fig. 3:
evaluating the active accuracy of the planned power flow in the step 4), and comparing the active power of the planned power flow of the line aiming at each line i in each planned time period
Active power measured by line
Statistical circuit plan tidal current deviation power
The statistical formula is as follows:
and 4) evaluating the active power accuracy of the planned power flow, setting a threshold value of power flow deviation of the line aiming at different voltage grades, considering that the accuracy of the line with the active power flow deviation smaller than the threshold value is qualified, and setting the active power flow deviation to be 0. And the active power flow calculation precision statistics is not carried out on the lines below 220 kV. Planned tidal current deviation power
The larger the line, the less accurate its calculation.
Evaluating the active power accuracy of the planned power flow in the step 4), and setting line power flow deviation threshold values aiming at different voltage levels, wherein the active power flow deviation threshold values of all the voltage levels are as shown in the following table:
evaluating the active accuracy of the planned power flow in the step 4), and counting the qualification rate Perc of the active power flow of the line aiming at the planned time period jLFjCalculating the average per-line offset power
The calculation formula is as follows:
evaluating the active accuracy of the planned power flow in the step 4), and comparing the qualification rates Perc of the active power flow in different time periodsLFjAnd line active deviation power
The active power flow calculation accuracy in different periods can be evaluated, and the planning time interval with poor accuracy in the corresponding planning day can be found out.
Evaluating the active accuracy of the planning power flow in the step 4), and calculating the average qualification rate Perc in 96 periods aiming at 96 scheduling planning periodsLFAvgAnd average deviation power in 96 time period
The calculation formula is as follows:
evaluating the active accuracy of the planned power flow in the step 4), and obtaining the average deviation power in 96 time periods
And 96-period average pass PercLFAvgThe method reflects the integral accuracy of the active power flow of the scheduling and planning operation mode of the corresponding planning day, the smaller the average deviation power is, the higher the average qualification rate is, andthe higher the accuracy of the power flow.
The active accuracy evaluation of the planned power flow in the step 4) can count the total sum of active power flow deviation in 96 periods of the line i
The calculation formula is as follows:
evaluating the active accuracy of the planned power flow in the step 4), and comparing the active power flow deviation sums of different lines
The line set with the most serious active power flow error corresponding to the planned day can be found out.
And 5) evaluating the accuracy of the planned tidal current reactive voltage, wherein the calculation accuracy of the node voltage mainly depends on the accuracy of the node reactive power setting and whether the voltage control target is correct. Therefore, the accuracy of the voltage result of the planning power flow node is focused.
And 5) evaluating the accuracy of the reactive voltage of the planned power flow, namely evaluating the accuracy of the node voltage of the planned power flow result by comparing the data of the operation mode of the scheduling plan with the measured data of the power grid operation corresponding to the planning date after the scheduling plan occurs.
Fig. 4 is a flowchart of voltage deviation calculation according to a preferred embodiment of the present invention, as shown in fig. 4:
step 5) of the accuracy evaluation of the reactive voltage of the planned power flow, aiming at each topological node i of each planned time interval, comparing the voltage of the node
And node measurement voltage
Counting node voltage deviation
The statistical formula is as follows:
and 5) evaluating the accuracy of the reactive voltage of the planned power flow, counting according to the voltage per unit value, setting a threshold value of the voltage deviation of the node to be 0.05, considering that the precision is qualified by the node with the voltage deviation of the node being less than the threshold value, and setting the voltage deviation to be 0. Deviation of voltage in planned power flow
The larger the node, the worse its computational accuracy.
Evaluating the accuracy of the reactive voltage of the planned power flow in the step 5), and counting the pass rate Perc of the node voltage aiming at the planned time period jVjCalculating an average per-node voltage deviation
The calculation formula is as follows:
evaluating the accuracy of the planned tidal current reactive voltage in the step 5), and comparing the voltage qualification rate Perc of the tidal current node at different voltage periodsVjAnd mean deviation of node voltage
The voltage calculation accuracy of different periods of time can be evaluated, and the planning time interval with poor voltage calculation accuracy in the corresponding planning day can be found out.
And 5) evaluating the accuracy of the reactive voltage of the planning power flow, namely calculating the average qualification in 96 time periods according to 96 scheduling planning time periodsRate PercVAvgAnd average offset voltage of 96 time periods
The calculation formula is as follows:
step 5), carrying out accuracy evaluation on the planned tidal current reactive voltage and carrying out average voltage deviation in 96 time periods
And 96-period average pass PercVAvgThe overall accuracy of the tidal current voltage of the operation mode of the scheduling plan corresponding to the planning day is reflected, the smaller the average voltage deviation is, the higher the average qualified rate is, and the higher the accuracy of the voltage is.
The accuracy evaluation of the planned tidal current reactive voltage in the step 5) can be used for counting the total sum of voltage deviations in 96 time periods of the bus node i
The calculation formula is as follows:
step 5), evaluating the accuracy of the planned tidal current reactive voltage, and comparing the sum of voltage deviations of different bus nodes
The node set with the most serious voltage error corresponding to the planned day can be found out.
The embodiment of the application provides an evaluation index system for the rationality of the planned power flow of the large power grid aiming at the day-ahead scheduling plan of the power system, solves the problem that the rationality of the planned power flow is not considered in the existing safety check method of the day-ahead scheduling plan, and has the following advantages:
1) the data reasonability evaluation result of the single-time-period operation mode can reflect the quality of the data at the planning moment.
2) The data quality evaluation results of the operation modes in multiple time periods can reflect the current and historical comprehensive levels of an evaluation object, and the rationality of the operation modes of the dispatching plan can be evaluated more comprehensively by utilizing the dispatching operation rule and the dispatching plan time sequence characteristics.
3) The data rationality of the scheduling plan operation mode can be comprehensively evaluated by the average data quality score index and the data quality qualification rate of the scheduling plan operation mode in 96 periods, and the higher the average data quality score index and the data quality qualification rate are, the higher the data rationality of the scheduling plan operation mode is.
4) The active power flow qualification rate and the line active deviation power can evaluate the active power flow calculation precision in different periods, and a planning time interval with poor precision in a corresponding planning day is found out.
5) The average deviation power in the 96 periods and the average qualification rate in the 96 periods can reflect the overall accuracy of the active power flow of the corresponding scheduling plan operation mode in the planning day, and the smaller the average deviation power is, the higher the average qualification rate is, and the higher the accuracy of the active power flow is.
6) By comparing the active power flow deviation sums of different lines, the line set with the most serious active power flow error corresponding to the planned day can be found out.
7) The flow node voltage qualification rate and the node voltage average deviation can evaluate the voltage calculation accuracy in different periods, and find out the planning time interval with poor voltage calculation accuracy in the corresponding planning day.
8) The average voltage deviation in the 96 periods and the average qualification rate in the 96 periods can reflect the overall accuracy of the tidal current voltage of the operation mode of the corresponding scheduling plan in the planning day, and the smaller the average voltage deviation is, the higher the average qualification rate is, and the higher the accuracy of the voltage is.
9) And the node set with the most serious voltage error corresponding to the planned day can be found by comparing the sum of the voltage deviations of different bus nodes.
The specific embodiments of the present application are illustrated as follows:
application verification is carried out by taking actual data of the Huazhong power grid 2015 at a certain day of 9 months as an example, and 3208 lines of 220kV and above are calculated on 6014 nodes.
Firstly, the rationality of the planning power flow data is evaluated. The calculation of the time average data quality score of each index 96 according to the single time planning load flow data rationality evaluation method is shown in fig. 5. The planned non-networking scores of the units are low, and the index evaluation details are checked to find that a large number of new energy units and small hydroelectric generating units are not networked due to the error of the power grid model.
The average data quality score at each moment is calculated 96 as shown in fig. 6, wherein the planned power flow data quality is poor in the period of 9:30-10:30, the analysis reason is that the power generation plan, the load prediction and the provincial section plan of a certain province are unbalanced, and the power output of the generator of the balance cluster is adjusted in order to control the provincial section power flow in the planned power flow calculation, so that the power output of the engine is inconsistent with the power generation plan.
According to the method for evaluating the rationality of the planned power flow data at a plurality of continuous moments, the evaluation indexes are calculated as shown in fig. 7, wherein the reactive power change index of the generator is low in score.
And evaluating the calculation accuracy of the planned load flow by only comparing with the actual operation data of the power grid. The active average deviation power of the line at the statistical time 96 and the qualification rate of the single-time planned power flow are shown in fig. 8, and it can be seen that the planning time interval with poor precision in the planned power flow on the day is 9:30-10:30, and is consistent with the interval with poor average data quality at each time in fig. 6.
The active power flow deviation sum of each line at 96 active power time points in the whole day is counted
In fig. 9, several lines with larger deviation are listed, that is, the line set with the most serious active power flow deviation in the day needs to be focused.
Fig. 10 is a diagram of a system for rationality evaluation of a planned power flow of a large power grid according to a preferred embodiment of the present invention. As shown in fig. 10, a system for rationality evaluation of a planned power flow of a large power grid, the system comprising:
a first establishing unit 1001 is configured to establish a first evaluation index set of single-period operation mode data rationality. Preferably, the first evaluation index set includes: the method comprises the steps of consistency of unit output and planned power, consistency of load active power and a predicted value, consistency of sub-province section active power flow and a sub-province total exchange plan, consistency of line state and a maintenance plan, planned non-networking of units, planned non-networking of loads, predicted value non-networking of loads, active power of balance nodes, reactive power of balance nodes, generator terminal voltage, bus node voltage and generator PQ node power factor.
A second establishing unit 1002, configured to establish a second evaluation index set of reasonable multiple time period operation manner data. Preferably, the second evaluation index set includes: the active power change of the generator, the active power change of the load, the reactive power change of the generator, the reactive power change of the load and the on-off state change of the capacitive reactance device.
A first obtaining unit 1003, configured to obtain a data quality score of each evaluation index in a first evaluation index set of any time period; and acquiring the average data quality scores of all the evaluation indexes in the first evaluation index set in any time period.
A second acquisition unit 1004 for acquiring a data quality score of each evaluation index in a second evaluation index set of a plurality of periods; and acquiring the average data quality scores of all the evaluation indexes in the second evaluation index set of a plurality of time periods.
The scoring unit 1005 is configured to determine an overall average data quality score of the first evaluation index set and the second evaluation index set based on the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set.
Preferably, the scoring unit 1005 is configured to: determining the overall average data quality scores of the first evaluation index set and the second evaluation index set based on the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set, including:
and respectively setting different weights for the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set, and determining the overall average data quality scores of the first evaluation index set and the second evaluation index set.
Preferably, the scoring unit 1005 is configured to: the higher the overall average data quality score is, the higher the rationality of the planning flow plan of the large power grid is.
The system 10 for performing rationality evaluation on a large power grid planned power flow according to the preferred embodiment of the present invention corresponds to the method 100 for performing rationality evaluation on a large power grid planned power flow according to the preferred embodiment of the present invention, and details thereof are not described herein again.
The invention has been described with reference to a few embodiments. However, other embodiments of the invention than the one disclosed above are equally possible within the scope of the invention, as would be apparent to a person skilled in the art from the appended patent claims.
Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to "a/an/the [ device, component, etc ]" are to be interpreted openly as referring to at least one instance of said device, component, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated.
Claims (6)
1. A method for rationality assessment of a large grid planned flow, the method comprising:
establishing a first evaluation index set with reasonable data of a single-time-period operation mode;
establishing a second evaluation index set with reasonable data of a plurality of time period operation modes;
acquiring a data quality score of each evaluation index in the first evaluation index set at any time interval; acquiring average data quality scores of all evaluation indexes in the first evaluation index set at any time period; the first set of evaluation metrics includes one or more of the following evaluation metrics:
the consistency of the output of the unit and the planned power, the consistency of the load active power and the predicted value, the consistency of the active power flow of the provincial section and the provincial total exchange plan, the consistency of the line state and the maintenance plan, the planned non-networking of the unit, the non-networking of the load predicted value, the active power of a balance node, the reactive power of the balance node, the terminal voltage of a generator, the node voltage of a bus and the power factor of a PQ node of the generator;
acquiring a data quality score of each evaluation index in the second evaluation index set of the plurality of time periods; acquiring average data quality scores of all evaluation indexes in the second evaluation index set in multiple time periods; the second set of evaluation metrics includes one or more of the following evaluation metrics:
the active power change of the generator, the active power change of the load, the reactive power change of the generator, the reactive power change of the load and the on-off state change of the capacitive reactance device;
determining an overall average data quality score of the first evaluation index set and the second evaluation index set based on the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set.
2. The method of claim 1, wherein determining an overall average data quality score for the first set of evaluation metrics and the second set of evaluation metrics based on the average data quality scores for all evaluation metrics in the first set of evaluation metrics and the average data quality scores for all evaluation metrics in the second set of evaluation metrics comprises:
and determining the overall average data quality scores of the first evaluation index set and the second evaluation index set based on the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set, and setting different weights for the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set respectively.
3. The method according to claim 1, wherein the higher the overall average data quality score, the higher the large grid plan flow plan rationality.
4. A system for rationality assessment of a large grid planned flow, the system comprising:
the first establishing unit is used for establishing a first evaluation index set with reasonable single-time-period operation mode data;
the second establishing unit is used for establishing a second evaluation index set with reasonable data of the multiple time interval operation modes;
the first acquisition unit is used for acquiring the data quality score of each evaluation index in the first evaluation index set in any time period; acquiring average data quality scores of all evaluation indexes in the first evaluation index set at any time period; the first set of evaluation metrics includes one or more of the following evaluation metrics:
the consistency of the output of the unit and the planned power, the consistency of the load active power and the predicted value, the consistency of the active power flow of the provincial section and the provincial total exchange plan, the consistency of the line state and the maintenance plan, the planned non-networking of the unit, the non-networking of the load predicted value, the active power of a balance node, the reactive power of the balance node, the terminal voltage of a generator, the node voltage of a bus and the power factor of a PQ node of the generator;
a second obtaining unit configured to obtain a data quality score of each evaluation index in the second evaluation index set of the plurality of time periods; acquiring average data quality scores of all evaluation indexes in the second evaluation index set in multiple time periods; the second set of evaluation metrics includes one or more of the following evaluation metrics:
the active power change of the generator, the active power change of the load, the reactive power change of the generator, the reactive power change of the load and the on-off state change of the capacitive reactance device;
a scoring unit configured to determine an overall average data quality score of the first evaluation index set and the second evaluation index set based on the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set.
5. The system of claim 4, the scoring unit to: determining an overall average data quality score of the first evaluation index set and the second evaluation index set based on the average data quality scores of all evaluation indexes in the first evaluation index set and the average data quality scores of all evaluation indexes in the second evaluation index set, including:
and determining the overall average data quality scores of the first evaluation index set and the second evaluation index set based on the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set, and setting different weights for the average data quality scores of all the evaluation indexes in the first evaluation index set and the average data quality scores of all the evaluation indexes in the second evaluation index set respectively.
6. The system of claim 4, the scoring unit to: the higher the overall average data quality score is, the higher the rationality of the large power grid planned power flow plan is.
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