CN114297249A - New energy project optimal selection ordering method considering power grid demand degree - Google Patents

New energy project optimal selection ordering method considering power grid demand degree Download PDF

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CN114297249A
CN114297249A CN202111669119.4A CN202111669119A CN114297249A CN 114297249 A CN114297249 A CN 114297249A CN 202111669119 A CN202111669119 A CN 202111669119A CN 114297249 A CN114297249 A CN 114297249A
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wind power
photovoltaic
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power
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CN114297249B (en
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邓笑冬
周野
李娟�
胡剑宇
蒋云松
李静
黄可
刘晔宁
方少雄
谭灵芝
方绍凤
范超
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China Energy Engineering Group Hunan Electric Power Design Institute Co Ltd
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China Energy Engineering Group Hunan Electric Power Design Institute Co Ltd
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    • 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
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    • 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
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Abstract

The invention discloses a method for optimizing and sequencing new energy projects. And collecting the existing and built new energy installation project conditions of each partition, acquiring the grid structure, load data, power distribution and power output conditions of the planning year, and providing a basic database for load flow calculation. Through load flow calculation and N-1 check, the regional bearing capacity under the conditions of regional wind power and photovoltaic N-1 and in a normal mode is determined in sequence, and a criterion is provided for determining the demand of a new energy project on a power grid. The method has the advantages that the condition of accessing the new energy project into the power grid and the resource quality are combined, the influence of the demand degree of the power grid on the new energy project is innovatively considered, the cooperativity of new energy project development and power grid construction is improved, and more scientific and reliable guidance is provided for reasonable and ordered development of new energy under the 'double-carbon' background.

Description

New energy project optimal selection ordering method considering power grid demand degree
Technical Field
The invention belongs to the technical field of power system automation, and particularly relates to a new energy project optimal sorting method considering power grid demand.
Background
By researching the influence analysis of the new energy project on the power grid demand degree, the power grid planning construction can be further coordinated to be adaptive to the new energy development. The demand degree of a power grid is considered, the new energy projects are preferably sequenced, scientific reference can be provided for further coordinating the development scale and speed of the new energy, and the method has important significance for constructing the development of a novel power system taking the new energy as a main body.
At present, the development of new energy of a regional power grid is mainly focused on a bearing capacity measuring and calculating method, and two types of models are mainly adopted: the first type is based on different cooperation strategies of new energy and an energy storage or other peak regulation power supply, and the consumption capacity of the new energy is evaluated according to the determined power supply structure and the peak regulation capacity; the other type is developed from the viewpoint of considering the peak shaving capacity of the power grid. And analyzing the electric power and electric quantity balance condition of the whole power grid to determine the new energy consumption capacity of the power grid. At present, a method for multi-factor comprehensive optimal sequencing of new energy projects considering the demand degree of a power grid is lacked.
In view of this, a new energy project optimal sorting method considering the power grid demand degree is researched, multiple factors are integrated to conduct optimal sorting on new energy projects, and the method has important practical value for solving the practical difficulties faced by planning designers and project deciders.
Disclosure of Invention
Aiming at the technical problems, the invention provides a new energy project optimal selection ordering method considering the power grid demand degree.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a new energy project optimal sorting method considering power grid demand degree comprises the following steps:
step S100: acquiring power grid data information, counting and planning new energy project distribution information, partitioning and sequencing project resources according to the power grid data information and the new energy project distribution information to obtain a partition project sequencing table;
step S200: collecting the existing and new energy installation project conditions of each partition, acquiring a grid structure, load data, various power supply distributions and power supply output conditions of a planned year, and obtaining a basic database in a small mode and a large noon mode;
step S300: carrying out load flow calculation by using a basic database in a small-abundance mode, adjusting the scale of wind power installations in the region, obtaining the bearing capacity of regional wind power under the condition of meeting the requirement of N-1 by using the load flow calculation and the calculation of N-1, adjusting the scale of the wind power installations in the region, obtaining the bearing capacity of regional wind power meeting normal delivery by using the load flow calculation, and judging the power grid demand degree of the wind power projects in the partition project sequencing table by combining the bearing capacity of the regional wind power under the condition of N-1 and the bearing capacity of the regional wind power meeting normal delivery;
step S400: on the basis that each partition obtained in the step S300 meets the internal wind power bearing capacity under the condition of 'N-1', performing load flow calculation by using a basic database under the Feng noon mode, adjusting the scale of the photovoltaic installation in the region, obtaining the regional photovoltaic bearing capacity under the condition of meeting 'N-1' by using the load flow calculation and the 'N-1' calculation, adjusting the scale of the photovoltaic installation in the region, obtaining the regional photovoltaic bearing capacity meeting normal delivery by using the load flow calculation, and performing power grid demand degree judgment on the photovoltaic projects in the partition project ranking table by combining the regional photovoltaic bearing capacity under the condition of 'N-1' and the regional wind power bearing capacity meeting normal delivery;
step S500: and sequencing the new energy projects by using a comprehensive optimization sequencing method by combining the partition project sequencing table, the power grid demand of the wind power project and the power grid demand of the photovoltaic project to obtain a new energy project optimization sequencing table.
Preferably, step S100 includes:
step S110: acquiring power grid data information and counting new energy project information, wherein the new energy project information comprises installed capacity of each project, geographical position of each project, resource information of each project and access distance of each project to a power grid;
step S120: obtaining the goodness and the badness of each project resource according to each project resource information, partitioning the new energy project resources according to the power grid data information and the geographic position of each project, and obtaining a new energy project condition table under each partition according to the installed capacity of each project and the goodness and the badness of each project resource;
step S130: and sequencing the new energy projects in the subareas according to the access distance of each project to the power grid to obtain a subarea project sequencing list.
