CN117875625A - Method and device for collaborative supervision of energy distribution - Google Patents
Method and device for collaborative supervision of energy distribution Download PDFInfo
- Publication number
- CN117875625A CN117875625A CN202311808615.2A CN202311808615A CN117875625A CN 117875625 A CN117875625 A CN 117875625A CN 202311808615 A CN202311808615 A CN 202311808615A CN 117875625 A CN117875625 A CN 117875625A
- Authority
- CN
- China
- Prior art keywords
- power
- data
- area
- scheme
- quality
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 53
- 238000004458 analytical method Methods 0.000 claims abstract description 207
- 238000012216 screening Methods 0.000 claims abstract description 36
- 238000004146 energy storage Methods 0.000 claims description 115
- 230000002159 abnormal effect Effects 0.000 claims description 86
- 238000010248 power generation Methods 0.000 claims description 78
- 238000012549 training Methods 0.000 claims description 27
- 238000004590 computer program Methods 0.000 claims description 18
- 238000012545 processing Methods 0.000 claims description 13
- 238000010276 construction Methods 0.000 claims description 8
- 230000005856 abnormality Effects 0.000 claims description 7
- 238000000605 extraction Methods 0.000 claims description 7
- 238000007405 data analysis Methods 0.000 claims description 6
- 238000013507 mapping Methods 0.000 claims description 6
- 230000001105 regulatory effect Effects 0.000 claims description 4
- 238000013442 quality metrics Methods 0.000 claims 1
- 238000012544 monitoring process Methods 0.000 abstract description 7
- 238000010586 diagram Methods 0.000 description 6
- 230000001276 controlling effect Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000004891 communication Methods 0.000 description 3
- 238000005070 sampling Methods 0.000 description 3
- 230000004913 activation Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000013527 convolutional neural network Methods 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000000306 recurrent effect Effects 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 230000002123 temporal effect Effects 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 230000003213 activating effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000001364 causal effect Effects 0.000 description 1
- 239000003034 coal gas Substances 0.000 description 1
- 230000010339 dilation Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 229910021389 graphene Inorganic materials 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000003345 natural gas Substances 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000003209 petroleum derivative Substances 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Landscapes
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The application relates to a method and a device for cooperatively monitoring energy distribution. The method comprises the following steps: acquiring data of a to-be-detected area of the area and electric power data of a power distribution network; carrying out quality analysis according to the electric energy data of the power grid, the data of the to-be-detected area and a preset quality analysis model to obtain a quality analysis result; and carrying out scheme screening according to the quality analysis result and a preset energy control scheme to obtain a target energy control scheme. By adopting the method, the power quality of the station area can be monitored in real time, so that the power quality of the station area is improved, the energy of the adjacent station area is reasonably distributed, the analysis efficiency and accuracy of the power quality can be improved by utilizing the preset quality analysis model, and meanwhile, the stable operation of the station area can be ensured based on the preset energy management and control scheme.
Description
Technical Field
The present disclosure relates to the field of power service operation technologies, and in particular, to a method and an apparatus for collaborative supervision of energy distribution.
Background
With the increasing economic, social and population growth, the global energy demand is increasing. Non-renewable energy sources such as coal, petroleum and natural gas occupy important roles in energy consumption structures in the world, so that reserves of the non-renewable energy sources are greatly reduced, and energy exploitation and consumption are extremely unbalanced. Meanwhile, the utilization of fossil energy also causes serious environmental pollution, and the greenhouse effect, haze and the like are increasingly aggravated, so that the life of people is influenced. At present, fully utilizing renewable energy sources becomes a main way for solving the problem of future energy sources. The related technology of distributed power generation represented by photovoltaic power generation and wind power generation in China provides guarantee and policy support, and the utilization of renewable energy sources is improved to a strategic height.
The condition that new energy wind power and photovoltaic are connected into a power distribution network is more and more common, but wind power and photovoltaic output power have strong uncertainty and randomness, and power quality indexes such as voltage deviation, voltage fluctuation, harmonic wave and three-phase unbalance of the power distribution network can be changed greatly after the new energy is connected.
In the conventional technology, monitoring and controlling of power quality in a power distribution network are mostly focused on a single area, power data are collected and analyzed through power quality detection equipment, and the area is controlled based on analysis results.
However, in the conventional technology, an abnormal area cannot be found out effectively and rapidly when abnormal fluctuation occurs in the power distribution network, and electric energy distribution of the area in the power distribution network cannot be integrated effectively.
Disclosure of Invention
Based on the above, it is necessary to provide a method and a device for collaborative supervision of energy distribution, which can rapidly supervise the power quality of a power distribution network in a power distribution network, reasonably coordinate and distribute energy among the power distribution network, and rapidly execute and leave the network operation on an abnormal power distribution network according to the power grid condition.
In a first aspect, the present application provides a method for collaborative supervision of energy distribution, comprising:
Acquiring data of a to-be-detected area of the area and electric power data of a power distribution network;
carrying out quality analysis according to the electric energy data of the power grid, the data of the to-be-detected area and a preset quality analysis model to obtain a quality analysis result;
and carrying out scheme screening according to the quality analysis result and a preset energy control scheme to obtain a target energy control scheme.
In one embodiment, performing mass analysis according to power grid power data, to-be-detected area data and a preset mass analysis model to obtain a mass analysis result, including:
inputting the electric energy data of the power grid and the data of the to-be-detected area into a preset data processing model for feature extraction to obtain training data and to-be-analyzed data;
inputting the characteristic data into a primary construction quality analysis model for model training to obtain a target quality analysis model;
inputting the data to be analyzed into a target quality analysis model for quality analysis to obtain a quality analysis result.
