CN114123169A - A fault recovery method for distribution network based on energy storage flexible switch - Google Patents

A fault recovery method for distribution network based on energy storage flexible switch Download PDF

Info

Publication number
CN114123169A
CN114123169A CN202111338641.4A CN202111338641A CN114123169A CN 114123169 A CN114123169 A CN 114123169A CN 202111338641 A CN202111338641 A CN 202111338641A CN 114123169 A CN114123169 A CN 114123169A
Authority
CN
China
Prior art keywords
energy storage
power
flexible switch
storage type
type flexible
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202111338641.4A
Other languages
Chinese (zh)
Other versions
CN114123169B (en
Inventor
康朋
周平
张朝华
张骏
谭昊
叶樊
张可
张林俊
周念成
陶安琪
罗永捷
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Chongqing Electric Power Design Institute Co ltd
Chongqing University
State Grid Corp of China SGCC
Original Assignee
Chongqing Electric Power Design Institute Co ltd
Chongqing University
State Grid Corp of China SGCC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Chongqing Electric Power Design Institute Co ltd, Chongqing University, State Grid Corp of China SGCC filed Critical Chongqing Electric Power Design Institute Co ltd
Priority to CN202111338641.4A priority Critical patent/CN114123169B/en
Publication of CN114123169A publication Critical patent/CN114123169A/en
Application granted granted Critical
Publication of CN114123169B publication Critical patent/CN114123169B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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
    • H02J3/001—Methods to deal with contingencies, e.g. abnormalities, faults or failures
    • 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
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • 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
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

本发明公开了一种基于储能型柔性开关的配电网故障恢复方法，包括：S1，根据配电区所在区域的山体滑坡灾害历史数据，评估损坏风险并确定储能型柔性开关安装位置；S2，计算并根据所述储能型柔性开关的蓄电池年循环寿命和寿命成本，以电能的储存和释放平滑功率波动、减小负荷需求不确定性，确定所述储能型柔性开关的控制策略；S3，以最小化投运成本为目标，计算并输出分布式电源功率输出值和使储能型柔性开关使用寿命最长的容量值。通过山评估山体滑坡损坏风险确定储能型柔性开关安装位置体，计算蓄电池年循环寿命和寿命成本，确定使用方式，最后结合分布式电源以最小化投运成本进行控制输出，提高了供电恢复效率和供电质量。

Figure 202111338641

The invention discloses a distribution network fault recovery method based on an energy storage type flexible switch. S2, calculate and determine the control strategy of the energy storage type flexible switch according to the battery annual cycle life and life cost of the energy storage type flexible switch to smooth the power fluctuation and reduce the load demand uncertainty by the storage and release of electric energy ; S3, with the goal of minimizing the cost of operation, calculate and output the power output value of the distributed power supply and the capacity value that maximizes the service life of the energy storage flexible switch. Determine the installation location of the energy storage flexible switch by evaluating the risk of landslide damage, calculate the battery's annual cycle life and life cost, determine the use method, and finally combine the distributed power source to minimize the operation cost to control the output, which improves the power supply recovery efficiency. and power quality.

