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:
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:
wherein
Is a variable of 0 to 1When the energy storage state is from charging to discharging,
in other cases
The depth of discharge at the moment before charging is taken as the depth of discharge at the moment before charging
Representing the cyclic discharge depth of the accumulator
Calculating the battery cycle life
The method comprises the following steps:
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:
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),
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:
wherein c is
DG,c
p,c
DCThe 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; p
DG,tIs divided intoActive power output of the distributed power supply; p
L,tPower is lost for operation;
power is lost for the line;
the two converters are respectively an energy storage type soft switch;
is a DC-DC converter power loss; x is the number of
i,x
j,y
iPlanning capacities of a VSC and a DC-DC at the i, j nodes of the intelligent energy storage soft switch are respectively set; omega
l、Ω
SOP-ES、Ω
ESThe 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.
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:
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:
wherein
Is a variable of 0 to 1, and when the energy storage state is charge to discharge,
in other cases
The depth of discharge at the moment before charging is taken as the depth of discharge at the moment before charging
Representing the cyclic discharge depth of the accumulator
Calculating the battery cycle life
The method comprises the following steps:
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:
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),
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:
wherein c is
DG,c
p,c
DCThe 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; p
DG,tActive power output is provided for the distributed power supply; p
L,tPower is lost for operation;
power is lost for the line;
the two converters are respectively an energy storage type soft switch;
is a DC-DC converter power loss; x is the number of
i,x
j,y
iPlanning capacities of a VSC and a DC-DC at the i, j nodes of the intelligent energy storage soft switch are respectively set; omega
l、Ω
SOP-ES、Ω
ESThe 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.