In one embodiment, performing scheme screening according to a quality analysis result and a preset energy control scheme to obtain a target energy control scheme, including:
when the quality analysis result is that the electric energy quality is normal, carrying out connection analysis on the power grid connection state of the transformer area to obtain a transformer area connection analysis result;
When the platform region connection analysis result shows that the platform region is in an off-grid state, grid-connected operation is carried out on the platform region, and quality analysis is carried out on the platform region, so that a target energy management and control scheme is obtained;
and when the platform area connection analysis result shows that the platform area is in the grid-connected state, carrying out scheme screening on the preset energy control scheme to obtain a grid-connected distribution control scheme.
In one embodiment, the method performs scheme screening according to the quality analysis result and a preset energy control scheme to obtain a target energy control scheme, and further includes:
when the quality analysis result is that the power quality is abnormal, determining abnormal data corresponding to the abnormal power quality;
identifying the abnormal data according to a preset platform area to obtain an abnormal identification result;
when the abnormal identification result is that the abnormal data belongs to the station area, carrying out scheme screening on a preset energy control scheme to obtain a quality abnormal control scheme;
and when the abnormal identification result is that the abnormal data does not belong to the station area, carrying out scheme screening on the preset energy control scheme to obtain an off-grid distribution management scheme.
In one embodiment, when the analysis result of the platform area connection is that the platform area is in the grid-connected state, the scheme screening is performed on the preset energy control scheme, and after the grid-connected distribution control scheme is obtained, the method further includes:
Determining the power generation power of a power generation station area, the residual energy storage capacity of an energy storage station area and the load power of a load station area according to the data of the station area to be detected;
determining a first target power supply scheme of the load platform area according to the generated power, the load power and the first preset power supply scheme; the first preset power supply scheme comprises power generation station area power supply and power distribution network common power supply;
analyzing the residual energy storage capacity to obtain a first capacity analysis result;
when the first capacity analysis result is that the residual energy storage capacity is larger than zero, issuing a regulation and control instruction to a power supply source in a first target power supply scheme, and transmitting the energy of the power supply source to an energy storage platform area according to the regulation and control instruction until the residual energy storage capacity is zero;
and ending the regulation and control operation when the first capacity analysis result is that the residual energy storage capacity is equal to zero.
In one embodiment, when the anomaly data does not belong to the station area as the anomaly identification result, the method further includes:
determining the power generation power of a power generation station area and the load power of a load station area according to the data of the station area to be detected;
Determining a second target power supply scheme of the load platform area according to the generated power, the load power and a second preset power supply scheme; the second preset power supply scheme comprises power generation station area power supply and common power supply of the power generation station area and the energy storage station area;
when the second preset power supply scheme supplies power to the power generation station area, determining the residual energy storage capacity of the energy storage station area;
analyzing the residual energy storage capacity to obtain a second capacity analysis result;
when the second capacity analysis result is that the residual energy storage capacity is greater than zero, issuing a regulation and control instruction to the power generation station area, and transmitting the energy of the power generation station area to the energy storage station area according to the regulation and control instruction until the residual energy storage capacity is zero;
and ending the regulation and control operation when the second capacity analysis result is that the residual energy storage capacity is equal to zero.
In a second aspect, the present application further provides an apparatus for collaborative supervision of energy distribution, including:
the data acquisition module is used for acquiring the data of the to-be-detected area of the area and the power grid electric energy data of the power distribution network;
the data analysis module is used for carrying out quality analysis according to the power grid electric energy data, the to-be-detected area data and the preset quality analysis model to obtain a quality analysis result;
and the scheme selection module is used for carrying out scheme screening according to the quality analysis result and a preset energy control scheme to obtain a target energy control scheme.
In a third aspect, the present application also provides a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring data of a to-be-detected area of the area and electric power data of a power distribution network;
carrying out quality analysis according to the electric energy data of the power grid, the data of the to-be-detected area and a preset quality analysis model to obtain a quality analysis result;
and carrying out scheme screening according to the quality analysis result and a preset energy control scheme to obtain a target energy control scheme.
In a fourth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
acquiring data of a to-be-detected area of the area and electric power data of a power distribution network;
carrying out quality analysis according to the electric energy data of the power grid, the data of the to-be-detected area and a preset quality analysis model to obtain a quality analysis result;
and carrying out scheme screening according to the quality analysis result and a preset energy control scheme to obtain a target energy control scheme.
In a fifth aspect, the present application also provides a computer program product comprising a computer program which, when executed by a processor, performs the steps of:
Acquiring data of a to-be-detected area of the area and electric power data of a power distribution network;
carrying out quality analysis according to the electric energy data of the power grid, the data of the to-be-detected area and a preset quality analysis model to obtain a quality analysis result;
and carrying out scheme screening according to the quality analysis result and a preset energy control scheme to obtain a target energy control scheme.
According to the method and the device for collaborative supervision of energy distribution, the electric energy data of the transformer area and the power distribution network, namely the data of the transformer area to be detected and the electric energy data of the power grid are obtained, then the data of the transformer area to be detected and the electric energy data of the power grid are analyzed and determined by utilizing the preset quality analysis model to determine whether the electric energy quality of the transformer area and the electric energy quality of the power distribution network are abnormal or not, the source of the abnormal electric energy quality is judged based on the quality analysis result, then the regulation and control of the transformer area and the power distribution network are realized based on the abnormal electric energy quality and the preset energy management and control scheme, the electric energy quality of the transformer area can be monitored in real time, the electric energy quality of the transformer area can be improved, the energy of the adjacent transformer area can be reasonably distributed, the analysis efficiency and the accuracy of the electric energy quality can be improved by utilizing the preset quality analysis model, and meanwhile, the stable operation of the transformer area can be ensured based on the preset energy management and control scheme.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are required to be used in the embodiments or the related technical descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for a person having ordinary skill in the art.
FIG. 1 is a flow diagram of a method of collaborative supervision of energy distribution in one embodiment;
FIG. 2 is a flow diagram of mass analysis in one embodiment;
FIG. 3 is a flow diagram of selecting an energy management scheme in one embodiment;
FIG. 4 is a block diagram of an apparatus for collaborative supervision of energy distribution in one embodiment;
fig. 5 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
In one embodiment, as shown in fig. 1, a method for collaborative supervision of energy distribution is provided, where this embodiment is applied to a terminal for illustration, it is understood that the method may also be applied to a server, and may also be applied to a system including a terminal and a server, and implemented through interaction between the terminal and the server. In this embodiment, the method includes the steps of:
Step 102, obtaining data of a to-be-detected area of the area and power grid power data of the power distribution network.
The power distribution network comprises a power generation station area, an energy storage station area and a load station area, wherein the power distribution network is an alternating current power grid.
The method comprises the steps of setting a sampling index of electric energy data, the number of groups of required sampled data groups and the interval time of each sampling in advance, then carrying out data acquisition on a platform area and a power distribution network, and obtaining one group of data of the platform area and one group of data of the power distribution network through one sampling operation. After the data acquisition of the set group number is completed, the acquired data of the plurality of groups of transformer areas are set as data of the transformer areas to be detected, and the acquired data of the plurality of groups of power distribution networks are set as power grid power data.
And 104, carrying out quality analysis according to the power grid electric energy data, the to-be-detected area data and a preset quality analysis model to obtain a quality analysis result.
The preset mass analysis model comprises an initial construction mass analysis model which is constructed based on a TCN (time convolutional neural network, temporal Convolutional Networks) model and a GRU (gate control circulation unit, gate Recurrent Unit) model.
For example, after the to-be-detected area data and the power grid power data are acquired, the to-be-detected area data and the power grid power data are subjected to data processing to obtain training data which can be used for model training and to-be-analyzed data for detection analysis.
Training the initially constructed quality analysis model by using training data to obtain a target quality analysis model, inputting data to be analyzed into the target quality analysis model, and analyzing the electric energy quality of the data to be analyzed to obtain a quality analysis result.
And 106, carrying out scheme screening according to the quality analysis result and a preset energy control scheme to obtain a target energy control scheme.
The preset energy control scheme comprises a grid-connected control scheme, a quality abnormality control scheme and an off-grid control scheme.
Illustratively, after the mass analysis is completed, the appropriate energy management scheme is screened among the preset energy management schemes based on the mass analysis results.
When the quality analysis result shows that the electric energy quality is abnormal, carrying out source analysis on data corresponding to the abnormal electric energy quality, wherein the source analysis comprises the following specific steps:
if the abnormal power quality corresponding data come from the platform area, selecting a quality abnormal control scheme for regulation and control;
if the abnormal power quality corresponding data does not come from the platform area, the platform area is subjected to off-grid operation, and then an off-grid distribution management and control scheme is selected for regulation and control.
When the quality analysis result is that the electric energy quality is normal, whether the station area is off-line is further judged, specifically:
If the platform area is in the off-grid state, grid-connected operation is carried out on the platform area, and then quality analysis is carried out again;
and if the platform area is in a grid-connected state, selecting a grid-connected distribution control scheme for regulation and control.
In the method for collaborative supervision of energy distribution, the electric energy data of the transformer area and the power distribution network, namely the data of the transformer area to be detected and the electric energy data of the power grid are obtained, then the data of the transformer area to be detected and the electric energy data of the power grid are analyzed and determined by utilizing a preset quality analysis model to determine whether the electric energy quality of the transformer area and the electric energy quality of the power distribution network are abnormal or not, the source of the abnormal electric energy quality is judged based on a quality analysis result, then the regulation and control of the transformer area and the power distribution network are realized based on the abnormal electric energy quality and a preset energy management and control scheme, the electric energy quality of the transformer area can be monitored in real time, so that the electric energy quality of the transformer area is improved, the energy of the adjacent transformer area is reasonably distributed, the analysis efficiency and the accuracy of the electric energy quality can be improved by utilizing the preset quality analysis model, and meanwhile, the stable operation of the transformer area can be ensured based on the preset energy management and control scheme.
In an exemplary embodiment, as shown in fig. 2, the quality analysis is performed according to the power grid power data, the to-be-detected area data and the preset quality analysis model to obtain a quality analysis result, which includes the following steps 202 to 206. Wherein:
Step 202, inputting electric energy data of a power grid and data of a to-be-detected platform area into a preset data processing model to perform feature extraction, and obtaining training data and data to be analyzed.
The preset data processing model comprises a sliding time window and a stack type noise reduction self-encoder.
The method includes the steps of dividing to-be-detected area data and power grid power data into multi-dimensional time series data in a sliding time window mode, then denoising the multi-dimensional time series data by using a pre-trained stack type denoising self-encoder to obtain denoised data, and dividing the denoised data into training data and to-be-analyzed data according to a preset proportion, wherein the proportion of the training data to the to-be-analyzed data is 1:9.
the encoding process of the self-encoder is formulated as:
wherein,output vector set representing hidden layer obtained by encoder,/->Representing the activation function of the input layer to the hidden layer, W being the coding weight matrix, x representing the sample data,/I>A training sample set representing a high dimensional space, b representing a coded bias vector.
The decoding process from the encoder is formulated as:
wherein,representation->Data set of the same dimension as the input sample set obtained by inverse transformation,/and method for obtaining the same >Representing the activation function of the hidden layer to the output layer, < >>Represents a decoding weight matrix and d represents a decoding bias vector.
And the self-encoder adopts the mean square error as a loss function, specifically:
the stack noise reduction self-encoder is composed of a plurality of self-encoders in a stacking way.
And 204, inputting the characteristic data into the primary construction quality analysis model for model training to obtain a target quality analysis model.
The initial construction quality analysis model is constructed based on a TCN (time convolutional neural network, temporal Convolutional Networks) model and a GRU (gate control circulation unit, gate Recurrent Unit) model.
Illustratively, a TCN-GRU model is built, wherein the TCN model comprises a causal convolution layer, an expansion convolution layer and a residual error connection structure, and performs feature extraction processing on data. And the expression of the dilation convolution is:
wherein x is the input sequence, f is the filter, d is the expansion coefficient, k is the convolution kernel size,ensuring that only convolution operations can be performed on past inputs.
Because a residual connection structure is used between layers in the TCN model, a Dropout layer is used in each layer to regularize the TCN model. And extracting the characteristics of the data by using the TCN model and transmitting the characteristic data to the GRU model for further processing. The expression of the GRU model is specifically:
Wherein,for input at time t, < >>For output or state at time t +.>Is the state at time t-1, w is the weight,/->For activating function->，/>To activate the function +.>、/>And->Is an intermediate variable.
After the TCN-GRU model is built, training data are input into the TCN-GRU model for model training, and a target quality analysis model is obtained.
And 206, inputting the data to be analyzed into a target quality analysis model for quality analysis to obtain a quality analysis result.
The data to be analyzed is input into the target quality analysis model for data analysis after model training is completed to obtain a target quality analysis model, and then a quality analysis result is obtained. The quality analysis results comprise electric energy quality indexes including, but not limited to, harmonic voltage distortion rate, harmonic voltage content rate, voltage deviation, power factor and three-phase unbalance.
In this embodiment, the training data and the data to be analyzed are obtained by preprocessing the collected data and dividing the preprocessed data, meanwhile, an initial quality analysis model is built based on the TCN model and the GRU model, then the training data is input into the initial quality analysis model for training, the data to be analyzed is input into the quality analysis project after training is completed, the quality analysis model is trained based on the collected data of the platform area and the power distribution network, and the same batch of data to be analyzed is adopted for quality analysis after training, so that the analysis efficiency and accuracy of the electric energy quality can be improved.
In an exemplary embodiment, as shown in fig. 3, performing scheme screening according to a quality analysis result and a preset energy control scheme to obtain a target energy control scheme, including:
when the quality analysis result is that the electric energy quality is normal, carrying out connection analysis on the power grid connection state of the transformer area to obtain a transformer area connection analysis result; when the platform region connection analysis result shows that the platform region is in an off-grid state, grid-connected operation is carried out on the platform region, and quality analysis is carried out on the platform region, so that a target energy management and control scheme is obtained; and when the platform area connection analysis result shows that the platform area is in the grid-connected state, carrying out scheme screening on the preset energy control scheme to obtain a grid-connected distribution control scheme.
The preset energy control scheme comprises a grid-connected distribution control scheme.
For example, when the quality analysis result is that the power quality is normal, it is necessary to further confirm whether the station is connected to the distribution network.
If the platform area is in the off-grid state, grid-connected operation is carried out on the platform area, then data are collected again and quality analysis is carried out, so that an energy management and control scheme to be executed is determined.
If the platform area is in the grid-connected state, selecting a grid-connected distribution control scheme from preset energy control schemes.
In this embodiment, by further confirming whether the station is connected to the power distribution network when determining that the power quality is normal, the power quality of the station can be effectively analyzed and the energy between stations can be conveniently distributed.
In an exemplary embodiment, as shown in fig. 3, the method performs scheme screening according to the quality analysis result and the preset energy control scheme to obtain a target energy control scheme, and further includes:
when the quality analysis result is that the power quality is abnormal, determining abnormal data corresponding to the abnormal power quality; identifying the abnormal data according to a preset platform area to obtain an abnormal identification result; when the abnormal identification result is that the abnormal data belongs to the station area, carrying out scheme screening on a preset energy control scheme to obtain a quality abnormal control scheme; and when the abnormal identification result is that the abnormal data does not belong to the station area, carrying out scheme screening on the preset energy control scheme to obtain an off-grid distribution management scheme.
The preset energy control scheme comprises a quality abnormality control scheme and an off-grid control scheme.
For example, upon determining that there is an abnormality in the power quality, the source of the abnormality data corresponding to the abnormal power quality is analyzed to determine whether the abnormal power quality is from the bay.
If abnormal data corresponding to abnormal power quality come from the station area, selecting a quality abnormal control scheme from preset energy control schemes.
If the abnormal data corresponding to the abnormal electric energy quality does not come from the platform area, off-grid operation is carried out on the platform area, then the off-grid distribution management scheme is selected from the preset energy management and control schemes, and energy distribution and control are carried out on the off-grid background area based on the off-grid distribution management and control scheme.
In the embodiment, whether the abnormal data corresponding to the abnormal power quality belong to the station areas is detected, so that the station areas are conveniently separated from the network when the power distribution network fluctuates, temporary energy coordination distribution is carried out among the station areas, and then the power grid is automatically connected to the network when the power grid is recovered to be normal, so that stable operation of the station areas is ensured.
In an exemplary embodiment, when the result of the analysis of the area connection is that the area is in the grid-connected state, the method further includes, after performing scheme screening on the preset energy control scheme to obtain a grid-connected distribution control scheme:
determining the power generation power of a power generation station area, the residual energy storage capacity of an energy storage station area and the load power of a load station area according to the data of the station area to be detected; determining a first target power supply scheme of the load platform area according to the generated power, the load power and the first preset power supply scheme; the first preset power supply scheme comprises power generation station area power supply and power distribution network common power supply; analyzing the residual energy storage capacity to obtain a first capacity analysis result; when the first capacity analysis result is that the residual energy storage capacity is larger than zero, issuing a regulation and control instruction to a power supply source in a first target power supply scheme, and transmitting the energy of the power supply source to an energy storage platform area according to the regulation and control instruction until the residual energy storage capacity is zero; and ending the regulation and control operation when the first capacity analysis result is that the residual energy storage capacity is equal to zero.
The power generation station area comprises a wind station area and a photovoltaic station area.
After determining that the control scheme is a grid-connected control scheme, the power generation power of the power generation station area, the residual energy storage capacity of the energy storage station area and the load power of the load station area are determined based on the acquired data of the to-be-detected station area. And then analyzing whether the power generation power of the power generation station area can meet the load power of the load station area, and determining the energy regulation and control operation based on the analysis result.
If the generated power meets the load power, the power generation area supplies power to the load area, and then whether the residual energy storage capacity of the energy storage area is larger than zero is judged, specifically:
when the residual energy storage capacity is larger than zero, the power generation station area transmits energy generated by the residual power to the energy storage station area until the residual energy storage capacity of the energy storage station area is zero;
and when the residual energy storage capacity is equal to zero, ending the regulation operation.
If the generated power does not meet the load power, the power generation area and the power distribution network supply power to the load area together, and then whether the residual energy storage capacity of the energy storage area is larger than zero is judged, specifically:
when the residual energy storage capacity is larger than zero, the power distribution network supplies power to the energy storage platform area until the residual energy storage capacity of the energy storage platform area is zero;
And when the residual energy storage capacity is equal to zero, ending the regulation operation.
In the embodiment, the power supply analysis is performed on the generated power of the power generation station area and the load power of the load station area to determine whether the power distribution network is needed to participate in power supply, then the power is supplied to the energy storage station area with the residual energy storage capacity while the power is supplied to the load station area, the station areas are separated from the network when the power distribution network fluctuates, temporary energy coordination distribution is performed among the station areas, and then the network is automatically accessed when the power grid is recovered to be normal, so that the stable operation of each station area is ensured.
In an exemplary embodiment, when the anomaly data belong to the station area as the anomaly identification result, the method further includes, after performing scheme screening on the preset energy management and control scheme to obtain a quality anomaly management and control scheme:
determining an abnormal quality index according to the abnormal power quality of the station area; determining a target regulation and control instruction according to the abnormal quality index and a preset regulation and control mapping relation; and issuing a target regulation and control instruction to the platform region, and executing regulation and control operation based on the target regulation and control instruction.
The quality abnormality control scheme comprises a preset regulation and control mapping relation between abnormal quality indexes and regulation and control instructions.
In an exemplary embodiment, when an abnormality occurs in the power quality in the area, a specific abnormal power quality index is determined, and a regulation operation to be performed is determined based on a preset regulation mapping relationship. The method comprises the following steps:
If the harmonic voltage distortion rate and the harmonic voltage content rate are abnormal, controlling and starting an active power filter of an abnormal area;
if the voltage deviation and the power factor are abnormal, controlling and starting the abnormal transformer area reactive power compensation device;
and if the three-phase unbalance is abnormal, controlling and starting an abnormal platform area reversing switch.
In the embodiment, when the power distribution network fluctuates, the control operation is performed on the station areas with abnormal power quality, so that the fluctuation in the station areas is eliminated, and the stable operation of each station area is ensured.
In an exemplary embodiment, when the anomaly data does not belong to the station area as the anomaly identification result, the method further includes, after performing scheme screening on the preset energy management and control scheme to obtain an off-grid distribution and control scheme:
determining the power generation power of a power generation station area and the load power of a load station area according to the data of the station area to be detected; determining a second target power supply scheme of the load platform area according to the generated power, the load power and a second preset power supply scheme; the second preset power supply scheme comprises power generation station area power supply and common power supply of the power generation station area and the energy storage station area; when the second preset power supply scheme supplies power to the power generation station area, determining the residual energy storage capacity of the energy storage station area;
Analyzing the residual energy storage capacity to obtain a second capacity analysis result; when the second capacity analysis result is that the residual energy storage capacity is greater than zero, issuing a regulation and control instruction to the power generation station area, and transmitting the energy of the power generation station area to the energy storage station area according to the regulation and control instruction until the residual energy storage capacity is zero; and ending the regulation and control operation when the second capacity analysis result is that the residual energy storage capacity is equal to zero.
The platform area comprises a power generation platform area, an energy storage platform area and a load platform area.
After determining that the control scheme is an off-grid control scheme, the power generation power of the power generation station area, the residual energy storage capacity of the energy storage station area and the load power of the load station area are determined based on the acquired data of the to-be-detected station area. And then analyzing whether the power generation power of the power generation station area can meet the load power of the load station area, and determining the energy regulation and control operation based on the analysis result.
And if the generated power does not meet the load power, the power generation area and the energy storage area supply power to the load area together.
If the generated power meets the load power, the power generation area supplies power to the load area, and then whether the residual energy storage capacity of the energy storage area is larger than zero is judged, specifically:
When the residual energy storage capacity is larger than zero, the power generation station area transmits energy generated by the residual power to the energy storage station area until the residual energy storage capacity of the energy storage station area is zero;
and when the residual energy storage capacity is equal to zero, ending the regulation operation.
In the embodiment, the power supply analysis is performed on the generated power of the power generation station area and the load power of the load station area to determine whether the energy storage station area is needed to participate in power supply, then the power is supplied to the energy storage station area with the residual energy storage capacity while the power generation station area is only needed to supply power to the load station area, the station areas are separated from the network when the power distribution network fluctuates, temporary energy coordination distribution is performed among the station areas, and then the network is automatically accessed when the power grid is recovered to be normal, so that the stable operation of each station area is ensured.
In one exemplary embodiment, a method of collaborative supervision of energy distribution is provided, the method comprising the steps of:
and acquiring data of the to-be-detected area of the area and power grid electric energy data of the power distribution network.
And inputting the electric energy data of the power grid and the data of the to-be-detected area into a preset data processing model to perform feature extraction, and obtaining training data and to-be-analyzed data.
Inputting the characteristic data into a primary construction quality analysis model for model training to obtain a target quality analysis model.
Inputting the data to be analyzed into a target quality analysis model for quality analysis to obtain a quality analysis result.
And when the quality analysis result is that the electric energy quality is normal, carrying out connection analysis on the power grid connection state of the transformer area to obtain a transformer area connection analysis result.
And when the platform region connection analysis result shows that the platform region is in the off-grid state, grid-connected operation is carried out on the platform region, and quality analysis is carried out on the platform region, so that a target energy control scheme is obtained.
And determining the power generation power of the power generation station area, the residual energy storage capacity of the energy storage station area and the load power of the load station area according to the data of the station area to be detected.
Determining a first target power supply scheme of the load platform area according to the generated power, the load power and the first preset power supply scheme; the first preset power supply scheme comprises power generation station area power supply and power distribution network common power supply.
And analyzing the residual energy storage capacity to obtain a first capacity analysis result.
And when the first capacity analysis result is that the residual energy storage capacity is greater than zero, issuing a regulation and control instruction to a power supply source in the first target power supply scheme, and transmitting the energy of the power supply source to the energy storage platform area according to the regulation and control instruction until the residual energy storage capacity is zero.
And ending the regulation and control operation when the first capacity analysis result is that the residual energy storage capacity is equal to zero.
In one exemplary embodiment, a method of collaborative supervision of energy distribution is provided, the method further comprising the steps of:
and acquiring data of the to-be-detected area of the area and power grid electric energy data of the power distribution network.
And inputting the electric energy data of the power grid and the data of the to-be-detected area into a preset data processing model to perform feature extraction, and obtaining training data and to-be-analyzed data.
Inputting the characteristic data into a primary construction quality analysis model for model training to obtain a target quality analysis model.
Inputting the data to be analyzed into a target quality analysis model for quality analysis to obtain a quality analysis result.
And when the quality analysis result is that the electric energy quality is normal, carrying out connection analysis on the power grid connection state of the transformer area to obtain a transformer area connection analysis result.
And when the platform area connection analysis result shows that the platform area is in the grid-connected state, carrying out scheme screening on the preset energy control scheme to obtain a grid-connected distribution control scheme.
And determining the power generation power of the power generation station area, the residual energy storage capacity of the energy storage station area and the load power of the load station area according to the data of the station area to be detected.
Determining a first target power supply scheme of the load platform area according to the generated power, the load power and the first preset power supply scheme; the first preset power supply scheme comprises power generation station area power supply and power distribution network common power supply.
And analyzing the residual energy storage capacity to obtain a first capacity analysis result.
And when the first capacity analysis result is that the residual energy storage capacity is greater than zero, issuing a regulation and control instruction to a power supply source in the first target power supply scheme, and transmitting the energy of the power supply source to the energy storage platform area according to the regulation and control instruction until the residual energy storage capacity is zero.
And ending the regulation and control operation when the first capacity analysis result is that the residual energy storage capacity is equal to zero.
And determining the power generation power of the power generation station area and the load power of the load station area according to the data of the station area to be detected.
Determining a second target power supply scheme of the load platform area according to the generated power, the load power and a second preset power supply scheme; the second preset power supply scheme comprises power generation station area power supply and common power supply of the power generation station area and the energy storage station area.
And when the second preset power supply scheme supplies power to the power generation station area, determining the residual energy storage capacity of the energy storage station area.
And analyzing the residual energy storage capacity to obtain a second capacity analysis result.
And when the second capacity analysis result is that the residual energy storage capacity is greater than zero, issuing a regulation and control instruction to the power generation station area, and transmitting the energy of the power generation station area to the energy storage station area according to the regulation and control instruction until the residual energy storage capacity is zero.
And ending the regulation and control operation when the second capacity analysis result is that the residual energy storage capacity is equal to zero.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides an apparatus for implementing the above-mentioned method for collaborative supervision of energy distribution. The implementation of the solution provided by the apparatus is similar to the implementation described in the above method, so the specific limitation in the embodiment of the apparatus for collaborative monitoring of energy allocation provided below may refer to the limitation of the method for collaborative monitoring of energy allocation described above, and will not be repeated herein.
In an exemplary embodiment, as shown in fig. 4, there is provided an apparatus for collaborative supervision of energy distribution, comprising: a data acquisition module 402, a data analysis module 404, and a scheme selection module 406, wherein:
the data acquisition module 402 is configured to acquire to-be-detected area data of an area and power grid power data of a power distribution network.
The data analysis module 404 is configured to perform mass analysis according to the power grid power data, the to-be-detected area data, and a preset mass analysis model, so as to obtain a mass analysis result.
The scheme selection module 406 is configured to perform scheme screening according to the quality analysis result and a preset energy control scheme, and obtain a target energy control scheme.
In an exemplary embodiment, the data analysis module 404 is further configured to input the electric power data of the electric power grid and the data of the to-be-detected area into a preset data processing model for feature extraction, so as to obtain training data and to-be-analyzed data; inputting the characteristic data into a primary construction quality analysis model for model training to obtain a target quality analysis model; inputting the data to be analyzed into a target quality analysis model for quality analysis to obtain a quality analysis result.
In an exemplary embodiment, the scheme selection module 406 is further configured to perform connection analysis on the power grid connection status of the transformer area when the quality analysis result is that the power quality is normal, so as to obtain a transformer area connection analysis result; when the platform region connection analysis result shows that the platform region is in an off-grid state, grid-connected operation is carried out on the platform region, and quality analysis is carried out on the platform region, so that a target energy management and control scheme is obtained; and when the platform area connection analysis result shows that the platform area is in the grid-connected state, carrying out scheme screening on the preset energy control scheme to obtain a grid-connected distribution control scheme.
In an exemplary embodiment, the scheme selection module 406 is further configured to determine, when the quality analysis result is that the power quality is abnormal, abnormal data corresponding to the abnormal power quality; identifying the abnormal data according to a preset platform area to obtain an abnormal identification result; when the abnormal identification result is that the abnormal data belongs to the station area, carrying out scheme screening on a preset energy control scheme to obtain a quality abnormal control scheme; and when the abnormal identification result is that the abnormal data does not belong to the station area, carrying out scheme screening on the preset energy control scheme to obtain an off-grid distribution management scheme.
In an exemplary embodiment, the device for collaborative supervision of energy distribution further includes a monitoring and regulating module, configured to determine, according to the to-be-detected area data of the area, a power generation power of the power generation area, a remaining energy storage capacity of the energy storage area, and a load power of the load area; determining a first target power supply scheme of the load platform area according to the generated power, the load power and the first preset power supply scheme; the first preset power supply scheme comprises power generation station area power supply and power distribution network common power supply; analyzing the residual energy storage capacity to obtain a first capacity analysis result; when the first capacity analysis result is that the residual energy storage capacity is larger than zero, issuing a regulation and control instruction to a power supply source in a first target power supply scheme, and transmitting the energy of the power supply source to an energy storage platform area according to the regulation and control instruction until the residual energy storage capacity is zero; and ending the regulation and control operation when the first capacity analysis result is that the residual energy storage capacity is equal to zero.
In an exemplary embodiment, the device for collaborative supervision of energy distribution further includes a monitoring and control module, further configured to determine an abnormal quality indicator according to an abnormal power quality of the station area; determining a target regulation and control instruction according to the abnormal quality index and a preset regulation and control mapping relation; and issuing a target regulation and control instruction to the platform region, and executing regulation and control operation based on the target regulation and control instruction.
In an exemplary embodiment, the device for collaborative supervision of energy distribution further includes a monitoring and regulating module, which is further configured to determine, according to the to-be-detected zone data of the zone, a power generation power of the power generation zone and a load power of the load zone; determining a second target power supply scheme of the load platform area according to the generated power, the load power and a second preset power supply scheme; the second preset power supply scheme comprises power generation station area power supply and common power supply of the power generation station area and the energy storage station area; when the second preset power supply scheme supplies power to the power generation station area, determining the residual energy storage capacity of the energy storage station area; analyzing the residual energy storage capacity to obtain a second capacity analysis result; when the second capacity analysis result is that the residual energy storage capacity is greater than zero, issuing a regulation and control instruction to the power generation station area, and transmitting the energy of the power generation station area to the energy storage station area according to the regulation and control instruction until the residual energy storage capacity is zero; and ending the regulation and control operation when the second capacity analysis result is that the residual energy storage capacity is equal to zero.
The above-described means of coordinated supervision of energy distribution may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one exemplary embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing the data of the area and the data of the distribution network. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of collaborative supervision of energy distribution.
It will be appreciated by those skilled in the art that the structure shown in fig. 5 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In an exemplary embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor performing the steps of the method embodiments described above when the computer program is executed.
In one exemplary embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method embodiments described above.
In an exemplary embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.
It should be noted that, the user information (including, but not limited to, user equipment information, user personal information, etc.) and the data (including, but not limited to, data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use, and processing of the related data are required to meet the related regulations.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.
Claims (10)
1. A method of collaborative supervision of energy distribution, the method comprising:
acquiring data of a to-be-detected area of the area and electric power data of a power distribution network;
performing quality analysis according to the power grid power data, the to-be-detected area data and a preset quality analysis model to obtain a quality analysis result;
and carrying out scheme screening according to the quality analysis result and a preset energy control scheme to obtain a target energy control scheme.
2. The method of claim 1, wherein the pre-set mass analysis model comprises an as-built mass analysis model; the step of carrying out quality analysis according to the power grid electric energy data, the to-be-detected area data and a preset quality analysis model to obtain a quality analysis result comprises the following steps:
inputting the electric energy data of the power grid and the data of the to-be-detected area into a preset data processing model to perform feature extraction, and obtaining training data and to-be-analyzed data;
inputting the characteristic data into a primary construction quality analysis model for model training to obtain a target quality analysis model;
inputting the data to be analyzed into the target quality analysis model for quality analysis to obtain a quality analysis result.
3. The method of claim 1, wherein the quality analysis result comprises a normal power quality; the preset energy control scheme comprises a grid-connected distribution control scheme; and performing scheme screening according to the quality analysis result and a preset energy control scheme to obtain a target energy control scheme, wherein the scheme comprises the following steps of:
when the quality analysis result is that the electric energy quality is normal, carrying out connection analysis on the power grid connection state of the transformer area to obtain a transformer area connection analysis result;
When the platform region connection analysis result shows that the platform region is in an off-grid state, grid-connected operation is carried out on the platform region, quality analysis is carried out on the platform region, and a target energy management and control scheme is obtained;
and when the platform area connection analysis result shows that the platform area is in a grid-connected state, carrying out scheme screening on the preset energy control scheme to obtain a grid-connected distribution control scheme.
4. A method according to claim 3, wherein the quality analysis results further comprise an electrical energy quality anomaly; the preset energy control scheme comprises a quality abnormality control scheme and an off-grid control scheme; and performing scheme screening according to the quality analysis result and a preset energy control scheme to obtain a target energy control scheme, and further comprising:
when the quality analysis result is that the power quality is abnormal, determining abnormal data corresponding to the abnormal power quality;
identifying the abnormal data according to a preset platform area to obtain an abnormal identification result;
when the abnormal identification result is that the abnormal data belongs to the station area, carrying out scheme screening on the preset energy control scheme to obtain a quality abnormal control scheme;
and when the abnormal identification result is that the abnormal data does not belong to the station area, carrying out scheme screening on the preset energy control scheme to obtain an off-grid distribution control scheme.
5. A method according to claim 3, wherein the bays comprise a power generation bay, a storage bay and a load bay; when the platform area connection analysis result shows that the platform area is in a grid-connected state, carrying out scheme screening on the preset energy control scheme to obtain a grid-connected distribution control scheme, wherein the method further comprises the following steps:
determining the power generation power of a power generation station area, the residual energy storage capacity of an energy storage station area and the load power of a load station area according to the data of the station area to be detected;
determining a first target power supply scheme of the load station area according to the generated power, the load power and a first preset power supply scheme; the first preset power supply scheme comprises power generation station area power supply and power distribution network common power supply;
analyzing the residual energy storage capacity to obtain a first capacity analysis result;
when the first capacity analysis result is that the residual energy storage capacity is larger than zero, issuing a regulation and control instruction to a power supply in the first target power supply scheme, and transmitting the energy of the power supply to the energy storage platform area according to the regulation and control instruction until the residual energy storage capacity is zero;
and ending the regulation and control operation when the first capacity analysis result is that the residual energy storage capacity is equal to zero.
6. The method of claim 4, wherein the quality anomaly management and control scheme includes a preset regulatory mapping of anomaly quality metrics to regulatory instructions; when the abnormal identification result is that the abnormal data belongs to the platform area, performing scheme screening on the preset energy control scheme, and obtaining a quality abnormal control scheme, wherein the method further comprises the following steps:
determining an abnormal quality index according to the abnormal power quality of the station area;
determining a target regulation and control instruction according to the abnormal quality index and a preset regulation and control mapping relation;
and issuing the target regulation and control instruction to the platform region, and executing regulation and control operation based on the target regulation and control instruction.
7. The method of claim 4, wherein the bays comprise a power generation bay, a storage bay, and a load bay; when the abnormal recognition result is that the abnormal data does not belong to the station area, performing scheme screening on the preset energy control scheme, and obtaining an off-grid distribution management scheme, wherein the method further comprises the following steps:
determining the power generation power of a power generation station area and the load power of a load station area according to the data of the station area to be detected;
determining a second target power supply scheme of the load station area according to the generated power, the load power and a second preset power supply scheme; the second preset power supply scheme comprises power generation station area power supply and common power supply of the power generation station area and the energy storage station area;
When the second preset power supply scheme supplies power to the power generation station area, determining the residual energy storage capacity of the energy storage station area;
analyzing the residual energy storage capacity to obtain a second capacity analysis result;
when the second capacity analysis result is that the residual energy storage capacity is greater than zero, a regulation and control instruction is issued to the power generation station area, and the energy of the power generation station area is transmitted to the energy storage station area according to the regulation and control instruction until the residual energy storage capacity is zero;
and ending the regulation and control operation when the second capacity analysis result is that the residual energy storage capacity is equal to zero.
8. An apparatus for coordinated supervision of energy distribution, the apparatus comprising:
the data acquisition module is used for acquiring the data of the to-be-detected area of the area and the power grid electric energy data of the power distribution network;
the data analysis module is used for carrying out quality analysis according to the power grid electric energy data, the to-be-detected area data and a preset quality analysis model to obtain a quality analysis result;
and the scheme selection module is used for carrying out scheme screening according to the quality analysis result and a preset energy control scheme to obtain a target energy control scheme.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311808615.2A CN117875625A (en) | 2023-12-26 | 2023-12-26 | Method and device for collaborative supervision of energy distribution |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311808615.2A CN117875625A (en) | 2023-12-26 | 2023-12-26 | Method and device for collaborative supervision of energy distribution |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117875625A true CN117875625A (en) | 2024-04-12 |
Family
ID=90580338
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311808615.2A Pending CN117875625A (en) | 2023-12-26 | 2023-12-26 | Method and device for collaborative supervision of energy distribution |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117875625A (en) |
-
2023
- 2023-12-26 CN CN202311808615.2A patent/CN117875625A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110082699B (en) | Low-voltage transformer area intelligent electric energy meter operation error calculation method and system | |
| Zhao et al. | User electricity behavior analysis based on K-means plus clustering algorithm | |
| Li et al. | An integrated missing-data tolerant model for probabilistic PV power generation forecasting | |
| CN114676883A (en) | Power grid operation management method, device and equipment based on big data and storage medium | |
| CN106980906B (en) | Spark-based Ftrl voltage prediction method | |
| Kaboli et al. | An expression-driven approach for long-term electric power consumption forecasting | |
| CN106779219A (en) | A kind of electricity demand forecasting method and system | |
| CN113780679B (en) | Load prediction method and device based on ubiquitous power Internet of things | |
| CN114021425A (en) | Power system operation data modeling and feature selection method and device, electronic equipment and storage medium | |
| CN117056776A (en) | Carbon emission monitoring method, apparatus, device, medium and computer program product | |
| CN117374920A (en) | Ultra-short-term prediction method, device and medium considering environmental factors | |
| WO2023179076A1 (en) | Mixed integer programming-based load decomposition method and apparatus for industrial facility | |
| CN117875625A (en) | Method and device for collaborative supervision of energy distribution | |
| Lu et al. | Residential Energy Consumption Forecasting Based on Federated Reinforcement Learning with Data Privacy Protection. | |
| CN113537607B (en) | Power failure prediction method | |
| CN114462771A (en) | Electricity utilization abnormity analysis method, device, equipment, medium and product | |
| CN114254828A (en) | Power load prediction method based on hybrid convolution feature extractor and GRU | |
| CN113705885A (en) | Power distribution network voltage prediction method and system integrating VMD, XGboost and optimized TCN | |
| Zhao et al. | Ultra-short-term power forecasting of wind farm cluster based on spatio-temporal graph neural network pattern prediction | |
| Dong et al. | Image-based with peak load ensemble prediction system for demand response in smart grid | |
| Kavakci et al. | Time Series Prediction of Solar Power Generation Using Trend Decomposition | |
| Demir et al. | Temperature prediction in microgrids using lstms: A case study | |
| Ding et al. | Short-Term Load Forecasting Method Based on Autoencoder and LSTNet Models | |
| Guo et al. | An Optimized Back Propagation Neural Network Based on Genetic Algorithm for Line Loss Calculation in Low-voltage Distribution Grid | |
| Lv et al. | The Data Cleaning of Electric Industrial Control Terminal Based on the iForest and Genetic BP Neural Network Algorithms |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |