CN112838621A - Electric power system frequency modulation capacity realization method considering new energy growth - Google Patents

Electric power system frequency modulation capacity realization method considering new energy growth Download PDF

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CN112838621A
CN112838621A CN202110085995.6A CN202110085995A CN112838621A CN 112838621 A CN112838621 A CN 112838621A CN 202110085995 A CN202110085995 A CN 202110085995A CN 112838621 A CN112838621 A CN 112838621A
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frequency modulation
capacity
photovoltaic
normal distribution
condition
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CN112838621B (en
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王梦圆
严正
王晗
徐潇源
黄晨洋
贠靖洋
程基峰
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Shanghai Jiaotong University
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/48—Controlling the sharing of the in-phase component
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers

Abstract

A method for realizing the frequency modulation capacity of a power system considering the increase of new energy comprises the steps of respectively collecting upward and downward frequency modulation quantity data of a power grid and measuring and calculating to obtain the upward and downward frequency modulation quantities of a target time period; according to the upward frequency modulation amount, the downward frequency modulation amount, the fan and the photovoltaic increment megawatt of the target time interval, the power grid frequency modulation resource demand of the target time interval is measured and calculated, and according to the actual operation data of the power grid, CPS1 and CPS2 are used as evaluation indexes to dynamically adjust the frequency modulation resource demand of the target time interval of the power grid. The method obtains the frequency modulation capacity requirement by measuring and calculating the deviation between the node load and the economic dispatching point, and then dynamically corrects according to the actual running condition. The method is used for calculating the demand of system frequency modulation resources, has clear physical significance, can fully utilize the historical data of the power grid, gives consideration to the rapid development of new energy, calculates aiming at a specific time period and a target power grid, and has the advantages that the result is more in line with the actual situation and the accuracy is higher.

Description

Electric power system frequency modulation capacity realization method considering new energy growth
Technical Field
The invention relates to a technology in the field of power system control, in particular to a method for realizing frequency modulation capacity of a power system considering new energy increase.
Background
The frequency modulation auxiliary service is an important part in the dispatching operation of the power system, and the accurate calculation of the frequency modulation capacity required by the system is an important precondition for organizing the market transaction of the frequency modulation auxiliary service and ensuring the safe and stable operation of the system. In actual power grid operation, an operator often sets a required frequency modulation capacity to a certain value according to experience, but in recent years, as the installed capacity of new energy is rapidly increased, the fluctuation of new energy output increases the fluctuation of a system power supply side, and the new energy output is difficult to predict, so that the safety and the economy of power grid operation cannot be considered by using a certain fixed value as the frequency modulation capacity. In order to consider the fluctuation of new energy output, a plurality of methods for calculating the frequency modulation capacity of the power grid in a data-driven mode based on historical data are proposed, and compared with the method for setting the frequency modulation capacity to a certain value only by experience, the method can better consider the operation condition of the power grid. However, the installed quantity of new energy resources is greatly increased year by year, the current frequency modulation capacity is estimated only by the historical new energy data, and the frequency modulation capacity demand condition of the power grid in a future period of time (such as one year) cannot be reasonably reflected, so that the invention provides a method for realizing the frequency modulation capacity of the power system considering the increase of the new energy resources.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a method for realizing the frequency modulation capacity of the power system considering the increase of new energy, wherein a fan and photovoltaic increment megawatts are introduced, the frequency modulation capacity is obtained by measuring and calculating the deviation of node load and an economic dispatching point, and dynamic correction is carried out according to the actual operation condition. The method is used for calculating the frequency modulation capacity of the system, has clear physical significance, can fully consider the rapid development of new energy, calculates aiming at a specific time period and a target power grid, and has higher accuracy, and the result is more in line with the actual condition of the power grid in a future time period.
The invention is realized by the following technical scheme:
the invention relates to a method for realizing the frequency modulation capacity of a power system considering the increase of new energy, which comprises the steps of respectively collecting the data of upward and downward frequency modulation quantities of a power grid and measuring and calculating the data to obtain the upward and downward frequency modulation quantities of a target time interval; according to the upward frequency modulation amount, the downward frequency modulation amount, the fan and the photovoltaic increment megawatt of the target time interval, the power grid frequency modulation capacity required by the target time interval is measured and calculated, and according to the actual operation data of the power grid, CPS1 and CPS2 are used as evaluation indexes to dynamically adjust the frequency modulation capacity of the power grid in the target time interval.
