CN114492085A - Regional power and electric quantity balancing method related to load and power supply joint probability distribution - Google Patents

Regional power and electric quantity balancing method related to load and power supply joint probability distribution Download PDF

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CN114492085A
CN114492085A CN202210337663.7A CN202210337663A CN114492085A CN 114492085 A CN114492085 A CN 114492085A CN 202210337663 A CN202210337663 A CN 202210337663A CN 114492085 A CN114492085 A CN 114492085A
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邓笑冬
谭灵芝
胡剑宇
周野
李娟�
余虎
蒋云松
李静
范超
黄可
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China Energy Engineering Group Hunan Electric Power Design Institute Co Ltd
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Abstract

The invention discloses a regional power and electric quantity balancing method related to load and power supply joint probability distribution, which comprises the following steps of: acquiring historical load preset hour data, annual regional maximum load, annual output preset hour data of various power supply installation machines, annual scale of various power supply installation machines and annual power generation; dividing a power balance characteristic period and a load period; calculating a load probability coefficient, probability output coefficients of various power supplies and utilization hours; acquiring a load prediction result, an electric quantity prediction result and planning the installed scale; carrying out electric power balance calculation; and calculating the electric quantity balance of the planned year of the region. According to the method, the power balance calculation of each time period in the regional planning year is carried out according to the load prediction result and the planning and installation scale of various installations, the load probability coefficient of each power balance characteristic period and the probability output coefficient of various power supplies are considered, so that the calculation result of the power balance tends to be reasonable, and scientific reference is provided for power grid planning and power supply layout.

Description

Regional power and electric quantity balancing method related to load and power supply joint probability distribution
Technical Field
The invention relates to the technical field of power system planning, in particular to a regional power and electric quantity balancing method related to load and power supply joint probability distribution.
Background
The power and electric quantity balance is a basic work in power grid planning, is mainly used for calculating whether the power generation and supply capacity of a power system can meet load requirements, and the calculation result can be used as the basis for regional power grid planning.
At present, a simple table method is mainly adopted for carrying out power and electric quantity balance calculation on a representative month in a regional power grid power and electric quantity method, and a simple estimation method is adopted for load and power output of the month. Under the era background of 'carbon peak reaching and carbon neutralization', new energy is developed in a crossing manner, an electric power system is developed towards a novel electric power system taking new energy as a main body, and the uncertainty of electric power and electric quantity balance calculation of a new energy power supply is increased due to the uncertainty of the output of the new energy power supply, and greater pressure is brought to power grid planning and power grid neutralization.
In view of this, a power and electricity balance measuring and calculating method considering probability distribution of loads and power supplies is researched, uncertainty of planning boundary conditions caused by uncertainty of output of new energy after planning and development is solved, and the method has important practical value.
Disclosure of Invention
The invention provides a regional power and electric quantity balancing method related to load and power supply joint probability distribution, and aims to solve the technical problem that related design basis is lacked in the planning and designing stages of power grid planning and power supply layout in the prior art.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
the invention provides a regional power and electric quantity balancing method related to load and power supply joint probability distribution, which comprises the following steps of:
step S100: acquiring annual historical load preset hour data within a preset year in an area, acquiring annual maximum load of the area within the preset year in the area, and annual output preset hour data of various power supplies; and acquiring the installed scale of various power supplies and the annual generated energy;
step S200: dividing the data into a plurality of power balance characteristic periods according to the maximum load and historical load preset hour data, and dividing each power balance characteristic period into a plurality of load time periods;
step S300: according to a plurality of load time intervals of each power balance characteristic period, calculating a load probability coefficient of each time interval of each power balance characteristic period and a probability output coefficient of each power supply in each year within a preset year, and calculating the utilization hours of each power supply;
step S400: acquiring a load prediction result, an electric quantity prediction result and planning installation scales of various installations of a regional planning year;
step S500: according to the load prediction result, the planning and installation scale of each type of installation machine, the load probability coefficient of each power balance characteristic period and the probability output coefficient of the power supply without regulation capacity, considering the reserve capacity of the power system and the power regulation capacity of the power supply, and carrying out power balance calculation in each period of the regional planning year;
step S600: and calculating the annual electric quantity balance of the regional planning by using the electric quantity prediction result, the installed planning scales of various power supplies and the utilization hours of various power supplies.
Preferably, the power balance characteristic periods in step S200 are four power balance characteristic periods of summer, winter, rich water period and dry water period, respectively, and the load periods are three load periods of late peak load period, mid-day peak load period and low valley load period, respectively.
Preferably, the power balance characteristic periods and the late peak load period, the mid peak load period, and the valley load period of each power balance characteristic period in step S200 are respectively: the power balance characteristic period includes: 7-9 months in summer, 12 months-2 months in the next year in winter, 4-6 months in rich water period and 9-11 months in dry water period; the load period includes: the late peak load period T1 is 19:00-21:00 evening, the mid-day peak load period T2 is 12:00-14:00 noon, and the valley load period T3 is 02:00-05:00 morning.
Preferably, the step S300 specifically includes the following steps:
step S310: calculating load probability coefficients of all time intervals in four power balance characteristic periods;
step S320: calculating various power output probability coefficients of each time period in four power balance characteristic periods;
step S330: and calculating the utilization hours of various power supplies in each year within the preset year, wherein the utilization hours of various power supplies are the average value of the ratio of the annual generated energy to the total installed power in the preset year.
Preferably, the load probability coefficients of the time periods in step S310 refer to load probability coefficients in three time periods of late peak load period, noon peak load period and valley load period;
the load probability coefficient at the late peak load period is: arranging corresponding load data between 19:00-21:00 evening in one power balance characteristic period from small to large, wherein the maximum value of 95% probability occurrence is the probability load of the late peak load period in the power balance characteristic period; the ratio of the probability load of the late peak load period to the annual maximum load is the load probability coefficient of the late peak load period between 19:00-21:00 in the evening of the year in the power balance characteristic period; averaging the load probability coefficients of the late peak load periods within a preset year within the power balance characteristic period, namely the load probability coefficient of the late peak load period of the power balance characteristic period in the regional planning year;
load probability coefficient at peak load noon: arranging corresponding load data between 12:00-14:00 in the middle of the power balance characteristic period from small to large, wherein the maximum value of 95% probability occurrence is the probability load of the power balance characteristic period at the middle peak load period; the ratio of the probability load of the peak load hour at noon to the maximum load of the year is the load probability coefficient of the peak load hour at noon between 12:00 and 14:00 in the noon of the year in the power balance characteristic period; averaging the load probability coefficients of the peak load hours at noon within the preset year of the power balance characteristic period, namely the load probability coefficients of the peak load hours at noon of the power balance characteristic period in the regional planning year;
load probability coefficient at trough load period: arranging corresponding load data of a power balance characteristic period in the morning between 02:00 and 05:00 from small to large, wherein the minimum value of 95% probability occurrence is the probability load of the power balance characteristic period in the valley load period; the ratio of the probability load of the valley load period to the annual maximum load of the current year is the load probability coefficient of the valley load period between 02:00 and 05:00 in the morning of the current year in the power balance characteristic period; and averaging the load probability coefficients of the valley load periods within the preset year of the power balance characteristic period, namely the load probability coefficient of the valley load period of the power balance characteristic period in the regional planning year.
Preferably, the types of power output probability coefficients of each time period in step S320 refer to the types of power output probability coefficients in three time periods, namely, late peak load time period, mid-day peak load time period and low valley load time period; four of the power balance characteristic periods, namely summer, winter, rich water period and dry water period;
the output probability coefficient of various power supplies at the late peak load period is as follows: arranging various corresponding power output data between 19:00-21:00 at night in one power balance characteristic period from small to large, wherein the minimum value of 95% probability is the power output probability of various power sources in the late peak load period in the power balance characteristic period; the ratio of the probability output of various power supplies in the late peak load period of the power balance characteristic period to the installed capacity of various power supplies in the current year is the probability coefficient of the output of various power supplies in the late peak load period between 19:00 and 21:00 at night of the power balance characteristic period in the current year; averaging the probability coefficients of power output of various power supplies at the late peak load period within the preset year of the power balance characteristic period, namely the probability coefficients of power output of various power supplies at the late peak load period of the power balance characteristic period in the regional planning year;
the output probability coefficient of various power supplies at the load period of the peak at noon: arranging the corresponding various power output data between 12:00-14:00 in the middle of the power balance characteristic period from small to large, wherein the minimum value of 95% probability is the power output probability of various power sources in the middle of the power balance characteristic period at the peak load time; the ratio of the probability output of various power supplies in the power balance characteristic period at the noon and peak load period to the installed capacity of various power supplies in the current year is a probability coefficient of the output of various power supplies in the noon and peak load period between 12:00 and 14:00 in the noon and peak load period in the power balance characteristic period in the current year; averaging the power output probability coefficients of various power supplies at the peak noon load period within the preset year limit of the power balance characteristic period, namely, the power output probability coefficients of various power supplies at the peak noon load period of the power balance characteristic period in the regional planning year;
the output probability coefficient of various power supplies at the valley load period is as follows: arranging various corresponding power output data of the power balance characteristic period in the morning between 02:00 and 05:00 from small to large, wherein the maximum value of 95 percent of probability is the probability output of various power supplies in the valley load period of the power balance characteristic period; the ratio of the probability output of each power supply in the valley load period of the power balance characteristic period to the installed capacity of each power supply in the current year is the probability coefficient of the output of each power supply in the valley load period between 02:00 and 05:00 in the early morning of the power balance characteristic period in the current year; and averaging the output probability coefficients of various power supplies in the valley load period of three years in the power balance characteristic period, namely obtaining the output probability coefficients of various power supplies in the valley load period of the power balance characteristic period in the regional planning year.
Preferably, the planned installation scale of each type of installation in step S400 is: scale of water and electricity installation
Figure 218594DEST_PATH_IMAGE001
Coal electric installation scale
Figure 322685DEST_PATH_IMAGE002
Installed scale of wind power
Figure 40105DEST_PATH_IMAGE003
Photovoltaic installation scale
Figure 435314DEST_PATH_IMAGE004
Biomass loading scale
Figure 436637DEST_PATH_IMAGE005
Scale of pumping and storing machine
Figure 259100DEST_PATH_IMAGE006
Gas-electric installation scale
Figure 463816DEST_PATH_IMAGE007
Energy storage and installation scale
Figure 662716DEST_PATH_IMAGE008
。
Preferably, the step S500 specifically includes the following steps:
step S510: performing initial power balance calculation at the late peak load time period by using the annual load prediction result of regional planning, the installed scales of various power supplies and the probability output coefficient of the power supply without regulation performance and considering the reserve capacity of the power system; the power sources with adjustable performance include coal power, gas power, energy storage and pumping storage. And the others are unregulated performance power supplies.
Step S520: determining a coal-electricity starting mode in the power balance characteristic period by using a power balance result at the output moment in the late peak load period;
step S530: obtaining the minimum startup coefficient of each coal-electricity unit, and calculating the minimum output of the coal-electricity units by using a coal-electricity startup mode:
step S540: and performing preliminary power balance calculation at a valley load period and a peak load period by utilizing the regional planning annual load prediction result, the installed scale of the power supply without the adjustable performance, the probability output coefficient of the power supply without the adjustable performance and the minimum output of the coal-electric unit, and taking the output of pumped storage, gas electricity and energy storage into consideration on the basis of the preliminary power balance to obtain power balance calculation results at the valley load period and the peak load period.
Preferably, the formula for calculating the minimum output of the coal-electric power unit in step S530 is as follows;
Figure 331595DEST_PATH_IMAGE009
wherein, the first and the second end of the pipe are connected with each other,
Figure 511910DEST_PATH_IMAGE010
is the minimum output of the coal-electricity unit,
Figure 266239DEST_PATH_IMAGE011
is as follows
Figure 940934DEST_PATH_IMAGE012
The installed capacity of the coal-fired electric unit,
Figure 464319DEST_PATH_IMAGE013
is as follows
Figure 894163DEST_PATH_IMAGE012
And k is the minimum starting coefficient of the coal electric unit, and the number of the coal electric units is the number of the coal electric units.
Preferably, in step S540, pumped storage, gas electricity, and stored energy output are determined according to the preliminary power balance calculation result. If the initial power balance calculation result is greater than 0, the pumped storage and energy storage output value is-1, and the gas-electricity output value is 0; and if the initial power balance calculation result is less than 0, the values of pumped storage, energy storage and gas-electricity output are 1.
Preferably, the formula for calculating the area planning year electric quantity balance in step S600 is as follows:
Figure 328599DEST_PATH_IMAGE014
wherein the content of the first and second substances,
Figure 603723DEST_PATH_IMAGE015
planning the annual electric quantity balance result for the region,
Figure 184877DEST_PATH_IMAGE016
planning the annual energy prediction result for the region,
Figure 520043DEST_PATH_IMAGE017
for the scale of water electric installation,
Figure 435915DEST_PATH_IMAGE018
The scale of the coal electric charging machine,
Figure 514730DEST_PATH_IMAGE019
For the scale of wind power installation,
Figure 12707DEST_PATH_IMAGE020
For the photovoltaic installation scale,
Figure 722037DEST_PATH_IMAGE021
For the scale of biomass loading machine,
Figure 672676DEST_PATH_IMAGE022
Is suitable for the scale of the pumping and storing machine,
Figure 742132DEST_PATH_IMAGE023
Is suitable for the scale of the gas-electric installation machine,
Figure 94616DEST_PATH_IMAGE024
Installing the scale for energy storage;
Figure 37164DEST_PATH_IMAGE025
hours for water electric installation,
Figure 147202DEST_PATH_IMAGE026
The number of hours of utilization of the coal electric installation machine,
Figure 567819DEST_PATH_IMAGE027
The number of hours for wind power installation,
Figure 492919DEST_PATH_IMAGE028
Hours of use for photovoltaic installation,
Figure 606368DEST_PATH_IMAGE029
Hours for biomass loading machine to use,
Figure 469282DEST_PATH_IMAGE030
Hours for the pump storage machine to use,
Figure 693590DEST_PATH_IMAGE031
The number of hours of utilization for the gas-electric installation machine,
Figure 755087DEST_PATH_IMAGE032
The number of hours of utilization of the energy storage machine.
The invention has the beneficial effects that:
according to the method, the load probability coefficient of each power balance characteristic period and the probability output coefficients of various power supplies are innovatively considered according to the load prediction result and the planning and installation scale of various installations, power balance calculation of each period in the regional planning year is carried out, the calculation result of the power balance tends to be reasonable, and scientific reference is provided for power grid planning and power supply layout planning.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
A regional power and electric quantity balancing method about load and power supply joint probability distribution comprises the following steps:
step S100: in the embodiment, the preset year is preferably three years, the preset hour is preferably 8760 hours, and the maximum load of the region in each year in the region in the last three years and the installed output of various types of unregulated power supplies such as hydropower, wind power and photovoltaic are 8760 hours. And acquiring the installed scale of various power supplies in each year and the generated energy in the current year. The power sources with adjustable performance include coal power, gas power, energy storage and pumping storage, and the other power sources without adjustable performance.
Step S200: and dividing power balance characteristic periods, namely summer, winter, rich water period and dry water period, and dividing late peak load period, noon peak load period and low valley load period of each power balance characteristic period according to the 8760-hour data of the load and the hydropower output.
Step S300: according to the summer, winter, rich water period and dry water period, and the late peak load period, the noon peak load period and the low valley load period of each power balance characteristic period, the load probability coefficient of each period in each season of the last three years and the probability output coefficient of each type of power supply without regulation capacity are calculated, and in the embodiment, the utilization hours of each type of power supply are calculated.
Step S400: and acquiring the load of the regional planning year, the electric quantity prediction result and the planning installation scale of various installations.
Step S500: and according to the load prediction result, the scale of each type of installed planning, the load probability coefficient of each power balance characteristic period and the probability output coefficient of each type of power supply, considering the reserve capacity of the power system and the power regulation capacity of each type of regulatory power supply, and performing power balance calculation in each period of the regional planning year.
Step S600: and (4) carrying out regional planning year electric quantity balance calculation by using the electric quantity prediction result, the installed planning scale of various power supplies and the utilization hours of various power supplies.
In some other embodiments, the method for dividing the power balance characteristic periods and the late peak load period, the mid peak load period, and the low valley load period of each power balance characteristic period in step S200 is as follows:
the summer is 7-9 months, the winter is 12 months-2 months of the next year, the rich water period is 4-6 months, and the dry water period is 9-11 months. The late peak load time period T1 is 19:00-21:00 at night, the noon peak load time period T2 is 12:00-14:00 at noon, and the small load time period T3 is 02:00-05:00 in the morning.
In some other embodiments, the step S300 specifically includes the following steps:
step S310, calculating a load probability coefficient of each time interval, specifically taking summer as an example;
step S311, summer late peak load probability coefficient: load data of the time periods between 19:00 and 21:00 in the evening of 7-9 months in summer in the year are arranged from small to large, wherein the maximum value of 95 percent of probability occurrence is the peak probability load in the evening in summer in the year. The ratio of the summer late peak probability load to the annual maximum load in the same year is the summer late peak load probability coefficient in the same year. The same statistical calculation is carried out on the data of three years, the load probability coefficients of the summer late peak corresponding to the three years are respectively obtained, the average value of the probability coefficients of the summer late peak of the three years is obtained, the load probability coefficient of the regional planning annual summer major mode can be obtained, and the generous mode is the late peak time period.
Figure 226389DEST_PATH_IMAGE033
Wherein the content of the first and second substances,
Figure 638915DEST_PATH_IMAGE034
is as follows
Figure 604597DEST_PATH_IMAGE035
The peak time of the late summer of the year is the maximum load,
Figure 786180DEST_PATH_IMAGE036
is as follows
Figure 897224DEST_PATH_IMAGE035
The minimum load in the peak time period in the late summer of the year,
Figure 797047DEST_PATH_IMAGE037
is as follows
Figure 363158DEST_PATH_IMAGE035
The probability load of late summer peak in the year and the summer is the probability that R in the formula is equal to 95 percent.
Figure 868088DEST_PATH_IMAGE038
Wherein the content of the first and second substances,
Figure 228663DEST_PATH_IMAGE039
is as follows
Figure 802732DEST_PATH_IMAGE035
The maximum load of the year is that of the load,
Figure 172534DEST_PATH_IMAGE040
is as follows
Figure 735233DEST_PATH_IMAGE035
Peak load probability coefficient in late summer.
Figure 532288DEST_PATH_IMAGE041
Wherein the content of the first and second substances,
Figure 593654DEST_PATH_IMAGE042
and planning the load probability coefficient of the annual summertime mode for the region.
Step S312: summer midday peak load probability coefficient: the load data of 12:00-14:00 in the peak hours at noon in summer are arranged from small to large, wherein the maximum value of 95% of the load data is the peak probability load at noon in summer, and the ratio of the peak probability load at noon in summer to the maximum load in the whole year is the peak probability coefficient at noon in summer in the current year. And carrying out the same statistical calculation on the data of three years to obtain the load probability coefficients of the summer noon and evening peak corresponding to the three years respectively, and averaging the summer noon and evening peak probability coefficients of the three years to obtain the load probability coefficient of the regional planning year in the summer noon mode, wherein the noon mode is the noon peak load period.
Figure 767146DEST_PATH_IMAGE043
Wherein the content of the first and second substances,
Figure 449931DEST_PATH_IMAGE044
is as follows
Figure 417887DEST_PATH_IMAGE035
The maximum load during the peak hours of the noon in the summer of the year,
Figure 984127DEST_PATH_IMAGE045
is as follows
Figure 695731DEST_PATH_IMAGE035
The minimum load is applied during the peak hours in the afternoon summer,
Figure 560919DEST_PATH_IMAGE046
is as follows
Figure 637460DEST_PATH_IMAGE035
Annual summer midday peak probability load.
Figure 220888DEST_PATH_IMAGE047
Wherein the content of the first and second substances,
Figure 391975DEST_PATH_IMAGE048
is as follows
Figure 580511DEST_PATH_IMAGE035
The maximum load of the year is that of the load,
Figure 890269DEST_PATH_IMAGE049
is as follows
Figure 960994DEST_PATH_IMAGE035
The load probability coefficient of the afternoon peak in the summer.
Figure 935772DEST_PATH_IMAGE050
Wherein the content of the first and second substances,
Figure 775552DEST_PATH_IMAGE051
and planning the load probability coefficient of the mode of summer and noon year for the region.