Figure 202111338641

Description

Power distribution network fault recovery method based on energy storage type flexible switch
Technical Field
The invention relates to the technical field of power distribution fault recovery, in particular to a power distribution network fault recovery method based on an energy storage type flexible switch.
Background
Because the existing energy sources for factories and families mainly depend on power supply, the safe and reliable operation of the power distribution network is the foundation for guaranteeing the normal operation of the society. Once the power distribution network fails, a power failure accident can be caused, economic losses of users and power supply companies are caused, and therefore the power supply recovery capability of the power distribution network is very important to the power supply reliability.
The traditional power distribution network power supply recovery is mainly realized through distributed power supplies such as wind power and photovoltaic and a relay protection device, but after an extreme natural event occurs, the fluctuation of new energy causes that a fault station area cannot be reliably supplied with power, the relay protection device is slow in response action, and unnecessary loss is caused by cutting off loads near fault points.
There is therefore a need for a flexible and efficient fault recovery method to ensure safe operation of a power distribution network.
Disclosure of Invention
The invention aims to provide a power distribution network fault recovery method based on an energy storage type flexible switch, which improves the fault recovery efficiency and the power supply quality of a power distribution network.
In order to solve the technical problem, an embodiment of the present invention provides a power distribution network fault recovery method based on an energy storage type flexible switch, including:
s1, evaluating the landslide damage risk and determining the installation position of the energy storage type flexible switch according to the landslide disaster historical data of the area where the power distribution area is located;
s2, calculating and determining a control strategy of the energy storage type flexible switch according to the annual cycle life and the life cost of a storage battery of the energy storage type flexible switch, the storage and release of electric energy smooth power fluctuation and load demand uncertainty reduction;
and S3, calculating and outputting a distributed power supply power output value and a capacity value which enables the service life of the energy storage type flexible switch to be longest with the aim of minimizing the operation cost.
Wherein the S1 includes:
obtaining a monotonic function m representing the hazard intensity of each distribution area from the mountain landslide historical data of the distribution area based on a regression methodiThe mountain landslide historical data comprise geographic positions, soil types and geological features;
determining corresponding hazard weight omega according to economic loss of post-disaster power distribution areaiAnd calculating and obtaining a landslide damage risk index SlComprises the following steps:
Figure BDA0003351502280000021
wherein ilIs the number of cells, nlThe total number of the transformer areas;
to SlNormalized to a value of 0,1]Interval, SlThe larger the damage caused by landslide is;
set as SlWhen the risk is larger than the set risk threshold value, the damage risk of landslide is high, and the energy storage type flexible switch needs to be installed to recover power supply after disaster.
Wherein the S1 includes:
according to historical landslide disaster data and geological information of the area where the power distribution area is located, the landslide probability under different slopes and different soil conditions is obtained through calculation, a monotonic function of damage strength is obtained through fitting based on a regression method, a landslide damage risk index is obtained according to post-disaster cost loss, and the installation position of the energy storage type soft switch is determined.
Wherein the S1 further includes:
setting the risk threshold.
Wherein the S2 includes:
calculating and establishing the energy storage type flexible switch control model according to the charge-discharge cycle process of the energy storage type flexible switch, the discharge depth at the moment before charging, the battery cycle life and the equivalent full cycle times which are established according to the energy storage life and are converted into the discharge cycles of different depths and are under the 100% discharge depth:
calculating the annual cycle life T of the storage battery according to the energy storage type flexible switch control modeli,cycAnd life cost Ci,ES。
Wherein the S2 includes:
the charge-discharge cycle process is that one charge-discharge cycle occurs at the moment when the energy storage type flexible switch is changed from the discharge process to the charge process:
Figure BDA0003351502280000031
wherein
Figure BDA0003351502280000032
Is a variable of 0 to 1When the energy storage state is from charging to discharging,
Figure BDA0003351502280000033
in other cases
Figure BDA0003351502280000034
The depth of discharge at the moment before charging is taken as the depth of discharge at the moment before charging
Figure BDA0003351502280000035
Representing the cyclic discharge depth of the accumulator
Figure BDA0003351502280000036
Figure BDA0003351502280000037
Figure BDA0003351502280000038
Calculating the battery cycle life
Figure BDA0003351502280000039
The method comprises the following steps:
Figure BDA00033515022800000310
wherein N is0The number of cycles, k, at which the battery reaches the end of its life with 100% deep charge-dischargepThe values of the curve fitting parameters are between 1.1 and 2.1;
calculating the equivalent full cycle times by converting the discharge cycle with the energy storage life established at different depths into the equivalent full cycle times under 100% of the discharge depth, wherein the daily equivalent full cycle times is Ni,eq：
Figure BDA00033515022800000311
Wherein S is the number of clustered scenes;
calculating the annual cycle life T of the storage batteryi,cycAnd life cost Ci,ESIs composed of
Ti,cyc＝N0/(365·Ni,eq) (7)，
Figure BDA0003351502280000041
Wherein, Ci,inv,ESFor the storage battery investment cost without considering the battery life, r is the discount rate.
Wherein the S3 includes:
s31, calculating and controlling a linear target function and constraint conditions through a convex relaxation or large M method, and ensuring that the power output and energy storage type flexible switch configuration range can enable the model to have a feasible solution;