The step of collecting the upward and downward frequency modulation data of the power grid is as follows: counting historical data of upward frequency modulation quantity deployed in the same month of the previous two years, fitting the data by using normal distribution according to data of 5min, recording the demand with the confidence coefficient of 95%, counting data with positive load change of nodes in the same month of the previous two years, fitting the data by using normal distribution, and recording the demand with the confidence coefficient of 95%.
The upward and downward frequency modulation data are as follows: taking the maximum value of the two as the upward frequency modulation amount of the target time interval
Figure BDA0002910817280000021
Taking the maximum value of the two as the negative frequency modulation quantity of the target time interval
Figure BDA0002910817280000022
Wherein:
Figure BDA00029108172800000218
is the upward frequency modulation amount of the target time interval;
Figure BDA0002910817280000023
normal score of upward modulation for same month deployment in previous two yearsThe mean value of the cloth;
Figure BDA0002910817280000024
the mean value of normal distribution that the node load change in the same month in the previous two years is positive;
Figure BDA00029108172800000219
is the confidence level; sigma1+Is the variance of the normal distribution of the upward frequency modulation deployed for the same month in the previous two years; sigma2+The variance of normal distribution is that the load change of the same-month node in the previous two years is positive; n is1+The number of samples of normal distribution of upward modulation frequency deployed in the same month in the previous two years; n is2+The number of samples of normal distribution in which the node load change is positive in the same month in the previous two years;
Figure BDA00029108172800000220
is the downward frequency modulation amount of the target time interval;
Figure BDA0002910817280000025
the mean value of normal distribution of downward frequency modulation quantity deployed in the same month in the previous two years;
Figure BDA0002910817280000026
the average value of normal distribution that the node load change of the same month in the previous two years is negative;
Figure BDA00029108172800000217
are all confidence levels; sigma1-Is the variance of the normal distribution of the down-modulation variables deployed for the same month in the previous two years; sigma2-The variance of normal distribution is that the load change of the same-month node in the previous two years is negative; n is1-The number of samples of normal distribution of downward frequency modulation quantity deployed in the same month in the previous two years; n is2-The number of samples of normal distribution in which the node load change is negative in the same month in the previous two years.
The fan and photovoltaic increment megawatt are embodied in the frequency modulation capacity by using the fan and photovoltaic increment megawatt for the newly added fan and photovoltaic capacity, and the megawatt capacity is increased every time the installed capacity of 1000 megawatts is newly increased.
The megawatt increment of the fan and the photovoltaic is as follows: the sum of the fan, the photovoltaic incremental frequency modulation capacity and the additional fan adjustment of the previous year:
Figure BDA0002910817280000027
wherein:
Figure BDA0002910817280000028
increasing the frequency modulation capacity for the fan in the year;
Figure BDA0002910817280000029
the frequency modulation capacity is increased for the fan in the previous year; additional fan adjustment
Figure BDA00029108172800000210
Figure BDA00029108172800000211
The mean value of the normal distribution fitted by the smooth function under the condition of the current fan capacity;
Figure BDA00029108172800000212
the mean value of normal distribution fitted by a frequency modulation smooth function under the windless condition;
Figure BDA00029108172800000221
as a confidence, 98.8%; sigmawThe variance of the normal distribution fitted for the smoothing function under the condition of the current fan capacity; sigmanwThe variance of the normal distribution fitted to the smoothing function in the absence of wind; n iswThe number of samples of normal distribution fitted for a smooth function under the condition of current fan capacity; n isnwThe number of samples of normal distribution fitted for the smooth function under windless conditions;
Figure BDA00029108172800000213
the photovoltaic increment frequency modulation capacity of the year;
Figure BDA00029108172800000214
the photovoltaic incremental frequency modulation capacity of the previous year(ii) a Additional photovoltaic adjustment
Figure BDA00029108172800000215
A mean value of normal distribution fitted for a smooth function under the current photovoltaic capacity;
Figure BDA00029108172800000216
the mean value of normal distribution fitted for the frequency modulation smoothing function under the condition of no photovoltaic;
Figure BDA00029108172800000222
as a confidence, 98.8%; sigmasA variance of a normal distribution fitted to a smoothing function under a current photovoltaic capacity; sigmansThe variance of a normal distribution fitted to a smooth function in the absence of a photovoltaic; n issThe number of samples of normal distribution fitted to a smoothing function under the current photovoltaic capacity; n isnsNumber of samples of a normal distribution fitted to a smooth function without photovoltaic.