Step S313: summer valley load probability coefficient: the load data of 2:00-5:00 in the morning in the summer valley load period are arranged in the order from small to large, wherein the minimum value of 95% is the summer valley load probability load, and the ratio of the summer valley load probability load to the annual maximum load is the summer small mode load probability coefficient. And carrying out the same statistical calculation on the data of three years to obtain load probability coefficients of a small summer mode corresponding to the three years respectively, and averaging the load probability coefficients of the small summer mode of the three years to obtain the load probability coefficients of the small summer mode of the year and the small summer mode of the area planning, wherein the small mode is a valley load time period.
Figure 193895DEST_PATH_IMAGE052
Wherein the content of the first and second substances,
Figure 486336DEST_PATH_IMAGE053
is as follows
Figure 343433DEST_PATH_IMAGE035
The maximum load in the valley period of the summer of the year,
Figure 490250DEST_PATH_IMAGE054
is as follows
Figure 141811DEST_PATH_IMAGE035
The minimum load in the valley period of the summer of the year,
Figure 859231DEST_PATH_IMAGE055
is as follows
Figure 254441DEST_PATH_IMAGE035
Annual summer low load probability load.
Figure 803234DEST_PATH_IMAGE056
Wherein the content of the first and second substances,
Figure 343805DEST_PATH_IMAGE057
is as follows
Figure 610838DEST_PATH_IMAGE035
The maximum load of the year is that of the load,
Figure 481843DEST_PATH_IMAGE058
is as follows
Figure 885142DEST_PATH_IMAGE035
Load probability coefficient of small mode in summer.
Figure 331036DEST_PATH_IMAGE059
Wherein the content of the first and second substances,
Figure 85365DEST_PATH_IMAGE060
and planning the load probability coefficient of the annual-summer small mode for the region.
Therefore, the load probability coefficients of three modes of annual summer, summer noon and summer minor in regional planning can be obtained. By applying the load data in winter, rich water period and dry water period, repeating the steps S311, S312 and S313, the load probability coefficients of big winter, midday winter, small winter, big winter, midday, small winter, big midday, small withered, midday and small withered in the area planning can be obtained respectively.
Step S320: calculating output probability coefficients of various types of non-adjustable performance power supplies in all time periods in four power balance characteristic periods, specifically taking summer wind power output as an example:
the power supply without regulation performance comprises wind power, photovoltaic, biomass and hydropower.
Wind power summer large formula output probability coefficient: the wind power data in the time period between 19:00 and 21:00 at night in 7-9 months in summer in one year are arranged in a sequence from small to large, wherein the minimum value of 95% probability is the wind power summer square type probability output in the current year, and the ratio of the summer square type probability output to the wind power installed capacity in the current year is the wind power probability output coefficient in the current year. And carrying out the same statistical calculation on the data of three years to obtain wind power summer large form probability output coefficients respectively corresponding to the three years, and averaging the wind power summer large form output coefficients of the three years to obtain the output coefficient of the wind power summer large form of the regional planning year.
Figure 822377DEST_PATH_IMAGE061
Wherein the content of the first and second substances,
Figure 549025DEST_PATH_IMAGE062
is as follows
Figure 978869DEST_PATH_IMAGE035
The maximum output of wind power in the peak time in the late summer in the year,
Figure 876287DEST_PATH_IMAGE063
is as follows
Figure 416989DEST_PATH_IMAGE035
The minimum wind power output is realized at the late peak in summer,
Figure 998143DEST_PATH_IMAGE064
is as follows
Figure 333310DEST_PATH_IMAGE035
And (4) outputting power at the probability of late peak in summer of annual wind power.
Figure 62231DEST_PATH_IMAGE065
Wherein the content of the first and second substances,
Figure 327996DEST_PATH_IMAGE066
is as follows
Figure 825974DEST_PATH_IMAGE035
The installed capacity of the annual wind power is determined,
Figure 269725DEST_PATH_IMAGE067
is as follows
Figure 485942DEST_PATH_IMAGE035
And wind power probability output coefficient of late peak in summer.
Figure 826837DEST_PATH_IMAGE068
Wherein the content of the first and second substances,
Figure 179321DEST_PATH_IMAGE069
the wind power probability output coefficient is summer high.
Wind power output probability coefficient of summer midday peak: the wind power output data of 12:00-14:00 in the summer mid-day peak period are arranged from small to large, wherein the minimum value of 95% is the wind power mid-day peak probability output in summer, the ratio of the summer mid-day peak probability output to the current year wind power installed capacity is the current year summer mid-day peak wind power probability output coefficient. And carrying out the same statistical calculation on the data of the three years to obtain wind power summer midday peak probability output coefficients corresponding to the three years respectively, and averaging the wind power summer midday peak output coefficients of the three years to obtain the output coefficient of the regional planning year wind power summer midday mode.
Figure 793973DEST_PATH_IMAGE070
Wherein the content of the first and second substances,
Figure 231908DEST_PATH_IMAGE071
is as follows
Figure 652525DEST_PATH_IMAGE035
The maximum output of wind power in the peak hours of the afternoon in summer of the year,
Figure 312045DEST_PATH_IMAGE072
is as follows
Figure 159915DEST_PATH_IMAGE035
The minimum output of wind power in the peak hours in the noon in summer of the year,
Figure 22829DEST_PATH_IMAGE073
is as follows
Figure 247137DEST_PATH_IMAGE035
And (4) outputting power at noon peak probability in summer by annual wind power.
Figure 574213DEST_PATH_IMAGE074
Wherein the content of the first and second substances,
Figure 45515DEST_PATH_IMAGE075
is as follows
Figure 458041DEST_PATH_IMAGE035
The installed capacity of the annual wind power is determined,
Figure 158144DEST_PATH_IMAGE076
is as follows
Figure 339727DEST_PATH_IMAGE035
And wind power probability output coefficient of the peak at noon in summer.
Figure 794979DEST_PATH_IMAGE077
Wherein the content of the first and second substances,
Figure 881753DEST_PATH_IMAGE078
and planning the output coefficient of the annual wind power summer and noon mode for the region.
The probability coefficient of wind power output of summer low valley load is as follows: the wind power output data of 2:00-5:00 in the morning in the summer valley load period are arranged from small to large, wherein the maximum value of 95% is the summer valley load wind power probability output, and the ratio of the summer valley load wind power probability output to the current-year wind power installed capacity is the current-year summer valley load wind power probability output coefficient. And carrying out the same statistical calculation on the data of three years to obtain the wind power summer valley load probability output coefficients corresponding to the three years respectively, and averaging the wind power summer valley load output coefficients of the three years to obtain the output coefficient of the wind power summer valley mode of the regional planning year.
Figure 447863DEST_PATH_IMAGE079
Wherein the content of the first and second substances,
Figure 421635DEST_PATH_IMAGE080
is as follows
Figure 47789DEST_PATH_IMAGE035
The maximum output of wind power in the valley period of summer in the year,
Figure 434908DEST_PATH_IMAGE081
is as follows
Figure 726081DEST_PATH_IMAGE035
The minimum output of wind power in the low load period of summer and the year,
Figure 882255DEST_PATH_IMAGE082
is as follows
Figure 679310DEST_PATH_IMAGE035
And outputting power according to the annual wind power summer low valley load probability.
Figure 225829DEST_PATH_IMAGE083
Wherein the content of the first and second substances,
Figure 399322DEST_PATH_IMAGE084
is as follows
Figure 596954DEST_PATH_IMAGE035
The installed capacity of the annual wind power is determined,
Figure 564910DEST_PATH_IMAGE085
is as follows
Figure 661042DEST_PATH_IMAGE035
And the annual summer low-valley load wind power probability output coefficient.
Figure 44749DEST_PATH_IMAGE086
Wherein the content of the first and second substances,
Figure 175517DEST_PATH_IMAGE087
and (4) planning the output coefficient of the annual wind power summer mode for the region.
Therefore, the wind power output probability coefficients of the three modes of the regional planning of big year and summer, noon in summer and small summer can be obtained, and the wind power output probability coefficients of big winter, noon in winter, small winter, big in abundance, small in abundance, big in insufficiency, small in insufficiency and small in insufficiency can be obtained by the same method.
The 8760-hour data of the photovoltaic, biomass, hydroelectric and other power supplies without regulating capacity are counted and calculated in the same mode, and various power output probability coefficients of big summer, small summer, big winter, small winter, big summer, big winter, big summer, big abundance, small abundance, big withered afternoon and small withered can be obtained.
Step S330: and calculating the utilization hours of various power supplies, wherein the utilization hours of various power supplies in the region planning year are the three-year average value of the ratio of the annual generated energy to the total installed power in nearly three years.
Taking wind power as an example:
Figure 501325DEST_PATH_IMAGE088
wherein
Figure 84753DEST_PATH_IMAGE089
Is a first
Figure 272151DEST_PATH_IMAGE035
The number of hours of wind power utilization per year,
Figure 257425DEST_PATH_IMAGE090
is as follows
Figure 567184DEST_PATH_IMAGE035
The annual wind power generation amount is calculated,
Figure 824858DEST_PATH_IMAGE091
is as follows
Figure 878265DEST_PATH_IMAGE035
The installed capacity of the annual wind power is determined,
Figure 655728DEST_PATH_IMAGE092
planning annual wind power utilization hours for the region.
The utilization hours of various power supplies in the regional planning year can be obtained by carrying out the same statistical calculation on the power supplies such as coal power, hydropower, photovoltaic, biomass and the like.
In some other embodiments, the maximum load of the regional planning year in step S400 is
Figure 136388DEST_PATH_IMAGE093
The result of the electric quantity prediction is
Figure 609921DEST_PATH_IMAGE094
And the planned installation scale of each type of installation is respectively the scale of the hydroelectric installation
Figure 467018DEST_PATH_IMAGE095
Coal electric installation scale
Figure 161305DEST_PATH_IMAGE096
Installed scale of wind power
Figure 750549DEST_PATH_IMAGE097
Photovoltaic installation scale
Figure 795865DEST_PATH_IMAGE098
Biomass loading scale
Figure 378025DEST_PATH_IMAGE099
Scale of pumping and storing machine
Figure 926818DEST_PATH_IMAGE100
Gas-electric installation scale
Figure 14860DEST_PATH_IMAGE101
Energy storage and installation scale
Figure 219576DEST_PATH_IMAGE102
。
In some other embodiments, the step S500 includes the following steps, for example, in summer:
step S510: and performing large-format preliminary power balance calculation by using the annual load prediction result of the regional planning, the installed scale of the power supply without the performance regulation and the probability output coefficient of the power supply without the performance regulation.
(1) Summer is as follows:
spare capacity: the spare capacity includes accident spare capacity and load spare capacity, which can ensure the power supply requirement and needs to be increased under the conditions of accidents, frequency modulation and the like.
Figure 152897DEST_PATH_IMAGE103
Figure 8727DEST_PATH_IMAGE104
Planning annual and summer reserve capacity for the region;
Figure 267670DEST_PATH_IMAGE105
planning the maximum load of the year for the region;
Figure 694103DEST_PATH_IMAGE106
the spare capacity factor, which is generally 0.14,
Figure 696694DEST_PATH_IMAGE107
is a summer square type load probability coefficient.
Figure 220079DEST_PATH_IMAGE108
Figure 571295DEST_PATH_IMAGE109
The calculation result is the initial power balance calculation result of summer university;
Figure 812921DEST_PATH_IMAGE110
the scale of the water installation is changed;
Figure 353623DEST_PATH_IMAGE111
installing scale for wind power;
Figure 669198DEST_PATH_IMAGE112
the photovoltaic installation scale is achieved;
Figure 269944DEST_PATH_IMAGE113
loading the biomass into a machine;
Figure 920237DEST_PATH_IMAGE114
the water-electricity probability output coefficient is summer high;
Figure 264631DEST_PATH_IMAGE115
wind power probability output coefficient in summer;
Figure 762608DEST_PATH_IMAGE116
the summer photovoltaic probability output coefficient is;
Figure 206359DEST_PATH_IMAGE117
is the probability output coefficient of summer large biomass.
Figure 422576DEST_PATH_IMAGE118
The maximum load for the year is planned for the area,
Figure 492033DEST_PATH_IMAGE119
is a summer-large-form load probability coefficient,
Figure 844516DEST_PATH_IMAGE120
planning the annual and summer reserve capacity for the area.
And (3) in the calculation result of the preliminary power balance, considering the output of various adjusting power supplies, specifically, considering the output of pumped storage, gas electricity and energy storage, and further calculating the power balance.
Figure 459169DEST_PATH_IMAGE121
Figure 897103DEST_PATH_IMAGE122
Is a pumping and accumulating machine,
Figure 583299DEST_PATH_IMAGE123
Is suitable for the scale of the gas-electric installation machine,
Figure 977241DEST_PATH_IMAGE124
The scale of energy storage and installation is changed;
Figure 90690DEST_PATH_IMAGE125
is the output coefficient of the large pumping storage in summer,
Figure 953604DEST_PATH_IMAGE126
is the power output coefficient of the atmosphere in summer,
Figure 177912DEST_PATH_IMAGE127
the energy storage output coefficient is summer high. If it is
Figure 504988DEST_PATH_IMAGE128
Greater than 0, then
Figure 976289DEST_PATH_IMAGE125
、
Figure 123237DEST_PATH_IMAGE126
、
Figure 151236DEST_PATH_IMAGE127
Take the value of-1, if
Figure 270502DEST_PATH_IMAGE128
Less than 0, then
Figure 725754DEST_PATH_IMAGE125
、
Figure 818387DEST_PATH_IMAGE126
、
Figure 384497DEST_PATH_IMAGE127
The value is 1.
