CN110768306A - Power supply capacity configuration method for improving emergency capacity of micro-grid in bottom-protected power grid - Google Patents

Power supply capacity configuration method for improving emergency capacity of micro-grid in bottom-protected power grid Download PDF

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CN110768306A
CN110768306A CN201911051692.1A CN201911051692A CN110768306A CN 110768306 A CN110768306 A CN 110768306A CN 201911051692 A CN201911051692 A CN 201911051692A CN 110768306 A CN110768306 A CN 110768306A
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power
grid
capacity
power supply
microgrid
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CN110768306B (en
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岑海凤
杨翔宇
许苑
李涛
欧阳金鑫
林琳
熊小伏
徐辉
陈坤
李梦阳
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Chongqing University
Guangzhou Power Supply Bureau Co Ltd
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Chongqing University
Guangzhou Power Supply Bureau Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means

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Abstract

The invention discloses a power supply capacity configuration method for improving the emergency capacity of a micro-grid in a bottom-guaranteed power grid, which is applied to a power distribution system comprising the micro-grid and comprises the step of establishing a bottom-guaranteed power grid maximum load power shortage rate index FlpsAnd the economic index F of the micro-gridcA power supply capacity optimal configuration model with the minimum as a target; constructing a constraint condition of a power supply capacity optimization configuration model; acquiring target power distribution system information, and solving a power supply capacity optimal configuration model of a target to obtain power supply capacity configuration information; and configuring the power supply capacity. On the basis of the existing method for optimizing and configuring the power supply capacity of the microgrid, the supporting capacity of different power supply configurations to the bottom-protected power grid is considered to be different, the operation principle of the microgrid and the operation mode of the microgrid in the bottom-protected power grid are analyzed and compared, the influence factors of the emergency supporting capacity of the microgrid are considered, and the microgrid in the bottom-protected power grid can provide effective emergency for the bottom-protected power gridAnd the support ensures the stable operation of important loads in the bottom-protected power grid.

Description

Power supply capacity configuration method for improving emergency capacity of micro-grid in bottom-protected power grid
Technical Field
The invention relates to the field of microgrid planning, in particular to a power supply capacity configuration method for improving the emergency capacity of a microgrid in a bottom-protected power grid.
Background
The southeast coastal areas of China are affected by weather conditions, and often have extreme weather such as typhoon, rainstorm and the like, so that a series of large-scale power failure accidents are caused. In order to ensure the power supply reliability of part of core areas, the construction of urban windproof disaster-resistant bottom-protection power grids has become a focus of attention.
The bottom-protecting power grid is a minimum-scale grid frame formed by carrying out differential construction on important loads, lines and stations in the power distribution network for the purpose of preventing adverse effects on the power distribution network caused by extreme weather, enhancing the risk resistance of a core region of a city and shortening the power restoration time of key loads under faults. In the process of building a bottom-protecting power grid, firstly, determining loads, lines and stations which are important elements, then transforming the net rack according to indexes such as cabling rate and survivability of the net rack to form a core backbone net rack of the bottom-protecting power grid, and finally, distributing enough number of guarantee power supplies in the net rack to ensure the power supply reliability of the bottom-protecting power grid under normal operation and disaster conditions. However, the current bottom-protection power grid mainly considers the planning problem of a grid structure, and mainly adopts a synchronous generator set in terms of selection of a guarantee power supply, but due to the defects of inflexible power control capability, low response speed and the like, the supporting capability for important loads is limited, and the requirements of wind-proof disaster-resistant bottom-protection power grid in coastal areas can not be met.
A microgrid is a modern distributed power system that integrates distributed power sources, energy storage devices, and loads together. Distributed power sources commonly used at present include gas turbines, photovoltaics, wind power, and stored energy. The output of each distributed power supply in the micro-grid can be flexibly adjusted and complemented, and the micro-grid can provide effective emergency support for important loads of the power distribution network under emergency conditions such as severe weather and the like, so that the running efficiency of the bottom-guaranteed power grid is improved. The emergency support capability of the microgrid is mainly determined by the capacity configuration condition of each power supply. The current commonly used power sources include gas turbines, photovoltaics, wind power, and stored energy. The gas turbine and the stored energy have better controllability, so that emergency power support can be effectively provided under severe meteorological conditions; wind power and photovoltaic are greatly influenced by weather conditions, but good economic benefits and environmental benefits can be brought. Therefore, the method gives consideration to the operation cost and the emergency support capability of the micro-grid, reasonably configures the capacity of various micro-power supplies in the micro-grid, and has important significance for the construction and the operation of a bottom-guaranteed power grid.
At present, many scholars mainly focus on the research on the problem of optimizing and configuring the capacity of a micro-grid power supply, wherein ① researches the operation mode of the micro-grid power supply by taking the economy of micro-grid operation as an optimization target and considering different optimization objects such as risk, pollution discharge and self reliability and different power supply types such as wind-solar complementation and light-storage coordination operation, ② researches the capacity optimizing and configuring of the micro-grid power supply by taking different indexes such as energy recovery cost, energy storage charge-discharge period and renewable energy consumption as optimization objects, but researches on improving the emergency support capacity of the micro-grid as the optimization target are rarely involved.
Therefore, the invention provides a power supply capacity configuration method for improving the emergency capacity of a micro-grid in a bottom-protected power grid, which aims at the application of the micro-grid in the bottom-protected power grid.
Disclosure of Invention
Aiming at the defects of the prior art, the problems to be solved by the invention are as follows: how to guarantee that the microgrid in the bottom-protecting power grid can provide effective emergency support for the bottom-protecting power grid and guarantee the stable operation of important loads in the bottom-protecting power grid.
In order to solve the technical problems, the invention adopts the following technical scheme:
a power supply capacity configuration method for improving the emergency capacity of a micro-grid in a guaranteed-base power grid is applied to a power distribution system comprising the micro-grid and comprises the following steps:
s1, establishing a base-guaranteed power grid maximum load power shortage rate index FlpsAnd the economic index F of the micro-gridcA power supply capacity optimal configuration model with the minimum as a target;
s2, constructing constraint conditions of a power supply capacity optimization configuration model;
s3, acquiring target power distribution system information, inputting the target power distribution system information into a power capacity optimization configuration model, and solving the power capacity optimization configuration model of the target based on the constraint condition of the power capacity optimization configuration model to obtain power capacity configuration information;
and S4, configuring the power capacity based on the power capacity configuration information.
Preferably, in step S1:
Figure BDA0002255482270000021
in the formula, PoutFor the output power of the distribution system, PloadFor the total load of the power distribution system,
Figure BDA0002255482270000022
the typical time of day t for the s season of the last year for the target power distribution system is the load
Figure BDA0002255482270000023
Is an important load at the typical time t of s season in the past year in the bottom-protected power grid.
Preferably, in step S1:
Fc＝CC+COM
in the formula, CCAs an initial investment cost index, COMIs an index of operation and maintenance cost;
Figure BDA0002255482270000024
in the formula (I), the compound is shown in the specification,
Figure BDA0002255482270000025
for the unit investment cost of the photovoltaic unit,
Figure BDA0002255482270000026
is the unit investment cost of the wind generating set,in order to realize the unit investment cost of the synchronous generator set,
Figure BDA0002255482270000028
for the unit investment cost of the energy storage battery,
Figure BDA0002255482270000029
is the installed capacity of the photovoltaic power generation,is the installed capacity of the wind turbine generator,in order to be the installed capacity of the gas turbine,
Figure BDA0002255482270000032
the installed capacity of the energy storage device;
Figure BDA0002255482270000033
wherein N is the configuration life,
Figure BDA0002255482270000034
for the unit operation and maintenance cost of the photovoltaic unit,
Figure BDA0002255482270000035
for the unit operation and maintenance cost of the wind generating set,
Figure BDA0002255482270000036
in order to synchronize the unit operation and maintenance cost of the generator set,
Figure BDA0002255482270000037
for the daily discharge of the energy storage battery on the s-th typical day,
Figure BDA0002255482270000038
the unit operation and maintenance cost of the energy storage battery on the s typical day.