The smoothing function includes:
a first part: calculating an adjustment load component for a period corresponding to the target period using a rolling average method based on the history data;
a second part: calculating an adjustment load component of a corresponding time period of the previous month by using a rolling average method based on historical data;
and a third part: calculating an adjustment load component of a corresponding time period in a month subsequent to the month in which the target time period is located by using a rolling average method based on the historical data;
the fourth part: calculating the adjustment load component of the previous hour of the corresponding time period in the same month of the month in which the target time period is based on the historical data by using a rolling average method;
the fifth part is that: calculating an adjustment load component of a next hour of a corresponding period in the same month as the month in which the target period is based on the history data using a rolling average method,
the five parts of the calculation modes of the smoothing function are as follows: and rolling and averaging the values of the previous and the next load values of each load value in the time interval to obtain a smooth load curve, wherein the difference between the actual load and the average load at the target moment is an adjusting load component.
The expression of the smoothing function corresponding to the current fan capacity is
Figure BDA0002910817280000031
Figure BDA0002910817280000032
Wherein: pwThe function is a smooth function under the condition of the current fan capacity;
Figure BDA0002910817280000033
the load component of the first part under the condition of the current fan capacity is adjusted;
Figure BDA0002910817280000034
the adjusted load component of the second part under the condition of the current fan capacity;
Figure BDA0002910817280000035
the adjustment load component of the third part under the condition of the current fan capacity;
Figure BDA0002910817280000036
the fourth part of the regulation load component under the condition of the current fan capacity;
Figure BDA0002910817280000037
the load component of the fifth part under the condition of the current fan capacity is adjusted; corresponding to the expression in the absence of wind as
Figure BDA0002910817280000038
Figure BDA0002910817280000039
Wherein: pnwThe function is a smooth function under the condition of no wind;
Figure BDA00029108172800000310
in the absence of windA regulated load component of the first part;
Figure BDA00029108172800000311
the adjustment load component of the second part under the windless condition;
Figure BDA00029108172800000312
the regulation load component of the third part under the windless condition;
Figure BDA00029108172800000313
the fourth part is the regulation load component under the windless condition;
Figure BDA00029108172800000314
the adjustment load component of the fifth part in the windless situation.
The expression of the smoothing function corresponding to the current photovoltaic capacity is
Figure BDA00029108172800000315
Figure BDA00029108172800000316
Wherein: psA smoothing function under the condition of the current photovoltaic capacity;
Figure BDA00029108172800000317
the regulation load component of the first part under the condition of the current photovoltaic capacity;
Figure BDA00029108172800000318
the regulated load component of the second part under the current photovoltaic capacity condition;
Figure BDA00029108172800000319
the regulation load component of the third part under the condition of the current photovoltaic capacity;
Figure BDA00029108172800000320
the adjustment load component of the fourth part under the condition of the current photovoltaic capacity;
Figure BDA00029108172800000321
the regulation load component of the fifth part under the condition of the current photovoltaic capacity; corresponding to the expression in the absence of photovoltaic
Figure BDA00029108172800000322
Figure BDA00029108172800000323
Wherein: pnsA smoothing function in the absence of photovoltaic;
Figure BDA00029108172800000324
a regulated load component for the first portion in the absence of photovoltaic conditions;
Figure BDA00029108172800000325
a regulated load component for the second portion in the absence of photovoltaic conditions;
Figure BDA00029108172800000326
a third portion of the regulated load component in the absence of photovoltaic conditions;
Figure BDA00029108172800000327
the fourth part is the regulation load component under the condition of no photovoltaic;
Figure BDA00029108172800000328
the regulated load component of the fifth section in the absence of photovoltaic.