Figure 358269DEST_PATH_IMAGE129
The power balance result under the condition of not calculating coal power output in summer square mode
Step S520: and determining the coal power starting mode in the season by using the power balance result at the moment of large load output. In particular to
Figure 984423DEST_PATH_IMAGE130
Figure 105963DEST_PATH_IMAGE131
Figure 662715DEST_PATH_IMAGE129
The result is a power balance result in the summer square type without calculating the coal power output, and the result is generally a negative value, namely, the power in the summer square type area has a gap in the case that the coal power is not started.
Figure 818890DEST_PATH_IMAGE132
For the actual starting scale, the coal-electric machine sets are arranged from large to small according to the loading capacity,
Figure 553627DEST_PATH_IMAGE133
is arranged at the second for installed capacity
Figure 162463DEST_PATH_IMAGE134
The installed capacity of the coal-electric machine of the station,
Figure 70376DEST_PATH_IMAGE135
to satisfy
Figure 268008DEST_PATH_IMAGE136
The minimum value of the condition.
Figure 235964DEST_PATH_IMAGE136
Figure 332096DEST_PATH_IMAGE137
The coal-electricity starting mode which can obtain the big summer needs is
Figure 981384DEST_PATH_IMAGE138
。
Step S530: and acquiring the minimum starting coefficient of each coal-electricity unit, and calculating the minimum output of the coal-electricity units by using a coal-electricity starting mode. The method specifically comprises the following steps:
and according to the coal-electricity starting mode, acquiring the minimum starting coefficient of each coal-electricity unit, and solving the minimum output of the coal-electricity units.
Figure 112151DEST_PATH_IMAGE139
Figure 437959DEST_PATH_IMAGE140
The minimum output of the coal-electricity unit,
Figure 755807DEST_PATH_IMAGE141
is as follows
Figure 208786DEST_PATH_IMAGE142
The installed capacity of the coal-fired electric unit,
Figure 194059DEST_PATH_IMAGE143
is as follows
Figure 503818DEST_PATH_IMAGE142
And the minimum starting coefficient of the coal electric unit.
Step S540: and carrying out small mode and noon mode electric power balance calculation by utilizing the regional planning annual load prediction result, the installed scale of the power supply without the adjustable performance, the probability output coefficient of the power supply without the adjustable performance and the minimum output of the coal-electric unit.
(2) And (5) small in summer:
Figure 495913DEST_PATH_IMAGE144
Figure 549320DEST_PATH_IMAGE145
the calculation result is the initial power balance calculation result in summer;
Figure 326783DEST_PATH_IMAGE146
the scale of the water installation is changed;
Figure 807443DEST_PATH_IMAGE147
installing scale for wind power;
Figure 365463DEST_PATH_IMAGE148
the photovoltaic installation scale is adopted;
Figure 143932DEST_PATH_IMAGE149
gauge for installing biomassMolding;
Figure 103798DEST_PATH_IMAGE150
the power output coefficient is the small water-electricity probability in summer;
Figure 693042DEST_PATH_IMAGE151
the probability output coefficient of the small wind power in summer is shown;
Figure 472780DEST_PATH_IMAGE152
the summer small photovoltaic probability output coefficient;
Figure 867989DEST_PATH_IMAGE153
the probability output coefficient of the small biomass in summer is shown;
Figure 869312DEST_PATH_IMAGE154
the minimum output of the coal-electricity unit in summer;
Figure 691774DEST_PATH_IMAGE155
planning the maximum load of the year for the region;
Figure 896491DEST_PATH_IMAGE156
the load probability coefficient is a summer minor mode load probability coefficient.
On the basis of the preliminary power balance, the output of pumped storage, gas electricity and energy storage is considered, and power balance calculation is further carried out, specifically, the output of pumped storage, gas electricity and energy storage is considered.
Figure 95391DEST_PATH_IMAGE157
Figure 764270DEST_PATH_IMAGE158
The scale of the pumping and storing machine,
Figure 944584DEST_PATH_IMAGE159
The scale of the gas-electric installation machine,
Figure 698913DEST_PATH_IMAGE160
And (5) storing energy and installing scale.
Figure 639188DEST_PATH_IMAGE161
Is a small pumping storage output coefficient in summer,
Figure 162573DEST_PATH_IMAGE162
is the small power output coefficient of summer,
Figure 326838DEST_PATH_IMAGE163
the energy storage output coefficient is summer high. If it is
Figure 772992DEST_PATH_IMAGE164
Greater than 0, then
Figure 313695DEST_PATH_IMAGE165
、
Figure 629270DEST_PATH_IMAGE166
The value is-1, and the value is,
Figure 230015DEST_PATH_IMAGE167
the value is 0; if it is
Figure 693358DEST_PATH_IMAGE164
Less than 0, then
Figure 224702DEST_PATH_IMAGE168
、
Figure 457100DEST_PATH_IMAGE169
、
Figure 166430DEST_PATH_IMAGE170
The value is 1.
Figure 366336DEST_PATH_IMAGE171
Namely the power balance result in the small summer mode.
(3) Summer noon:
Figure 560426DEST_PATH_IMAGE173
Figure 912910DEST_PATH_IMAGE174
calculating the result of the preliminary power balance in summer and noon;
Figure 793141DEST_PATH_IMAGE175
the scale of the water installation is changed;
Figure 231076DEST_PATH_IMAGE176
installing scale for wind power;
Figure 104223DEST_PATH_IMAGE177
the photovoltaic installation scale is adopted;
Figure 311213DEST_PATH_IMAGE178
loading the biomass into a machine;
Figure 424663DEST_PATH_IMAGE179
the water and electricity probability output coefficient in summer and noon is obtained;
Figure 287577DEST_PATH_IMAGE180
the wind power probability output coefficient is the wind power probability output coefficient in summer and noon;
Figure 511885DEST_PATH_IMAGE181
the photovoltaic probability output coefficient in summer and noon is obtained;
Figure 25912DEST_PATH_IMAGE182
the biomass probability output coefficient in summer and noon is obtained;
Figure 44683DEST_PATH_IMAGE183
the minimum output of the coal-electricity unit in summer;
Figure 457210DEST_PATH_IMAGE184
planning the maximum load of the year for the region;
Figure 422892DEST_PATH_IMAGE185
is a load probability coefficient in a summer and noon mode.
On the basis of the preliminary power balance, the output of various adjusting power supplies is considered, and further power balance calculation is carried out, specifically, the output of pumped storage, gas electricity and energy storage is considered.
Figure 604474DEST_PATH_IMAGE186
Figure 252537DEST_PATH_IMAGE187
Is suitable for the scale of the pumping and storing machine,
Figure 886780DEST_PATH_IMAGE188
Is suitable for the scale of the gas-electric installation machine,
Figure 452891DEST_PATH_IMAGE189
The scale of the energy storage machine is increased.
Figure 692242DEST_PATH_IMAGE190
Is a small pumping storage output coefficient in summer,
Figure 318396DEST_PATH_IMAGE191
is the small power output coefficient of summer,
Figure 626886DEST_PATH_IMAGE192
the energy storage output coefficient is summer high. If it is
Figure 996688DEST_PATH_IMAGE193
Greater than 0, then
Figure 152862DEST_PATH_IMAGE194
、
Figure 887600DEST_PATH_IMAGE195
The value is-1, and the value is,
Figure 496436DEST_PATH_IMAGE196
the value is 0; if it is
Figure 591300DEST_PATH_IMAGE193
Less than 0, then
Figure 601981DEST_PATH_IMAGE197
、
Figure 569937DEST_PATH_IMAGE191
、
Figure 603752DEST_PATH_IMAGE192
The value is 1.
Figure 315356DEST_PATH_IMAGE198
Namely the power balance result in the summer and the noon mode.
In the small mode and the noon mode
Figure 367495DEST_PATH_IMAGE199
、
Figure 506352DEST_PATH_IMAGE198
And when the output power is less than 0, the coal-electricity output power of the small mode and the power of the noon mode can be improved, so that the small mode and the noon mode are balanced in power. In the small mode and the noon mode
Figure 89780DEST_PATH_IMAGE199
、
Figure 542758DEST_PATH_IMAGE198
Greater than 0 indicates that even if the coal electricity output in the compression area reaches the minimum scale, the small mode and the midday mode still have surplus electricity to be sent out.
In some other embodiments, the calculation manner of step S600 is specifically:
Figure 262453DEST_PATH_IMAGE200
Figure 759162DEST_PATH_IMAGE201
planning the annual electric quantity balance result for the region,
Figure 829886DEST_PATH_IMAGE202
planning the annual energy prediction result for the region,
Figure 883293DEST_PATH_IMAGE203
for the scale of water electric installation,
Figure 660756DEST_PATH_IMAGE204
The scale of the coal electric charging machine,
Figure 141416DEST_PATH_IMAGE205
For the scale of wind power installation,
Figure 886387DEST_PATH_IMAGE206
For the photovoltaic installation scale,
Figure 477905DEST_PATH_IMAGE207
For the scale of biomass loading machine,
Figure 172192DEST_PATH_IMAGE208
Is suitable for the scale of the pumping and storing machine,
Figure 27015DEST_PATH_IMAGE209
Is suitable for the scale of the gas-electric installation machine,
Figure 806753DEST_PATH_IMAGE210
Installing the scale for energy storage;
Figure 388912DEST_PATH_IMAGE211
hours for water and electricity to be installed,
Figure 203285DEST_PATH_IMAGE212
The number of hours of utilization of the coal electric installation machine,
Figure 25747DEST_PATH_IMAGE213
The number of hours for wind power installation,
Figure 230464DEST_PATH_IMAGE214
Hours of use for photovoltaic installation,
Figure 429364DEST_PATH_IMAGE215
Hours for biomass loading machine to use,
Figure 285193DEST_PATH_IMAGE216
Hours for the pumped storage machine to use,
Figure 278557DEST_PATH_IMAGE217
The number of hours of utilization for the gas-electric installation machine,
Figure 32886DEST_PATH_IMAGE218
The number of hours of utilization of the energy storage machine.
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the present invention, and all such changes or substitutions are included in the scope of the present invention. Moreover, the technical solutions in the embodiments of the present invention may be combined with each other, but it is necessary to be able to be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be considered to be absent, and is not within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.

Claims (10)

1. The regional power and electric quantity balancing method related to load and power supply joint probability distribution is characterized by comprising the following steps of:
step S100: acquiring annual historical load preset hour data within a preset year in the region, acquiring annual maximum load of the region within the preset year in the region, and annual installed output preset hour data of various power supplies; acquiring the scale of each power supply installation and the annual generated energy;
step S200: dividing the data into a plurality of power balance characteristic periods according to the maximum load and historical load preset hour data, and dividing each power balance characteristic period into a plurality of load time periods;
step S300: according to a plurality of load time intervals of each power balance characteristic period, calculating a load probability coefficient of each time interval of each power balance characteristic period and a probability output coefficient of each power supply in each year within a preset year, and calculating the utilization hours of each power supply;
step S400: acquiring a load prediction result, an electric quantity prediction result and planning installation scales of various installations of a regional planning year;
step S500: according to the load prediction result, the planning and installation scale of each type of installation machine, the load probability coefficient of each power balance characteristic period and the probability output coefficient of the power supply without regulation capacity, considering the reserve capacity of the power system and the power regulation capacity of the power supply, and carrying out power balance calculation in each period of the regional planning year;
step S600: and calculating the annual electric quantity balance of the regional planning by using the electric quantity prediction result, the installed planning scales of various power supplies and the utilization hours of various power supplies.
2. The method of claim 1, wherein the power balance characteristic periods in step S200 are four power balance characteristic periods, namely summer, winter, rich water period and dry water period, and the load periods are three load periods, namely late peak load period, mid-day peak load period and low valley load period.
3. The method of claim 2, wherein the power balance characteristic periods and the peak load late period, peak load noon period and valley load period of each power balance characteristic period in the step S200 are respectively as follows: the power balance characteristic period includes: 7-9 months in summer, 12 months-2 months in the next year in winter, 4-6 months in rich water period and 9-11 months in dry water period; the load period includes: the late peak load period T1 is 19:00-21:00 evening, the mid-day peak load period T2 is 12:00-14:00 noon, and the valley load period T3 is 02:00-05:00 morning.
4. The method of claim 2, wherein the step S300 specifically includes the following steps:
step S310: calculating load probability coefficients of all time intervals in four power balance characteristic periods;
step S320: calculating various power output probability coefficients of each time period in four power balance characteristic periods;
step S330: and calculating the utilization hours of various power supplies in each year within the preset year, wherein the utilization hours of various power supplies are the average value of the ratio of the annual generated energy to the total installed power in the preset year.
5. The method of claim 4, wherein the load probability coefficients of each time segment in step S310 refer to load probability coefficients in three time segments, namely late peak load time, mid peak load time and low valley load time;
the load probability coefficient at the late peak load period is: arranging corresponding load data between 19:00-21:00 evening in one power balance characteristic period from small to large, wherein the maximum value of 95% probability occurrence is the probability load of the late peak load period in the power balance characteristic period; the ratio of the probability load of the late peak load period to the annual maximum load is the load probability coefficient of the late peak load period between 19:00-21:00 in the evening of the year in the power balance characteristic period; averaging the load probability coefficients of the late peak load period within a preset year in the power balance characteristic period;
load probability coefficient at peak load noon: arranging corresponding load data between 12:00-14:00 in the middle of the power balance characteristic period from small to large, wherein the maximum value of 95% probability occurrence is the probability load of the power balance characteristic period at the middle peak load period; the ratio of the probability load of the peak load hour at noon to the maximum load of the year is the load probability coefficient of the peak load hour at noon between 12:00 and 14:00 in the noon of the year in the power balance characteristic period; averaging the load probability coefficients of the load at the noon peak load period within the preset year of the power balance characteristic period;
load probability coefficient at trough load period: arranging corresponding load data of a power balance characteristic period in the morning between 02:00 and 05:00 from small to large, wherein the minimum value of 95% probability occurrence is the probability load of the power balance characteristic period in the valley load period; the ratio of the probability load of the valley load period to the annual maximum load of the current year is the load probability coefficient of the valley load period between 02:00 and 05:00 in the morning of the current year in the power balance characteristic period; and averaging the load probability coefficients of the low-valley load periods within the preset year of the power balance characteristic period.
6. The method of claim 4, wherein the types of power output probability coefficients of each time period in the step S320 refer to the types of power output probability coefficients of three time periods, namely, late peak load period, mid peak load period and low valley load period; four of the power balance characteristic periods, namely summer, winter, rich water period and dry water period;
the output probability coefficient of various power supplies at the late peak load period is as follows: arranging various corresponding power output data between 19:00-21:00 at night in one power balance characteristic period from small to large, wherein the minimum value of 95% probability is the power output probability of various power sources in the late peak load period in the power balance characteristic period; the ratio of the probability output of various power supplies in the late peak load period of the power balance characteristic period to the installed capacity of various power supplies in the current year is the probability coefficient of the output of various power supplies in the late peak load period between 19:00 and 21:00 at night of the power balance characteristic period in the current year; averaging the power output probability coefficients of various power supplies at the late peak load period within the preset year of the power balance characteristic period;
the output probability coefficient of various power supplies at the load period of the peak at noon: arranging the corresponding various power output data between 12:00-14:00 in the middle of the power balance characteristic period from small to large, wherein the minimum value of 95% probability is the power output probability of various power sources in the middle of the power balance characteristic period at the peak load time; the ratio of the probability output of various power supplies in the power balance characteristic period at the noon and peak load period to the installed capacity of various power supplies in the current year is a probability coefficient of the output of various power supplies in the noon and peak load period between 12:00 and 14:00 in the noon and peak load period in the power balance characteristic period in the current year; averaging the power output probability coefficients of various power supplies at the peak load hours at noon within the preset year of the power balance characteristic period;
the output probability coefficient of various power supplies at the valley load period is as follows: arranging various corresponding power output data of the power balance characteristic period in the morning between 02:00 and 05:00 from small to large, wherein the maximum value of 95 percent of probability is the probability output of various power supplies in the valley load period of the power balance characteristic period; the ratio of the probability output of each power supply in the valley load period of the power balance characteristic period to the installed capacity of each power supply in the current year is the probability coefficient of the output of each power supply in the valley load period between 02:00 and 05:00 in the early morning of the power balance characteristic period in the current year; and averaging the output probability coefficients of various power supplies in the valley load period of three years in the power balance characteristic period.
7. The method according to claim 1, wherein the planning installed scales of the various installed machines in the step S400 are respectively as follows: scale of water and electricity installation
Figure 211823DEST_PATH_IMAGE001
Coal electric installation scale
Figure 922159DEST_PATH_IMAGE002
Installed scale of wind power
Figure 352003DEST_PATH_IMAGE003
Photovoltaic installation scale
Figure 531312DEST_PATH_IMAGE004
Biomass loading scale
Figure 806436DEST_PATH_IMAGE005
Scale of pumping and storing machine
Figure 636857DEST_PATH_IMAGE006
Gas-electric installation scale
Figure 972024DEST_PATH_IMAGE007
Energy storage and installation scale
Figure 638628DEST_PATH_IMAGE008
。
8. The method of claim 1, wherein the step S500 specifically includes the following steps:
step S510: performing initial power balance calculation at the late peak load time period by using the annual load prediction result of regional planning, the installed scales of various power supplies and the probability output coefficient of the power supply without regulation performance and considering the reserve capacity of the power system;
step S520: determining a coal-electricity starting mode in the power balance characteristic period by using a power balance result at the output moment in the late peak load period;
step S530: obtaining the minimum startup coefficient of each coal-electricity unit, and calculating the minimum output of the coal-electricity units by using a coal-electricity startup mode:
step S540: and performing preliminary power balance calculation at a valley load period and a peak load period by utilizing the regional planning annual load prediction result, the installed scale of the power supply without the adjustable performance, the probability output coefficient of the power supply without the adjustable performance and the minimum output of the coal-electric unit, and taking the output of pumped storage, gas electricity and energy storage into consideration on the basis of the preliminary power balance to obtain power balance calculation results at the valley load period and the peak load period.
9. The method of claim 8, wherein the minimum output of the coal-electric power unit is calculated in step S530 according to the formula;
Figure 717443DEST_PATH_IMAGE009
wherein the content of the first and second substances,
Figure 215420DEST_PATH_IMAGE010
is the minimum output of the coal-electricity unit,
Figure 174018DEST_PATH_IMAGE011
is as follows
Figure 124656DEST_PATH_IMAGE012
The installed capacity of the coal-fired electric unit,
Figure 944845DEST_PATH_IMAGE013
is as follows
Figure 297329DEST_PATH_IMAGE012
And k is the minimum starting coefficient of the coal electric unit, and the number of the coal electric units is the number of the coal electric units.
10. The regional power electricity balance method of any claim 1 to 9, wherein the formula for calculating regional planned year electricity balance in step S600 is as follows:
Figure 426828DEST_PATH_IMAGE014
wherein the content of the first and second substances,
Figure 864762DEST_PATH_IMAGE015
planning the annual electric quantity balance result for the region,
Figure 223062DEST_PATH_IMAGE016
planning the annual energy prediction result for the region,
Figure 695632DEST_PATH_IMAGE017
for the scale of water electric installation,
Figure 996032DEST_PATH_IMAGE018
The scale of the coal electric charging machine,
Figure 921263DEST_PATH_IMAGE019
For the scale of wind power installation,
Figure 145571DEST_PATH_IMAGE020
For the photovoltaic installation scale,
Figure 144751DEST_PATH_IMAGE021
For the scale of biomass loading machine,
Figure 429102DEST_PATH_IMAGE022
Is suitable for the scale of the pumping and storing machine,
Figure 28579DEST_PATH_IMAGE023
Is suitable for the scale of the gas-electric installation machine,
Figure 56578DEST_PATH_IMAGE024
Installing the scale for energy storage;
Figure 238161DEST_PATH_IMAGE025
hours for water electric installation,
Figure 365517DEST_PATH_IMAGE026
The number of hours of utilization of the coal electric installation machine,
Figure 265339DEST_PATH_IMAGE027
The number of hours for wind power installation,
Figure 35979DEST_PATH_IMAGE028
Hours of use for photovoltaic installation,
Figure 337647DEST_PATH_IMAGE029
Hours for biomass loading machine to use,
Figure 635904DEST_PATH_IMAGE030
Hours for the pump storage machine to use,
Figure 23023DEST_PATH_IMAGE031
The number of hours of utilization for the gas-electric installation machine,
Figure 579776DEST_PATH_IMAGE032
The number of hours of utilization of the energy storage machine.
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