Preferably, in step S2, the constraint conditions of the power capacity optimization configuration model include a maximum installed capacity constraint of the distributed power supply, a distributed power supply output constraint, an energy storage charging and discharging constraint, a grid-connected node voltage constraint, a power balance constraint, and a micro-grid and bottom-guaranteed grid power exchange constraint, where:
the maximum installed capacity constraint of the distributed power supply comprises the following steps:
Figure BDA0002255482270000039
Figure BDA00022554822700000310
Nwtand NpvGetting the whole;
in the formula, NwtThe number of the wind driven generators in the target area, d is the diameter of the wind wheel of the wind driven generatorL is the target region length, W is the target region width, NpvThe number of solar panels in the target area, SpvAnd SesRespectively the floor area of the photovoltaic cell and the energy storage device;
distributed power output constraints include:
Figure BDA00022554822700000311
in the formula (I), the compound is shown in the specification,
Figure BDA00022554822700000312
is the installed capacity of the photovoltaic power generation,
Figure BDA00022554822700000313
is the installed capacity of the wind turbine generator,
Figure BDA00022554822700000314
in order to be the installed capacity of the gas turbine,
Figure BDA00022554822700000315
the installed capacity of the energy storage device;
the power balance constraints include:
Figure BDA0002255482270000041
in the formula (I), the compound is shown in the specification,
Figure BDA0002255482270000042
load in the microgrid at time t, NrAs for the kind of the new energy generator,for the power of the r-th new energy generator at the moment t,
Figure BDA0002255482270000044
for preserving the load in the grid at time t in a typical day of the s-th season,
Figure BDA0002255482270000045
the power transmitted from the microgrid to the bottom-protected power grid at the moment t;
the micro-grid and guaranteed-base power grid power exchange constraints comprise:
Figure BDA0002255482270000046
in the formula (I), the compound is shown in the specification,
Figure BDA0002255482270000047
and
Figure BDA0002255482270000048
the maximum power and the minimum power which are allowed to be exchanged by the micro-grid and the bottom-guaranteed grid respectively;
grid-connected node voltage constraints include:
Ui,min≤Ui≤Ui,max
in the formula of Ui,maxAnd Ui,minRespectively the upper limit and the lower limit, U, of the voltage amplitude of the grid-connected node i of the micro-gridiThe voltage amplitude of a microgrid grid-connected node i is obtained;
the energy storage charge-discharge constraint comprises:
Figure BDA0002255482270000049
wherein:
Figure BDA00022554822700000410
and
Figure BDA00022554822700000411
respectively, the maximum capacity and the minimum remaining capacity of stored energy;
Figure BDA00022554822700000412
the residual capacity of energy storage at the moment t;and
Figure BDA00022554822700000414
the charging and discharging power at time t.
Preferably, in step S3,
the indices were normalized according to the following formula:
Figure BDA00022554822700000415
Figure BDA00022554822700000416
the evaluation indexes are compared in pairs, and a judgment matrix U is derived as (U)ji)n×nWherein u isjiAs an evaluation index siAnd sjThe value of the numerical value obtained by comparison is an odd number between 1 and 9, and the numerical value is respectively expressed as the same important, more important, very important and absolutely important index of the former index and the latter index; when the value is an even number between 1 and 9, the importance degree of the two-two comparison of the indexes is between two adjacent odd numbers.
When the index siAnd sjWhen making a comparison, assume siIs 1, then sjIs uji. Assuming that the sum of the j-th column elements of the matrix U is Σ j, then
Figure BDA0002255482270000051
Is the index sjRelative importance of.
Based on
Figure BDA0002255482270000052
After the weight corresponding to each evaluation index is calculated, the sum of the two indexes multiplied by the respective weight is the minimum, and the installed capacity of the wind turbine generator set in the microgrid is solved through a genetic algorithm
Figure BDA0002255482270000053
Installed capacity of photovoltaic unit
Figure BDA0002255482270000054
Installed capacity of synchronous generator setAnd installed capacity of energy storage battery
Figure BDA0002255482270000056
In summary, the invention provides a power capacity configuration method for improving the emergency capacity of a micro-grid in a bottom-protected power grid, which is used for solving the problem of insufficient efficiency of the bottom-protected power grid caused by too single guarantee power supply in the construction of the existing bottom-protected power grid network frame. On the basis of the existing optimal configuration method of the power supply capacity of the microgrid, the different supporting capacities of different power supply configurations on the bottom-guaranteed power grid are considered, the operation principle of the microgrid and the operation mode of the microgrid in the bottom-guaranteed power grid are analyzed and compared, the influence factors of the emergency supporting capacity of the microgrid are considered, the supporting capacity of the microgrid is reflected by the maximum load shortage rate, meanwhile, the construction and operation cost of the microgrid are considered, and the objective function of the optimal configuration of the power supply capacity of the microgrid is constructed. The method has the advantages that constraint conditions such as maximum installed capacity constraint of the distributed power supply, output constraint of the distributed power supply, energy storage charging and discharging constraint, power balance constraint, power exchange constraint of the micro-grid and the bottom-protected grid and the like are considered, a configuration scheme of the power supply capacity of the micro-grid is obtained by adopting a genetic algorithm, effective emergency support can be provided for the bottom-protected grid by the micro-grid in the bottom-protected grid, and stable operation of important loads in the bottom-protected grid is guaranteed.
Drawings
For purposes of promoting a better understanding of the objects, aspects and advantages of the invention, reference will now be made in detail to the present invention as illustrated in the accompanying drawings, in which:
FIG. 1 is a flow chart of an embodiment of a method for configuring power capacity to improve emergency capability of a microgrid in a guaranteed-base power grid according to the present invention;
fig. 2 is a flowchart of a microgrid operation mode considering a guaranteed operation.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
As shown in fig. 1 and 2, the present invention discloses a power capacity configuration method for improving the emergency capability of a microgrid in a guaranteed-base power grid, which is applied to a power distribution system including the microgrid, and comprises the following steps:
s1, establishing a base-guaranteed power grid maximum load power shortage rate index FlpsAnd the economic index F of the micro-gridcA power supply capacity optimal configuration model with the minimum as a target;
establishing a maximum load power shortage rate index F of the bottom-protected power grid according to important load in the bottom-protected power grid and the micro-grid and the capacity of the existing guaranteed power supply in the bottom-protected power gridlps(ii) a Establishing an economic index F of the microgrid according to initial investment cost and operation maintenance cost of the stored energy and unit capacity of each distributed power supplyc。
S2, constructing constraint conditions of a power supply capacity optimization configuration model;
s3, acquiring target power distribution system information, inputting the target power distribution system information into a power capacity optimization configuration model, and solving the power capacity optimization configuration model of the target based on the constraint condition of the power capacity optimization configuration model to obtain power capacity configuration information;
the target power distribution system information includes: and (3) setting the rated capacity of a wind driven generator, a solar battery, a gas turbine and an energy storage battery selected from the micro-grid on a site with the area of S, the length of L and the width of W. The load of the target distribution system in each season of the past year is typical day
Figure BDA0002255482270000061
The important load of each season typical day in the past year in the bottom-protected power grid is
Figure BDA0002255482270000062
Guarantee the capacity of the power supply in the bottom-protected power grid as
Figure BDA0002255482270000063
In the invention, a day is selected from each season as a typical day, and then the load condition of the typical day is used for representing the load condition of each day in the whole season.
And S4, configuring the power capacity based on the power capacity configuration information.
The invention is used for solving the problem of insufficient bottom-protecting power grid efficiency caused by too single guarantee power supply in the construction of the existing bottom-protecting power grid network frame. On the basis of the existing method for optimizing and configuring the power supply capacity of the microgrid, the method considers that different power supply configurations have different supporting capacities on the bottom-guaranteed power grid, analyzes and compares the operation principle of the microgrid and the operation mode of the microgrid in the bottom-guaranteed power grid, considers the influence factors of the emergency supporting capacity of the microgrid, reflects the supporting capacity of the microgrid according to the maximum load power shortage rate, and simultaneously considers the construction and operation costs of the microgrid, thereby constructing the objective function of optimizing and configuring the power supply capacity of the microgrid. The method has the advantages that constraint conditions such as maximum installed capacity constraint of the distributed power supply, output constraint of the distributed power supply, energy storage charging and discharging constraint, power balance constraint, power exchange constraint of the micro-grid and the bottom-protected grid and the like are considered, a configuration scheme of the power supply capacity of the micro-grid is obtained by adopting a genetic algorithm, effective emergency support can be provided for the bottom-protected grid by the micro-grid in the bottom-protected grid, and stable operation of important loads in the bottom-protected grid is guaranteed.
In the specific implementation, in step S1:
Figure BDA0002255482270000064
in the formula, PoutFor the output power of the distribution system, PloadFor the total load of the power distribution system,
Figure BDA0002255482270000065
the typical time of day t for the s season of the last year for the target power distribution system is the load
Figure BDA0002255482270000066
Is an important load at the typical time t of s season in the past year in the bottom-protected power grid.
Under the bad weather condition, distributed power supplies such as wind power and photovoltaic can not generate electricity effectively, the synchronous generator and the energy storage support the stable operation of the load in the system by the maximum power discharge, if the load in the system reaches the maximum value at the moment, the load power shortage of the system also reaches the maximum value, and the expression is as follows:
Figure BDA0002255482270000071
in the formula (I), the compound is shown in the specification,
Figure BDA0002255482270000072
in order to guarantee the maximum power of the power supply in the power grid,
Figure BDA0002255482270000073
for the maximum load in the micro grid,
Figure BDA0002255482270000074
to preserve the maximum load in the grid.
In the specific implementation, in step S1:
Fc＝CC+COM
in the formula, CCAs an initial investment cost index, COMIs an index of operation and maintenance cost;
in the formula (I), the compound is shown in the specification,for the unit investment cost of the photovoltaic unit,
Figure BDA0002255482270000077
is the unit investment cost of the wind generating set,
Figure BDA0002255482270000078
in order to realize the unit investment cost of the synchronous generator set,
Figure BDA0002255482270000079
for the unit investment cost of the energy storage battery,
Figure BDA00022554822700000710
is the installed capacity of the photovoltaic power generation,
Figure BDA00022554822700000711
is the installed capacity of the wind turbine generator,
Figure BDA00022554822700000712
in order to be the installed capacity of the gas turbine,
Figure BDA00022554822700000713
the installed capacity of the energy storage device;
Figure BDA00022554822700000714
wherein N is the configuration life,
Figure BDA00022554822700000715
for the unit operation and maintenance cost of the photovoltaic unit,
Figure BDA00022554822700000716
for the unit operation and maintenance cost of the wind generating set,in order to synchronize the unit operation and maintenance cost of the generator set,
Figure BDA00022554822700000718
for the daily discharge of the energy storage battery on the s-th typical day,
Figure BDA00022554822700000719
the unit operation and maintenance cost of the energy storage battery on the s typical day.