The upward and downward frequency modulation amount of the target time period refers to: demand for capacity of upward frequency modulation
Figure BDA00029108172800000329
Figure BDA0002910817280000041
Downward frequency modulation capacity demand
Figure BDA0002910817280000042
The evaluation indexes are as follows: the average of CPS1 scores per month and the rolling average of CPS1 over 12 months are used to adjust the capacity requirements of the AGC per hour over the month. CPS1 indexes mainly consider the relation between the average value of ACE and the average value of frequency deviation in a control area, and measure whether the root mean square value of the long-term (such as one month) frequency deviation of a power grid is in a limited range or not by taking the average value of 1min as a reference, so that the influence of the area ACE on the frequency deviation of the whole interconnected power grid in a period of time is evaluated, and the comprehensive control performance of the area is reflected. CPS2 index examines whether the average value of the ACE in the control area meets the requirement of a given threshold value, takes the average value of 10min as a reference, can minimize the number of times of unit adjustment when the CPS1 target is completed, plays a role in reducing the deviation plan trend and the deviation plan electric quantity among areas, and evaluates the frequency modulation capacity and the continuous adjustment capacity of the control area.
The dynamic adjustment of the frequency modulation capacity of the power grid in the target time period is as follows: when the average value of CPS1 in a month is lower than 140%, 10% of frequency modulation capacity is additionally added in each hour in the month. If the rolling average value of CPS1 in 12 months is lower than 140%, then additional 10% FM capacity is added in next month per hour, and if CPS1 score is lower than 100%, then 20% FM capacity is added.
Technical effects
Compared with the prior art, the method considers the influence of the new energy output increase on the frequency modulation capacity demand in a mode of fan increment megawatt and photovoltaic increment megawatt. The frequency modulation capacity is defined as the deviation between the node load and the economic dispatching point by combining the newly added installed capacity of the new energy of the power grid, the historical data of the power grid is fully utilized, the target power grid and the future time period are calculated in a targeted mode, the result is more in line with the actual situation, and the accuracy is higher. And finally, dynamic correction is carried out according to the actual operation condition, so that the reliability of the calculated required frequency modulation capacity is improved, and the system safety is better guaranteed.
Drawings
FIG. 1 is a flow chart of the present invention.
Fig. 2 is an information flow diagram of a power system frequency modulation capacity calculation system.
Detailed Description
The embodiment relates to a power system frequency modulation capacity calculation system for considering new energy growth, which comprises: collection module, frequency modulation amount calculation module, new forms of energy calculation module, frequency modulation demand module and dynamic adjustment module, wherein: the acquisition module is used for acquiring and recording the load value, the upward frequency modulation amount and the downward frequency modulation amount of each time period of the power system, and the CPS1 score and the CPS2 score of each month; the frequency modulation amount calculation module is used for calculating the upward frequency modulation amount and the downward frequency modulation amount of each target time interval of the power system according to historical data; the new energy calculating module is used for calculating fan increment megawatts and photovoltaic increment megawatts; the frequency modulation demand module is used for calculating an upward frequency modulation demand and a downward frequency modulation demand of a target time period according to the results calculated by the frequency modulation amount calculation module and the new energy calculation module; the dynamic adjustment module is used for dynamically correcting the upward frequency modulation requirement and the downward frequency modulation requirement of the power grid according to the time running condition of the power grid, namely CPS1 and CPS2 indexes; the acquisition module is connected with the frequency modulation amount calculation module and is used for transmitting historical data such as load values, upward frequency modulation amounts, downward frequency modulation amounts and the like of each time period of the power system; the acquisition module is connected with the new energy calculation module and is used for transmitting the fan, the photovoltaic increment megawatt and related historical data, and meanwhile, the fan and the photovoltaic increment megawatt calculated by the new energy calculation module are transmitted to the acquisition module for recording; the acquisition module is connected with the dynamic adjustment module and transmits data of CPS1 scores and CPS2 scores of each month in actual operation; the frequency modulation amount calculation module and the new energy calculation module are connected with the frequency modulation demand module and provide data required by calculating the frequency modulation demand; and the dynamic adjusting module is connected with the frequency modulation demand module to correct the frequency modulation demand.