Preferably, step S200 includes:
step S210: collecting project information of existing and new energy installation projects of each partition, wherein the project information comprises the sum of the existing partitions and the wind and power machines under construction and the sum of the existing partitions and the photovoltaic installation machines under construction;
step S220: acquiring a grid structure, load data, various power distributions and power output information of a planned year, obtaining load data in a small-size mode and a large-size mode according to the grid structure and the load data of the planned year, obtaining the sum of the power outputs of various power supplies except new energy in the small-size mode and the sum of the power outputs of various power supplies except the new energy in the large-size mode according to the power distributions and the power output information, and obtaining a wind power total output value in the small-size mode, a wind power total output value in the large-size mode and a photovoltaic total output value in the large-size mode according to the power output information; obtaining a wind power output coefficient of the Feng mode, a wind power output coefficient of the Feng mode and a photovoltaic output coefficient of the Feng mode according to the wind power total output value of the Feng mode, the photovoltaic total output value of the Feng mode, the sum of the existing partitioned wind power installations and the sum of the existing partitioned photovoltaic installations;
step S230: constructing a basic database under the Feng Xiao mode and the Feng Wu mode according to a grid structure of a planned year, load data under the Feng Xiao mode and the Feng Wu mode, distribution of various power supplies, the power output sum of various power supplies except new energy in the Feng Xiao mode, the power output sum of various power supplies except new energy in the Feng Wu mode, the power output sum of various power supplies existing in a subarea mode, the power output sum of a wind power installation under construction, the power output coefficient of a photovoltaic installation existing in a subarea mode, the power output coefficient of the Feng Wu mode, the power output coefficient of the Feng Xiao mode and the photovoltaic power output coefficient of the Feng Wu mode.
Preferably, step S220 specifically includes:
Figure BDA0003448977600000031
Figure BDA0003448977600000032
Figure BDA0003448977600000033
wherein, Cfx0For wind power total output value in small mode, Cfw0For wind power generation of the Feng-noon mode, Cgw0For the Town mode photovoltaic total output value, F0For the division of the existing and under construction wind installation assemblies, G0For the sum of the photovoltaic assembling machines which are partitioned and under construction, lambda x is the wind power output coefficient of the Fengxi mode, and lambda w is the Fengxi modeAnd the wind power output coefficient and kw are the photovoltaic output coefficient of the Feng noon mode.
Preferably, step S300 includes:
step S310: performing power flow calculation according to the basic database in the small and large mode to obtain a basic power flow calculation result in the small and large mode;
step S320: based on a basic load flow calculation result in a small mode, sequentially increasing the installed scale of wind power in the region according to the item sequence in the partition item sequence table, and obtaining the wind power bearing capacity of the region under the condition of meeting the condition of N-1 by utilizing load flow calculation and N-1 calculation;
step S330: based on a basic load flow calculation result in a small-size mode, sequentially increasing the installed scale of wind power in the region according to the item sequence in the partition item sequence table, and obtaining the wind power bearing capacity of the region under the condition of meeting normal delivery by utilizing load flow calculation;
step S340: and judging the power grid demand degree of the wind power projects in the partition project sequencing list according to the regional wind power bearing capacity under the condition of meeting the 'N-1' and the regional wind power bearing capacity under the condition of meeting the normal sending.
Preferably, step S320 is specifically:
F'＝F0+F0'+F1+F2…Fk1
Figure BDA0003448977600000041
wherein F ' is regional wind power bearing capacity under the condition of meeting the requirement of ' N-1 ', and F0For partitioning of the sum of existing wind installations, F0' for a partition building wind installation aggregate, FiPlanning the installed capacity of the ith wind power project in a subarea, Fk1Plan kth for intra-partition1Installed capacity, λ, of individual wind power projectsxThe wind power output coefficient under the rich and small mode, Px is the sum of the output of various power supplies except new energy under the rich and small mode, DxLoad data in a small-scale mode, M is the total number of wind power plant items, and ZxSurplus of regional electric power in a small and large mode;
step S330 specifically includes:
F”＝F0+F0'+F1+…Fk2
Figure BDA0003448977600000042
wherein F' is the regional wind power bearing capacity under the condition of meeting normal delivery, and Fk2Plan kth for intra-partition2Installed capacity of each wind power project.
Step S340 includes:
when the wind power project i belongs to [1, k ]1]Judging that the demand degree of the wind power project on the power grid is A type;
when the wind power project i belongs to (k)1,k2]Judging that the demand degree of the wind power project on the power grid is B type;
when the wind power project i belongs to (k)2,M]And judging that the demand degree of the wind power project on the power grid is type C.
Preferably, step S400 includes:
step S410: carrying out load flow calculation according to a basic database in the Town mode and in combination with a wind power project with the power grid demand degree of A type to obtain a basic load flow calculation result in the Town mode;
step S420: based on a basic load flow calculation result in a Feng-noon mode, sequentially increasing the photovoltaic installed scale in the region according to the item sequence in the partition item sequence table, and obtaining the photovoltaic bearing capacity of the region under the condition of meeting the condition of N-1 by utilizing load flow calculation and N-1 calculation;
step S430: based on a basic load flow calculation result in a Feng-noon mode, sequentially increasing the photovoltaic installed scale in the region according to the item sequence in the partition item sequence table, and obtaining the photovoltaic bearing capacity of the region under the condition of meeting normal sending-out by utilizing load flow calculation;
step S440: and judging the power grid demand degree of the photovoltaic projects in the partition project sequencing list according to the regional photovoltaic bearing capacity under the condition of meeting the 'N-1' and the regional photovoltaic bearing capacity under the condition of meeting the normal sending.