In specific implementation, in step S2, the constraint conditions of the power capacity optimization configuration model include a maximum installed capacity constraint of the distributed power supply, a distributed power supply output constraint, an energy storage charging and discharging constraint, a grid-connected node voltage constraint, a power balance constraint, and a micro-grid and bottom-guaranteed grid power exchange constraint, where:
the maximum installed capacity constraint of the distributed power supply comprises the following steps:
Figure BDA00022554822700000720
Figure BDA00022554822700000721
Nwtand NpvGetting the whole;
in the formula, NwtThe number of the wind driven generators in the target area, d is the diameter of a wind wheel of the wind driven generator, L is the length of the target area, W is the width of the target area, NpvThe number of solar panels in the target area, SpvAnd SesRespectively the floor area of the photovoltaic cell and the energy storage device;
distributed power output constraints include:
in the formula (I), the compound is shown in the specification,is the installed capacity of the photovoltaic power generation,
Figure BDA0002255482270000083
is the installed capacity of the wind turbine generator,
Figure BDA0002255482270000084
in order to be the installed capacity of the gas turbine,the installed capacity of the energy storage device;
the power balance constraints include:
in the formula (I), the compound is shown in the specification,
Figure BDA0002255482270000087
load in the microgrid at time t, NrAs for the kind of the new energy generator,
Figure BDA0002255482270000088
for the power of the r-th new energy generator at the moment t,
Figure BDA0002255482270000089
for preserving the load in the grid at time t in a typical day of the s-th season,
Figure BDA00022554822700000810
the power transmitted from the microgrid to the bottom-protected power grid at the moment t;
the micro-grid and guaranteed-base power grid power exchange constraints comprise:
in the formula (I), the compound is shown in the specification,and
Figure BDA00022554822700000813
the maximum power and the minimum power which are allowed to be exchanged by the micro-grid and the bottom-guaranteed grid respectively;
grid-connected node voltage constraints include:
Ui,min≤Ui≤Ui,max
in the formula of Ui,maxAnd Ui,minRespectively the upper limit and the lower limit, U, of the voltage amplitude of the grid-connected node i of the micro-gridiThe voltage amplitude of a microgrid grid-connected node i is obtained;
the energy storage charge-discharge constraint comprises:
Figure BDA0002255482270000091
wherein:
Figure BDA0002255482270000092
and
Figure BDA0002255482270000093
respectively, the maximum capacity and the minimum remaining capacity of stored energy;
Figure BDA0002255482270000094
the residual capacity of energy storage at the moment t;
Figure BDA0002255482270000095
and
Figure BDA0002255482270000096
the charging and discharging power at time t.
In the specific implementation, in step S3,
the indices were normalized according to the following formula:
Figure BDA0002255482270000098
the evaluation indexes are compared in pairs, and a judgment matrix U is derived as (U)ji)n×nWherein u isjiAs an evaluation index siAnd sjThe value of the numerical value obtained by comparison is an odd number between 1 and 9, and the numerical value is respectively expressed as the same important, more important, very important and absolutely important index of the former index and the latter index; when the value is an even number between 1 and 9, the importance degree of the two-two comparison of the indexes is between two adjacent odd numbers.
When the index siAnd sjWhen making a comparison, assume siIs heavyTo an extent of 1, then sjIs uji. Assuming that the sum of the j-th column elements of the matrix U is Σ j, then
Figure BDA0002255482270000099
Is the index sjRelative importance of.
Based on
Figure BDA00022554822700000910
After the weight corresponding to each evaluation index is calculated, the sum of the two indexes multiplied by the respective weight is the minimum, and the installed capacity of the wind turbine generator set in the microgrid is solved through a genetic algorithm
Figure BDA00022554822700000911
Installed capacity of photovoltaic unit
Figure BDA00022554822700000912
Installed capacity of synchronous generator setAnd installed capacity of energy storage battery
Figure BDA00022554822700000914
The solution by genetic algorithm is prior art and will not be described in detail herein.
The invention considers the complex matching relation of each distributed power supply, energy storage, energy resources in coastal areas and important loads in the bottom-guaranteed power grid in the micro-grid, adopts the maximum load power shortage index to reflect the emergency supporting capacity of the micro-grid to the bottom-guaranteed power grid on the basis of analyzing the power characteristics of each power supply, simultaneously considers the construction and operation cost of the micro-grid, and optimizes the installed capacities of different distributed power supplies in the micro-grid to ensure that the emergency supporting capacity and the construction cost of the micro-grid are optimal. Compared with the traditional microgrid power supply optimal configuration method, the optimized microgrid capacity configuration scheme ensures that the microgrid can effectively and actively support important loads in a bottom-guaranteed power grid after ensuring the load power supply of the region of the microgrid, ensures the power supply reliability of the loads and saves the economic cost.
Finally, it is noted that the above-mentioned embodiments illustrate rather than limit the invention, and that, while the invention has been described with reference to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (5)

1. A power supply capacity configuration method for improving the emergency capacity of a microgrid in a guaranteed-base power grid is characterized in that the method is applied to a power distribution system comprising the microgrid, and comprises the following steps:
s1, establishing a base-guaranteed power grid maximum load power shortage rate index FlpsAnd the economic index F of the micro-gridcA power supply capacity optimal configuration model with the minimum as a target;
s2, constructing constraint conditions of a power supply capacity optimization configuration model;
s3, acquiring target power distribution system information, inputting the target power distribution system information into a power capacity optimization configuration model, and solving the power capacity optimization configuration model of the target based on the constraint condition of the power capacity optimization configuration model to obtain power capacity configuration information;
and S4, configuring the power capacity based on the power capacity configuration information.
2. The method according to claim 1, wherein in step S1:
Figure FDA0002255482260000011
in the formula, PoutFor the output power of the distribution system, PloadFor the total load of the power distribution system,
Figure FDA0002255482260000012
Figure FDA0002255482260000013
for loads at time t of a typical day of the s-season of the last year of the target power distribution system,
Figure FDA0002255482260000014
is an important load at the typical time t of s season in the past year in the bottom-protected power grid.
3. The method according to claim 1, wherein in step S1:
Fc＝CC+COM
in the formula, CCAs an initial investment cost index, COMIs an index of operation and maintenance cost;
Figure FDA0002255482260000015
in the formula (I), the compound is shown in the specification,
Figure FDA0002255482260000016
for the unit investment cost of the photovoltaic unit,
Figure FDA0002255482260000017
is the unit investment cost of the wind generating set,
Figure FDA0002255482260000018
in order to realize the unit investment cost of the synchronous generator set,
Figure FDA0002255482260000019
for the unit investment cost of the energy storage battery,
Figure FDA00022554822600000110
for photovoltaic installationsThe capacity of the electric power transmission device is,
Figure FDA00022554822600000111
is the installed capacity of the wind turbine generator,
Figure FDA00022554822600000112
in order to be the installed capacity of the gas turbine,
Figure FDA00022554822600000113
the installed capacity of the energy storage device;
Figure FDA00022554822600000114
wherein N is the configuration life,
Figure FDA00022554822600000115
for the unit operation and maintenance cost of the photovoltaic unit,
Figure FDA00022554822600000116
for the unit operation and maintenance cost of the wind generating set,
Figure FDA00022554822600000117
in order to synchronize the unit operation and maintenance cost of the generator set,for the daily discharge of the energy storage battery on the s-th typical day,
Figure FDA0002255482260000021
the unit operation and maintenance cost of the energy storage battery on the s typical day.
4. The power capacity configuration method for improving the emergency capability of the microgrid in the guaranteed-base power grid according to claim 1, wherein in step S2, the constraint conditions of the power capacity optimization configuration model include a maximum installed capacity constraint of a distributed power supply, a distributed power supply output constraint, an energy storage charge and discharge constraint, a grid-connected node voltage constraint, a power balance constraint and a microgrid-guaranteed-base power grid power exchange constraint, wherein:
the maximum installed capacity constraint of the distributed power supply comprises the following steps:
Figure FDA0002255482260000022
Nwtand NpvGetting the whole;
in the formula, NwtThe number of the wind driven generators in the target area, d is the diameter of a wind wheel of the wind driven generator, L is the length of the target area, W is the width of the target area, NpvThe number of solar panels in the target area, SpvAnd SesRespectively the floor area of the photovoltaic cell and the energy storage device;
distributed power output constraints include:
Figure FDA0002255482260000024
in the formula (I), the compound is shown in the specification,is the installed capacity of the photovoltaic power generation,
Figure FDA0002255482260000026
is the installed capacity of the wind turbine generator,
Figure FDA0002255482260000027
in order to be the installed capacity of the gas turbine,
Figure FDA0002255482260000028
the installed capacity of the energy storage device;
the power balance constraints include:
Figure FDA0002255482260000029
in the formula (I), the compound is shown in the specification,
Figure FDA00022554822600000210
load in the microgrid at time t, NrAs for the kind of the new energy generator,
Figure FDA00022554822600000211
for the power of the r-th new energy generator at the moment t,
Figure FDA00022554822600000212
for preserving the load in the grid at time t in a typical day of the s-th season,
Figure FDA00022554822600000213
the power transmitted from the microgrid to the bottom-protected power grid at the moment t;
the micro-grid and guaranteed-base power grid power exchange constraints comprise:
Figure FDA0002255482260000031
in the formula (I), the compound is shown in the specification,
Figure FDA0002255482260000032
and
Figure FDA0002255482260000033
the maximum power and the minimum power which are allowed to be exchanged by the micro-grid and the bottom-guaranteed grid respectively;
grid-connected node voltage constraints include:
Ui,min≤Ui≤Ui,max
in the formula of Ui,maxAnd Ui,minRespectively the upper limit and the lower limit of the voltage amplitude of the grid-connected node i of the micro-grid，UiThe voltage amplitude of a microgrid grid-connected node i is obtained;
the energy storage charge-discharge constraint comprises:
Figure FDA0002255482260000034
wherein:
Figure FDA0002255482260000035
and
Figure FDA0002255482260000036
respectively, the maximum capacity and the minimum remaining capacity of stored energy;
Figure FDA0002255482260000037
the residual capacity of energy storage at the moment t;
Figure FDA0002255482260000038
and
Figure FDA0002255482260000039
the charging and discharging power at time t.
5. The method according to claim 1, wherein in step S3,
the indices were normalized according to the following formula:
Figure FDA00022554822600000310
the evaluation indexes are compared in pairs, and a judgment matrix U is derived as (U)ji)n×nWherein u isjiAs an evaluation index siAnd sjComparing the obtained numbersThe value is an odd number between 1 and 9 and respectively represents that the former index and the latter index are equally important, more important, very important and absolutely important; when the value is an even number between 1 and 9, the importance degree of the two-two comparison of the indexes is between two adjacent odd numbers;
when the index siAnd sjWhen making a comparison, assume siIs 1, then sjIs uji. Assuming that the sum of the j-th column elements of the matrix U is Σ j, thenThe relative importance degree of the index sj is obtained;
based on
Figure FDA00022554822600000313
After the weight corresponding to each evaluation index is calculated, the sum of the two indexes multiplied by the respective weight is the minimum, and the installed capacity of the wind turbine generator set in the microgrid is solved through a genetic algorithm
Figure FDA0002255482260000041
Installed capacity of photovoltaic unit
Figure FDA0002255482260000042
Installed capacity of synchronous generator set
Figure FDA0002255482260000043
And installed capacity of energy storage battery
Figure FDA0002255482260000044
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