The method for realizing the frequency modulation capacity of the power system considering the new energy increase based on the system comprises the following steps:
collecting upward frequency modulation data of the power grid, and calculating the upward frequency modulation of the target time period according to the step 1.1;
collecting downward frequency modulation data of the power grid, and calculating downward frequency modulation of the target time period according to the step 2.1;
for the newly added fan capacity, fan increment megawatts are used for embodying in the frequency modulation capacity, the megawatt capacity is increased every time 1000 megawatts of installed capacity is newly increased, and the fan increment megawatts in the target time period is calculated according to the step 3.1;
for the newly increased photovoltaic capacity, the photovoltaic increment megawatts is used for embodying in the frequency modulation capacity, the megawatt capacity is increased every time the 1000 megawatt installed capacity is newly increased, and the fan increment megawatts in the target time period is calculated according to the step 4.1;
calculating the power grid frequency modulation capacity requirement of the target time period according to the step 5.1 according to the upward frequency modulation amount, the downward frequency modulation amount, the fan increment megawatt and the photovoltaic increment megawatt of the target time period;
and according to the actual operation data of the power grid, correcting the frequency modulation capacity of the power grid in the target time period according to the step 6.1 by using CPS1 and CPS2 as evaluation indexes.
Compared with the prior art, the method fully considers the increase of new energy in a period of time in the future, carries out targeted calculation on a specific time period and a target power grid, can meet the objective requirement of the annual increase of the installed capacity of the new energy in recent years and the demand of electric power marketization, has more practical results and higher accuracy, and is favorable for ensuring the system stability under the condition of vigorous development of the new energy.
The foregoing embodiments may be modified in many different ways by those skilled in the art without departing from the spirit and scope of the invention, which is defined by the appended claims and all changes that come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.

Claims (10)

1. A method for realizing the frequency modulation capacity of a power system considering the increase of new energy is characterized in that the upward and downward frequency modulation quantity of a target time period is obtained by respectively collecting the upward and downward frequency modulation quantity data of a power grid and measuring and calculating; according to the upward frequency modulation amount, the downward frequency modulation amount, the fan and the photovoltaic increment megawatt of the target time interval, measuring and calculating the power grid frequency modulation resource demand of the target time interval, and dynamically adjusting the frequency modulation resource demand of the power grid target time interval by using CPS1 and CPS2 as evaluation indexes according to the actual operation data of the power grid;
the step of collecting the upward and downward frequency modulation data of the power grid is as follows: counting historical data of upward frequency modulation quantity deployed in the same month of the previous two years, fitting the data by using normal distribution for one data in 5min, recording the demand quantity with the confidence coefficient of 95%, counting the data with the load change of nodes in the same month of the previous two years being positive, fitting the data by using normal distribution, and recording the demand quantity with the confidence coefficient of 95%;
the fan and photovoltaic increment megawatt are embodied in the frequency modulation capacity by using the fan and photovoltaic increment megawatt for the newly added fan and photovoltaic capacity, and the megawatt capacity is increased every time the installed capacity of 1000 megawatts is newly increased.
2. The method for realizing the frequency modulation capacity of the power system in consideration of the new energy increase as claimed in claim 1, wherein the upward and downward frequency modulation data are: taking the maximum value of the two as the upward frequency modulation amount of the target time interval
Figure FDA0002910817270000011
Figure FDA0002910817270000012
Taking the maximum value of the two as the negative frequency modulation quantity of the target time interval
Figure FDA0002910817270000013
Figure FDA0002910817270000014
Wherein:
Figure FDA00029108172700000116
is the upward frequency modulation amount of the target time interval;
Figure FDA0002910817270000015
the mean value of normal distribution of upward frequency modulation quantity deployed in the same month in the previous two years;
Figure FDA0002910817270000016
the mean value of normal distribution that the node load change in the same month in the previous two years is positive;
Figure FDA0002910817270000017
is the confidence level; sigma1+Is the variance of the normal distribution of the upward frequency modulation deployed for the same month in the previous two years; sigma2+The variance of normal distribution is that the load change of the same-month node in the previous two years is positive; n is1+The number of samples of normal distribution of upward modulation frequency deployed in the same month in the previous two years; n is2+The number of samples of normal distribution in which the node load change is positive in the same month in the previous two years;
Figure FDA00029108172700000117
is the downward frequency modulation amount of the target time interval;
Figure FDA0002910817270000018
the mean value of normal distribution of downward frequency modulation quantity deployed in the same month in the previous two years;
Figure FDA0002910817270000019
the average value of normal distribution that the node load change of the same month in the previous two years is negative;
Figure FDA00029108172700000110
are all confidence levels; sigma1-Is the variance of the normal distribution of the down-modulation variables deployed for the same month in the previous two years; sigma2-The variance of normal distribution is that the load change of the same-month node in the previous two years is negative; n is1-The number of samples of normal distribution of downward frequency modulation quantity deployed in the same month in the previous two years; n is2-The number of samples of normal distribution in which the node load change is negative in the same month in the previous two years.
3. The method for realizing the frequency modulation capacity of the power system considering the new energy increase as claimed in claim 1, wherein the blower and the photovoltaic increment megawatt are as follows:the sum of the fan, the photovoltaic incremental frequency modulation capacity and the additional fan adjustment of the previous year:
Figure FDA00029108172700000111
wherein:
Figure FDA00029108172700000112
increasing the frequency modulation capacity for the fan in the year;
Figure FDA00029108172700000113
the frequency modulation capacity is increased for the fan in the previous year; additional fan adjustment
Figure FDA00029108172700000114
Figure FDA00029108172700000115
The mean value of the normal distribution fitted by the smooth function under the condition of the current fan capacity;
Figure FDA0002910817270000021
the mean value of normal distribution fitted by a frequency modulation smooth function under the windless condition;
Figure FDA0002910817270000022
as a confidence, 98.8%; sigmawThe variance of the normal distribution fitted for the smoothing function under the condition of the current fan capacity; sigmanwThe variance of the normal distribution fitted to the smoothing function in the absence of wind; n iswThe number of samples of normal distribution fitted for a smooth function under the condition of current fan capacity; n isnwThe number of samples of normal distribution fitted for the smooth function under windless conditions;
Figure FDA0002910817270000023
the photovoltaic increment frequency modulation capacity of the year;
Figure FDA00029108172700000215
the photovoltaic incremental frequency modulation capacity of the previous year; additional photovoltaic adjustment
Figure FDA0002910817270000024
Figure FDA0002910817270000025
A mean value of normal distribution fitted for a smooth function under the current photovoltaic capacity;
Figure FDA0002910817270000026
the mean value of normal distribution fitted for the frequency modulation smoothing function under the condition of no photovoltaic;
Figure FDA0002910817270000027
as a confidence, 98.8%; sigmasA variance of a normal distribution fitted to a smoothing function under a current photovoltaic capacity; sigmansThe variance of a normal distribution fitted to a smooth function in the absence of a photovoltaic; n issThe number of samples of normal distribution fitted to a smoothing function under the current photovoltaic capacity; n isnsNumber of samples of a normal distribution fitted to a smooth function without photovoltaic.
4. The method as claimed in claim 1, wherein the smoothing function comprises:
1) a first part: calculating an adjustment load component for a period corresponding to the target period using a rolling average method based on the history data;
2) a second part: calculating an adjustment load component of a corresponding time period of the previous month by using a rolling average method based on historical data;
3) and a third part: calculating an adjustment load component of a corresponding time period in a month subsequent to the month in which the target time period is located by using a rolling average method based on the historical data;
4) the fourth part: calculating the adjustment load component of the previous hour of the corresponding time period in the same month of the month in which the target time period is based on the historical data by using a rolling average method;
5) the fifth part is that: calculating the adjustment load component of the next hour of the corresponding time period in the same month of the month in which the target time period is based on the historical data by using a rolling average method;
the five parts of the calculation modes of the smoothing function are as follows: and rolling and averaging the values of the previous and the next load values of each load value in the time interval to obtain a smooth load curve, wherein the difference between the actual load and the average load at the target moment is an adjusting load component.
5. The method as claimed in claim 1 or 4, wherein the smoothing function is expressed as the smoothing function corresponding to the current fan capacity
Figure FDA0002910817270000028
Figure FDA0002910817270000029
Wherein: pwThe function is a smooth function under the condition of the current fan capacity;
Figure FDA00029108172700000210
the load component of the first part under the condition of the current fan capacity is adjusted;
Figure FDA00029108172700000211
the adjusted load component of the second part under the condition of the current fan capacity;
Figure FDA00029108172700000212
the adjustment load component of the third part under the condition of the current fan capacity;
Figure FDA00029108172700000213
the fourth part of the regulation load component under the condition of the current fan capacity;
Figure FDA00029108172700000214
the load component of the fifth part under the condition of the current fan capacity is adjusted; corresponding to the expression in the absence of wind as
Figure FDA0002910817270000031
Figure FDA0002910817270000032
Wherein: pnwThe function is a smooth function under the condition of no wind;
Figure FDA0002910817270000033
the adjustment load component of the first part under the windless condition;
Figure FDA0002910817270000034
the adjustment load component of the second part under the windless condition;
Figure FDA0002910817270000035
the regulation load component of the third part under the windless condition;
Figure FDA0002910817270000036
the fourth part is the regulation load component under the windless condition;
Figure FDA0002910817270000037
the adjustment load component of the fifth part in the windless situation.
6. The method as claimed in claim 5, wherein the smoothing function is expressed as the current photovoltaic capacity
Figure FDA0002910817270000038
Figure FDA0002910817270000039
Wherein: psA smoothing function under the condition of the current photovoltaic capacity;
Figure FDA00029108172700000310
the regulation load component of the first part under the condition of the current photovoltaic capacity;
Figure FDA00029108172700000311
the regulated load component of the second part under the current photovoltaic capacity condition;
Figure FDA00029108172700000312
the regulation load component of the third part under the condition of the current photovoltaic capacity;
Figure FDA00029108172700000313
the adjustment load component of the fourth part under the condition of the current photovoltaic capacity;
Figure FDA00029108172700000314
the regulation load component of the fifth part under the condition of the current photovoltaic capacity; corresponding to the expression in the absence of photovoltaic
Figure FDA00029108172700000315
Figure FDA00029108172700000316
Wherein: pnsA smoothing function in the absence of photovoltaic;
Figure FDA00029108172700000317
a regulated load component for the first portion in the absence of photovoltaic conditions;
Figure FDA00029108172700000318
a regulated load component for the second portion in the absence of photovoltaic conditions;
Figure FDA00029108172700000319
a third portion of the regulated load component in the absence of photovoltaic conditions;
Figure FDA00029108172700000320
the fourth part is the regulation load component under the condition of no photovoltaic;
Figure FDA00029108172700000321
the regulated load component of the fifth section in the absence of photovoltaic.
7. The method as claimed in claim 1, wherein the step of implementing the fm capacity of the power system in consideration of the new energy increase comprises: upward frequency modulated resource demand
Figure FDA00029108172700000322
Figure FDA00029108172700000323
Downward frequency modulated resource demand
Figure FDA00029108172700000324
8. The method for realizing the frequency modulation capacity of the power system considering the new energy increase as claimed in claim 1, wherein the evaluation index is: using an average of CPS1 scores per month and a rolling average of CPS1 over 12 months to adjust the capacity requirements of the AGC per hour over the month; the CPS1 index reflects the relation between the ACE average value and the frequency deviation average value of the control area, takes the average value of 1min as a reference, measures whether the root mean square value of the long-term frequency deviation of the power grid is in a limited range, is used for evaluating the influence of the area ACE on the frequency deviation of the whole interconnected power grid within a period of time and reflects the comprehensive control performance of the area; the CPS2 index reflects whether the average value of the ACE in the control area meets the requirement of a given threshold value, the average value of 10min is taken as a reference, the number of times of unit adjustment can be minimized when the CPS1 target is completed, the effects of reducing deviation plan power flow and deviation plan electric quantity among areas are achieved, and the frequency modulation capacity and continuous adjustment capacity of the control area are evaluated.
9. The method for realizing the frequency modulation capacity of the power system considering the new energy increase as claimed in claim 1, wherein the dynamically adjusting the demand of the frequency modulation resource in the target time period of the power grid is as follows: when the average value of CPS1 in a month is lower than 140%, 10% of frequency modulation capacity is additionally added in each hour in the month.
10. A system for calculating a demand for a frequency modulated resource in a power system based on data analysis according to any one of the preceding claims, comprising: collection module, frequency modulation amount calculation module, new forms of energy calculation module, frequency modulation demand module and dynamic adjustment module, wherein: the acquisition module is used for acquiring and recording the load value, the upward frequency modulation amount and the downward frequency modulation amount of each time period of the power system, and the CPS1 score and the CPS2 score of each month; the frequency modulation amount calculation module is used for calculating the upward frequency modulation amount and the downward frequency modulation amount of each target time interval of the power system according to historical data; the new energy calculating module is used for calculating fan increment megawatts and photovoltaic increment megawatts; the frequency modulation demand module is used for calculating an upward frequency modulation demand and a downward frequency modulation demand of a target time period according to the results calculated by the frequency modulation amount calculation module and the new energy calculation module; the dynamic adjustment module is used for dynamically correcting the upward frequency modulation requirement and the downward frequency modulation requirement of the power grid according to the time running condition of the power grid, namely CPS1 and CPS2 indexes; the acquisition module is connected with the frequency modulation amount calculation module and is used for transmitting historical data such as load values, upward frequency modulation amounts, downward frequency modulation amounts and the like of each time period of the power system; the acquisition module is connected with the new energy calculation module and is used for transmitting the fan, the photovoltaic increment megawatt and related historical data, and meanwhile, the fan and the photovoltaic increment megawatt calculated by the new energy calculation module are transmitted to the acquisition module for recording; the acquisition module is connected with the dynamic adjustment module and transmits data of CPS1 scores and CPS2 scores of each month in actual operation; the frequency modulation amount calculation module and the new energy calculation module are connected with the frequency modulation demand module and provide data required by calculating the frequency modulation demand; and the dynamic adjusting module is connected with the frequency modulation demand module to correct the frequency modulation demand.
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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070213878A1 (en) * 2006-03-07 2007-09-13 Siemens Power Transmission & Distribution, Inc. Apparatus and method for predictive control of a power generation system
CN108832658A (en) * 2018-06-22 2018-11-16 三峡大学 A kind of wind power penetration limit calculation method considering frequency constraint and wind-powered electricity generation frequency modulation
CN109490676A (en) * 2018-12-27 2019-03-19 国电南瑞科技股份有限公司 New energy unit fm capacity on-line monitoring method and system
CN109936152A (en) * 2018-11-09 2019-06-25 西南交通大学 Power grid frequency modulation control method after high permeability wind-electricity integration, wind-driven generator
CN110661285A (en) * 2019-08-27 2020-01-07 华北电力大学 Configuration method for primary frequency modulation rotation reserve capacity after new energy grid connection
CN110994703A (en) * 2019-11-30 2020-04-10 江苏省电力有限公司电力科学研究院 Frequency modulation capacity demand allocation method considering multiple frequency modulation resources
CN111598388A (en) * 2020-04-09 2020-08-28 国家电网有限公司 Online evaluation method for frequency modulation resource demand of real-time market of power grid

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070213878A1 (en) * 2006-03-07 2007-09-13 Siemens Power Transmission & Distribution, Inc. Apparatus and method for predictive control of a power generation system
CN101438367A (en) * 2006-03-07 2009-05-20 西门子电力输送及配电有限公司 Apparatus and method for predictive control of a power generation system
CN108832658A (en) * 2018-06-22 2018-11-16 三峡大学 A kind of wind power penetration limit calculation method considering frequency constraint and wind-powered electricity generation frequency modulation
CN109936152A (en) * 2018-11-09 2019-06-25 西南交通大学 Power grid frequency modulation control method after high permeability wind-electricity integration, wind-driven generator
CN109490676A (en) * 2018-12-27 2019-03-19 国电南瑞科技股份有限公司 New energy unit fm capacity on-line monitoring method and system
CN110661285A (en) * 2019-08-27 2020-01-07 华北电力大学 Configuration method for primary frequency modulation rotation reserve capacity after new energy grid connection
CN110994703A (en) * 2019-11-30 2020-04-10 江苏省电力有限公司电力科学研究院 Frequency modulation capacity demand allocation method considering multiple frequency modulation resources
CN111598388A (en) * 2020-04-09 2020-08-28 国家电网有限公司 Online evaluation method for frequency modulation resource demand of real-time market of power grid

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
PRIYANKA KUSHWAHA等: "Assessment of Energy Storage Potential for Primary Frequency Response Adequacy in Future Grids", 《2018 8TH IEEE INDIA INTERNATIONAL CONFERENCE ON POWER ELECTRONICS (IICPE)》 *
李生虎等: "基于有功备用的风电机组一次调频能力及调频效果分析", 《电工电能新技术》 *
杨家琪等: "考虑新能源性能风险的调频辅助服务市场出清与调度策略", 《电力系统自动化》 *
胡佳怡，等: "考虑新能源出力特性的华东电网新能源消纳承载能力分析", 《水电能源科学》 *
赵万宗等: "互联电网CPS标准下计及一次调频的最优AGC控制模型", 《中国电机工程学报》 *

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