and S32, controlling the distributed power supply and the energy storage type soft switch to recover power supply to the disaster area, and obtaining the minimum distributed power supply output condition and energy storage type soft switch capacity input which can meet the fault recovery by minimizing the operation cost of the fault recovery equipment.
Wherein the S32 includes:
according to the condition that the operation cost of the power supply equipment meeting the post-disaster power supply requirement is minimum, calculating an objective function as follows:
Figure BDA0003351502280000042
Figure BDA0003351502280000043
wherein c isDG，cp，cDCThe investment costs of unit power of the distributed power supply, the converter and the DC-DC converter are respectively saved; r is the discount rate; pDG,tIs divided intoActive power output of the distributed power supply; pL,tPower is lost for operation;
Figure BDA0003351502280000044
power is lost for the line;
Figure BDA0003351502280000045
the two converters are respectively an energy storage type soft switch;
Figure BDA0003351502280000051
is a DC-DC converter power loss; x is the number ofi,xj,yiPlanning capacities of a VSC and a DC-DC at the i, j nodes of the intelligent energy storage soft switch are respectively set; omegal、ΩSOP-ES、ΩESThe system comprises a circuit, the energy storage type soft switch and the storage battery node set, and needs to meet a power balance equation, energy storage charge-discharge constraints, storage battery electric energy time sequence equations, storage battery scheduling period charge state equations, power flow equations, distributed power supply power constraints and power grid operation safety constraints.
Compared with the prior art, the power distribution network fault recovery method based on the energy storage type flexible switch provided by the embodiment of the invention has the following advantages:
according to the power distribution network fault recovery method based on the energy storage type flexible switch, the installation position body of the energy storage type flexible switch is determined by mountain evaluation of landslide damage risks, the annual cycle life and the life cost of a storage battery are calculated, the use mode is determined, and finally the distributed power supply is combined to minimize the commissioning cost to control output, so that the power supply recovery efficiency and the power supply quality are improved, and the fault recovery efficiency and the power supply quality of a power distribution network are improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a schematic step flow diagram of a method for recovering a power distribution network fault based on an energy storage type flexible switch according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of the step S3 in an embodiment of the method for recovering a fault of a power distribution network based on an energy storage type flexible switch according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, fig. 1 is a schematic flowchart illustrating a process of a power distribution network fault recovery method based on an energy storage type flexible switch according to an embodiment of the present invention; fig. 2 is a schematic flowchart of the step S3 in an embodiment of the method for recovering a fault of a power distribution network based on an energy storage type flexible switch according to the present invention.
In a specific embodiment, the method for recovering the fault of the power distribution network based on the energy storage type flexible switch comprises the following steps:
s1, evaluating the landslide damage risk and determining the installation position of the energy storage type flexible switch according to the landslide disaster historical data of the area where the power distribution area is located;
s2, calculating and determining a control strategy of the energy storage type flexible switch according to the annual cycle life and the life cost of a storage battery of the energy storage type flexible switch, the storage and release of electric energy smooth power fluctuation and load demand uncertainty reduction;
and S3, calculating and outputting a distributed power supply power output value and a capacity value which enables the service life of the energy storage type flexible switch to be longest with the aim of minimizing the operation cost.
The mounting position of the energy storage type flexible switch is determined by evaluating the landslide damage risk of the mountain, the annual cycle life and the service life cost of the storage battery are calculated, the use mode is determined, and finally the output is controlled by combining a distributed power supply with the minimized commissioning cost, so that the power supply recovery efficiency and the power supply quality are improved, and the fault recovery efficiency and the power supply quality of the power distribution network are improved.
In this application, first, the risk of landslide damage according to the evaluation is obtained and the installation position of the energy storage type flexible switch is determined, and the evaluation process is not limited, in an embodiment, the S1 includes:
obtaining a monotonic function m representing the hazard intensity of each distribution area from the mountain landslide historical data of the distribution area based on a regression methodiThe mountain landslide historical data comprise geographic positions, soil types and geological features;
determining corresponding hazard weight omega according to economic loss of post-disaster power distribution areaiAnd calculating and obtaining a landslide damage risk index SlComprises the following steps:
Figure BDA0003351502280000071
wherein ilIs the number of cells, nlThe total number of the transformer areas;
to SlNormalized to a value of 0,1]Interval, SlThe larger the damage caused by landslide is;
set as SlWhen the risk is larger than the set risk threshold value, the damage risk of landslide is high, and the energy storage type flexible switch needs to be installed to recover power supply after disaster.
