CN116683493A - Distribution transformer overload self-adaptive control method and system based on mobile energy storage - Google Patents
Distribution transformer overload self-adaptive control method and system based on mobile energy storage Download PDFInfo
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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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
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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
- H02J3/001—Methods to deal with contingencies, e.g. abnormalities, faults or failures
- H02J3/00125—Transmission line or load transient problems, e.g. overvoltage, resonance or self-excitation of inductive loads
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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
- H02J9/00—Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting
- H02J9/04—Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting in which the distribution system is disconnected from the normal source and connected to a standby source
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Abstract
The application discloses a distribution transformer overload self-adaptive control method and a system based on mobile energy storage, wherein the method comprises the following steps: acquiring rated capacity and expected load rate of a transformer for supplying power to a power transmission line; acquiring the actual load total capacity of the power transmission line at the last moment and the storage electric quantity consumed by the energy storage device for supplying power to the power transmission line; based on rated capacity, expected load rate, actual load total capacity of the power transmission line at the last moment and actual stored electricity consumed by the energy storage device, output capacity provided by the energy storage device for power supply of the power transmission line at the next moment is adaptively adjusted, so that the actual load rate of the transformer is within a specified range. According to the application, the output capacity of the energy storage device to the power transmission line is adaptively controlled through the adaptive control algorithm, so that the energy storage device provides power for users when heavy overload occurs, and the energy storage device supplements itself when the power is full, so that virtuous circle is realized, the reliability of a power grid is increased, and the problem of heavy overload of a pairing transformer is effectively solved.
Description
Technical Field
The application relates to the technical field of power supply, in particular to a distribution transformer overload self-adaptive control method and system based on mobile energy storage.
Background
The rapid development of economic construction promotes the revolution of the power industry, and simultaneously, with the continuous improvement of the life quality of people, the industrial electricity, the commercial electricity and the resident life electricity are rapidly increased, and the increasing trend is diversified. Different electricity utilization areas, daily load curves are influenced by factors such as seasons, weather conditions, characteristic days, electricity utilization areas and the like, huge differences are presented under different situations, and partial loads have extremely large peak-valley differences. The use frequency of the high-power electrical appliance is greatly increased, so that the power load is increased, the distribution transformer is operated to critical capacity, and the distribution transformer is in a bad operation state of heavy load and even overload, and even causes the burning loss of the transformer. Particularly, the special period of major holidays such as summer and spring festival with high temperature is a high-incidence period of transformer faults, so that the complaint rate of residents is increased, and the economic loss is serious.
Therefore, how to maintain the normal operation state of the distribution transformer and reduce the heavy overload of the distribution equipment such as the distribution transformer is a problem to be solved.
Disclosure of Invention
The application mainly aims to provide a distribution transformer overload self-adaptive control method and system based on mobile energy storage, which can solve the technical problem of distribution transformer overload in the prior art.
In order to achieve the above object, a first aspect of the present application provides a method for adaptive control of load-changing and overload of a power distribution transformer based on mobile energy storage, the method comprising:
acquiring rated capacity and expected load rate of a transformer for supplying power to a power transmission line;
acquiring the actual load total capacity of the power transmission line at the last moment and the storage electric quantity consumed by the energy storage device for supplying power to the power transmission line;
based on rated capacity, expected load rate, actual load total capacity of the power transmission line at the last moment and actual stored electricity consumed by the energy storage device, output capacity provided by the energy storage device for power supply of the power transmission line at the next moment is adaptively adjusted, so that the actual load rate of the transformer is within a specified range.
In order to achieve the above object, a second aspect of the present application provides a mobile energy storage-based adaptive control system for load-changing and overload, the system comprising: an energy storage device and an energy storage control device;
the energy storage device is used for providing the stored electric quantity consumed by supplying power to the power transmission line at the last moment for the energy storage control device;
the energy storage control device is used for acquiring rated capacity and expected load rate of a transformer for supplying power to the power transmission line, acquiring actual load total capacity of the power transmission line at the last moment and storage electric quantity consumed by the energy storage device for supplying power to the power transmission line, adaptively adjusting output capacity provided by the energy storage device for supplying power to the power transmission line at the next moment based on the rated capacity, the expected load rate, the actual load total capacity of the power transmission line at the last moment and the actual storage electric quantity consumed by the energy storage device, and controlling output of the energy storage device according to the adjusted output capacity;
The energy storage device is also used for supplying power to the power transmission line according to the output capacity indicated in the control command of the energy storage control device, so that the actual load rate of the transformer is within a specified range.
To achieve the above object, a third aspect of the present application provides a computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of:
acquiring rated capacity and expected load rate of a transformer for supplying power to a power transmission line;
acquiring the actual load total capacity of the power transmission line at the last moment and the storage electric quantity consumed by the energy storage device for supplying power to the power transmission line;
based on rated capacity, expected load rate, actual load total capacity of the power transmission line at the last moment and actual stored electricity consumed by the energy storage device, output capacity provided by the energy storage device for power supply of the power transmission line at the next moment is adaptively adjusted, so that the actual load rate of the transformer is within a specified range.
To achieve the above object, a fourth aspect of the present application provides a computer apparatus including a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of:
Acquiring rated capacity and expected load rate of a transformer for supplying power to a power transmission line;
acquiring the actual load total capacity of the power transmission line at the last moment and the storage electric quantity consumed by the energy storage device for supplying power to the power transmission line;
based on rated capacity, expected load rate, actual load total capacity of the power transmission line at the last moment and actual stored electricity consumed by the energy storage device, output capacity provided by the energy storage device for power supply of the power transmission line at the next moment is adaptively adjusted, so that the actual load rate of the transformer is within a specified range.
The embodiment of the application has the following beneficial effects:
according to the obtained actual total capacity of the load, the actual stored electric quantity consumed by the energy storage device, the given rated capacity and the expected load rate, the capacity output of the energy storage device to the power transmission line is adaptively controlled through an adaptive control algorithm, so that the adaptive adjustment of the output of the energy storage device is realized. The output capacity of the energy storage device is reasonably controlled according to the distribution history data, and the problem of heavy overload of the pairing transformer is effectively solved. In addition, the energy storage device can provide emergency power for the power grid when emergency power failure occurs, can be installed at the power utilization terminal user, provides power for the user when heavy overload occurs, supplies the power to the user when the power is abundant, effectively maintains the normal running state of the distribution transformer, reduces the failure rate of the distribution equipment such as the distribution transformer, improves the power utilization service quality, realizes virtuous circle and increases the reliability of the power grid. Meanwhile, the energy storage device can assist in fault repair, so that fault recovery time is reduced to the greatest extent, and economic loss is reduced.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Wherein:
FIG. 1 is a flow chart of a method for adaptive control of a load of a distribution transformer based on mobile energy storage in an embodiment of the application;
FIG. 2 is a block diagram of a configuration of a mobile energy storage-based adaptive control system for load distribution and transformation in an embodiment of the present application;
fig. 3 is a block diagram of a configuration of a mobile energy storage-based adaptive control system for load balancing of a power distribution transformer according to another embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The distribution transformer is used as a key ring of distribution links, is not only a core device for voltage transformation, but also a direct upper-level power supply for electricity utilization and electricity taking of users, and has an important role in a power distribution and utilization system. In actual operation, under the influence of load prediction and user factors, the situation of heavy overload of the distribution transformer exists in various areas more or less. The heavy overload phenomenon of the distribution transformer directly affects the power supply reliability of the power distribution network, in addition, the service life of the distribution transformer is in a certain sense dependent on the service life of the insulating material, and the aging speed of the insulating material is mainly dependent on the temperature of the insulating material, so that the heavy overload phenomenon accompanied with high temperature also damages the service life of the distribution transformer.
Therefore, the application prevents the heavy load or overload of the distribution transformer based on the energy storage device, fills up the power storage device when the output of the power grid is insufficient, and charges the energy storage device when the power grid is full. The energy storage device of the present application may be a mobile energy storage device.
As shown in fig. 1, in one embodiment, a method for adaptive control of a load of a power distribution transformer based on mobile energy storage is provided. The method for adaptively controlling the load of the distribution transformer based on the mobile energy storage specifically comprises the following steps:
S100: and obtaining the rated capacity and the expected load rate of a transformer for supplying power to the power transmission line.
Specifically, the execution body of the embodiment is an energy storage control device, and the rated capacity S of the transformer E And the desired load rate may be given manually. The desired load factor is within a prescribed range.
Under the condition that no energy storage device supplies power, the calculation formula of the transformer load rate of the transformer area is as follows:
wherein beta is 1 Is the load rate of the transformer, S E For the rated capacity of the transformer, S is the total capacity of the load calculated for the bay. Since no energy storage device assists the transformer in powering the line, the total load capacity, i.e. the actual output capacity of the transformer.
In one particular embodiment, β 1 When the load is more than or equal to 80%, the distribution transformer can be identified as heavy load, and beta 1 And when the load is more than or equal to 100%, the distribution transformer can be considered to be overloaded.
As is known from the definition of the load factor, the maximum load factor is related to the maximum load, and the maximum load is influenced by the load acceleration and time, so that in order to prevent the heavy overload problem, the heavy overload of the distribution transformer can be effectively controlled by using a method of reducing the molecules, namely, reducing the actual output capacity of the transformer.
The application uses the energy storage device to assist the transformer in supplying power to realize the purpose of preventing the distribution transformer from overload. When the energy storage device is used, the calculation formula of the transformer load rate of the transformer area is as follows:
Wherein beta is 1 Is the load rate of the transformer, S E For rated capacity of transformer, S is calculated load total capacity for transformer area, S C Is the output capacity of the energy storage device, thus S-S C Is the actual output capacity of the transformer.
As can be seen from the formula (3), the present embodiment can control S C Thereby ensuring beta 1 Not exceeding the prescribed range.
S200: and acquiring the actual total load capacity of the power transmission line at the last moment and the storage electric quantity consumed by the energy storage device for supplying power to the power transmission line.
Specifically, through the intelligent sensing device installed at three-phase circuit, can gather the voltage current data of circuit, intelligent sensing device can send the voltage current data who gathers to energy storage controlling means through wireless transmission mode.
The power supply mode of the sensing device (sensor) can be CT power taking.
The actual load total capacity of the power transmission line can be calculated according to the voltage and the current of the line.
The energy storage control device is connected with the energy storage device and can acquire the storage electric quantity consumed by the energy storage device for supplying power to the power transmission line.
The stored electric quantity consumed by the energy storage device is not more than the maximum stored electric quantity Q of the energy storage device max 。
The relation between the output capacity and the stored electricity of the energy storage device is shown in formula (4):
Wherein t is the duration.
S300: based on rated capacity, expected load rate, actual load total capacity of the power transmission line at the last moment and actual stored electricity consumed by the energy storage device, output capacity provided by the energy storage device for power supply of the power transmission line at the next moment is adaptively adjusted, so that the actual load rate of the transformer is within a specified range.
Specifically, according to the actual situation, the output capacity S of the energy storage device C Not without limitation, it is bounded and tends to stabilize with time integration (charge-discharge consistency). Rated capacity S E The actual load total capacity S is constant from the factory and varies with the on-line load. The purpose of this embodiment is to let the output capacity S of the energy storage device C Under the condition that the corresponding condition is met, the total capacity S of the follow-up actual load changes, so that the load rate of the transformer does not exceed a specified range, and the transformer is prevented from being overloaded and overloaded.
According to the embodiment, the capacity output of the energy storage device to the power transmission line is adaptively controlled through an adaptive control algorithm according to the obtained actual total capacity of the load, the actual stored electric quantity consumed by the energy storage device, the given rated capacity and the given expected load rate, so that the adaptive adjustment of the output of the energy storage device is realized. The output capacity of the energy storage device is reasonably controlled according to the distribution history data, and the problem of heavy overload of the pairing transformer is effectively solved. In addition, the energy storage device can provide emergency power for the power grid when emergency power failure occurs, can be installed at the power utilization terminal user, provides power for the user when heavy overload occurs, supplies the power to the user when the power is abundant, effectively maintains the normal running state of the distribution transformer, reduces the failure rate of the distribution equipment such as the distribution transformer, improves the power utilization service quality, realizes virtuous circle and increases the reliability of the power grid. Meanwhile, the energy storage device can assist in fault repair, so that fault recovery time is reduced to the greatest extent, and economic loss is reduced.
Although the energy storage device can assist the transformer to realize safe power supply, how to design the charging and discharging rules of the energy storage device is key to playing the advantages of the mobile energy storage device, but no better solution exists for the problem.
Based on the above, in one embodiment, step S300 specifically includes:
and according to the rated capacity, the expected load rate, the actual total load capacity of the power transmission line at the last moment and the actual stored electric quantity consumed by the movable energy storage device, the output capacity provided by the energy storage device for supplying power to the power transmission line at the next moment is adaptively adjusted through the fuzzy controller.
Specifically, the actual total load capacity S is characterized by different time, and is subject to time, weather, season, etc., and has a large uncertainty, theoretically, only the output capacity S of the energy storage device is required C The purpose can be achieved by changing along with the change of the actual total load capacity S. However, the actual situation is more complicated, and the following effect is influenced by the capacity of the energy storage device, the detection speed and precision of the total capacity S of the actual load, the action speed of the energy storage control device and the like.
Therefore, the present embodiment adjusts the output capacity of the energy storage device through the fuzzy controller, so that the output capacity S of the energy storage device C The change along with the change of the actual total load capacity S quickly achieves the aim of better preventing the overload or the overload of the transformer.
Fuzzy control is the application of fuzzy mathematics in a control system and is a nonlinear intelligent control method based on fuzzy set theory, fuzzy language variables and fuzzy logic reasoning. The fuzzy control can effectively control a system which is nonlinear, time-varying, incapable of or difficult to establish an accurate mathematical model, and the fuzzy system has simple equipment, good robustness and obvious economic benefit.
The fuzzy controller comprises a blurring process, a fuzzy logic reasoning process and a defuzzification process of the input quantity. And obtaining an input variable of the fuzzy controller according to the rated capacity, the expected load rate, the actual total load capacity of the power transmission line at the last moment and the actual storage electric quantity consumed by the movable energy storage device, wherein the output variable of the fuzzy controller is the output capacity of the energy storage device.
Fuzzy control belongs to intelligent control, does not depend on a mathematical model, and performs reasoning by means of a series of control rules obtained by expert experience knowledge so as to obtain a control output quantity. Nonlinear control can be realized without establishing an exact mathematical model for the object, and the method has better robustness and flexibility. Therefore, the output capacity provided by the energy storage device for power supply of the power transmission line can be effectively and rapidly adjusted in a self-adaptive mode through the fuzzy controller, the advantage of the energy storage device is exerted by designing the charging and discharging rule of the energy storage device through the fuzzy controller, the auxiliary transformer is used for realizing safe power supply, the normal running state of the distribution transformer is maintained, the paired transformer is prevented from being overloaded again, the failure rate of distribution equipment such as the distribution transformer is reduced, and the power utilization service quality is improved.
In one embodiment, adaptively adjusting, by the fuzzy controller, an output capacity provided by the energy storage device to power the transmission line at a next time based on the rated capacity, the desired load rate, the total actual load capacity of the transmission line at the previous time, and the actual stored power consumed by the mobile energy storage device, includes:
calculating to obtain a target error and a corresponding error change rate according to the rated capacity, the expected load rate, the actual total load capacity of the power transmission line at the last moment and the actual stored electric quantity consumed by the energy storage device;
the target error and the error change rate are used as input variables of the fuzzy controller, the output capacity of the energy storage device required to be provided for the power transmission line is used as the output variables of the fuzzy controller, the output variables are changed along with the change of the input variables through the fuzzy controller, and the output capacity of the energy storage device provided for supplying power to the power transmission line at the next moment is adjusted in a self-adaptive mode.
Specifically, in one embodiment, the target error is a total capacity error, and the total capacity error and the error change rate of the actual load total capacity and the theoretical load total capacity of the power transmission line are calculated according to the rated capacity, the expected load rate, the actual load total capacity of the power transmission line at the last moment and the actual storage electric quantity consumed by the energy storage device. The total capacity error and the error change rate are taken as input variables of the fuzzy controller, and the output capacity of the energy storage device is taken as output variables of the fuzzy controller.
The total capacity error is the difference between the actual load total capacity and the theoretical load total capacity.
More specifically:
total capacity error= |actual load total capacity-theoretical load total capacity= |s- (β) 0 S E +S C0 )|
Theoretical total load capacity of beta 0 S E +S C0 ，β 0 For the expected load rate, S is the total capacity of the actual load, S C0 And the theoretical output capacity of the energy storage device is obtained through the fuzzy controller at the last moment.
The error rate of change in this embodiment is obtained by differentiating the total capacity error.
In addition, the relationship between the actual output capacity and the theoretical output capacity of the energy storage device and the actual stored electricity consumed by the energy storage device is as follows:
wherein S is C To the actual output capacity of the energy storage device, Q C For the actual stored power consumed by the energy storage device, Q C0 Theoretical storage electric quantity required to be consumed by energy storage device, Q max Is the maximum stored power of the energy storage device.
In another embodiment, the target error is a load rate error, and the load rate error and the error change rate of the actual load rate and the theoretical load rate of the transformer are calculated according to the rated capacity, the expected load rate, the actual total load capacity of the power transmission line at the last moment and the actual stored electric quantity consumed by the energy storage device.
The error rate of change of the present embodiment is obtained by differentiating the load rate error.
In addition, the relationship between the actual output capacity of the energy storage device and the actual stored power consumed by the energy storage device is as follows:
wherein S is C To the actual output capacity of the energy storage device, Q C For the actual stored power consumed by the energy storage device, Q max Is the maximum stored power of the energy storage device.
In another embodiment, the target error is an output capacity error of the transformer, and the output capacity error and the error change rate of the actual output capacity and the theoretical output capacity of the transformer are calculated according to the rated capacity, the expected load rate, the actual total load capacity of the power transmission line at the last moment and the actual stored electric quantity consumed by the energy storage device.
Output capacity error of transformer = actual output capacity-theoretical output capacity = | (S-SC) - β 0 S E |
The error rate of change in this embodiment is obtained by differentiating the output capacity error of the transformer.
In addition, the relationship between the actual output capacity of the energy storage device and the actual stored power consumed by the energy storage device is as follows:
wherein S is C To the actual output capacity of the energy storage device, Q C For the actual stored power consumed by the energy storage device, Q max Is the maximum stored power of the energy storage device.
In one embodiment, the target error and the error change rate are taken as input variables of the fuzzy controller, the output capacity of the energy storage device required to be provided for the power transmission line is taken as output variables of the fuzzy controller, the output variables are changed along with the change of the input variables through the fuzzy controller, and the output capacity of the energy storage device provided for supplying power for the power transmission line at the next moment is adaptively adjusted, and the method comprises the following steps:
obtaining an initial change range of a target error according to the change range of rated capacity, expected load rate, total load capacity of the power transmission line and the change range of the storage electric quantity of the energy storage device;
obtaining an initial change range of a corresponding error change rate according to the initial change range of the target error;
acquiring an initial variation range of output capacity which can be provided by the energy storage device for power supply of the power transmission line;
and according to the initial change range of the target error, the initial change range of the error change quantity and the initial change range of the output capacity of the energy storage device, sequentially carrying out fuzzification, fuzzy reasoning and defuzzification processing to obtain the output capacity of the energy storage device.
Specifically, the rated capacity S of a distribution transformer E Is a fixed value, the desired load factor beta 0 Also a fixed value, the variation range of the total load capacity S of the transmission line is known as S min ,S max ]. Storage of energy storage devicesThe variation range of the electric quantity Q is also known as [0, Q max ]. Actual output capacity S of energy storage device C Or theoretical output capacity S calculated by fuzzy controller C0 Is known as [ -P min ,P max ]。
Taking the target error as the total capacity error as an example, total capacity error=actual load total capacity-theoretical load total capacity=s- (β) 0 S E +S C0 ) From this, it can be seen that the total capacity error is initially varied. The error change rate is obtained by differentiating the total capacity error, and the initial change range of the error change rate can be calculated when the initial change range of the total capacity error is known.
The initial variation range before adjustment in this embodiment refers to the basic domain or the natural domain or the input domain or the initial domain of the variable.
The initial variation range before adjustment is the basic domain or the natural domain or the input domain or the initial domain of the variable.
Because the input quantity and the output quantity are accurate quantities, the fuzzy language variables are set, and language values are selected to fuzzify the quantities.
The fuzzy reasoning is specifically a process that the fuzzy controller performs fuzzy reasoning according to the established fuzzy control rule table.
The output of the fuzzy controller is a fuzzy set that must be converted to a non-fuzzy output for use in the tuning process. Therefore, the de-blurring process is required.
In one embodiment, according to the initial variation range of the target error, the initial variation range of the error variation and the initial variation range of the output capacity of the energy storage device, sequentially performing fuzzification, fuzzy reasoning and defuzzification processing to obtain the output capacity of the energy storage device, including:
the quantization factors of the input variables are adopted to map the initial change range of the target error and the initial change range of the error change rate to the fuzzy domain, and the scale factors of the output variables are adopted to map the initial change range of the output capacity to the fuzzy domain;
performing fuzzy division on fuzzy universe of target errors to obtain fuzzy aggregation universe of target errors including first fuzzy subsets of a first preset number;
performing fuzzy division on the fuzzy universe of the error change rate to obtain a fuzzy aggregation universe of which the error change rate comprises a second fuzzy subset with a second preset number;
carrying out fuzzy division on fuzzy domains of the output capacity of the energy storage device to obtain fuzzy aggregation domains of which the output capacity of the energy storage device comprises a third fuzzy subset with a third preset number;
According to the target error, a first distribution function is adopted to obtain a membership function of a fuzzy aggregation domain for representing the target error after the target error is fuzzified;
according to the error change rate, a second distribution function is adopted to obtain a membership function of a fuzzy aggregation domain for representing the error change rate after the error change rate is fuzzified;
according to the output capacity of the energy storage device, a third distribution function is adopted to obtain a membership function which is used for representing a fuzzy aggregation domain of the output capacity of the energy storage device after the output capacity of the energy storage device is subjected to fuzzification;
obtaining fuzzy controller output based on fuzzy aggregation domain, membership function and by inquiring established fuzzy control rule table, obtaining fuzzy output quantity;
and performing defuzzification operation on the fuzzy output quantity according to the scale factor of the output variable to obtain the output capacity of the energy storage device.
Specifically, the variable range before the input variable is adjusted and the variable range before the output variable is adjusted are subjected to fuzzification processing by using the quantization factor of the input variable and the scaling factor of the output variable, so as to obtain the fuzzy domain of the input variable and the fuzzy domain of the output variable. And carrying out fuzzy division on the fuzzy universe through the fuzzy subsets, so that the fuzzy universe is discretized, and a fuzzy aggregation universe is obtained. The quantization factor of the input variable and the scaling factor of the output variable are variable domain scaling factors. By designing the expansion factors, the input and output domains can be adjusted on line.
Multiplying the quantization factor of the target error by the initial change range of the target error to obtain the change range of the target error after adjustment.
Multiplying the quantization factor of the error change rate by the initial change range of the error change rate to obtain the change range after the error change rate is adjusted.
And multiplying the scale factor of the output capacity of the energy storage device by the initial change range of the output capacity of the energy storage device to obtain the change range of the output capacity of the energy storage device after adjustment.
The initial change range before adjustment is the basic domain or the natural domain or the input domain or the initial domain of the variable, and the change range after adjustment is the fuzzy quantization range or the fuzzy domain.
For example, the fuzzy aggregate argument of the target error is e= {0,1,2,3,4,5,6}
The fuzzy aggregate domain of error rate is: ec= {0,1,2,3,4,5,6}
The fuzzy aggregation theory of the energy storage device is as follows: s is S C0 ＝{-3,-2,-1,0,1,2,3}。
For example, the fuzzy arguments of the target error are divided into fuzzy aggregation arguments e= {0,1,2,3,4,5,6} using 7 first fuzzy subsets. A first fuzzy subset corresponds to a linguistic value in NL, NM, NS, ZO, PS, PM, PL.
The fuzzy arguments using 7 second fuzzy subset partition error rates are fuzzy aggregation arguments ec= {0,1,2,3,4,5,6}. A second fuzzy subset corresponds to a linguistic value in { NL, NM, NS, ZO, PS, PM, PL }.
Fuzzy arguments dividing output capacity using 7 third fuzzy subsets are fuzzy aggregation arguments S C0 = { -3, -2, -1,0,1,2,3}. A third fuzzy subset corresponds to a linguistic value in { NL, NM, NS, ZO, PS, PM, PL }.
The language values in NL, NM, NS, ZO, PS, PM, PL correspond to the negative big, negative middle, negative small, zero, positive small, median, positive big fuzzy concepts, respectively.
In this particular embodiment, 7 linguistic variables are used to describe the input and output variables, resulting in a fuzzy subset of the input linguistic variables. Input and output variables of the variable domain fuzzy controller are fuzzified and mapped onto fuzzy aggregation domains defined by 7 fuzzy subsets.
Of course, the number of the first fuzzy subset, the second fuzzy subset and the third fuzzy subset may be the same or different, and the first fuzzy subset, the second fuzzy subset and the third fuzzy subset may use the same linguistic variable or linguistic value or may use different linguistic variable or linguistic value.
The first distribution function, the second distribution function and the third distribution function may be the same or different, and are specifically configured according to practical situations. The distribution function may be selected from triangle, gaussian, trapezoid, etc., without being limited thereto.
Preferably, the first distribution function, the second distribution function and the third distribution function each select a triangle (trimf) as the shape of the fuzzy subset in the universe.
In the embodiment, a fuzzy control rule table is obtained by analyzing the control process of the energy storage device and designing fuzzy rules based on the change rules in different control stages; and meanwhile, determining membership functions and defuzzification strategies of the fuzzy controller, so that the Mamdani fuzzy controller can be designed. And carrying out fuzzy reasoning according to a Mamdani fuzzy reasoning rule to obtain fuzzy output quantity. The output of the fuzzy controller is a fuzzy set which must be converted to a non-fuzzy output for the tuning process, and therefore requires a sharpening operation to sharpen the fuzzy output according to the scale factor of the output variable, converting the fuzzy output to a sharpening value.
Alternatively, the deblurring method of the control output is center of gravity (centroid).
In the above embodiment, expert experience is summarized, and a fuzzy control rule table of the control system is established as shown in table 1:
TABLE 1
Of course, table 1 is merely an exemplary illustration, and the specific fuzzy control rule table is set according to the actual situation, which is not limited by the present application.
According to the embodiment, the output capacity of the energy storage device is transmitted to the power transmission line to supply power for the power transmission line through fuzzification, fuzzy reasoning and fuzzy operation, the auxiliary transformer of the energy storage device is used for supplying power for the power transmission line, and fuzzy closed-loop control of the variable domain of the distribution transformer overload self-adaptive control is realized.
In one embodiment, according to the initial variation range of the target error, the initial variation range of the error variation and the initial variation range of the output capacity of the energy storage device, the output capacity of the energy storage device is obtained through fuzzification, fuzzy reasoning and defuzzification processing in sequence, and the method further comprises:
and adaptively adjusting the quantization factor of the input variable and the scaling factor of the output variable according to the actual value of the target error, wherein the quantization factor of the input variable comprises the quantization factor of the target error and the quantization factor of the error change rate, and the scaling factor of the output variable comprises the scaling factor of the output capacity.
Specifically, when the values of the quantization factor and the scaling factor are changed, the domain will also change correspondingly in a certain angle. If the quantization factor is unchanged and the error is continuously reduced, the domain range at the moment is too large relative to the input fuzzy quantity of the fuzzy controller, the control fuzzy rule is too rough to divide, the number of the used control rules is reduced, and the adjusting effect is weakened.
Therefore, in the present embodiment, when the error is continuously reduced, the quantization factor of the input variable is increased, so that the domain range is compressed with respect to the input blur amount. Similarly, the scaling factor is reduced, allowing the domain range to be compressed for output.
When the error is continuously increased, the quantization factor of the input variables is reduced, the resolution of the two input variables is reduced, and the scale factor is increased, so that the system response is quickened.
According to the embodiment, the influence of the quantization factor and the scaling factor on the performance of the fuzzy control system is fully considered, the values of the quantization factor and the scaling factor are adaptively adjusted according to the actual value of the target error, different response rules of the system in different error ranges can be realized, and the system is ensured to meet efficient tracking. The embodiment designs a self-adaptive method, so that the control of fuzzy control is more sensitive, and the error of the system is reduced.
In one embodiment, the quantization factor of the input variable and the scaling factor of the output variable are adaptively adjusted by the following equation (1):
wherein K is e For initial quantization factor of target error, K ec K is the initial quantization factor of the error rate SC To output an initial scale factor for the capacity,adaptive quantization factor for target error, +. >Adaptive quantization factor for error rate of change, < ->E is a target error, which is an adaptive scale factor of output capacity.
In particular, when the error e is large, the problem of the quick response of the system is fully considered,and->Taking smaller values, decreasing the resolution of both input variables while increasing +.>The system response is quickened.
When the error e is small, the error is small,and->Take larger value, increase resolution of two input variables, and at the same time, decreaseAnd excessive system jitter is avoided.
According to the thought, a proper self-adaptive law is selected in the fuzzy control process, a fuzzy self-adaptive controller is constructed, the quantization factor of an input variable and the scale factor of an output variable are adaptively adjusted, three rules of a formula (1) are used for realizing the self-adaptive error change of the quantization factor of the input variable and the scale factor of the output variable, and the control performance of the system can be improved.
The error e in the formula (1) is obtained by normalizing the original error e. That is, the value of e in the formula (1) is obtained by normalizing the original error e.
The original error e has an error range of [ e ] min ，e max ]The error range is determined based on the error magnitude. For example, the error range of the original error e may be set to [0,2 ]Or [0,4]]The present invention is not limited to this, and the upper and lower limits may be set appropriately according to the actual error.
Normalization step, for example, when the error range e is set to [0,4], normalization is to scale the interval of [0,4] to [0,1], assuming that the error e=2, the normalized value is 0.5.
In one embodiment, the step S200 of obtaining the actual total load capacity of the power transmission line at the last moment includes:
collecting voltage data and current data of each phase of a three-phase power transmission line through a sensing device arranged on the power transmission line;
according to the voltage data and the current data, calculating a three-phase voltage average value and a three-phase current average value of the three-phase power transmission line;
and calculating to obtain the actual load total capacity of the power transmission line according to the three-phase voltage average value and the three-phase current average value.
In particular, the method comprises the steps of,
wherein S is the total capacity of an actual load, U is the average value of three-phase voltages, and I is the average value of three-phase currents.
In another embodiment, the step S200 of obtaining the actual total load capacity of the transmission line at the last moment includes:
according to the voltage data and the current data, calculating the actual load capacity of each phase line of the three-phase power transmission line, and according to the actual load capacity of the three-phase power transmission line, obtaining the actual load total capacity of the power transmission line.
In particular, the method comprises the steps of,
wherein S is the total capacity of an actual load, U1, U2 and U3 are three-phase voltages respectively, and I1, I2 and I3 are three-phase currents respectively.
The capacity of the present application represents power.
Referring to fig. 2, the present application further provides a mobile energy storage based adaptive control system for load balancing of a load balancing unit, where the mobile energy storage based adaptive control system 10 for load balancing of a load balancing unit includes: an energy storage device 11 and an energy storage control device 12;
an energy storage device 11 for providing the stored energy consumed for supplying power to the transmission line at the previous moment to the energy storage control device 12;
the energy storage control device 12 is configured to obtain a rated capacity and an expected load rate of a transformer for supplying power to the power transmission line, obtain an actual total load capacity of the power transmission line at a previous time and a storage power consumed by the energy storage device 11 for supplying power to the power transmission line, adaptively adjust an output capacity provided by the energy storage device 11 for supplying power to the power transmission line at a next time based on the rated capacity, the expected load rate, the actual total load capacity of the power transmission line at the previous time and the actual storage power consumed by the energy storage device 11, and control an output of the energy storage device 11 according to the adjusted output capacity;
the energy storage device 11 is further configured to supply power to the power transmission line according to the output capacity indicated in the control command of the energy storage control device 12, so that the actual load factor of the transformer is within a specified range.
Specifically, referring to fig. 2, given a desired load rate β 0 And rated capacity S E 。
The energy storage control device 12 is responsive to a given desired load factor beta 0 And rated capacity S E The change range (constraint range) of the total actual load capacity S of the power transmission line configured for the energy storage control device 12, the change range (constraint range) of the storage electric quantity Q consumable by the energy storage device 11, and the change range (constraint range) of the actual output capacity Sc that the energy storage device 11 can provide for power transmission line power supply are obtained, the output capacity Sc0 that the energy storage device 11 needs to output is obtained, and the energy storage device 11 is controlled to supply power transmission line with the output capacity Sc 0. The output capacity SC0 is a theoretical output capacity, and the actual output capacity SC of the energy storage device 11 may be different from the theoretical output capacity SC 0.
Meanwhile, the energy storage device 11 and the power transmission line can timely feed back the storage electric quantity Q consumed by the energy storage device 11 and the actual total load capacity S to the energy storage control device 12.
The consumed stored energy Q has an integral relationship with the actual output capacity Sc of the energy storage device 11 over time.
In one embodiment, the energy storage control device 12 includes a fuzzy controller;
the energy storage control device 12 is specifically configured to calculate a target error and a corresponding error change rate according to a rated capacity, an expected load rate, an actual total load capacity of the power transmission line at a previous moment, and an actual stored power consumed by the energy storage device 11;
The target error and the error change rate are taken as input variables of the fuzzy controller, the output capacity of the energy storage device 11 required to be provided for the power transmission line is taken as the output variables of the fuzzy controller, the output variables are changed along with the change of the input variables through the fuzzy controller, and the output capacity of the energy storage device 11 provided for supplying power for the power transmission line at the next moment is adaptively adjusted.
Specifically, referring to FIG. 3, the energy storage control device 12 includes a fuzzy controller for performing quantization or fuzzification, fuzzy inference and anti-fuzzification operations. Specific steps refer to the above method, and are not described herein.
Because the geographical conditions of each region are complex, resident residence distribution is very wide, and thus the construction difficulty of a power grid is very high, and although a power grid company basically realizes the electrification of household users under the condition of large-scale construction and investment, the electricity utilization quality of the users is still a great difficulty to be solved. The application solves the problem of heavy overload of the distribution transformer based on the mobile energy storage PCS technology. The self-adaptive fuzzy control algorithm is designed aiming at the problem of heavy overload, so that the comprehensive control scheme of the mobile energy storage device under the influence of factors such as storage capacity, output power and the like is simple in design and easy to realize, and is a feasible scheme for treating the heavy overload of the distribution transformer. The system mainly comprises a signal acquisition end and a mobile power end, wherein the mobile power end mainly comprises a storage battery, a BMM, a PCS and the like.
With the continuous development of economy, the living standard of people is increasingly improved, and industrial electricity or resident living electricity is rapidly increased. Meanwhile, the requirements of users on stable supply of electric energy are also increasing. The long-term heavy overload operation of the 10kV power distribution network transformer can accelerate the aging of the weak points of the lines, so that the weak point faults are caused, low-voltage power failure is caused, even medium-voltage faults are caused, and the load loss, the operation maintenance and the personnel waste of rush repair are caused. This not only affects social production, causing economic losses, but also directly affects the living order of the people. Therefore, the problem of heavy overload of public distribution transformer of the rural power network is always a difficult problem affecting the running development of the distribution network. In order to improve the electricity quality of rural users, the satisfaction degree of third party clients is improved. The reasons and treatment strategies of the heavy overload of the public distribution transformer of the rural power network are needed to be studied and discussed, and the problem of the heavy overload of the public distribution transformer of the rural power network is solved. The application is expected to effectively inhibit the heavy overload problem by a self-adaptive mode of peak clipping and valley filling through a mobile energy storage PCS technology and a closed-loop control technology, and the scheme of the application has larger market and popularization value.
Those skilled in the art will appreciate that the processes implementing all or part of the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, and the program may be stored in a non-volatile computer readable storage medium, and the program may include the processes of the embodiments of the methods as above when executed. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application, which are described in detail and are not to be construed as limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.
Claims (10)
1. The method for adaptively controlling the load of the distribution transformer based on the mobile energy storage is characterized by comprising the following steps of:
acquiring rated capacity and expected load rate of a transformer for supplying power to a power transmission line;
acquiring the actual load total capacity of the power transmission line at the last moment and the storage electric quantity consumed by an energy storage device for supplying power to the power transmission line;
and based on the rated capacity, the expected load rate, the actual total load capacity of the power transmission line at the last moment and the actual stored electric quantity consumed by the energy storage device, adaptively adjusting the output capacity provided by the energy storage device for supplying power to the power transmission line at the next moment, so that the actual load rate of the transformer is within a specified range.
2. The method of claim 1, wherein the adaptively adjusting the output capacity provided by the energy storage device to power the transmission line at a next time based on the rated capacity, a desired load rate, a total actual load capacity of the transmission line at a previous time, and an actual stored power consumed by the energy storage device, comprises:
and according to the rated capacity, the expected load rate, the actual total load capacity of the power transmission line at the last moment and the actual storage electric quantity consumed by the movable energy storage device, the output capacity provided by the energy storage device for supplying power to the power transmission line at the next moment is adaptively adjusted through a fuzzy controller.
3. The method of claim 2, wherein the adaptively adjusting, by the fuzzy controller, the output capacity provided by the energy storage device to power the transmission line at a next time based on the rated capacity, the desired load rate, the total actual load capacity of the transmission line at the previous time, and the actual stored power consumed by the mobile energy storage device, comprises:
calculating to obtain a target error and a corresponding error change rate according to the rated capacity, the expected load rate, the actual total load capacity of the power transmission line at the last moment and the actual stored electric quantity consumed by the energy storage device;
And taking the target error and the error change rate as input variables of a fuzzy controller, taking output capacity required to be provided by an energy storage device for the power transmission line as output variables of the fuzzy controller, and realizing that the output variables change along with the change of the input variables by the fuzzy controller so as to adaptively adjust the output capacity provided by the energy storage device for supplying power to the power transmission line at the next moment.
4. A method according to claim 3, wherein the taking the target error and the error change rate as input variables of a fuzzy controller and taking output capacity required by an energy storage device to supply power to the power transmission line as output variables of the fuzzy controller, the output variables being changed along with the input variable changes by the fuzzy controller, so as to adaptively adjust the output capacity provided by the energy storage device to supply power to the power transmission line at the next moment, comprises:
obtaining an initial change range of the target error according to the rated capacity, the expected load rate, the change range of the total load capacity of the power transmission line and the change range of the storage electric quantity of the energy storage device;
obtaining an initial change range of a corresponding error change rate according to the initial change range of the target error;
Acquiring an initial variation range of output capacity which can be provided by the energy storage device for power supply of the power transmission line;
and according to the initial change range of the target error, the initial change range of the error change amount and the initial change range of the output capacity of the energy storage device, sequentially carrying out fuzzification, fuzzy reasoning and defuzzification processing to obtain the output capacity of the energy storage device.
5. The method according to claim 4, wherein the obtaining the output capacity of the energy storage device according to the initial variation range of the target error, the initial variation range of the error variation, and the initial variation range of the output capacity of the energy storage device sequentially through fuzzification, fuzzy reasoning, and defuzzification processing includes:
the initial change range of the target error and the initial change range of the error change rate are mapped to a fuzzy domain by adopting quantization factors of input variables, and the initial change range of the output capacity is mapped to the fuzzy domain by adopting scaling factors of output variables;
performing fuzzy division on fuzzy universe of target errors to obtain fuzzy aggregation universe of first fuzzy subsets, wherein the target errors comprise a first preset number;
Performing fuzzy division on the fuzzy universe of the error change rate to obtain a fuzzy aggregation universe of a second fuzzy subset, wherein the error change rate comprises a second preset number;
carrying out fuzzy division on fuzzy domains of the output capacity of the energy storage device to obtain fuzzy aggregation domains of which the output capacity of the energy storage device comprises a third preset number of third fuzzy subsets;
according to the target error, a first distribution function is adopted to obtain a membership function which is used for representing a fuzzy aggregation domain of the target error after the target error is fuzzified;
according to the error change rate, a second distribution function is adopted to obtain a membership function of a fuzzy aggregation domain for representing the error change rate after the error change rate is subjected to fuzzification;
according to the output capacity of the energy storage device, a third distribution function is adopted to obtain a membership function which is used for representing a fuzzy aggregation domain of the output capacity of the energy storage device after the output capacity of the energy storage device is subjected to fuzzification;
obtaining fuzzy controller output based on the fuzzy aggregation domain and membership function and by inquiring an established fuzzy control rule table, and obtaining fuzzy output quantity;
and performing defuzzification operation on the fuzzy output quantity according to the scale factor of the output variable to obtain the output capacity of the energy storage device.
6. The method according to claim 5, wherein the obtaining the output capacity of the energy storage device according to the initial variation range of the target error, the initial variation range of the error variation, and the initial variation range of the output capacity of the energy storage device sequentially through fuzzification, fuzzy reasoning, and defuzzification processing, further comprises:
and adaptively adjusting the quantization factor of the input variable and the scaling factor of the output variable according to the actual value of the target error, wherein the quantization factor of the input variable comprises the quantization factor of the target error and the quantization factor of the error change rate, and the scaling factor of the output variable comprises the scaling factor of the output capacity.
7. The method of claim 6, wherein the quantization factor of the input variable and the scaling factor of the output variable are adaptively adjusted by the following equation (1):
wherein K is e For initial quantization factor of target error, K ec K is the initial quantization factor of the error rate SC To output an initial scale factor for the capacity,adaptive quantization factor for target error, +.>Adaptive quantization factor for error rate of change, < ->E is a target error, which is an adaptive scale factor of output capacity.
8. The method according to claim 1, wherein the obtaining the actual total load capacity of the power transmission line at the last moment comprises:
collecting voltage data and current data of each phase of the three-phase transmission line through a sensing device arranged on the transmission line;
according to the voltage data and the current data, calculating a three-phase voltage average value and a three-phase current average value of the three-phase power transmission line;
and calculating to obtain the actual load total capacity of the power transmission line according to the three-phase voltage average value and the three-phase current average value.
9. A mobile energy storage based adaptive control system for load distribution and transformation, the system comprising: an energy storage device and an energy storage control device;
the energy storage device is used for providing the stored electric quantity consumed by supplying power to the power transmission line at the last moment for the energy storage control device;
the energy storage control device is used for acquiring rated capacity and expected load rate of a transformer for supplying power to the power transmission line, acquiring actual load total capacity of the power transmission line at the last moment and storage electric quantity consumed by the energy storage device for supplying power to the power transmission line, and adaptively adjusting output capacity of the energy storage device provided for the power transmission line at the next moment based on the rated capacity, the expected load rate, the actual load total capacity of the power transmission line at the last moment and the actual storage electric quantity consumed by the energy storage device, and controlling output of the energy storage device according to the adjusted output capacity;
The energy storage device is also used for supplying power to the power transmission line according to the output capacity indicated in the control command of the energy storage control device, so that the actual load rate of the transformer is within a specified range.
10. The system of claim 9, wherein the energy storage control device comprises a fuzzy controller;
the energy storage control device is specifically configured to calculate a target error and a corresponding error change rate according to the rated capacity, the expected load rate, the total actual load capacity of the power transmission line at the last moment and the actual storage electric quantity consumed by the energy storage device;
and taking the target error and the error change rate as input variables of a fuzzy controller, taking output capacity required to be provided by an energy storage device for the power transmission line as output variables of the fuzzy controller, and realizing that the output variables change along with the change of the input variables by the fuzzy controller so as to adaptively adjust the output capacity provided by the energy storage device for supplying power to the power transmission line at the next moment.
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