Preferably, step S420 is specifically:
G'＝G0+G0'+G1+…Gb1
Figure BDA0003448977600000051
wherein G ' is the regional photovoltaic bearing capacity under the condition of satisfying ' N-1 ', G0For zoning of the existing photovoltaic installation sum, G0' for the Sum of photovoltaic installations under construction, GjPlanning installed capacity, G, of jth photovoltaic project in a partitionb1Planning the b-th in the subarea1Installed capacity, λ, of individual photovoltaic projectswIs the wind power output coefficient k in the Feng noon modewIs the photovoltaic output coefficient in the mode of Feng noon, PwThe sum of the output of various power supplies except new energy in the Feng Wu mode, DwLoad data in the mode of Toyobo noon, N is the total number of wind power plant items, ZwSurplus of regional electric power in the Feng Wu mode;
step S430 specifically includes:
G”＝G0+G0'+G1+…Gb2
Figure BDA0003448977600000052
wherein G' satisfies the regional photovoltaic bearing capacity under normal delivery, Gb2Planning the b-th in the subarea2Installed capacity of individual photovoltaic projects.
Step S440 includes:
when the photovoltaic item j belongs to [1, b ]1]Judging the power grid demand degree of the photovoltaic project to be type A;
when the photovoltaic item j belongs to (b)1,b2]Judging that the demand degree of the photovoltaic project on the power grid is B type;
when the photovoltaic item j belongs to (b)2,N]And judging that the demand degree of the photovoltaic project on the power grid is type C.
Preferably, step S500 includes:
step S510: calculating the optimal value of each project of the new energy by combining the installed capacity, the access power grid distance and the resource goodness and badness of the new energy project, the power grid demand of the wind power project and the power grid demand of the photovoltaic project in the partition project ranking table;
step S520: and sequencing the new energy projects according to the optimized values of the projects of the new energy.
Preferably, step S510 specifically includes:
Yi＝αFi+βLfi+δRfi+ηQfi
Yj＝αGj+βLgj+δRgj+ηQgj
wherein, YiPlanning the preferred value of the ith wind power project for the subarea, FiPlanning the installed capacity, L, of the ith wind power project in the subareafiPlanning the distance of the ith wind power project to be connected into the power grid in the subarea, RfiPlanning the quality degree, Q, of the ith wind power project resource in the subareafiPlanning the power grid demand degree of the ith wind power project for the subareas; y isjFor the preferred value, G, of the planned jth photovoltaic project in the partitionjPlanning installed capacity, L, of jth photovoltaic project in a partitiongjPlanning the distance, R, of the j-th photovoltaic project to be connected into the power grid in the subareagjPlanning the quality degree, Q, of the j-th photovoltaic project resource in the subareagiAnd planning the power grid demand degree of the jth photovoltaic project in the subarea.
The method for optimizing and sequencing the new energy project comprises the steps of firstly counting and planning the partition distribution condition of the new energy project, and obtaining a partition project sequencing table by combining with power grid data information to provide a basis for optimizing and sequencing the new energy project. And collecting the existing and built new energy installation project conditions of each partition, acquiring the grid structure, load data, power distribution and power output conditions of the planning year, and providing a basic database for load flow calculation. Through load flow calculation and N-1 check, the regional bearing capacity under the conditions of regional wind power and photovoltaic N-1 and in a normal mode is determined in sequence, and a criterion is provided for determining the demand of a new energy project on a power grid. The influence of the demand degree of the power grid on the new energy project is innovatively considered by combining the wind area project sequencing table, the cooperativity of the new energy project development and the power grid construction is improved, and more scientific and reliable guidance is provided for the reasonable and ordered development of the new energy under the 'double-carbon' background.
Drawings
Fig. 1 is a flowchart of a new energy project optimization ranking method considering a power grid demand degree according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the present invention is further described in detail below with reference to the accompanying drawings.
In one embodiment, as shown in fig. 1, a new energy project optimization ranking method considering grid demand degree includes the following steps:
step S100: and acquiring power grid data information, counting and planning new energy project distribution information, partitioning and sequencing project resources according to the power grid data information and the new energy project distribution information, and obtaining a partition project sequencing table.
Specifically, the power grid data information refers to the distribution condition of a 500kV transformer substation and the open-loop condition of power grid operation.
In one embodiment, step S100 includes:
step S110: acquiring power grid data information and counting new energy project information, wherein the new energy project information comprises installed capacity of each project, geographical position of each project, resource information of each project and access distance of each project to a power grid;
step S120: obtaining the goodness and the badness of each project resource according to each project resource information, partitioning the new energy project resources according to the power grid data information and the geographic position of each project, and obtaining a new energy project condition table under each partition according to the installed capacity of each project and the goodness and the badness of each project resource;
step S130: and sequencing the new energy projects in the subareas according to the access distance of each project to the power grid to obtain a subarea project sequencing list.
Specifically, the resource information of each project is used to obtain the goodness of the resource, for example, the resource information of the wind power refers to indexes such as wind speed and wind resource density. The photovoltaic resource information refers to a series of conditions such as a total solar radiation value and the like, and the quality of the resource can be obtained according to the resource information. The photoelectric items and the partitioned photovoltaics need to be sorted respectively, and the partition item sorting table obtained in step S130 specifically includes:
partition 1 wind power project sequencing table
Figure BDA0003448977600000071
Figure BDA0003448977600000081
Zone 1 photovoltaic project sequencing table
Photovoltaic project numbering Photovoltaic project capacity Distance to grid Degree of superiority and inferiority of resource
1 G1 Lg1 Rg1
2 G2 Lg2 Rg2
… … … …
j Gj Lgj Rgj
… … … …
N GN LgN RgN
Wherein L isf1<Lf2<…Lfi<…LfM
Lg1<Lg2<…Lgj<…LgN
Wherein, F1、F2…Fi…FMPlanning the installed capacity, L, of the ith wind power project in the subareaf1、Lf2…Lfi…LfMPlanning the distance of the ith wind power project to be connected into the power grid in the subarea, Rf1、Rf2…Rfi…RfMAnd planning the quality degree of the ith wind power project resource in the partition.
Wherein G is1、G2…Gj…GNPlanning the jth light in a partitionInstalled capacity of the volt project, Lg1、Lg2…Lgj…LgNPlanning the distance, R, of the j-th photovoltaic project to be connected into the power grid in the subareag1、Rg2…Rgj…RgNAnd planning the resource quality degree of the jth photovoltaic project in the partition.
Step S200: collecting the existing and new energy installation project conditions of each partition, acquiring the grid structure, load data, various power supply distributions and power supply output conditions of the planned year, and obtaining a basic database in the small and large modes and the mid-day mode.
Specifically, the small-large mode refers to a specific mode (generally 2:00-5:00 in 3-5 months in the morning) with a small load in the water-large period, in the mode, the wind power output is large, the photovoltaic output is not output, the load is generally small, the region delivery is large, and the mode can be used for determining the maximum bearing capacity of the wind power installation machine. The Feng noon mode refers to a specific mode (generally, 12:00-14:00 noon in 3-5 months) in the middle of the full-water period, and in the mode, the wind power output is slightly smaller than that in the full-water mode, the photovoltaic output is larger, the area delivery is larger, and the mode can be used for determining the maximum bearing capacity of the photovoltaic installation.
Acquiring a grid structure (including substation parameters and line parameters), load data (load data of each substation), power distribution conditions (which substation each type of substation is connected to) and power output conditions of a planned year, establishing a basic power flow calculation database in a small-size-in-the-year mode and a large-noon-year mode, and performing power flow calculation and 'N-1' checking by using special software such as BPA (business process platform) and the like.
In one embodiment, step S200 includes:
step S210: collecting project information of existing and new energy installation projects of each partition, wherein the project information comprises the sum of the existing partitions and the wind and power machines under construction and the sum of the existing partitions and the photovoltaic installation machines under construction;
step S220: acquiring a grid structure, load data, various power distributions and power output information of a planned year, obtaining load data in a small-size mode and a large-size mode according to the grid structure and the load data of the planned year, obtaining the sum of the power outputs of various power supplies except new energy in the small-size mode and the sum of the power outputs of various power supplies except the new energy in the large-size mode according to the power distributions and the power output information, and obtaining a wind power total output value in the small-size mode, a wind power total output value in the large-size mode and a photovoltaic total output value in the large-size mode according to the power output information; obtaining a wind power output coefficient of the Feng mode, a wind power output coefficient of the Feng mode and a photovoltaic output coefficient of the Feng mode according to the wind power total output value of the Feng mode, the photovoltaic total output value of the Feng mode, the sum of the existing partitioned wind power installations and the sum of the existing partitioned photovoltaic installations;
step S230: constructing a basic database under the Feng Xiao mode and the Feng Wu mode according to a grid structure of a planned year, load data under the Feng Xiao mode and the Feng Wu mode, distribution of various power supplies, the power output sum of various power supplies except new energy in the Feng Xiao mode, the power output sum of various power supplies except new energy in the Feng Wu mode, the power output sum of various power supplies existing in a subarea mode, the power output sum of a wind power installation under construction, the power output coefficient of a photovoltaic installation existing in a subarea mode, the power output coefficient of the Feng Wu mode, the power output coefficient of the Feng Xiao mode and the photovoltaic power output coefficient of the Feng Wu mode.
Further, the output coefficient of the photovoltaic small-size mode is 0.
In one embodiment, step S220 specifically includes:
Figure BDA0003448977600000091
Figure BDA0003448977600000092
Figure BDA0003448977600000093
wherein, Cfx0For wind power total output value in small mode, Cfw0For wind power generation of the Feng-noon mode, Cgw0For the Town mode photovoltaic total output value, F0For the division of the existing and under construction wind installation assemblies, G0For partitioning to existing andin the sum of the photovoltaic installation machines under construction, lambda x is a wind power output coefficient of a small mode, lambda w is a wind power output coefficient of a mid-day mode, and kw is a photovoltaic output coefficient of a mid-day mode.
Step S300: carrying out load flow calculation by using a basic database in a small-size mode, adjusting the scale of wind power installation in a region, obtaining the bearing capacity of regional wind power meeting the requirement of N-1 by using the load flow calculation and the N-1 calculation, adjusting the scale of the wind power installation in the region, obtaining the bearing capacity of regional wind power meeting normal delivery by using the load flow calculation, and judging the power grid demand degree of the wind power projects in the partition project sequencing table by combining the bearing capacity of regional wind power under the N-1 condition and the bearing capacity of regional wind power meeting the normal delivery.
In one embodiment, step S300 includes:
step S310: performing power flow calculation according to the basic database in the small and large mode to obtain a basic power flow calculation result in the small and large mode;
step S320: based on a basic load flow calculation result in a small mode, sequentially increasing the installed scale of wind power in the region according to the item sequence in the partition item sequence table, and obtaining the wind power bearing capacity of the region under the condition of meeting the condition of N-1 by utilizing load flow calculation and N-1 calculation;
step S330: based on a basic load flow calculation result in a small-size mode, sequentially increasing the installed scale of wind power in the region according to the item sequence in the partition item sequence table, and obtaining the wind power bearing capacity of the region under the condition of meeting normal delivery by utilizing load flow calculation;
step S340: and judging the power grid demand degree of the wind power projects in the partition project sequencing list according to the regional wind power bearing capacity under the condition of meeting the 'N-1' and the regional wind power bearing capacity under the condition of meeting the normal sending.
Specifically, sequentially increasing the wind power installed scale means that under the condition of the original installed scale, the capacity F1 of one wind power plant is increased, whether the N-1 check is met or not is calculated, if yes, the capacity F2 of the wind power plant is increased, and the calculation is performed again until the limit value is calculated.
In one embodiment, step S320 specifically includes:
F'＝F0+F0'+F1+F2…Fk1
Figure BDA0003448977600000101
wherein F ' is regional wind power bearing capacity under the condition of meeting the requirement of ' N-1 ', and F0For partitioning of the sum of existing wind installations, F0' for a partition building wind installation aggregate, FiPlanning the installed capacity of the ith wind power project in a subarea, Fk1Plan kth for intra-partition1Installed capacity, λ, of individual wind power projectsxThe wind power output coefficient under the rich and small mode, Px is the sum of the output of various power supplies except new energy under the rich and small mode, DxLoad data in a small-scale mode, M is the total number of wind power plant items, and ZxThe surplus of regional power in a small and large mode is achieved.
Specifically, the regional power surplus Z meets the load flow calculation N-1 check, namely after any line or transformer N-1 is disconnected, the main transformer and the line power meet the requirements of the overload capacity of the main transformer and the limit transmission capacity of the line, and at the moment, a wind power project i belongs to [1, k ]1]The method can meet the requirement of sending out the wind power project without adding any equipment on the power grid side, and can judge that the requirement of the wind power on the power grid is A type.
Step S330 specifically includes:
F”＝F0+F0'+F1+…Fk2
Figure BDA0003448977600000111
wherein F' is the regional wind power bearing capacity under the condition of meeting normal delivery, and Fk2Plan kth for intra-partition2Installed capacity of each wind power project.
The requirement of normal sending is met, namely, under a normal mode, the main transformer and the line power meet the requirements of main transformer capacity and line limit transmission capacity. However, after the line or the main transformer N-1 is disconnected, the main transformer and the line power do not meet the requirements of the overload capacity of the main transformer and the limit transmission capacity of the line.
At the moment, the wind power project i belongs to (k)1,k2]The safety and stability requirements of the wind power plant access system can be met only by configuring a stability control generator tripping device on the side of the power grid, and the requirement degree of the project on the power grid can be judged to be type B.
Wind power project i e (k)2,M]The requirement of a power grid for further reinforcing the network can meet the requirement of a wind power plant access system, and the requirement of the project on the power grid can be judged to be type C. The obtained partition wind power project sequencing table is as follows:
Figure BDA0003448977600000112
Figure BDA0003448977600000121
step S400: on the basis that each partition obtained in the step S300 meets the internal wind power bearing capacity under the condition of 'N-1', performing load flow calculation by using a basic database under the Feng noon mode, adjusting the scale of the photovoltaic installation in the region, obtaining the regional photovoltaic bearing capacity under the condition of meeting 'N-1' by using the load flow calculation and the 'N-1' calculation, adjusting the scale of the photovoltaic installation in the region, obtaining the regional photovoltaic bearing capacity meeting normal delivery by using the load flow calculation, and performing power grid demand degree judgment on the photovoltaic projects in the partition project ranking table by combining the regional photovoltaic bearing capacity under the condition of 'N-1' and the regional wind power bearing capacity meeting normal delivery.
Specifically, when calculating the basic power flow at noon, the existing wind power F0 in the area and the installed scale of all the type-A wind power projects calculated in the previous step need to be considered.
In one embodiment, step S400 includes:
step S410: carrying out load flow calculation according to a basic database in the Town mode and in combination with a wind power project with the power grid demand degree of A type to obtain a basic load flow calculation result in the Town mode;
step S420: based on a basic load flow calculation result in a Feng-noon mode, sequentially increasing the photovoltaic installed scale in the region according to the item sequence in the partition item sequence table, and obtaining the photovoltaic bearing capacity of the region under the condition of meeting the condition of N-1 by utilizing load flow calculation and N-1 calculation;
step S430: based on a basic load flow calculation result in a Feng-noon mode, sequentially increasing the photovoltaic installed scale in the region according to the item sequence in the partition item sequence table, and obtaining the photovoltaic bearing capacity of the region under the condition of meeting normal sending-out by utilizing load flow calculation;
step S440: and judging the power grid demand degree of the photovoltaic projects in the partition project sequencing list according to the regional photovoltaic bearing capacity under the condition of meeting the 'N-1' and the regional photovoltaic bearing capacity under the condition of meeting the normal sending.
In one embodiment, step S420 specifically includes:
G'＝G0+G0'+G1+…Gb1
Figure BDA0003448977600000122
wherein G ' is the regional photovoltaic bearing capacity under the condition of satisfying ' N-1 ', G0For zoning of the existing photovoltaic installation sum, G0' for the Sum of photovoltaic installations under construction, GjPlanning installed capacity, G, of jth photovoltaic project in a partitionb1Planning the b-th in the subarea1Installed capacity, λ, of individual photovoltaic projectswIs the wind power output coefficient k in the Feng noon modewIs the photovoltaic output coefficient in the Feng noon mode, PwThe sum of the output of various power supplies except new energy in the Feng Wu mode, DwLoad data in the mode of Toyobo noon, N is the total number of wind power plant items, ZwThe surplus of regional electric power in the mode of abundance at noon.
And the surplus Z of the regional power meets the requirement of load flow calculation N-1 check, namely after any line or transformer N-1 is disconnected, the main transformer and the line power meet the requirements of overload capacity of the main transformer and the limit transmission capacity of the line. When the photovoltaic item j is [1, b ]1]The requirement of the photovoltaic project on the power grid can be judged to be type A.
Step S430 specifically includes:
G”＝G0+G0'+G1+…Gb2
Figure BDA0003448977600000131
wherein G' satisfies the regional photovoltaic bearing capacity under normal delivery, Gb2Planning the b-th in the subarea2Installed capacity of individual photovoltaic projects.
The surplus of regional electric power meets the requirement of normal sending, namely, under a normal mode, the main transformer and the line power meet the requirements of main transformer capacity and line limit transmission capacity. However, after the line or the main transformer N-1 is disconnected, the main transformer and the line power do not meet the requirements of the overload capacity of the main transformer and the limit transmission capacity of the line.
At the moment, the photovoltaic item j belongs to (b)1,b2]And the safety and stability requirements of the photovoltaic field access system can be met only by configuring a stability control generator tripping device on the side of the power grid, and the requirement degree of the project on the power grid can be judged to be B type.
Photovoltaic item j e (b)2,N]The requirement of a power grid for further reinforcing the network can meet the requirement of a photovoltaic power station access system, and the requirement of the project on the power grid can be judged to be type C. The obtained partitioned photovoltaic project sequencing table is as follows:
Figure BDA0003448977600000132
Figure BDA0003448977600000141
step S500: and sequencing the new energy projects by using a comprehensive optimization sequencing method by combining the partition project sequencing table, the power grid demand of the wind power project and the power grid demand of the photovoltaic project to obtain a new energy project optimization sequencing table.
In one embodiment, step S500 includes:
step S510: and calculating the optimal value of each project of the new energy by combining the installed capacity, the access power grid distance and the resource goodness and badness of the new energy project, the power grid demand of the wind power project and the power grid demand of the photovoltaic project in the partition project ranking table.
In one embodiment, step S510 specifically includes:
Yi＝αFi+βLfi+δRfi+ηQfi
Yj＝αGj+βLgj+δRgj+ηQgj
wherein, YiPlanning the preferred value of the ith wind power project for the subarea, FiPlanning the installed capacity, L, of the ith wind power project in the subareafiPlanning the distance of the ith wind power project to be connected into the power grid in the subarea, RfiPlanning the quality degree, Q, of the ith wind power project resource in the subareafiPlanning the power grid demand degree of the ith wind power project for the subareas; y isjFor the preferred value, G, of the planned jth photovoltaic project in the partitionjPlanning installed capacity, L, of jth photovoltaic project in a partitiongjPlanning the distance, R, of the j-th photovoltaic project to be connected into the power grid in the subareagjPlanning the quality degree, Q, of the j-th photovoltaic project resource in the subareagiAnd planning the power grid demand degree of the jth photovoltaic project in the subarea.
Step S520: and sequencing the new energy projects according to the optimized values of the projects of the new energy.
Specifically, the smaller the preferred value Y is, the better the item development degree is, specifically:
Figure BDA0003448977600000142
Figure BDA0003448977600000151
photovoltaic project numbering Project capacity Length of access line Degree of superiority and inferiority of resource Degree of demand of power grid Preferred value
1 G1 Lf1 Rg1 A Y1
… … … … A …
b1 Gb1 Lk1 Rgk1 A Yb1
b1+1 Gb1+1 Lk1+1 Rgk1+1 B Yb1+1
… … … … B …
b2 Gb2 Lfi Rgfi B Yb2
b2+1 Gb2+1 Lfi Rgfi C Yb2+1
… … … … C …
N GN Lfm Rgfm C YN
The invention discloses a new energy project optimal sorting method considering power grid requirements. And collecting the existing and built new energy installation project conditions of each partition, acquiring the grid structure, load data, power distribution and power output conditions of the planning year, and providing a basic database for load flow calculation. Through load flow calculation and N-1 check, the regional bearing capacity under the conditions of regional wind power and photovoltaic N-1 and in a normal mode is determined in sequence, and a criterion is provided for determining the demand of a new energy project on a power grid. The method has the advantages that the condition of accessing the new energy project into the power grid and the quality of resources are combined, the influence of the demand degree of the power grid on the new energy project is innovatively considered, the cooperativity of new energy project development and power grid construction is improved, and more scientific and reliable guidance is provided for reasonable and ordered development of new energy under the 'double-carbon' background.
The method for optimally ordering the new energy project considering the power grid requirement provided by the invention is described in detail above. The principles and embodiments of the present invention are explained herein using specific examples, which are presented only to assist in understanding the core concepts of the present invention. It should be noted that, for those skilled in the art, it is possible to make various improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the scope of the claims of the present invention.

Claims (10)

1. A new energy project optimal sorting method considering power grid demand degree is characterized by comprising the following steps:
step S100: acquiring power grid data information, counting and planning new energy project distribution information, partitioning and sequencing project resources according to the power grid data information and the new energy project distribution information to obtain a partition project sequencing table;
step S200: collecting the existing and new energy installation project conditions of each partition, acquiring a grid structure, load data, various power supply distributions and power supply output conditions of a planned year, and obtaining a basic database in a small mode and a large noon mode;
step S300: carrying out load flow calculation by using the basic database in the small-scale mode, adjusting the scale of wind power installation in the region, obtaining the bearing capacity of regional wind power meeting the requirement of N-1 by using the load flow calculation and the calculation of N-1, adjusting the scale of the wind power installation in the region, obtaining the bearing capacity of regional wind power meeting the requirement of normal delivery by using the load flow calculation, and carrying out power grid demand degree judgment on the wind power projects in the partition project sequencing table by combining the bearing capacity of regional wind power under the condition of N-1 and the bearing capacity of regional wind power meeting the requirement of normal delivery;
step S400: on the basis that each partition obtained in the step S300 meets the internal wind power bearing capacity under the condition of N-1, performing load flow calculation by using the basic database under the Feng noon mode, adjusting the scale of the photovoltaic installation in the region, obtaining the regional photovoltaic bearing capacity under the condition of meeting N-1 by using the load flow calculation and the N-1 calculation, adjusting the scale of the photovoltaic installation in the region, obtaining the regional photovoltaic bearing capacity meeting normal delivery by using the load flow calculation, and determining the power grid demand degree of the photovoltaic projects in the partition project ranking table by combining the regional photovoltaic bearing capacity under the condition of N-1 and the regional wind power bearing capacity meeting normal delivery;
step S500: and sequencing the new energy projects by utilizing a comprehensive optimal sequencing method by combining the partition project sequencing table, the power grid demand degree of the wind power project and the power grid demand degree of the photovoltaic project to obtain a new energy project optimal sequencing table.
2. The method according to claim 1, wherein step S100 comprises:
step S110: acquiring power grid data information and counting new energy project information, wherein the new energy project information comprises installed capacity of each project, geographical position of each project, resource information of each project and access distance of each project to a power grid;
step S120: obtaining the goodness and the badness of each project resource according to the resource information of each project, partitioning the new energy project resources according to the power grid data information and the geographical position of each project, and obtaining a new energy project condition table under each partition according to the installed capacity and the goodness and the badness of each project resource;
step S130: and sequencing the new energy projects in the subareas according to the distance of each project accessed to the power grid to obtain a subarea project sequencing list.
3. The method according to claim 2, wherein step S200 comprises:
step S210: collecting project information of existing and new energy installation machines in each partition, wherein the project information comprises the sum of the existing and new energy installation machines in the partition and the sum of the existing and new energy installation machines in the partition;
step S220: acquiring a grid structure, load data, various power distributions and power output information of a planned year, obtaining load data in a small-to-large and high-noon mode according to the grid structure and the load data of the planned year, obtaining the sum of the power outputs of various power supplies except new energy in the small-to-large mode and the sum of the power outputs of various power supplies except the new energy in the high-noon mode according to the power distributions and the power output information, and obtaining a wind power total output value in the small-to-large mode, a wind power total output value in the high-noon mode and a photovoltaic total output value in the high-noon mode according to the power output information; obtaining a wind power output coefficient of the large and small mode, a wind power output coefficient of the large and small mode and a photovoltaic output coefficient of the large and small mode according to the total wind power output value of the large and small mode, the total photovoltaic output value of the large and small mode, the sum of the partitioned existing wind power installations and the sum of the partitioned existing photovoltaic installations;
step S230: and constructing a basic database under the Feng Xiao mode and the Feng Wu mode according to the grid structure of the planned year, the load data under the Feng Xiao and Feng Wu modes, the distribution of various power supplies, the sum of the power supplies of the Feng Xiao modes except new energy, the sum of the power supplies of the Feng Wu modes except new energy, the sum of the partition existing and under-construction wind power installations, the sum of the partition existing and under-construction photovoltaic installations, the Feng Wu mode wind power output coefficient, the Feng Xiao mode wind power output coefficient and the Feng Wu mode photovoltaic output coefficient.
4. The method according to claim 3, wherein step S220 is specifically:
Figure FDA0003448977590000021
Figure FDA0003448977590000022
Figure FDA0003448977590000023
wherein, Cfx0For wind power total output value in small mode, Cfw0For wind power generation of the Feng-noon mode, Cgw0For the Toyomi mode photovoltaic total output value, F0For partitioning of the sum of existing wind installations, G0The method is characterized in that lambda x is the wind power output coefficient of the small mode, lambda w is the wind power output coefficient of the mid-day mode, and kw is the photovoltaic output coefficient of the mid-day mode.
5. The method of claim 4, wherein step S300 comprises:
step S310: performing load flow calculation according to the basic database in the small and large mode to obtain a basic load flow calculation result in the small and large mode;
step S320: based on the basic load flow calculation result in the small-scale mode, sequentially increasing the installed scale of wind power in the region according to the item sequence in the partition item sequence table by utilizing load flow calculation and N-1 calculation to obtain the wind power bearing capacity of the region under the condition of meeting the N-1;
step S330: based on the basic load flow calculation result in the small-size mode, sequentially increasing the installed scale of the regional wind power according to the item sequence in the partition item sequence table, and obtaining the regional wind power bearing capacity under the condition of meeting the normal delivery condition by utilizing load flow calculation;
step S340: and judging the power grid demand degree of the wind power projects in the partition project sequencing list according to the regional wind power bearing capacity under the condition of meeting the 'N-1' requirement and the regional wind power bearing capacity under the condition of meeting the normal sending-out requirement.
6. The method according to claim 5, wherein step S320 is specifically:
F'＝F0+F0'+F1+F2…Fk1
Figure FDA0003448977590000031
k1∈[1,M]
wherein F ' is regional wind power bearing capacity under the condition of meeting the requirement of ' N-1 ', and F0For partitioning of the sum of existing wind installations, F0' for a partition building wind installation aggregate, FiPlanning the installed capacity of the ith wind power project in a subarea, Fk1Plan kth for intra-partition1Installed capacity, λ, of individual wind power projectsxThe wind power output coefficient under the rich and small mode, Px is the sum of the output of various power supplies except new energy under the rich and small mode, DxLoad data in a small-scale mode, M is a wind power plantTotal number of items, ZxSurplus of regional electric power in a small and large mode;
step S330 specifically includes:
F”＝F0+F0'+F1+…Fk2
Figure FDA0003448977590000032
k2∈[k1,M]
wherein F' is the regional wind power bearing capacity under the condition of meeting normal delivery, and Fk2Plan kth for intra-partition2Installed capacity of each wind power project.
Step S340 includes:
when the wind power project i belongs to [1, k ]1]Judging that the demand degree of the wind power project on the power grid is A type;
when the wind power project i belongs to (k)1,k2]Judging that the demand degree of the wind power project on the power grid is B type;
when the wind power project i belongs to (k)2,M]And judging that the demand degree of the wind power project on the power grid is type C.
7. The method of claim 6, wherein step S400 comprises:
step S410: carrying out load flow calculation according to the basic database in the Feng noon mode and in combination with the wind power project with the power grid demand degree of A type to obtain a basic load flow calculation result in the Feng noon mode;
step S420: based on the basic load flow calculation result in the Feng noon mode, sequentially increasing the installed photovoltaic scale in the region according to the item sequence in the partition item sequence table by utilizing load flow calculation and N-1 calculation to obtain the photovoltaic bearing capacity of the region under the condition of meeting the condition of N-1;
step S430: based on the basic load flow calculation result in the Feng' ang mode, sequentially increasing the photovoltaic installed scale in the region according to the item sequence in the partition item sequence table, and obtaining the photovoltaic bearing capacity of the region under the condition of meeting the requirement of normal delivery by utilizing load flow calculation;
step S440: and judging the power grid demand degree of the photovoltaic projects in the partition project sequencing list according to the regional photovoltaic bearing capacity under the condition of meeting the 'N-1' and the regional photovoltaic bearing capacity under the condition of meeting the normal sending.
8. The method according to claim 7, wherein step S420 specifically comprises:
G'＝G0+G0'+G1+…Gb1
Figure FDA0003448977590000041
b1∈[1,N]
wherein G ' is the regional photovoltaic bearing capacity under the condition of satisfying ' N-1 ', G0Is the total sum of the partition existing photovoltaic installation machines, G'0For zoning under construction photovoltaic installation assembly, GjPlanning installed capacity, G, of jth photovoltaic project in a partitionb1Planning the b-th in the subarea1Installed capacity, λ, of individual photovoltaic projectswIs the wind power output coefficient k in the Feng noon modewIs the photovoltaic output coefficient in the Feng noon mode, PwThe sum of the output of various power supplies except new energy in the Feng Wu mode, DwLoad data in the mode of Toyobo noon, N is the total number of wind power plant items, ZwSurplus of regional electric power in the Feng Wu mode;
step S430 specifically includes:
G”＝G0+G0'+G1+…Gb2
Figure FDA0003448977590000051
b2∈[b1,N]
wherein G' satisfies the regional photovoltaic bearing capacity under normal delivery, Gb2Planning the b-th in the subarea2Installation of individual photovoltaic projectCapacity.
Step S440 includes:
when the photovoltaic item j belongs to [1, b ]1]Judging the power grid demand degree of the photovoltaic project to be type A;
when the photovoltaic item j belongs to (b)1,b2]Judging that the demand degree of the photovoltaic project on the power grid is B type;
when the photovoltaic item j belongs to (b)2,N]And judging that the demand degree of the photovoltaic project on the power grid is type C.
9. The method of claim 8, wherein step S500 comprises:
step S510: calculating the optimal value of each project of the new energy by combining the installed capacity, the access power grid distance and the resource goodness of the new energy project in the partition project ranking table, the power grid demand of the wind power project and the power grid demand of the photovoltaic project;
step S520: and sequencing the new energy projects according to the optimized values of the projects of the new energy.
10. The method according to claim 9, wherein step S510 specifically includes:
Yi＝αFi+βLfi+δRfi+ηQfi
Yj＝αGj+βLgj+δRgj+ηQgj
wherein, YiPlanning the preferred value of the ith wind power project for the subarea, FiPlanning the installed capacity, L, of the ith wind power project in the subareafiPlanning the distance of the ith wind power project to be connected into the power grid in the subarea, RfiPlanning the quality degree, Q, of the ith wind power project resource in the subareafiPlanning the power grid demand degree of the ith wind power project for the subareas; y isjPlanning preference value, G, of jth photovoltaic project in subareajPlanning installed capacity, L, of jth photovoltaic project in a partitiongjPlanning the distance, R, of the j-th photovoltaic project to be connected into the power grid in the subareagjPlanning the jth light in a partitionDegree of quality of the underlying project resource, QgiAnd planning the power grid demand degree of the jth photovoltaic project in the subarea.
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