The application includes, but is not limited to, obtaining a monotonic function m representing the hazard intensity of each station zone by using a regression methodiBesides the geographic position, the soil type and the geological characteristics, the mountain landslide historical data can also be characterized by other characteristics, and a person skilled in the art can reasonably select different types of characteristic data according to the influence of calculation precision, weight and the like, wherein the different types of characteristic data can be caused by rainfall in different areas,Earthquakes and the like all change the possibility of landslide. For example, the weight of the soil type is different in different regions according to historical data, as shown in the south, although the soil type is the same in the mountain, the rainfall in some regions is less, and the rainfall in some regions is more. In addition, in some areas, the temperature difference between day and night is poor, and the mountain landslide is easily caused by serious expansion and contraction, or other factors and the like, and the application does not limit the temperature difference.
It should be noted that, in the feature selection and weight selection for affecting landslide in the present application, it may be determined that the setting is performed according to preset parameters and types, or the setting may be performed in a dynamic manner, for example, an address structure of the region is input in advance, and then the dynamic adjustment of the weights for different features is implemented in combination with future meteorological conditions, such as temperature, wind power, rainfall, and the like, or after a device failure occurs, the parameters are adjusted according to the maintenance condition and difficulty of the device, and the like, so that the difference between the parameters and the actual condition becomes smaller. If after a landslide occurs, the power gray scale is carried out, the difficulty is found to be far greater than the expected difficulty, and the power quality is difficult to achieve the expected value after the power recovery, so that the possibility of the landslide occurring in the area can be properly improved, and the power recovery strategy is changed. Alternatively, the ability to withstand a disaster such as landslide is improved due to the improvement of the restoration ability by the update of the power equipment itself, and the threshold value may be appropriately increased or decreased due to the deterioration of the equipment.
Specifically, the S1 includes:
according to historical landslide disaster data and geological information of the area where the power distribution area is located, the landslide probability under different slopes and different soil conditions is obtained through calculation, a monotonic function of damage strength is obtained through fitting based on a regression method, a landslide damage risk index is obtained according to post-disaster cost loss, and the installation position of the energy storage type soft switch is determined.
In order to implement the above dynamic optimization configuration and achieve the optimal power supply effect, in one embodiment, the S1 further includes:
setting the risk threshold.
It should be noted that the setting of the risk threshold may be manually adjusted or may be automatically adjusted by the system. The manual adjustment is that a worker inputs the risk threshold value through a control panel or a remote input mode, the automatic adjustment is that the whole control system automatically evaluates the risk threshold value based on the conditions of maintenance times, service life and the like of equipment to generate the risk threshold value, and the setting mode of the risk threshold value is not limited in the application.
The lowest-cost use is realized by calculating the energy storage capacity, the effect, the service life and the like of the energy storage type flexible switch, and specific parameter calculation is not limited.
The voltage source converter in the energy storage type flexible switch can flexibly transmit active power flow and adjust reactive power, and after a part of power supply stations in a transformer area are damaged due to landslide, other distributed power sources in the transformer area are called to recover power supply of the transformer area in a disaster.
And in the energy storage link, the load demand uncertainty is reduced through smooth power fluctuation of electric energy storage and release, and when the distributed power supplies in other transformer areas are new energy with large output fluctuation, the energy storage link can adjust the fluctuation to ensure the power supply recovery quality.
The traditional soft switch containing energy storage only meets the power balance equation, energy storage charge state constraint, charge and discharge power constraint and the like, and can possibly cause over-discharge of the storage battery, reduce the service life of the battery and increase the investment cost of the structure.
Therefore, there is a need in the present application to solve the above-mentioned problems and reduce the use cost, and in one embodiment, the S2 includes:
calculating and establishing the energy storage type flexible switch control model according to the charge-discharge cycle process of the energy storage type flexible switch, the discharge depth at the moment before charging, the battery cycle life and the equivalent full cycle times which are established according to the energy storage life and are converted into the discharge cycles of different depths and are under the 100% discharge depth:
according to the energy storage type flexible switch control model,calculating the annual cycle life T of the storage batteryi,cycAnd life cost Ci,ES。
Wherein the S2 includes:
the charge-discharge cycle process is that one charge-discharge cycle occurs at the moment when the energy storage type flexible switch is changed from the discharge process to the charge process:
Figure BDA0003351502280000091
wherein
Figure BDA0003351502280000092
Is a variable of 0 to 1, and when the energy storage state is charge to discharge,
Figure BDA0003351502280000093
in other cases
Figure BDA0003351502280000094
The depth of discharge at the moment before charging is taken as the depth of discharge at the moment before charging
Figure BDA0003351502280000095
Representing the cyclic discharge depth of the accumulator
Figure BDA0003351502280000096
Figure BDA0003351502280000097
Figure BDA0003351502280000098
Calculating the battery cycle life
Figure BDA0003351502280000099
The method comprises the following steps:
Figure BDA00033515022800000910
wherein N is0The number of cycles, k, at which the battery reaches the end of its life with 100% deep charge-dischargepThe values of the curve fitting parameters are between 1.1 and 2.1;
calculating the equivalent full cycle times by converting the discharge cycle with the energy storage life established at different depths into the equivalent full cycle times under 100% of the discharge depth, wherein the daily equivalent full cycle times is Ni,eq：
Figure BDA0003351502280000101
Wherein S is the number of clustered scenes;
calculating the annual cycle life T of the storage batteryi,cycAnd life cost Ci,ESIs composed of
Ti,cyc＝N0/(365·Ni,eq) (7)，
Figure BDA0003351502280000102
Wherein, Ci,inv,ESFor the storage battery investment cost without considering the battery life, r is the discount rate.
The model can change the charge-discharge strategy of the energy storage type soft switch, reduce unnecessary charge-discharge depth, prolong the service life of elements on the basis of recovering power supply, and further reduce cost.
It should be noted that the above embodiment is only one way of calculation, and other modes may also be used for calculation, which is not limited in this application.
After the application completes the usage strategy of the energy storage type flexible switch, the distributed power supply and the corning control are required to realize power restoration, and a specific calculation process and the control are not limited, in one embodiment, the S3 includes:
s31, calculating and controlling a linear target function and constraint conditions through a convex relaxation or large M method, and ensuring that the power output and energy storage type flexible switch configuration range can enable the model to have a feasible solution;
and S32, controlling the distributed power supply and the energy storage type soft switch to recover power supply to the disaster area, and obtaining the minimum distributed power supply output condition and energy storage type soft switch capacity input which can meet the fault recovery by minimizing the operation cost of the fault recovery equipment.
The method for recovering the power distribution network fault, which simultaneously considers the adjusting effect of the energy storage type flexible switch and the distributed power supply on the power distribution network, is provided in the step S3:
the core of the algorithm in the application is as follows:
in the first stage, through historical landslide disaster data and geological information of a power distribution station area, the probability of landslide under the conditions of different slopes, different soil qualities and the like is found, and a monotonic function of the hazard intensity is obtained through fitting based on a regression method.
And then combining the post-disaster cost loss to obtain a landslide damage risk index and determine the installation position of the energy storage type soft switch.
The second stage controls the distributed power supply and the energy storage type soft switch to recover power supply for the disaster-stricken area, obtains the minimum distributed power supply output condition and the energy storage type soft switch capacity input which can meet the fault recovery by minimizing the operation cost of the fault recovery equipment, aims to find the minimum operation cost of the power supply equipment which meets the power supply requirement after the disaster,
specifically, in one embodiment, the S32 includes:
according to the condition that the operation cost of the power supply equipment meeting the post-disaster power supply requirement is minimum, calculating an objective function as follows:
Figure BDA0003351502280000111
Figure BDA0003351502280000112
wherein c isDG，cp，cDCThe investment costs of unit power of the distributed power supply, the converter and the DC-DC converter are respectively saved; r is the discount rate; pDG,tActive power output is provided for the distributed power supply; pL,tPower is lost for operation;
Figure BDA0003351502280000113
power is lost for the line;
Figure BDA0003351502280000114
the two converters are respectively an energy storage type soft switch;
Figure BDA0003351502280000115
is a DC-DC converter power loss; x is the number ofi,xj,yiPlanning capacities of a VSC and a DC-DC at the i, j nodes of the intelligent energy storage soft switch are respectively set; omegal、ΩSOP-ES、ΩESThe system comprises a circuit, the energy storage type soft switch and the storage battery node set, and needs to meet a power balance equation, energy storage charge-discharge constraints, storage battery electric energy time sequence equations, storage battery scheduling period charge state equations, power flow equations, distributed power supply power constraints and power grid operation safety constraints.
In one embodiment of the present application, a method for recovering a power distribution network fault based on an energy storage type flexible switch includes the following 4 steps:
1) fitting a monotonic function of the hazard intensity based on a regression method according to the mountain landslide disaster historical data of the power distribution transformer area, and obtaining the weight of each transformer area based on the post-disaster economic loss.
2) And (3) calculating a landslide damage risk index (1), and obtaining the mountable position of the energy storage type flexible switch through a threshold value.
3) And (3) controlling the output of the distributed power supply and the capacity of the energy storage type flexible switch to recover power supply to the fault area, linearizing a target function and a constraint condition by a convex relaxation or large M method, and calculating (9) by using a matlab to ensure that the configuration range of the output of the power supply and the energy storage type flexible switch can enable the model to have a feasible solution.
4) With the aim of minimizing the operation cost, the power output value of the distributed power supply and the capacity value which enables the service life of the energy storage type flexible switch to be longest are optimized through a cplex commercial solver.
In summary, according to the power distribution network fault recovery method based on the energy storage type flexible switch provided by the embodiment of the invention, the installation position body of the energy storage type flexible switch is determined by evaluating the mountain landslide damage risk, the annual cycle life and the life cost of the storage battery are calculated, the use mode is determined, and finally the distributed power supply is combined to minimize the operation cost to control the output, so that the power supply recovery efficiency and the power supply quality are improved, and the fault recovery efficiency and the power supply quality of the power distribution network are improved.
The method for recovering the power distribution network fault based on the energy storage type flexible switch 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 method and its core concepts. 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 (8)

1.一种基于储能型柔性开关的配电网故障恢复方法，其特征在于，包括：1. a power distribution network fault recovery method based on energy storage type flexible switch, is characterized in that, comprises: S1，根据配电区所在区域的山体滑坡灾害历史数据，评估山体滑坡损坏风险并确定储能型柔性开关安装位置；S1, according to the historical data of landslide disasters in the area where the power distribution area is located, evaluate the risk of landslide damage and determine the installation location of the energy storage flexible switch; S2，计算并根据所述储能型柔性开关的蓄电池年循环寿命和寿命成本，以电能的储存和释放平滑功率波动、减小负荷需求不确定性，确定所述储能型柔性开关的控制策略；S2, calculate and determine the control strategy of the energy storage type flexible switch according to the battery annual cycle life and life cost of the energy storage type flexible switch to smooth the power fluctuation and reduce the load demand uncertainty by the storage and release of electric energy ; S3，以最小化投运成本为目标，计算并输出分布式电源功率输出值和使储能型柔性开关使用寿命最长的容量值。S3, with the goal of minimizing the cost of operation, calculate and output the power output value of the distributed power supply and the capacity value that maximizes the service life of the energy storage flexible switch. 2.如权利要求1所述基于储能型柔性开关的配电网故障恢复方法，其特征在于，所述S1包括：2. The distribution network fault recovery method based on an energy storage type flexible switch according to claim 1, wherein the S1 comprises: 由所述配电台区山体滑坡历史数据基于回归方法得到表示各台区危害强度的单调函数mi，所述山体滑坡历史数据包括地理位置、土壤类型、地质特征；A monotonic function mi representing the hazard intensity of each station area is obtained based on the regression method from the historical data of landslides in the distribution station area, and the historical data of landslides includes geographic location, soil type, and geological characteristics; 根据灾后配电区经济损失确定对应危害权重ωi，计算并获得山体滑坡损害风险指标Sl为：The corresponding hazard weight ω i is determined according to the economic loss of the power distribution area after the disaster, and the landslide damage risk index S l is calculated and obtained as:
Figure FDA0003351502270000011
Figure FDA0003351502270000011
 其中il为台区数，nl为台区总数；where i l is the number of stations, and n l is the total number of stations; 对Sl进行归一化，将其值取在[0,1]区间，Sl越大即受山体滑坡损害越大；Normalize S l and set its value in the interval [0,1], the larger S l is, the greater the damage caused by the landslide; 设定当Sl大于设定风险阈值时表示山体滑坡损害风险较高，需要在安装所述储能型柔性开关以实现灾后恢复供电。It is set that when S l is greater than the set risk threshold, it means that the risk of landslide damage is high, and the energy storage type flexible switch needs to be installed to restore power supply after a disaster. 3.如权利要求2所述基于储能型柔性开关的配电网故障恢复方法，其特征在于，所述S1包括：3. The distribution network fault recovery method based on an energy storage type flexible switch according to claim 2, wherein the S1 comprises: 根据所述配电区所在区域的历史山体滑坡灾害数据和地质信息，计算获得不同坡度、不同土质条件下山体滑坡概率，并基于回归方法拟合得到危害强度单调函数，以及根据灾后成本损失得到山体滑坡损害风险指标并确定所述储能型软开关安装位置。According to the historical landslide disaster data and geological information in the area where the power distribution area is located, the landslide probability under different slopes and soil conditions is calculated and obtained, and the hazard intensity monotonic function is obtained by fitting based on the regression method, and the landslide probability is obtained according to the post-disaster cost loss. Landslide damage risk index and determine the installation location of the energy storage soft switch. 4.如权利要求3所述基于储能型柔性开关的配电网故障恢复方法，其特征在于，所述S1还包括:4. the power distribution network fault recovery method based on energy storage type flexible switch as claimed in claim 3, is characterized in that, described S1 also comprises: 设置所述风险阈值。Set the risk threshold. 5.如权利要求4所述基于储能型柔性开关的配电网故障恢复方法，其特征在于，所述S2包括：5. The distribution network fault recovery method based on an energy storage type flexible switch according to claim 4, wherein the S2 comprises: 计算并根据所述储能型柔性开关的充放电循环过程、充电前一时刻的放电深度、电池循环寿命和根据储能寿命建立为各次不同深度的放电循环折算为100％放电深度下的等效全循环次数建立所述储能型柔性开关控制模型：Calculate and convert according to the charging and discharging cycle process of the energy storage type flexible switch, the depth of discharge at the previous moment of charging, the battery cycle life and the discharge cycles of different depths established according to the energy storage life to 100% depth of discharge, etc. The energy storage type flexible switch control model is established according to the number of effective full cycles: 根据所述储能型柔性开关控制模型，计算蓄电池年循环寿命Ti,cyc和寿命成本Ci,ES。According to the energy storage type flexible switch control model, the annual cycle life T i,cyc and life cost C i,ES of the battery are calculated. 6.如权利要求5所述基于储能型柔性开关的配电网故障恢复方法和装置，其特征在于，所述S2包括：6. The distribution network fault recovery method and device based on an energy storage type flexible switch according to claim 5, wherein the S2 comprises: 所述充放电循环过程为一次充放电循环发生在所述储能型柔性开关由放电过程变为充电过程的时刻：The charge-discharge cycle process is that a charge-discharge cycle occurs at the moment when the energy storage type flexible switch changes from a discharge process to a charge process:
Figure FDA0003351502270000021
Figure FDA0003351502270000021
 其中
Figure FDA0003351502270000022
是一个0-1变量,当储能状态为充电到放电时，
Figure FDA0003351502270000023
其他情况下
Figure FDA0003351502270000024
Figure FDA0003351502270000025
in
Figure FDA0003351502270000022
is a 0-1 variable, when the energy storage state is from charging to discharging,
Figure FDA0003351502270000023
in other cases
Figure FDA0003351502270000024
Figure FDA0003351502270000025
 所述充电前一时刻的放电深度为以充电前一时刻的放电深度
Figure FDA0003351502270000026
代表蓄电池循环放电深度
Figure FDA0003351502270000027
The depth of discharge at the moment before charging is the depth of discharge at the moment before charging
Figure FDA0003351502270000026
Represents battery cycle depth of discharge
Figure FDA0003351502270000027
Figure FDA0003351502270000028
Figure FDA0003351502270000028
Figure FDA0003351502270000029
Figure FDA0003351502270000029
 计算所述电池循环寿命
Figure FDA00033515022700000210
包括：Calculate the battery cycle life
Figure FDA00033515022700000210
include:
Figure FDA00033515022700000211
Figure FDA00033515022700000211
 其中N0为电池以100％放电深度充放电，达到寿命终点时的循环次数，kp为曲线拟合参数，取值在1.1到2.1之间；Among them, N 0 is the number of cycles when the battery is charged and discharged at 100% depth of discharge and reaches the end of its life, and k p is the curve fitting parameter, which ranges from 1.1 to 2.1; 计算所述等效全循环次数为将储能寿命建立为各次不同深度的放电循环折算为100％放电深度下的等效全循环次数，其中，日等效全循环次数为Ni,eq：The calculation of the equivalent full cycle number is to establish the energy storage life as the equivalent full cycle number at 100% discharge depth by establishing the energy storage life as the discharge cycles of different depths, wherein the daily equivalent full cycle number is N i,eq :
Figure FDA0003351502270000031
Figure FDA0003351502270000031
 其中S为聚类的场景数；where S is the number of clustered scenes; 计算蓄电池年循环寿命Ti,cyc和寿命成本Ci,ES为Calculate the battery's annual cycle life T i,cyc and life cost C i,ES as Ti,cyc＝N0/(365·Ni,eq) (7)，T i,cyc =N 0 /(365·N i,eq ) (7),
Figure FDA0003351502270000032
Figure FDA0003351502270000032
 其中，Ci,in,vES为未计及电池寿命的蓄电池投资成本,r为贴现率。Among them, C i,in,vES is the battery investment cost without taking into account the battery life, and r is the discount rate. 7.如权利要求6所述基于储能型柔性开关的配电网故障恢复方法，其特征在于，所述S3包括：7. The distribution network fault recovery method based on an energy storage type flexible switch according to claim 6, wherein the S3 comprises: S31，通过凸松弛或大M法线性化目标函数和约束条件计算和控制，保证电源出力和储能型柔性开关配置范围可使模型具有可行解；S31, calculating and controlling the linearized objective function and constraint conditions through convex relaxation or large M method, ensuring that the power output and the configuration range of the energy storage type flexible switch can make the model have a feasible solution; S32，控制分布式电源和储所述能型软开关对受灾区域恢复供电，通过最小化故障恢复设备的投运成本，得到能够满足故障恢复的最小分布式电源出力情况和储能型软开关容量投入。S32, controlling the distributed power supply and the energy storage soft switch to restore power to the disaster-affected area, and by minimizing the commissioning cost of the fault recovery equipment, obtain the minimum distributed power output and energy storage soft switch capacity that can meet the fault recovery put in. 8.如权利要求7所述基于储能型柔性开关的配电网故障恢复方法，其特征在于，所述S32包括：8. The distribution network fault recovery method based on an energy storage type flexible switch according to claim 7, wherein the S32 comprises: 依据满足灾后供电需求的供电设备投运成本最小的条件，计算目标函数为：According to the condition that the operation cost of the power supply equipment that meets the post-disaster power supply demand is the smallest, the calculation objective function is:
Figure FDA0003351502270000033
Figure FDA0003351502270000033
Figure FDA0003351502270000041
Figure FDA0003351502270000041
 其中cDG，cp，cDC分别为分布式电源、变流器、DC-DC转换器单位功率投资成本；r为贴现率；PDG,t为分布式电源有功出力；PL,t为运行损耗功率；
Figure FDA0003351502270000042
为线路损耗功率；
Figure FDA0003351502270000043
分别为储能式软开关两个变流器功率损耗；
Figure FDA0003351502270000044
为DC-DC转换器功率损耗；xi,xj,yi分别为智能储能软开关i,j节点处VSC和DC-DC的规划容量；Ωl、ΩSOP-ES、ΩES分别为线路、所述储能型软开关、所述蓄电池节点集合，需要满足功率平衡方程、储能荷电状态上下限、储能充放电约束、蓄电池电能时序方程、蓄电池调度周期荷电状态方程、潮流方程、分布式电源功率约束和电网运行安全约束。Among them, c DG , c p , and c DC are the unit power investment costs of distributed power sources, converters, and DC-DC converters, respectively; r is the discount rate; PD G,t is the active power output of distributed power sources; P L,t is the running power loss;
Figure FDA0003351502270000042
is the power loss of the line;
Figure FDA0003351502270000043
are the power losses of the two converters of the energy storage soft-switching;
Figure FDA0003351502270000044
is the power loss of the DC-DC converter; x i , x j , y i are the planned capacities of VSC and DC-DC at nodes i, j of the smart energy storage soft switch; Ω l , Ω SOP-ES , Ω ES are respectively The circuit, the energy storage soft switch, and the battery node set need to satisfy the power balance equation, the upper and lower limits of the energy storage state of charge, the energy storage charge and discharge constraints, the battery power time sequence equation, the battery scheduling cycle state of charge equation, and the power flow. Equations, Distributed Generation Power Constraints, and Grid Operation Safety Constraints.
CN202111338641.4A 2021-11-12 2021-11-12 A distribution network fault recovery method based on energy storage flexible switch Active CN114123169B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111338641.4A CN114123169B (en) 2021-11-12 2021-11-12 A distribution network fault recovery method based on energy storage flexible switch

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111338641.4A CN114123169B (en) 2021-11-12 2021-11-12 A distribution network fault recovery method based on energy storage flexible switch

Publications (2)

Publication Number Publication Date
CN114123169A true CN114123169A (en) 2022-03-01
CN114123169B CN114123169B (en) 2024-12-10

Family

ID=80378925

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111338641.4A Active CN114123169B (en) 2021-11-12 2021-11-12 A distribution network fault recovery method based on energy storage flexible switch

Country Status (1)

Country Link
CN (1) CN114123169B (en)

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106952005A (en) * 2016-01-06 2017-07-14 四川大学 A Risk Assessment Method for Power System Considering Rainfall Landslide Geological Hazards
CN109687458A (en) * 2019-03-05 2019-04-26 东北电力大学 Consider the space truss project method of regional distribution network risk tolerance difference
CN110738378A (en) * 2019-10-31 2020-01-31 黄淮学院 mountain debris flow disaster prediction method and prediction system
CN111563621A (en) * 2020-04-30 2020-08-21 中国地质调查局武汉地质调查中心 Method, system, device and storage medium for assessing risk of regional landslide
CN111815106A (en) * 2020-05-21 2020-10-23 南瑞集团有限公司 A power grid emergency method based on multi-source information
CN113224800A (en) * 2021-04-29 2021-08-06 广东电网有限责任公司 Service life constraint considered and flexible energy storage optimized scheduling method
CN113609752A (en) * 2021-06-28 2021-11-05 广西电网有限责任公司电力科学研究院 Distribution transformer loss evaluation system and method for southwest vortex

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106952005A (en) * 2016-01-06 2017-07-14 四川大学 A Risk Assessment Method for Power System Considering Rainfall Landslide Geological Hazards
CN109687458A (en) * 2019-03-05 2019-04-26 东北电力大学 Consider the space truss project method of regional distribution network risk tolerance difference
CN110738378A (en) * 2019-10-31 2020-01-31 黄淮学院 mountain debris flow disaster prediction method and prediction system
CN111563621A (en) * 2020-04-30 2020-08-21 中国地质调查局武汉地质调查中心 Method, system, device and storage medium for assessing risk of regional landslide
CN111815106A (en) * 2020-05-21 2020-10-23 南瑞集团有限公司 A power grid emergency method based on multi-source information
CN113224800A (en) * 2021-04-29 2021-08-06 广东电网有限责任公司 Service life constraint considered and flexible energy storage optimized scheduling method
CN113609752A (en) * 2021-06-28 2021-11-05 广西电网有限责任公司电力科学研究院 Distribution transformer loss evaluation system and method for southwest vortex

Also Published As

Publication number Publication date
CN114123169B (en) 2024-12-10

Similar Documents

Publication Publication Date Title
CN110729770B (en) An Optimization Algorithm of Active Distribution Network Load Fault Recovery Strategy
Li et al. On the determination of battery energy storage capacity and short-term power dispatch of a wind farm
CN107332234B (en) A multi-fault repair method for active distribution network considering the intermittent nature of renewable energy
CN112383086B (en) Island micro-grid day-ahead energy-standby combined optimization scheduling method
CN110690702B (en) Active power distribution network optimal scheduling and operation method considering comprehensive bearing capacity
CN109802387A (en) A kind of elastic power distribution network multistage service restoration method containing microgrid
JPWO2017150376A1 (en) Power system
JP2018160964A (en) Power system
Mohammadi et al. Adaptive voltage-based load shedding scheme for the DC microgrid
CN117833320A (en) A method and system for optimizing the scheduling of energy storage in a distributed photovoltaic distribution network
CN116316607A (en) Combined optimization scheduling method, system, equipment and medium
CN106230014B (en) A kind of emergency energy management strategies suitable for light storage type building microgrid
JP2018148627A (en) Power system
Nakamura et al. Green base station using robust solar system and high performance lithium ion battery for next generation wireless network (5G) and against mega disaster
CN116436020B (en) Demand determination method and system for new energy grid-connected aggregation station
CN114123169A (en) A fault recovery method for distribution network based on energy storage flexible switch
KR102444388B1 (en) Optimal energy operation method for microgrids
CN117175618A (en) Distributed scheduling method for 5G base station energy storage participation standby and frequency modulation auxiliary service
CN114188980B (en) Transparent micro-grid group economic operation domain generation method considering energy storage device
CN111106622B (en) Active power distribution network power supply recovery method based on RMPC
CN114123170A (en) A fault recovery method for distribution network under flood disaster
Liu et al. Innovative energy management system for energy storage systems of multiple-type with cascade utilization battery
Essakiappan et al. Coordinated power and energy management using cluster of microgrids to improve grid availability and resiliency
Zhang et al. Enhancing power grid resilience against typhoon disasters by scheduling of generators along with optimal transmission switching
CN114256837A (en) A multi-energy complementary distributed power control method and system

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant