CN117526575A - One-key sequential control method and system for power distribution network - Google Patents
One-key sequential control method and system for power distribution network 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
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
- H02J13/00034—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving an electric power substation
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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
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
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- H—ELECTRICITY
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
- H02J13/00036—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving switches, relays or circuit breakers
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- 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
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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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
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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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
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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Abstract
The invention relates to the technical field of power distribution network control, and discloses a one-key sequential control method and a one-key sequential control system for a power distribution network, wherein the method comprises the following steps: according to the running state information of each device in the transformer substation, calculating to obtain a transformer substation running load sequence; predicting the operation load of the transformer substation by using a transformer substation operation load prediction model; load distribution is carried out on the total load of the transformer substation according to the priority of the electric equipment; and identifying and obtaining current opening and closing parameters of power distribution protection equipment corresponding to different electric equipment, and further generating corresponding control instructions to carry out one-key sequential control. According to the method, the operation load sequence is coded and represented by combining with the time sequence information of the operation load, and the attention calculation is performed by combining with the sparsity of the coding, so that the robustness and the accuracy of the operation load prediction result are improved, a power distribution network control instruction which enables the difference degree between the loads and the fluctuation degree of the operation load sequence of the electric equipment to be minimum is generated, the power distribution efficiency of the power distribution network is improved, and one-key sequential control is realized.
Description
Technical Field
The invention relates to the field of power distribution network control, in particular to a one-key sequential control method and system for a power distribution network.
Background
With the development of social economy, the power generation and transmission and transformation devices are continuously increased in various places, the grid structure is more complex and changeable, and the following problems exist by adopting the traditional grid switching operation and maintenance management mode: 1) The operation time of the equipment shutdown and re-service tasks is concentrated, serial waiting is needed under the multitasking condition, so that the full remote control coverage rate is reduced, the operation time of the equipment is too long, and the overhaul working period is seriously influenced; 2) The safety of the power grid excessively depends on the experience of a monitor to prevent misoperation events, and potential safety hazards such as misoperation caused by fatigue of staff and the like exist; 3) The remote control operation is regulated and controlled to realize the operation of the isolation disconnecting link, the problem that the logic error prevention function at the station end still has insufficient topological error prevention rule exists, and the real-time information monitoring has a dead zone in the operation process, so that the error prevention mechanism cannot meet the seamless closed loop management requirement of the full chain. The remote sequential control operation can effectively solve the problems, and the current sequential control mode of the transformer substation is partially studied, but the remote sequential control operation of the transformer substation still needs to be further optimized, especially in the aspects of operation instruction generation, scheduling planning and the like. The optimal operating strategy under different equipment types and operating conditions needs to be considered, and the running environment which is changed continuously needs to be self-adaptive. Aiming at the problem, the invention provides a one-key sequential control method and a one-key sequential control system for a power distribution network, which realize the instant control and monitoring of electric equipment of a transformer substation through self-adaptive strategy generation, avoid the time delay of manual operation and improve the operation efficiency and the safety of the transformer substation.
Disclosure of Invention
In view of the above, the present invention provides a one-key sequential control method for a power distribution network, which aims to: 1) The method comprises the steps of collecting and calculating operation load sequences of different electric equipment in a power distribution network to form an operation load sequence of a transformer substation, carrying out coding representation on the operation load sequence by combining time sequence information of the operation load, carrying out attention calculation by combining sparsity of coding, improving robustness of a prediction operation load result to a sparse coding result, realizing operation load prediction of the transformer substation, constructing an objective function which enables the difference degree between the distribution load of the electric equipment and the prediction load and the fluctuation degree of the operation load sequence of the electric equipment after the distribution load to be minimum according to the prediction result, solving to obtain a load distribution scheme which enables the whole energy efficiency of the transformer substation to be optimal, and improving the distribution efficiency of the power distribution network; 2) And constructing an opening and closing parameter image information identification model to identify and obtain current opening and closing parameters of power distribution protection equipment corresponding to different electric equipment, generating corresponding control instructions according to a load distribution scheme and current opening and closing parameter information corresponding to the electric equipment, ensuring normal operation of each transformer substation in the power distribution network, avoiding the electric equipment with problems from affecting power utilization of other electric equipment, and realizing one-key sequential control management of the power distribution network.
In order to achieve the above purpose, the one-key sequential control method for the power distribution network provided by the invention comprises the following steps:
s1: the method comprises the steps of collecting running state information of each device of a transformer substation in a power distribution network, wherein the running state information comprises voltage and current information of each electric device and opening and closing state image information of distribution protection equipment;
s2: according to the running state information of each device in the transformer substation, calculating to obtain a transformer substation running load sequence;
s3: a substation operation load prediction model is constructed based on a supervised learning mode of a fused attention mechanism, and the substation operation load is predicted, wherein the substation operation load prediction model takes a substation operation load sequence as input and a predicted operation load as output;
s4: according to the operation load prediction result of the transformer substation, carrying out load distribution on the total load of the transformer substation according to the priority of the electric equipment, and obtaining a load distribution scheme which enables the overall energy efficiency of the transformer substation to be optimal;
s5: the method comprises the steps of constructing an opening and closing parameter image information identification model to identify current opening and closing parameters of power distribution protection equipment corresponding to different electric equipment, wherein the opening and closing parameter image information identification model takes current opening and closing state images of the power distribution protection equipment corresponding to different electric equipment as input and takes identified opening and closing parameters as output;
S6: and generating a corresponding control instruction according to the load distribution scheme and current switching-on and switching-off parameter information corresponding to the electric equipment, and sending the generated control instruction to the corresponding equipment for one-key sequential control.
As a further improvement of the present invention:
optionally, the step S1 of collecting operation state information of each device of the substation in the power distribution network includes:
the method comprises the steps of collecting operation state information of all equipment of a transformer substation in a power distribution network, wherein the transformer substation comprises electric equipment and power distribution protection equipment, and the collected operation state information of all the equipment of the transformer substation is as follows:
{X n ＝(X n (t 1 ),X n (t 2 ),...,X n (t h ),...,X n (t H ))|n∈[1,N]}
X n (t h )＝(U n (t h ),I n (t h ),M n (t h ))
wherein:
X n the method comprises the steps of representing an nth electric device in a transformer substation and an operation state information sequence corresponding to power distribution protection equipment, wherein N represents the total number of electric devices of electric energy transmitted by the transformer substation;
X n (t h ) Indicating that the nth electric equipment and corresponding power distribution protection equipment in transformer substation are at t h Time running state information including t of nth electric equipment in transformer substation h Time voltage information U n (t h ) Current information I n (t h ) And the switching-on and switching-off state image information M of the corresponding power distribution protection equipment n (t h )；
(t 1 ,t 2 ,...,t H ) And the acquisition time of the running state information of each device of the transformer substation in the power distribution network is represented. In an embodiment of the invention, t H Representing the current time;
in the embodiment of the invention, the transformer substation is used for receiving the electric energy of the power supply side of the power distribution network and transmitting the electric energy to a plurality of corresponding electric equipment, and the power distribution protection equipment is used for performing switching-off and switching-on control on the power transmission circuits of different electric equipment and protecting the power transmission circuits of different electric equipment.
Optionally, the operation load sequence of the substation is calculated in the step S2, including:
according to the operation state information of each device in the transformer substation, calculating to obtain a transformer substation operation load sequence, wherein the calculation flow of the transformer substation operation load sequence is as follows:
s21: obtaining energy consumption damage rates and power factors of different electric equipment, wherein the energy consumption damage rate of the nth electric equipment is alpha n The power factor is；
S22: calculating to obtain the load of each electric equipment of the transformer substation at different acquisition time, wherein the nth electric equipment is at t h The load of time is:
wherein:
Q n (t h ) The nth electric equipment is at t h Load of time, t h ∈[t 1 ,t H ]；
S23: the loads of the electric equipment are ordered according to the acquisition time sequence to form an operation load sequence of the electric equipment, and the operation load sequences of all the electric equipment form a substation operation load sequence, wherein the substation operation load sequence is as follows:
x＝(x(1),x(2),...,x(n),...,x(N)) T
x(n)＝(Q n (t 1 ),Q n (t 2 ),...,Q n (t h ),...,Q n (t H ))
Wherein:
x represents a substation operation load sequence;
x (n) represents the operation load sequence of the nth electric equipment in the transformer substation;
t represents the transpose.
Optionally, in the step S3, a substation operation load prediction model is constructed based on a supervised learning mode of a fused attention mechanism, including:
a substation operation load prediction model is constructed based on a supervised learning mode of a fused attention mechanism, the substation operation load is predicted by using the substation operation load prediction model to obtain a predicted operation load of the substation, the substation operation load prediction model takes a substation operation load sequence as input and the predicted operation load as output, wherein the substation operation load prediction model comprises an input layer, a coding mapping layer, an attention calculation layer and an output layer;
the input layer is used for receiving the operation load sequence of the transformer substation, the coding mapping layer is used for respectively coding and mapping the operation load sequences of different electric equipment in the operation load sequence of the transformer substation, the attention calculation layer is used for carrying out attention calculation on the coding mapping results, generating attention weighted operation load sequence coding mapping results of different electric equipment, the output layer is used for converting the attention weighted operation load sequence coding mapping results of the electric equipment into predicted operation loads, and the predicted operation loads of all the electric equipment are used as the predicted operation loads of the transformer substation to be output.
Optionally, in the step S3, predicting the operation load of the substation by using a substation operation load prediction model includes:
predicting the operation load of the transformer substation by using a prediction model of the operation load of the transformer substation, wherein the prediction process comprises the following steps:
s31: the input layer receives a substation operation load sequence x;
s32: the coding mapping layer respectively carries out coding mapping on the operation load sequences of different electric equipment in the operation load sequence x of the transformer substation, wherein the coding mapping formula of the operation load sequence x (n) is as follows:
wherein:
q n (t h ) Represents Q n (t h ) Is a result of the code mapping of (a);
y (n) represents the code mapping result of the operation load sequence x (n);
s33: the attention calculation layer performs attention calculation on the coding mapping result to generate attention weighted operation load sequence coding mapping results of different electric equipment, wherein the attention weighted operation load sequence coding mapping results of the nth electric equipment in the transformer substation are as follows:
Y(n)＝(P n (t 1 ),P n (t 2 ),...,P n (t h ),...,P n (t H ))
P n (t h )＝q n (t h )e n (h)
wherein:
e n (h) Representing the code mapping result q n (t h ) P is the concentration of n (t h ) Representing the code mapping result q n (t h ) Attention weighted results of (2);
y (n) represents the weighted attention of the nth electric equipment in the transformer substation and then the load sequence coding mapping result is operated;
exp (·) represents an exponential function that bases on the natural constant;
L represents Q n (t h ) The code mapping result q of (2) n (t h ) Is a length of (2);
W 1 ,W 2 representing an attention calculation weight;
s34: the output layer converts the weighted attention of the electric equipment into a predicted operation load, and outputs the predicted operation load of all the electric equipment as the predicted operation load of the transformer substation, wherein the predicted operation load of the transformer substation is as follows:
c＝(c(1),c(2),...,c(n),...,c(N))
c(n)＝Y(n)(W 3 ) T
wherein:
y (n) represents the weighted attention of the nth electric equipment in the transformer substation and then the load sequence coding mapping result is operated;
W 3 representing a prediction matrix, T representing a transpose;
c (n) represents the predicted operation load of the nth electric equipment in the transformer substation;
c represents the predicted operating load of the substation.
Optionally, in the step S4, load distribution is performed on the total load of the substation according to the priority of the electric equipment according to the prediction result of the operation load of the substation, including:
according to the operation load prediction result of the transformer substation, carrying out load distribution on the total load of the transformer substation according to the priority of the electric equipment, wherein the load distribution flow is as follows:
s41: constructing an optimal distribution objective function of the total load of the transformer substation:
ρ n ＝15％×(max(x(n))-min(x(n)))
θ＝(θ(1),θ(2),...,θ(n),...,θ(N))
x(n)＝(Q n (t 1 ),Q n (t 2 ),...,Q n (t h ),...,Q n (t H ))
wherein:
indicating the priority degree of the nth electric equipment; in the embodiment of the present invention, < > a->The larger the power consumption equipment is, the higher the priority of the power consumption equipment is;
Q n (t h ) The nth electric equipment is at t h Load of time, t h ∈[t 1 ,t H ]；
F (theta) represents an optimal distribution objective function of the total load of the transformer substation;
θ= (θ (1), θ (2), θ (N)) represents a load distribution result of N electric devices in the substation, and θ (N) represents a load distribution result of N electric devices in the substation;
sigma (x (n)) represents the standard deviation of the sequence x (n), sigma (x (n), θ (n)) represents the standard deviation of the sequence (x (n), θ (n)), max (x (n)) represents the maximum value in the sequence x (n), and min (x (n)) represents the minimum value in the sequence x (n);
the |c (n) -theta (n) | represents the degree of difference between the distribution load of the nth electric equipment and the predicted load,
the fluctuation degree of the running load sequence of the electric equipment after load distribution is represented;
ρ n representing control parameters;
s42: initializing parameter θ 0 ＝(θ 0 (1),θ 0 (2),...,θ 0 (n),...,θ 0 (N)), wherein the parameter satisfies the following threshold condition:
wherein:
sum represents the maximum load that the substation can distribute;
s43: setting the current iteration number of the parameter as D, setting the maximum iteration number as D, and setting the D-th iteration result of the parameter as theta d ＝(θ d (1),θ d (2),...,θ d (n),...,θ d (N)), the initial value of d is 0;
s44: and carrying out iterative updating on the parameters, wherein the iterative formula is as follows:
λ d+1 ＝λ d +grad(F(λ d ))||λ d -c||
wherein:
grad(F(θ d ) F (θ) d ) Is a gradient of (2); in the embodiment of the invention, the objective function F (theta) is optimally distributed on the total load of the transformer substation, and the theta is derived d Substituting the result to obtain F (θ) d ) Is a gradient of (2);
i represent L1 norm;
s45: let d=d+1, return to step S44 until d+1=d, and select the parameter with the largest iteration number and meeting the threshold condition as the load distribution scheme for optimizing the overall energy efficiency of the substation.
Optionally, constructing an opening and closing parameter image information identification model in the step S5 to identify and obtain current opening and closing parameters of power distribution protection devices corresponding to different electric equipment, including:
the method comprises the steps of constructing an opening and closing parameter image information identification model, wherein the opening and closing parameter image information identification model takes current opening and closing state images of distribution protection equipment corresponding to different electric equipment as input and takes identified opening and closing parameters as output, the opening and closing parameter image information identification model comprises an input layer, an image segmentation layer, a characteristic image generation layer and an output layer, the input layer is used for receiving the current opening and closing state images of the distribution protection equipment corresponding to different electric equipment, the image segmentation layer is used for carrying out segmentation processing on the current opening and closing state images to obtain a plurality of sub-images, the characteristic image generation layer is used for extracting characteristic vectors of the sub-images to form a characteristic image, and the output layer is used for carrying out mapping calculation on the characteristic image to identify the current opening and closing parameters of the distribution protection equipment corresponding to the electric equipment;
The current opening and closing parameters of the power distribution protection equipment corresponding to different electric equipment are identified by utilizing an opening and closing parameter image information identification model, wherein the current opening and closing parameter identification flow of the power distribution protection equipment corresponding to the nth electric equipment is as follows:
s51: an input layer receives a current opening and closing state image M of power distribution protection equipment corresponding to the nth electric equipment n (t H )；
S52: the image segmentation layer carries out segmentation processing on the current opening and closing state image to obtain a plurality of sub-images with the overlapping pixel number reaching S pixels of the adjacent images;
s53: the characteristic map generation layer adds the pixel points of the sub-images linearly, and the linear addition results of the pixel points of the sub-images are processed sequentially by adopting convolution kernels with different scales to obtain characteristic vectors of the sub-images; according to sonSequencing the sub-image feature vectors in the sequence of the images in the current opening and closing state image to form a current opening and closing state image M n (t H ) Corresponding characteristic diagram m n ；
S54: the output layer is used for carrying out mapping calculation on the feature map, and identifying and obtaining current opening and closing parameters of power distribution protection equipment corresponding to electric equipment, wherein the current opening and closing parameters of the nth electric equipment are as follows:
λ n ＝Softmax(W T m n )
wherein:
w represents a feature map conversion matrix;
Softmax(W T m n ) Representing W is T m n Converting the current opening and closing parameters into two-dimensional vectors, respectively corresponding to the probability of 1 or 0 of the current opening and closing parameters, and selecting the current opening and closing parameters with the highest probability for output;
λ n representing current opening and closing parameters of power distribution protection equipment corresponding to nth electric equipment, wherein lambda n =0 indicates that the power distribution protection device corresponding to the nth electric equipment is in a switching-off state, lambda n And the symbol 1 indicates that the power distribution protection device corresponding to the nth electric equipment is in a closing state.
Optionally, in the step S6, according to a load distribution scheme and switching-on/off parameter information corresponding to the electric equipment, a corresponding control instruction is generated to perform one-key sequential control, including:
generating a corresponding control instruction according to a load distribution scheme and switching-on and switching-off parameter information corresponding to electric equipment, and sending the generated control instruction to corresponding control equipment for one-key sequential control, wherein the control instruction generation flow of the nth electric equipment is as follows:
s61: acquiring a load distribution result theta of an nth electric device in a load distribution scheme * (n) opening and closing parameter lambda n ；
S62: if theta is * (n) exceeding a preset load threshold, generating a virtual parameter lambda * =1, and for virtual parameter λ * Switching-on and switching-off parameter lambda n Performing an exclusive nor operation, and if the operation result is 1, not performing the nth operation The switching-on and switching-off operation of the power distribution protection equipment corresponding to the electric equipment is performed, and if the operation result is 0, a switching-on and switching-off operation instruction of the power distribution protection equipment corresponding to the nth electric equipment is generated;
s63: if the brake-separating operation command is not generated, the load distribution result theta is calculated * And (n) generating a power transmission regulation instruction of the nth electric equipment.
In order to solve the above problems, the present invention provides a one-key sequential control system for a power distribution network, which is characterized in that the system comprises:
the load management module is used for collecting the running state information of each device of the transformer substation in the power distribution network, calculating to obtain a transformer substation running load sequence according to the running state information of each device of the transformer substation, constructing a transformer substation running load prediction model based on a supervision learning mode of a fused attention mechanism, predicting the running load of the transformer substation, and distributing the load of the total load of the transformer substation according to the priority of electric equipment according to the running load prediction result of the transformer substation;
the switching-on/off control module is used for constructing a switching-on/off parameter image information identification model to identify and obtain current switching-on/off parameters of power distribution protection equipment corresponding to different electric equipment;
the command control device is used for generating corresponding control commands according to the load distribution scheme and current switching-on and switching-off parameter information corresponding to the electric equipment, and sending the generated control commands to the corresponding equipment for one-key sequential control.
In order to solve the above-mentioned problems, the present invention also provides an electronic apparatus including:
a memory storing at least one instruction;
the communication interface is used for realizing the communication of the electronic equipment; and
And the processor executes the instructions stored in the memory to realize the one-key sequential control method for the power distribution network.
In order to solve the above-mentioned problems, the present invention further provides a computer readable storage medium, where at least one instruction is stored, where the at least one instruction is executed by a processor in an electronic device to implement the one-key sequential control method for a power distribution network.
Compared with the prior art, the invention provides a one-key sequential control method for a power distribution network, which has the following advantages:
firstly, the scheme provides a transformer substation load prediction and distribution mode, and a transformer substation operation load prediction model is utilized to predict the transformer substation operation load, wherein the prediction flow is as follows: the input layer receives a substation operation load sequence x; the coding mapping layer respectively carries out coding mapping on the operation load sequences of different electric equipment in the operation load sequence x of the transformer substation, wherein the coding mapping formula of the operation load sequence x (n) is as follows:
y(n)＝(q n (t 1 ),q n (t 2 ),...,q n (t h ),...,q n (t H ))
Wherein: q n (th) represents Q n (t h ) Is a result of the code mapping of (a); y (n) represents the code mapping result of the operation load sequence x (n); the attention calculation layer performs attention calculation on the coding mapping result to generate attention weighted operation load sequence coding mapping results of different electric equipment, wherein the attention weighted operation load sequence coding mapping results of the nth electric equipment in the transformer substation are as follows:
Y(n)＝(P n (t 1 ),P n (t 2 ),...,P n (t h ),...,P n (t H ))
P n (t h )＝q n (t h )e n (h)
wherein: e, e n (h) Representing the code mapping result q n (t h ) Attention of (a)，P n (t h ) Representing the code mapping result q n (t h ) Attention weighted results of (2); y (n) represents the weighted attention of the nth electric equipment in the transformer substation and then the load sequence coding mapping result is operated; exp (·) represents an exponential function that bases on the natural constant; l represents Q n (t h ) The code mapping result q of (2) n (t h ) Is a length of (2); w (W) 1 ,W 2 Representing an attention calculation weight; the output layer converts the weighted attention of the electric equipment into a predicted operation load, and outputs the predicted operation load of all the electric equipment as the predicted operation load of the transformer substation, wherein the predicted operation load of the transformer substation is as follows:
c＝(c(1),c(2),...,c(n),...,c(N))
c(n)＝Y(n)(W 3 ) T
wherein: y (n) represents the weighted attention of the nth electric equipment in the transformer substation and then the load sequence coding mapping result is operated; w (W) 3 Representing a prediction matrix, T representing a transpose; c (n) represents the predicted operation load of the nth electric equipment in the transformer substation; c represents the predicted operating load of the substation. According to the operation load prediction result of the transformer substation, carrying out load distribution on the total load of the transformer substation according to the priority of the electric equipment, wherein the load distribution flow is as follows: constructing an optimal distribution objective function of the total load of the transformer substation:
ρ n ＝15％×(max(x(n))-min(x(n)))
θ＝(θ(1),θ(2),...,θ(n),...,θ(N))
x(n)＝(Q n (t 1 ),Q n (t 2 ),...,Q n (th),...,Q n (t H ))
wherein:indicating the priority degree of the nth electric equipment; q (Q) n (t h ) The nth electric equipment is at t h Load of time, t h ∈[t 1 ,t H ]The method comprises the steps of carrying out a first treatment on the surface of the F (theta) represents an optimal distribution objective function of the total load of the transformer substation; θ= (θ (1), θ (2), θ (N)) represents a load distribution result of N electric devices in the substation, and θ (N) represents a load distribution result of N electric devices in the substation; sigma (x (n)) represents the standard deviation of the sequence x (n), sigma (x (n), θ (n)) represents the standard deviation of the sequence (x (n), θ (n)), max (x (n)) represents the maximum value in the sequence x (n), and min (x (n)) represents the minimum value in the sequence x (n); the |c (n) -theta (n) | represents the difference degree between the distribution load and the prediction load of the nth electric equipment, and the load is +.>The fluctuation degree of the running load sequence of the electric equipment after load distribution is represented; ρ n Representing the control parameters. According to the scheme, the operation load sequences of different electric equipment in the power distribution network are collected and calculated to form the operation load sequences of the transformer substation, the operation load sequences are coded and represented by combining time sequence information of the operation loads, attention calculation is conducted by combining sparsity of the codes, robustness of a prediction operation load result to the sparse coding result is improved, the operation load prediction of the transformer substation is achieved, an objective function which enables the difference degree between the distribution load of the electric equipment and the prediction load and the fluctuation degree of the operation load sequences of the electric equipment after the distribution load is minimized is constructed according to the prediction result, a load distribution scheme which enables the whole energy efficiency of the transformer substation to be optimal is obtained through solving, and the distribution efficiency of the power distribution network is improved.
Meanwhile, the scheme provides a power distribution network control instruction generation mode, and current opening and closing parameters of power distribution protection equipment corresponding to different electric equipment are identified and obtained by utilizing an opening and closing parameter image information identification model, wherein the current opening and closing parameter identification flow of the power distribution protection equipment corresponding to the nth electric equipment is as follows: an input layer receives a current opening and closing state image M of power distribution protection equipment corresponding to the nth electric equipment n (t H ) The method comprises the steps of carrying out a first treatment on the surface of the The image segmentation layer carries out segmentation processing on the current opening and closing state image to obtain a plurality of sub-images with the overlapping pixel number reaching S pixels of the adjacent images; feature graphics primitiveLayering to linearly add the pixel points of the sub-images, and sequentially processing the linear addition results of the pixel points of the sub-images by adopting convolution kernels with different scales to obtain feature vectors of the sub-images; sequencing the sub-image feature vectors according to the sequence of the sub-images in the current opening and closing state image to form a current opening and closing state image M n (t H ) Corresponding characteristic diagram m n The method comprises the steps of carrying out a first treatment on the surface of the The output layer is used for carrying out mapping calculation on the feature map, and identifying and obtaining current opening and closing parameters of power distribution protection equipment corresponding to electric equipment, wherein the current opening and closing parameters of the nth electric equipment are as follows:
λ n ＝Softmax(W T m n )
Wherein: w represents a feature map conversion matrix; softmax (W) T m n ) Representing W is T m n Converting the current opening and closing parameters into two-dimensional vectors, respectively corresponding to the probability of 1 or 0 of the current opening and closing parameters, and selecting the current opening and closing parameters with the highest probability for output; lambda (lambda) n Representing current opening and closing parameters of power distribution protection equipment corresponding to nth electric equipment, wherein lambda n =0 indicates that the power distribution protection device corresponding to the nth electric equipment is in a switching-off state, lambda n And the symbol 1 indicates that the power distribution protection device corresponding to the nth electric equipment is in a closing state. Generating a corresponding control instruction according to a load distribution scheme and switching-on and switching-off parameter information corresponding to electric equipment, and sending the generated control instruction to corresponding control equipment for one-key sequential control, wherein the control instruction generation flow of the nth electric equipment is as follows: acquiring a load distribution result theta of an nth electric device in a load distribution scheme * (n) opening and closing parameter lambda n The method comprises the steps of carrying out a first treatment on the surface of the If theta is * (n) exceeding a preset load threshold, generating a virtual parameter lambda * =1, and for virtual parameter λ * Switching-on and switching-off parameter lambda n Performing an exclusive OR operation, if the operation result is 1, not performing switching-on/off operation of the power distribution protection equipment corresponding to the nth electric equipment, and if the operation result is 0, generating a switching-off operation instruction of the power distribution protection equipment corresponding to the nth electric equipment; if the brake-separating operation command is not generated, the load distribution result theta is calculated * (n) generating the power delivered by the nth powered deviceAnd (5) regulating and controlling the instruction. According to the scheme, the current opening and closing parameters of the distribution protection equipment corresponding to different electric equipment are obtained through identification by constructing an opening and closing parameter image information identification model, corresponding control instructions are generated according to the load distribution scheme and the current opening and closing parameter information corresponding to the electric equipment, normal operation of each transformer substation in the distribution network is guaranteed, the problem that the electric equipment affects power utilization of other electric equipment is avoided, and one-key sequential control management of the distribution network is achieved.
Drawings
Fig. 1 is a schematic flow chart of a one-key sequential control method for a power distribution network according to an embodiment of the present invention;
FIG. 2 is a functional block diagram of a push-to-talk control system for a power distribution network according to one embodiment of the present invention;
in fig. 2: 100 is used for a one-key sequential control system of a power distribution network, 101 is used for a load management module, 102 is used for a switching-on/off control module, and 103 is used for an instruction control device;
fig. 3 is a schematic structural diagram of an electronic device for implementing a one-key sequential control method for a power distribution network according to an embodiment of the present invention.
In fig. 3: 1 an electronic device, 10 a processor, 11 a memory, 12 a program, 13 a communication interface;
the achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the application provides a one-key sequential control method for a power distribution network. The execution subject of the one-key sequential control method for the power distribution network comprises at least one of a server, a terminal and the like which can be configured to execute the method provided by the embodiment of the application. In other words, the one-key sequential control method for the distribution network may be performed by software or hardware installed in a terminal device or a server device, and the software may be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like.
Example 1:
s1: and acquiring running state information of each device of the transformer substation in the power distribution network, wherein the running state information comprises voltage and current information of each electric equipment and opening and closing state image information of distribution protection equipment.
And in the step S1, the operation state information of each device of the transformer substation in the power distribution network is acquired, and the method comprises the following steps:
the method comprises the steps of collecting operation state information of all equipment of a transformer substation in a power distribution network, wherein the transformer substation comprises electric equipment and power distribution protection equipment, and the collected operation state information of all the equipment of the transformer substation is as follows:
{X n ＝(X n (t 1 ),X n (t 2 ),...,X n (t h ),...,X n (t H ))|n∈[1,N]}
X n (t h )＝(U n (t h ),I n (t h ),M n (t h ))
Wherein:
X n the method comprises the steps of representing an nth electric device in a transformer substation and an operation state information sequence corresponding to power distribution protection equipment, wherein N represents the total number of electric devices of electric energy transmitted by the transformer substation;
X n (t h ) Indicating that the nth electric equipment and corresponding power distribution protection equipment in transformer substation are at t h Time running state information including t of nth electric equipment in transformer substation h Time voltage information U n (t h ) Current information I n (t h ) And the switching-on and switching-off state image information M of the corresponding power distribution protection equipment n (t h )；
(t 1 ,t 2 ,...,t H ) And the acquisition time of the running state information of each device of the transformer substation in the power distribution network is represented.
S2: and calculating to obtain a substation operation load sequence according to the operation state information of each device in the substation.
And step S2, calculating to obtain a substation operation load sequence, wherein the step S comprises the following steps:
according to the operation state information of each device in the transformer substation, calculating to obtain a transformer substation operation load sequence, wherein the calculation flow of the transformer substation operation load sequence is as follows:
s21: obtaining energy consumption damage rates and power factors of different electric equipment, wherein the energy consumption damage rate of the nth electric equipment is alpha n The power factor is；
S22: calculating to obtain the load of each electric equipment of the transformer substation at different acquisition time, wherein the nth electric equipment is at t h The load of time is:
wherein:
Q n (t h ) The nth electric equipment is at t h Load of time, t h ∈[t 1 ,t H ]；
S23: the loads of the electric equipment are ordered according to the acquisition time sequence to form an operation load sequence of the electric equipment, and the operation load sequences of all the electric equipment form a substation operation load sequence, wherein the substation operation load sequence is as follows:
x＝(x(1),x(2),...,x(n),...,x(N)) T
x(n)＝(Q n (t 1 ),Q n (t 2 ),...,Q n (t h ),...,Q n (t H ))
wherein:
x represents a substation operation load sequence;
x (n) represents the operation load sequence of the nth electric equipment in the transformer substation;
t represents the transpose.
S3: and constructing a substation operation load prediction model based on a supervised learning mode of a fused attention mechanism, and predicting the substation operation load, wherein the substation operation load prediction model takes a substation operation load sequence as input and the predicted operation load as output.
In the step S3, a substation operation load prediction model is constructed based on a supervised learning mode of a fusion attention mechanism, and the method comprises the following steps:
a substation operation load prediction model is constructed based on a supervised learning mode of a fused attention mechanism, the substation operation load is predicted by using the substation operation load prediction model to obtain a predicted operation load of the substation, the substation operation load prediction model takes a substation operation load sequence as input and the predicted operation load as output, wherein the substation operation load prediction model comprises an input layer, a coding mapping layer, an attention calculation layer and an output layer;
The input layer is used for receiving the operation load sequence of the transformer substation, the coding mapping layer is used for respectively coding and mapping the operation load sequences of different electric equipment in the operation load sequence of the transformer substation, the attention calculation layer is used for carrying out attention calculation on the coding mapping results, generating attention weighted operation load sequence coding mapping results of different electric equipment, the output layer is used for converting the attention weighted operation load sequence coding mapping results of the electric equipment into predicted operation loads, and the predicted operation loads of all the electric equipment are used as the predicted operation loads of the transformer substation to be output.
And in the step S3, the operation load of the transformer substation is predicted by using a prediction model of the operation load of the transformer substation, and the method comprises the following steps:
predicting the operation load of the transformer substation by using a prediction model of the operation load of the transformer substation, wherein the prediction process comprises the following steps:
s31: the input layer receives a substation operation load sequence x;
s32: the coding mapping layer respectively carries out coding mapping on the operation load sequences of different electric equipment in the operation load sequence x of the transformer substation, wherein the coding mapping formula of the operation load sequence x (n) is as follows:
y(n)＝(q n (t 1 ),q n (t 2 ),...,q n (t h ),...,q n (t H ))
wherein:
q n (t h ) Represents Q n (t h ) Is a result of the code mapping of (a);
y (n) represents the code mapping result of the operation load sequence x (n);
S33: the attention calculation layer performs attention calculation on the coding mapping result to generate attention weighted operation load sequence coding mapping results of different electric equipment, wherein the attention weighted operation load sequence coding mapping results of the nth electric equipment in the transformer substation are as follows:
Y(n)＝(P n (t 1 ),P n (t 2 ),...,P n (t h ),...,P n (t H ))
P n (t h )＝q n (t h )e n (h)
wherein:
e n (h) Representing the code mapping result q n (t h ) P is the concentration of n (t h ) Representing the code mapping result q n (t h ) Attention weighted results of (2);
y (n) represents the weighted attention of the nth electric equipment in the transformer substation and then the load sequence coding mapping result is operated;
exp (·) represents an exponential function that bases on the natural constant;
l represents Q n (t h ) The code mapping result q of (2) n (t h ) Is a length of (2);
W 1 ,W 2 representing an attention calculation weight;
s34: the output layer converts the weighted attention of the electric equipment into a predicted operation load, and outputs the predicted operation load of all the electric equipment as the predicted operation load of the transformer substation, wherein the predicted operation load of the transformer substation is as follows:
c＝(c(1),c(2),...,c(n),...,c(N))
c(n)＝Y(n)(W 3 ) T
wherein:
y (n) represents the weighted attention of the nth electric equipment in the transformer substation and then the load sequence coding mapping result is operated;
W 3 representing a prediction matrix, T representing a transpose;
c (n) represents the predicted operation load of the nth electric equipment in the transformer substation;
c represents the predicted operating load of the substation.
S4: and according to the operation load prediction result of the transformer substation, carrying out load distribution on the total load of the transformer substation according to the priority of the electric equipment, and obtaining a load distribution scheme which enables the overall energy efficiency of the transformer substation to be optimal.
And in the step S4, according to the operation load prediction result of the transformer substation, the load distribution is carried out on the total load of the transformer substation according to the priority of the electric equipment, and the method comprises the following steps:
according to the operation load prediction result of the transformer substation, carrying out load distribution on the total load of the transformer substation according to the priority of the electric equipment, wherein the load distribution flow is as follows:
s41: constructing an optimal distribution objective function of the total load of the transformer substation:
ρ n ＝15％×(max(x(n))-min(x(n)))
θ＝(θ(1),θ(2),...,θ(n),...,θ(N))
x(n)＝(Q n (t 1 ),Q n (t 2 ),...,Q n (t h ),...,Q n (t H ))
wherein:
indicating the priority degree of the nth electric equipment; in the embodiment of the present invention, < > a->The larger the power consumption equipment is, the higher the priority of the power consumption equipment is;
Q n (t h ) The nth electric equipment is at t h Load of time, t h ∈[t 1 ,t H ]；
F (theta) represents an optimal distribution objective function of the total load of the transformer substation;
θ= (θ (1), θ (2), θ (N)) represents a load distribution result of N electric devices in the substation, and θ (N) represents a load distribution result of N electric devices in the substation;
sigma (x (n)) represents the standard deviation of the sequence x (n), sigma (x (n), θ (n)) represents the standard deviation of the sequence (x (n), θ (n)), max (x (n)) represents the maximum value in the sequence x (n), and min (x (n)) represents the minimum value in the sequence x (n);
The |c (n) -theta (n) | represents the degree of difference between the distribution load of the nth electric equipment and the predicted load,
the fluctuation degree of the running load sequence of the electric equipment after load distribution is represented;
ρ n representing control parameters;
s42: initializing parameter θ 0 ＝(θ 0 (1),θ 0 (2),...,θ 0 (n),...,θ 0 (N)), wherein the parameter satisfies the following threshold condition:
wherein:
sum represents the maximum load that the substation can distribute;
s43: setting the current iteration number of the parameter as d and the maximum iteration number as dD, the D iteration result of the parameter is theta d ＝(θ d (1),θ d (2),...,θ d (n),...,θ d (N)), the initial value of d is 0;
s44: and carrying out iterative updating on the parameters, wherein the iterative formula is as follows:
θ d+1 ＝θ d +grad(F(θ d ))||θ d -c||
wherein:
grad(F(θ d ) F (θ) d ) Is a gradient of (2); in the embodiment of the invention, the objective function F (theta) is optimally distributed on the total load of the transformer substation, and the theta is derived d Substituting the result to obtain F (θ) d ) Is a gradient of (2);
i represent L1 norm;
s45: let d=d+1, return to step S44 until d+1=d, and select the parameter with the largest iteration number and meeting the threshold condition as the load distribution scheme for optimizing the overall energy efficiency of the substation.
S5: and constructing an opening and closing parameter image information identification model to identify current opening and closing parameters of the power distribution protection equipment corresponding to different electric equipment, wherein the opening and closing parameter image information identification model takes current opening and closing state images of the power distribution protection equipment corresponding to different electric equipment as input and takes the identified opening and closing parameters as output.
And S5, constructing an opening and closing parameter image information identification model to identify and obtain current opening and closing parameters of distribution protection equipment corresponding to different electric equipment, wherein the method comprises the following steps:
the method comprises the steps of constructing an opening and closing parameter image information identification model, wherein the opening and closing parameter image information identification model takes current opening and closing state images of distribution protection equipment corresponding to different electric equipment as input and takes identified opening and closing parameters as output, the opening and closing parameter image information identification model comprises an input layer, an image segmentation layer, a characteristic image generation layer and an output layer, the input layer is used for receiving the current opening and closing state images of the distribution protection equipment corresponding to different electric equipment, the image segmentation layer is used for carrying out segmentation processing on the current opening and closing state images to obtain a plurality of sub-images, the characteristic image generation layer is used for extracting characteristic vectors of the sub-images to form a characteristic image, and the output layer is used for carrying out mapping calculation on the characteristic image to identify the current opening and closing parameters of the distribution protection equipment corresponding to the electric equipment;
the current opening and closing parameters of the power distribution protection equipment corresponding to different electric equipment are identified by utilizing an opening and closing parameter image information identification model, wherein the current opening and closing parameter identification flow of the power distribution protection equipment corresponding to the nth electric equipment is as follows:
S51: an input layer receives a current opening and closing state image M of power distribution protection equipment corresponding to the nth electric equipment n (t H )；
S52: the image segmentation layer carries out segmentation processing on the current opening and closing state image to obtain a plurality of sub-images with the overlapping pixel number reaching S pixels of the adjacent images;
s53: the characteristic map generation layer adds the pixel points of the sub-images linearly, and the linear addition results of the pixel points of the sub-images are processed sequentially by adopting convolution kernels with different scales to obtain characteristic vectors of the sub-images; sequencing the sub-image feature vectors according to the sequence of the sub-images in the current opening and closing state image to form a current opening and closing state image M n (t H ) Corresponding characteristic diagram m n ；
S54: the output layer is used for carrying out mapping calculation on the feature map, and identifying and obtaining current opening and closing parameters of power distribution protection equipment corresponding to electric equipment, wherein the current opening and closing parameters of the nth electric equipment are as follows:
λ n ＝Softmax(W T m n )
wherein:
w represents a feature map conversion matrix;
Softmax(W T m n ) Representing W is T m n Converting the current opening and closing parameters into two-dimensional vectors, respectively corresponding to the probability of 1 or 0 of the current opening and closing parameters, and selecting the current opening and closing parameters with the highest probability for output;
λ n representing current opening and closing parameters of power distribution protection equipment corresponding to nth electric equipment, wherein lambda n =0 represents the firstThe distribution protection equipment corresponding to n electric equipment is in a switching-off state, lambda n And the symbol 1 indicates that the power distribution protection device corresponding to the nth electric equipment is in a closing state.
S6: and generating a corresponding control instruction according to the load distribution scheme and current switching-on and switching-off parameter information corresponding to the electric equipment, and sending the generated control instruction to the corresponding equipment for one-key sequential control.
In the step S6, corresponding control instructions are generated according to the load distribution scheme and the switching-on/off parameter information corresponding to the electric equipment to perform one-key sequential control, including:
generating a corresponding control instruction according to a load distribution scheme and switching-on and switching-off parameter information corresponding to electric equipment, and sending the generated control instruction to corresponding control equipment for one-key sequential control, wherein the control instruction generation flow of the nth electric equipment is as follows:
s61: acquiring a load distribution result theta of an nth electric device in a load distribution scheme * (n) opening and closing parameter lambda n ；
S62: if theta is * (n) exceeding a preset load threshold, generating a virtual parameter lambda * =1, and for virtual parameter λ * Switching-on and switching-off parameter lambda n Performing an exclusive OR operation, if the operation result is 1, not performing switching-on/off operation of the power distribution protection equipment corresponding to the nth electric equipment, and if the operation result is 0, generating a switching-off operation instruction of the power distribution protection equipment corresponding to the nth electric equipment;
S63: if the brake-separating operation command is not generated, the load distribution result theta is calculated * And (n) generating a power transmission regulation instruction of the nth electric equipment.
Example 2:
fig. 2 is a functional block diagram of a one-touch sequential control system for a power distribution network according to an embodiment of the present invention, which may implement the one-touch sequential control method for a power distribution network in embodiment 1.
The one-touch sequential control system 100 for a power distribution network of the present invention may be installed in an electronic device. Depending on the functions implemented, the one-key sequential control system for a power distribution network may include a load management module 101, an opening and closing control module 102, and an instruction control device 103. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
The load management module 101 is configured to collect operation state information of each device of a substation in the power distribution network, calculate to obtain a substation operation load sequence according to the operation state information of each device in the substation, construct a substation operation load prediction model based on a supervised learning mode of a fused attention mechanism, predict the substation operation load, and distribute loads to the total load of the substation according to the substation operation load prediction result and the priority of electric equipment;
The switching-on/off control module 102 is used for constructing a switching-on/off parameter image information identification model to identify and obtain current switching-on/off parameters of power distribution protection equipment corresponding to different electric equipment;
the instruction control device 103 is configured to generate a corresponding control instruction according to the load distribution scheme and current switching parameter information corresponding to the electric device, and send the generated control instruction to the corresponding device for one-key sequential control.
In detail, the modules in the one-key sequential control system 100 for a power distribution network in the embodiment of the present invention use the same technical means as the one-key sequential control method for a power distribution network described in fig. 1, and can produce the same technical effects, which are not described herein.
Example 3:
fig. 3 is a schematic structural diagram of an electronic device for implementing a one-touch sequential control method for a power distribution network according to an embodiment of the present invention.
The electronic device 1 may comprise a processor 10, a memory 11, a communication interface 13 and a bus, and may further comprise a computer program, such as program 12, stored in the memory 11 and executable on the processor 10.
The memory 11 includes at least one type of readable storage medium, including flash memory, a mobile hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device 1, such as a removable hard disk of the electronic device 1. The memory 11 may in other embodiments also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic device 1. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device 1. The memory 11 may be used not only for storing application software installed in the electronic device 1 and various types of data, such as codes of the program 12, but also for temporarily storing data that has been output or is to be output.
The processor 10 may be comprised of integrated circuits in some embodiments, for example, a single packaged integrated circuit, or may be comprised of multiple integrated circuits packaged with the same or different functions, including one or more central processing units (Central Processing unit, CPU), microprocessors, digital processing chips, graphics processors, combinations of various control chips, and the like. The processor 10 is a Control Unit (Control Unit) of the electronic device, connects respective parts of the entire electronic device using various interfaces and lines, executes or executes programs or modules (a program 12 for realizing one-touch Control for a power distribution network, etc.) stored in the memory 11, and invokes data stored in the memory 11 to perform various functions of the electronic device 1 and process the data.
The communication interface 13 may comprise a wired interface and/or a wireless interface (e.g. WI-FI interface, bluetooth interface, etc.), typically used to establish a communication connection between the electronic device 1 and other electronic devices and to enable connection communication between internal components of the electronic device.
The bus may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory 11 and at least one processor 10 etc.
Fig. 3 shows only an electronic device with components, it being understood by a person skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or may combine certain components, or may be arranged in different components.
For example, although not shown, the electronic device 1 may further include a power source (such as a battery) for supplying power to each component, and preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management, and the like are implemented through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device 1 may further include various sensors, bluetooth modules, wi-Fi modules, etc., which will not be described herein.
The electronic device 1 may optionally further comprise a user interface, which may be a Display, an input unit, such as a Keyboard (Keyboard), or a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device 1 and for displaying a visual user interface.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
It should be noted that, the foregoing reference numerals of the embodiments of the present invention are merely for describing the embodiments, and do not represent the advantages and disadvantages of the embodiments. And the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, apparatus, article or method that comprises the element.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (9)
1. A one-touch sequential control method for a power distribution network, the method comprising:
s1: the method comprises the steps of collecting running state information of each device of a transformer substation in a power distribution network, wherein the running state information comprises voltage and current information of each electric device and opening and closing state image information of distribution protection equipment;
s2: according to the running state information of each device in the transformer substation, calculating to obtain a transformer substation running load sequence;
s3: a substation operation load prediction model is constructed based on a supervised learning mode of a fused attention mechanism, and the substation operation load is predicted, wherein the substation operation load prediction model takes a substation operation load sequence as input and a predicted operation load as output;
s4: according to the operation load prediction result of the transformer substation, carrying out load distribution on the total load of the transformer substation according to the priority of the electric equipment, and obtaining a load distribution scheme which enables the overall energy efficiency of the transformer substation to be optimal;
S5: the method comprises the steps of constructing an opening and closing parameter image information identification model to identify current opening and closing parameters of power distribution protection equipment corresponding to different electric equipment, wherein the opening and closing parameter image information identification model takes current opening and closing state images of the power distribution protection equipment corresponding to different electric equipment as input and takes identified opening and closing parameters as output;
s6: and generating a corresponding control instruction according to the load distribution scheme and current switching-on and switching-off parameter information corresponding to the electric equipment, and sending the generated control instruction to the corresponding equipment for one-key sequential control.
2. The one-key sequential control method for a power distribution network according to claim 1, wherein the step S1 of collecting operation state information of each device of a substation in the power distribution network includes:
the method comprises the steps of collecting operation state information of all equipment of a transformer substation in a power distribution network, wherein the transformer substation comprises electric equipment and power distribution protection equipment, and the collected operation state information of all the equipment of the transformer substation is as follows:
{X n ＝(X n (t 1 ),X n (t 2 ),...,X n (t h ),...,X n (t H ))|n∈[1,N]}
X n (t h )＝(U n (t h ),I n (t h ),M n (t h ))
wherein:
X n representing nth consumer in substation and corresponding power distributionThe operation state information sequence of the protection equipment, wherein N represents the total number of electric equipment of electric energy transmitted by the transformer substation;
X n (t h ) Indicating that the nth electric equipment and corresponding power distribution protection equipment in transformer substation are at t h Time running state information including t of nth electric equipment in transformer substation h Time voltage information U n (t h ) Current information I n (t h ) And the switching-on and switching-off state image information M of the corresponding power distribution protection equipment n (t h )；
(t 1 ,t 2 ,...,t H ) And the acquisition time of the running state information of each device of the transformer substation in the power distribution network is represented.
3. The one-key sequential control method for a power distribution network according to claim 2, wherein in the step S2, a substation operation load sequence is calculated according to operation state information of each device in the substation, and the method comprises the following steps:
according to the operation state information of each device in the transformer substation, calculating to obtain a transformer substation operation load sequence, wherein the calculation flow of the transformer substation operation load sequence is as follows:
s21: obtaining energy consumption damage rates and power factors of different electric equipment, wherein the energy consumption damage rate of the nth electric equipment is alpha n The power factor is
S22: calculating to obtain the load of each electric equipment of the transformer substation at different acquisition time, wherein the nth electric equipment is at t h The load of time is:
wherein:
Q n (t h ) The nth electric equipment is at t h Load of time, t h ∈[t 1 ,t H ]；
S23: the loads of the electric equipment are ordered according to the acquisition time sequence to form an operation load sequence of the electric equipment, and the operation load sequences of all the electric equipment form a substation operation load sequence, wherein the substation operation load sequence is as follows:
x＝(x(1),x(2),...,x(n),...,x(N)) T
x(n)＝(Q n (t 1 ),Q n (t 2 ),...,Q n (t h ),...,Q n (t H ))
Wherein:
x represents a substation operation load sequence;
x (n) represents the operation load sequence of the nth electric equipment in the transformer substation;
t represents the transpose.
4. The one-key sequential control method for a power distribution network according to claim 1, wherein the step S3 of constructing a substation operation load prediction model based on a supervised learning mode of a fused attention mechanism comprises:
a substation operation load prediction model is constructed based on a supervised learning mode of a fused attention mechanism, the substation operation load is predicted by using the substation operation load prediction model to obtain a predicted operation load of the substation, the substation operation load prediction model takes a substation operation load sequence as input and the predicted operation load as output, wherein the substation operation load prediction model comprises an input layer, a coding mapping layer, an attention calculation layer and an output layer;
the input layer is used for receiving the operation load sequence of the transformer substation, the coding mapping layer is used for respectively coding and mapping the operation load sequences of different electric equipment in the operation load sequence of the transformer substation, the attention calculation layer is used for carrying out attention calculation on the coding mapping results, generating attention weighted operation load sequence coding mapping results of different electric equipment, the output layer is used for converting the attention weighted operation load sequence coding mapping results of the electric equipment into predicted operation loads, and the predicted operation loads of all the electric equipment are used as the predicted operation loads of the transformer substation to be output.
5. The one-key sequential control method for power distribution network according to claim 4, wherein the predicting the operation load of the substation by using the operation load prediction model of the substation in step S3 includes:
predicting the operation load of the transformer substation by using a prediction model of the operation load of the transformer substation, wherein the prediction process comprises the following steps:
s31: the input layer receives a substation operation load sequence x;
s32: the coding mapping layer respectively carries out coding mapping on the operation load sequences of different electric equipment in the operation load sequence x of the transformer substation, wherein the coding mapping formula of the operation load sequence x (n) is as follows:
y(n)＝(q n (t 1 ),q n (t 2 ),...,q n (t h ),...,q n (t H ))
wherein:
q n (t h ) Represents Q n (t h ) Is a result of the code mapping of (a);
y (n) represents the code mapping result of the operation load sequence x (n);
s33: the attention calculation layer performs attention calculation on the coding mapping result to generate attention weighted operation load sequence coding mapping results of different electric equipment, wherein the attention weighted operation load sequence coding mapping results of the nth electric equipment in the transformer substation are as follows:
Y(n)＝(P n (t 1 ),P n (t 2 ),...,P n (t h ),...,P n (t H ))
P n (t h )＝q n (t h )e n (h)
wherein:
e n (h) Representing the code mapping result q n (t h ) P is the concentration of n (t h ) Representing the code mapping result q n (t h ) Attention weighted results of (2);
y (n) represents the weighted attention of the nth electric equipment in the transformer substation and then the load sequence coding mapping result is operated;
exp (·) represents an exponential function that bases on the natural constant;
l represents Q n (t h ) The code mapping result q of (2) n (t h ) Is a length of (2);
W 1 ,W 2 representing an attention calculation weight;
s34: the output layer converts the weighted attention of the electric equipment into a predicted operation load, and outputs the predicted operation load of all the electric equipment as the predicted operation load of the transformer substation, wherein the predicted operation load of the transformer substation is as follows:
c＝(c(1),c(2),...,c(n),...,c(N))
c(n)＝Y(n)(W 3 ) T
wherein:
y (n) represents the weighted attention of the nth electric equipment in the transformer substation and then the load sequence coding mapping result is operated;
W 3 representing a prediction matrix, T representing a transpose;
c (n) represents the predicted operation load of the nth electric equipment in the transformer substation;
c represents the predicted operating load of the substation.
6. The one-key sequential control method for power distribution network according to claim 5, wherein in step S4, according to the operation load prediction result of the substation, load distribution is performed on the total load of the substation according to the priority of the electric equipment, and the method comprises the following steps:
according to the operation load prediction result of the transformer substation, carrying out load distribution on the total load of the transformer substation according to the priority of the electric equipment, wherein the load distribution flow is as follows:
s41: constructing an optimal distribution objective function of the total load of the transformer substation:
ρ n ＝15％×(max(x(n))-min(x(n)))
θ＝(θ(1),θ(2),...,θ(n),...,θ(N))
x(n)＝(Q n (t 1 ),Q n (t 2 ),...,Q n (t h ),...,Q n (t H ))
Wherein:
indicating the priority degree of the nth electric equipment;
Q n (t h ) The nth electric equipment is at t h Load of time, t h ∈[t 1 ,t H ]；
F (theta) represents an optimal distribution objective function of the total load of the transformer substation;
θ= (θ (1), θ (2), θ (N)) represents a load distribution result of N electric devices in the substation, and θ (N) represents a load distribution result of N electric devices in the substation;
sigma (x (n)) represents the standard deviation of the sequence x (n), sigma (x (n), theta (n)) represents the standard deviation of the sequence (x (n), theta (n)),
max (x (n)) represents the maximum value in the sequence x (n), and min (x (n)) represents the minimum value in the sequence x (n);
the |c (n) -theta (n) | represents the degree of difference between the distribution load of the nth electric equipment and the predicted load,
indicating consumer after load distributionThe degree of fluctuation of the operating load sequence;
ρ n representing control parameters;
s42: initializing parameter θ 0 ＝(θ 0 (1),θ 0 (2),...,θ 0 (n),...,θ 0 (N)), wherein the parameter satisfies the following threshold condition:
wherein:
sum represents the maximum load that the substation can distribute;
s43: setting the current iteration number of the parameter as D, setting the maximum iteration number as D, and setting the D-th iteration result of the parameter as theta d ＝(λ d (1),λ d (2),...,λ d (n),...,λ d (N)), the initial value of d is 0;
s44: and carrying out iterative updating on the parameters, wherein the iterative formula is as follows:
λ d+1 ＝λ d +grad(F(λ d ))||λ d -c||
wherein:
grad(F(θ d ) F (θ) d ) Is a gradient of (2);
I represent L1 norm;
s45: let d=d+1, return to step S44 until d+1=d, and select the parameter with the largest iteration number and meeting the threshold condition as the load distribution scheme for optimizing the overall energy efficiency of the substation.
7. The one-key sequential control method for a power distribution network according to claim 1, wherein the step S5 of constructing an opening and closing parameter image information recognition model to recognize current opening and closing parameters of power distribution protection devices corresponding to different electric devices comprises:
the method comprises the steps of constructing an opening and closing parameter image information identification model, wherein the opening and closing parameter image information identification model takes current opening and closing state images of distribution protection equipment corresponding to different electric equipment as input and takes identified opening and closing parameters as output, the opening and closing parameter image information identification model comprises an input layer, an image segmentation layer, a characteristic image generation layer and an output layer, the input layer is used for receiving the current opening and closing state images of the distribution protection equipment corresponding to different electric equipment, the image segmentation layer is used for carrying out segmentation processing on the current opening and closing state images to obtain a plurality of sub-images, the characteristic image generation layer is used for extracting characteristic vectors of the sub-images to form a characteristic image, and the output layer is used for carrying out mapping calculation on the characteristic image to identify the current opening and closing parameters of the distribution protection equipment corresponding to the electric equipment;
The current opening and closing parameters of the power distribution protection equipment corresponding to different electric equipment are identified by utilizing an opening and closing parameter image information identification model, wherein the current opening and closing parameter identification flow of the power distribution protection equipment corresponding to the nth electric equipment is as follows:
s51: an input layer receives a current opening and closing state image M of power distribution protection equipment corresponding to the nth electric equipment n (t H )；
S52: the image segmentation layer carries out segmentation processing on the current opening and closing state image to obtain a plurality of sub-images with the overlapping pixel number reaching S pixels of the adjacent images;
s53: the characteristic map generation layer adds the pixel points of the sub-images linearly, and the linear addition results of the pixel points of the sub-images are processed sequentially by adopting convolution kernels with different scales to obtain characteristic vectors of the sub-images; sequencing the sub-image feature vectors according to the sequence of the sub-images in the current opening and closing state image to form a current opening and closing state image M n (t H ) Corresponding characteristic diagram m n ；
S54: the output layer is used for carrying out mapping calculation on the feature map, and identifying and obtaining current opening and closing parameters of power distribution protection equipment corresponding to electric equipment, wherein the current opening and closing parameters of the nth electric equipment are as follows:
λ n ＝Softmax(W T m n )
wherein:
w represents a feature map conversion matrix;
Softmax(W T m n ) Representing W is T m n Converting the current opening and closing parameters into two-dimensional vectors, respectively corresponding to the probability of 1 or 0 of the current opening and closing parameters, and selecting the current opening and closing parameters with the highest probability for output;
λ n representing current opening and closing parameters of power distribution protection equipment corresponding to nth electric equipment, wherein lambda n =0 indicates that the power distribution protection device corresponding to the nth electric equipment is in a switching-off state, lambda n And the symbol 1 indicates that the power distribution protection device corresponding to the nth electric equipment is in a closing state.
8. The one-key sequential control method for a power distribution network according to claim 1, wherein in the step S6, corresponding control instructions are generated to perform one-key sequential control according to a load distribution scheme and switching-on and switching-off parameter information corresponding to electric equipment, and the method comprises the following steps:
generating a corresponding control instruction according to a load distribution scheme and switching-on and switching-off parameter information corresponding to electric equipment, and sending the generated control instruction to corresponding control equipment for one-key sequential control, wherein the control instruction generation flow of the nth electric equipment is as follows:
s61: acquiring a load distribution result theta of an nth electric device in a load distribution scheme * (n) opening and closing parameter lambda n ；
S62: if theta is * (n) exceeding a preset load threshold, generating a virtual parameter lambda * =1, and for virtual parameter λ * Switching-on and switching-off parameter lambda n Performing an exclusive OR operation, if the operation result is 1, not performing switching-on/off operation of the power distribution protection equipment corresponding to the nth electric equipment, and if the operation result is 0, generating a switching-off operation instruction of the power distribution protection equipment corresponding to the nth electric equipment;
s63: if the brake-separating operation command is not generated, the load distribution result theta is calculated * And (n) generating a power transmission regulation instruction of the nth electric equipment.
9. A one-touch sequential control system for a power distribution network, the system comprising:
the load management module is used for collecting the running state information of each device of the transformer substation in the power distribution network, calculating to obtain a transformer substation running load sequence according to the running state information of each device of the transformer substation, constructing a transformer substation running load prediction model based on a supervision learning mode of a fused attention mechanism, predicting the running load of the transformer substation, and distributing the load of the total load of the transformer substation according to the priority of electric equipment according to the running load prediction result of the transformer substation;
the switching-on/off control module is used for constructing a switching-on/off parameter image information identification model to identify and obtain current switching-on/off parameters of power distribution protection equipment corresponding to different electric equipment;
The command control device is used for generating corresponding control commands according to the load distribution scheme and current switching-on and switching-off parameter information corresponding to the electric equipment, and sending the generated control commands to the corresponding equipment for one-key sequential control so as to realize the one-key sequential control method for the power distribution network according to any one of claims 1-8.
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