CN115811079A - Distributed power distribution network electric energy quality control method, device, terminal and storage medium - Google Patents
Distributed power distribution network electric energy quality control method, device, terminal and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of distributed power grid regulation and control, in particular to a method, a device, a terminal and a storage medium for controlling the power quality of a distributed power distribution network, wherein the method comprises the steps of firstly acquiring a plurality of first feeder waveform data sets corresponding to a plurality of load feeders; then extracting an abnormal waveform data set according to the plurality of first feeder waveform data sets; determining a target power feeder according to the abnormal waveform data set and a plurality of second waveform data sets corresponding to the plurality of power feeders; and finally, adjusting the power supply accessed to the target power supply feeder line according to the abnormal waveform data set. According to the embodiment of the invention, the power feeder with the highest abnormal relevance with the abnormal load feeder is found, and the quality of the power distribution network can be improved after the power feeder is adjusted in a targeted manner, so that the quality of the power of each load feeder can be ensured, and when the power feeder is adjusted in an iterative manner, the processes of network structure analysis and data calculation can be reduced, and the method has the advantages of low calculation cost and high efficiency.
Description
Technical Field
The invention relates to the technical field of distributed power grid regulation and control, in particular to a method, a device, a terminal and a storage medium for controlling the power quality of a distributed power distribution network.
Background
Distributed Generation (DG) refers to a power source Distributed at a user end and mainly consumed on site. The system comprises solar energy, natural gas, biomass energy, wind energy, hydroenergy, hydrogen energy, geothermal energy, ocean energy, resource comprehensive utilization power generation (including coal mine gas power generation), energy storage and the like.
The distributed power distribution network is a novel power supply system which is connected with a plurality of distributed power supplies and has a completely different traditional power supply mode, and in order to meet the needs of specific users or support the economic operation of the existing power distribution network, the distributed power distribution network is distributed near the users in a dispersed mode, and is a small modular independent power supply which is compatible with the environment and has the power generation power of thousands of watts to fifty megawatts; it is usually located near the user.
The distributed power supply is connected to the grid for power generation, so that the transmission loss of a long line can be reduced, and the technical effect of peak clipping and valley filling is realized. However, the distributed power supply can bring harmonic waves possibly generated during grid connection after grid connection, and meanwhile, due to the fact that the distributed power supply is connected, the voltage of a grid connection point can be raised, and therefore the voltage fluctuation range of the whole power distribution network is enlarged.
Therefore, the power quality problem of the power distribution network connected with the distributed power supply should be found in time, so that a solid foundation is laid for finding the root of the power quality problem of the power distribution network in time and eliminating the power quality problem caused by the connection of the distributed power supply.
Based on this, a power quality control method for a distributed power distribution network needs to be developed and designed.
Disclosure of Invention
The embodiment of the invention provides a method, a device, a terminal and a storage medium for controlling the power quality of a distributed power distribution network, which are used for solving the problem that the power quality of the power distribution network is not easy to control after a distributed power supply is connected in the prior art.
In a first aspect, an embodiment of the present invention provides a method for controlling power quality of a distributed power distribution network, including:
a distributed power distribution network electric energy quality control method is characterized by comprising the following steps:
acquiring a plurality of first feeder waveform data sets corresponding to a plurality of load feeders, wherein the plurality of power feeders and the plurality of load feeders are respectively and electrically connected with a bus, a load is accessed to the bus through the load feeders, and a distributed power supply is connected to the power grid through the power feeders for power generation;
extracting an abnormal waveform data set from the plurality of first feeder waveform data sets, wherein the abnormal waveform data set corresponds to an abnormal feeder with abnormal power supply among the plurality of feeders, and the abnormal waveform data set characterizes abnormal characteristics of the abnormal feeder;
determining a target power feed line from the set of abnormal waveform data and a plurality of second waveform data sets corresponding to the plurality of power feed lines;
and adjusting the power supply accessed to the target power supply feeder according to the abnormal waveform data set.
In one possible implementation, the first feeder waveform data set includes a first feeder voltage waveform data set, and the extracting an outlier waveform data set from the plurality of first feeder waveform data sets includes:
acquiring a bus voltage waveform data set of the bus;
determining the frequency of the voltage according to the bus voltage waveform data set;
according to the frequency of the voltage, fundamental wave extraction is carried out on the multiple first feeder voltage waveform data sets to obtain multiple fluctuation data sets, wherein the fluctuation data sets represent the fluctuation of the load feeder voltage;
determining a target load feeder from the plurality of fluctuation data sets;
and extracting to obtain an abnormal waveform data set according to the fluctuation data set of the target load feeder line and the first feeder voltage waveform data set of the target load feeder line.
In one possible implementation, the determining a frequency of a voltage from the bus voltage waveform data set includes:
determining the number of samples according to the sampling frequency of the bus voltage waveform data set;
a data taking step: according to the number of the samples, taking out a plurality of bus voltage waveform data from the bus voltage waveform data set according to the sequence of sampling time;
accumulating the plurality of taken bus voltage waveform data to obtain an accumulated sum;
if the absolute value of the accumulated sum is larger than a threshold value, adjusting the number of the samples, and skipping to the data taking step;
otherwise, determining the frequency of the voltage according to the number of the samples and the sampling frequency of the bus voltage waveform data set.
In one possible implementation manner, the performing fundamental wave extraction on the plurality of first feeder voltage waveform data sets according to the frequency of the voltage to obtain a plurality of fluctuation data sets includes:
for each of the plurality of first feeder voltage waveform data sets, performing the steps of:
dividing the first feeder voltage waveform data set into a plurality of vectors according to the frequency of the voltage, wherein the acquisition period of a plurality of elements in the vectors corresponds to the frequency of the voltage;
obtaining a fluctuation data set according to a first formula and the vectors, wherein the first formula is as follows:
where Vol (k) is the kth element of the wave data set, U k (M) is the M-th element of the k-th vector, M is the total number of elements in the vector, cos () is the cosine function, ω 0 The frequency of the voltage is delta t, and the sampling interval of the waveform data of the first feeder line voltage is delta t;
the extracting and obtaining an abnormal waveform data set according to the fluctuation data set of the target load feeder line and the first feeder line voltage waveform data set of the target load feeder line comprises:
for the plurality of vectors in each first feeder voltage waveform data set, performing the steps of:
obtaining an abnormal waveform data set according to a second formula, the fluctuation data set and the vectors, wherein the second formula is as follows:
where, abn (n) is the nth element in the abnormal waveform data set, [ ] is the rounding function, and MOD () is the remainder function.
In one possible implementation, the first feeder waveform data set includes a first feeder current waveform data set, and the extracting an abnormal waveform data set from the plurality of first feeder waveform data sets includes:
acquiring a bus voltage waveform data set of the bus;
determining the frequency of the voltage according to the bus voltage waveform data set;
performing reactive power extraction on the plurality of first feeder current waveform data sets according to the frequency of the voltage to obtain a plurality of first reactive data sets;
determining a target load feeder from the plurality of first reactive data sets;
and taking the first reactive data set of the target load feeder line as an abnormal waveform data set.
In one possible implementation, the reactive power extracting the plurality of first feeder current waveform data sets according to the frequency of the voltage to obtain a plurality of first reactive data sets includes:
for each of the plurality of first feeder current waveform data sets, performing the steps of:
dividing the first feeder voltage waveform data set into a plurality of vectors according to the frequency of the voltage, wherein the acquisition periods of a plurality of elements in the vectors correspond to the frequency of the voltage;
obtaining a first reactive data set according to a third formula and the vectors, wherein the third formula is:
where Rea (k) is the kth element of the first reactive data set, I k (M) is the mth element of the kth vector, M is the total number of elements in the vector, sin () is a sine function, ω 0 At is the frequency of the voltage, Δ t is the sampling interval of the first feeder current waveform data.
In one possible implementation, the determining a target power supply feed from the set of abnormal waveform data and a plurality of sets of second waveform data corresponding to the plurality of power supply feeds includes:
determining a plurality of voltage anomaly characteristics according to the abnormal waveform data set, a fourth formula and a plurality of second waveform data sets if the abnormal waveform data set is extracted based on the first feeder voltage waveform data set, wherein the fourth formula is:
UFeature (j) is the voltage abnormality characteristic of the jth power supply feeder, abn (N) is the nth element of the voltage abnormal waveform data set, N is the total number of the elements in the voltage abnormal waveform data set, and U is the total number of the elements in the voltage abnormal waveform data set j (n) is the nth element of the jth second waveform data set;
selecting a power supply feeder line with the voltage abnormal characteristic value exceeding a threshold value as a target power supply feeder line;
if the abnormal waveform data set is extracted based on a first feeder current waveform data set, extracting a plurality of second reactive data sets from a plurality of second waveform data sets and determining a plurality of current abnormality characteristics from the abnormal waveform data set, a fifth formula and a plurality of second reactive data sets, wherein the fifth formula is:
wherein IFeature (j) is the current anomaly characteristic of the jth power feeder, rea (K) is the kth element of the first reactive data set, K is the total number of elements in the first reactive data set, and Rea' (K) is the kth element of the jth second reactive data set;
and selecting the power supply feeder with the current abnormal characteristic value exceeding the threshold as a target power supply feeder.
In a second aspect, an embodiment of the present invention provides a power quality evaluation device for a power distribution network accessed by a distributed power supply, which is used to implement the power quality control method for the power distribution network in the first aspect or any one of the possible implementation manners of the first aspect, where the power quality evaluation device for the power distribution network accessed by the distributed power supply includes:
the system comprises a load feeder data acquisition module, a bus and a distributed power supply, wherein the load feeder data acquisition module is used for acquiring a plurality of first feeder waveform data sets corresponding to a plurality of load feeders, the plurality of power feeders and the plurality of load feeders are respectively and electrically connected with the bus, loads are accessed to the bus through the load feeders, and the distributed power supply is subjected to grid-connected power generation through the power feeders;
an abnormal waveform data extraction module, configured to extract an abnormal waveform data set according to the plurality of first feeder waveform data sets, where the abnormal waveform data set corresponds to an abnormal feeder with abnormal power supply among the plurality of feeders, and the abnormal waveform data set characterizes abnormal characteristics of the abnormal feeder;
a target power feeder location module to determine a target power feeder based on the set of abnormal waveform data and a plurality of sets of second waveform data corresponding to the plurality of power feeders;
and (c) a second step of,
and the power output adjusting module is used for adjusting the power accessed to the target power feeder according to the abnormal waveform data set.
In a third aspect, an embodiment of the present invention provides a terminal, which includes a memory and a processor, where the memory stores a computer program that is executable on the processor, and the processor executes the computer program to implement the steps of the method according to the first aspect or any one of the possible implementation manners of the first aspect.
In a fourth aspect, the present invention provides a computer-readable storage medium, which stores a computer program that, when executed by a processor, implements the steps of the method as described in the first aspect or any one of the possible implementations of the first aspect.
Compared with the prior art, the implementation mode of the invention has the following beneficial effects:
the embodiment of the invention discloses a power quality control method for a distributed power distribution network, which comprises the following steps of firstly obtaining a plurality of first feeder waveform data sets corresponding to a plurality of load feeders, wherein the plurality of power feeders and the plurality of load feeders are respectively and electrically connected with a bus, a load is accessed to the bus through the load feeders, and a distributed power supply is connected to the bus through the power feeders for grid-connected power generation; then, extracting an abnormal waveform data set according to the plurality of first feeder waveform data sets, wherein the abnormal waveform data set corresponds to an abnormal feeder with abnormal power supply in the plurality of feeders, and the abnormal waveform data set characterizes abnormal characteristics of the abnormal feeder; then, determining a target power supply feed line based on the abnormal waveform data set and a plurality of second waveform data sets corresponding to the plurality of power supply feed lines; and finally, adjusting the power supply accessed to the target power supply feeder according to the abnormal waveform data set. According to the embodiment of the invention, starting from each load feeder, the point of the electric energy intelligent connection problem of the load feeder and the abnormal load feeder are determined, then, according to the abnormal data of the abnormal load feeder, the abnormal characteristics of a plurality of power feeders are extracted according to the abnormal data, the power feeder with the highest abnormal relevance with the abnormal load feeder is found, and after targeted adjustment is carried out, the quality of the electric energy of the power distribution network can be improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
Fig. 1 is a flowchart of a power quality control method for a distributed power distribution network according to an embodiment of the present invention;
fig. 2 is a topology structure diagram of a distributed power distribution network according to an embodiment of the present invention;
FIG. 3 is a causal graph of power quality provided by an embodiment of the present invention;
fig. 4 is a functional block diagram of a power quality evaluation device for a distribution network to which a distributed power supply is connected according to an embodiment of the present invention;
fig. 5 is a functional block diagram of a terminal according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
To make the objects, technical solutions and advantages of the present invention more apparent, the following description is given by way of embodiments with reference to the accompanying drawings.
The following is a detailed description of the embodiments of the present invention, which is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
Fig. 1 is a flowchart of a method for controlling power quality of a distributed power distribution network according to an embodiment of the present invention.
As shown in fig. 1, it shows an implementation flowchart of a method for controlling power quality of a distributed power distribution network according to an embodiment of the present invention, which is detailed as follows:
in step 101, a plurality of first feeder waveform data sets corresponding to a plurality of load feeders are obtained, wherein a plurality of power feeders and the plurality of load feeders are respectively electrically connected to a bus, a load is connected to the bus through the load feeders, and a distributed power source is grid-connected to generate power through the power feeders.
In step 102, an abnormal waveform data set is extracted from the plurality of first feeder waveform data sets, wherein the abnormal waveform data set corresponds to an abnormal feeder with abnormal power supply in the plurality of feeders, and the abnormal waveform data set characterizes abnormal characteristics of the abnormal feeder.
In some embodiments, the first feeder waveform data set comprises a first feeder voltage waveform data set, said step 102 comprising:
acquiring a bus voltage waveform data set of the bus;
determining the frequency of the voltage according to the bus voltage waveform data set;
according to the frequency of the voltage, fundamental wave extraction is carried out on the multiple first feeder voltage waveform data sets to obtain multiple fluctuation data sets, wherein the fluctuation data sets represent the fluctuation of the load feeder voltage;
determining a target load feeder from the plurality of fluctuation data sets;
and extracting to obtain an abnormal waveform data set according to the fluctuation data set of the target load feeder line and the first feeder voltage waveform data set of the target load feeder line.
In some embodiments, said determining a frequency of a voltage from said bus voltage waveform data set comprises:
determining the number of samples according to the sampling frequency of the bus voltage waveform data set;
a data extraction step: according to the number of the samples, a plurality of bus voltage waveform data are taken out from the bus voltage waveform data set according to the sequence of sampling time;
accumulating the taken out multiple bus voltage waveform data to obtain an accumulated sum;
if the absolute value of the accumulated sum is larger than a threshold value, adjusting the number of the samples, and skipping to the data taking step;
otherwise, determining the frequency of the voltage according to the number of the samples and the sampling frequency of the bus voltage waveform data set.
In some embodiments, the performing fundamental wave extraction on the plurality of first feeder voltage waveform data sets according to the frequency of the voltage to obtain a plurality of waveform data sets includes:
for each of the plurality of first feeder voltage waveform data sets, performing the steps of:
dividing the first feeder voltage waveform data set into a plurality of vectors according to the frequency of the voltage, wherein the acquisition periods of a plurality of elements in the vectors correspond to the frequency of the voltage;
obtaining a fluctuation data set according to a first formula and the vectors, wherein the first formula is as follows:
where Vol (k) is the kth element of the wave data set, U k (M) is the M-th element of the k-th vector, M is the total number of elements in the vector, cos () is the cosine function, ω 0 The frequency of the voltage is delta t, and the sampling interval of the waveform data of the first feeder line voltage is delta t;
the extracting and obtaining an abnormal waveform data set according to the fluctuation data set of the target load feeder line and the first feeder line voltage waveform data set of the target load feeder line comprises:
for the plurality of vectors in each first feeder voltage waveform dataset, performing the steps of:
obtaining an abnormal waveform data set according to a second formula, the fluctuation data set and the vectors, wherein the second formula is as follows:
where, abn (n) is the nth element in the abnormal waveform data set, [ ] is the rounding function, and MOD () is the remainder function.
In some embodiments, the first feedline waveform dataset comprises a first feedline current waveform dataset, said step 102 comprising:
a waveform data set, extracting an abnormal waveform data set, comprising:
acquiring a bus voltage waveform data set of the bus;
determining the frequency of the voltage according to the bus voltage waveform data set;
performing reactive power extraction on the plurality of first feeder line current waveform data sets according to the frequency of the voltage to obtain a plurality of first reactive data sets;
determining a target load feeder from the plurality of first reactive data sets;
and taking the first reactive data set of the target load feeder line as an abnormal waveform data set.
In some embodiments, the reactive power extracting the plurality of first feeder current waveform data sets according to the frequency of the voltage to obtain a plurality of first reactive data sets comprises:
for each of the plurality of first feeder current waveform data sets, performing the steps of:
dividing the first feeder voltage waveform data set into a plurality of vectors according to the frequency of the voltage, wherein the acquisition periods of a plurality of elements in the vectors correspond to the frequency of the voltage;
obtaining a first reactive data set according to a third formula and the vectors, wherein the third formula is:
where Rea (k) is the kth element of the first reactive data set, I k (M) is the M-th element of the kth vector, M is the total number of elements in the vector, sin () is a sine function, ω 0 At is the frequency of the voltage, Δ t is the sampling interval of the first feeder current waveform data.
Illustratively, as shown in fig. 2, a distributed power distribution network includes a bus 202 connected to a main power supply 201, a load 206 connected to the bus 202 through a load feeder 205, and a distributed power supply 204 connected to the bus 202 through a power feeder 203 and connected to the main power supply 201 for grid-connected power generation.
As described above, distributed power sources are implemented in various forms, such as solar panels, wind generators, energy storage power generation devices, and the like, the distributed power generation devices and a main power supply are synchronized to generate power, and one technology adopts a power electronic technology to regulate and control output voltage and current of the distributed power generation devices, so as to implement synchronization.
Fig. 3 shows a causal diagram of distributed power generation with the main aspects of power quality being voltage fluctuations, current harmonics, power factor reduction and waveform distortion, respectively. The grid-connected output fluctuation of the power generation equipment mainly influences the voltage and current harmonic waves of a power grid, and the distributed power supply mainly adopts power electronics as the output end of a grid-connected interface, so that the waveform distortion of the current harmonic waves and the voltage is mainly influenced on the grid-connected interface, the voltage fluctuation, the power factor reduction and the waveform distortion are mainly influenced on the control method, and the power quasi-harmonic waves and the power factor reduction are mainly influenced on a load side.
From the above analysis, it can be seen that the impact of the distributed power supply on the power quality mainly includes the voltage characteristics: voltage fluctuation and voltage waveform distortion, and also includes current characteristics: current harmonics and power factor are reduced.
In the aspect of analyzing the power quality, the embodiment of the invention mainly starts from a load feeder line and acquires waveform data sets of a preset time period, such as a voltage waveform data set and/or a current waveform data set.
In terms of voltage characteristics, the period of the voltage waveform is determined according to the frequency of the bus voltage. The data set of the load feeder line is divided according to the period of the voltage waveform, the data belonging to one voltage waveform is divided into a vector, and then the amplitude of each periodic wave can be extracted according to a first formula:
where Vol (k) is the kth element of the wave data set, U k (M) is the mth element of the kth vector, M is the total number of elements in the vector, cos () is a cosine function, ω 0 The frequency of the voltage is delta t, and the sampling interval of the waveform data of the first feeder line voltage is delta t;
according to the formula, a fluctuation data set corresponding to each load feeder line can be determined, the meaning of each element numerical value in the fluctuation data set is the amplitude of a complete wave (the amplitudes of a plurality of waves can be realized by adjusting a data sampling interval), and if the amplitude of one wave in the plurality of waves exceeds a preset upper limit value, the situation that the voltage exceeds the limit exists is shown; or the difference between the maximum amplitude and the minimum amplitude of the plurality of waves exceeds a threshold, indicating that the volatility is out of tolerance.
Through the analysis, the load feeder line with abnormal voltage fluctuation can be determined, and an abnormal data set of the load feeder line can be extracted through a second formula, wherein the second formula is as follows:
where, abn (n) is the nth element in the abnormal waveform data set, [ ] is the rounding function, and MOD () is the remainder function.
For current characterization, in addition to the cause of current harmonics, most current quality issues are caused by distributed power sources, where an important item is power factor reduction, and in one embodiment, the feeder line with power quality issues is determined by extracting a reactive data set.
For the aspect of extracting the reactive data, the embodiment of the invention divides the current data set into sampling data segments with the same voltage period according to the frequency of the voltage, and determines the first reactive data set according to a third formula by a plurality of vectors formed by a plurality of sampling data segments, wherein the third formula is as follows:
where Rea (k) is the kth element of the first reactive data set, I k (M) is the mth element of the kth vector, M is the total number of elements in the vector, sin () is a sine function, ω 0 At is the frequency of the voltage, Δ t is the sampling interval of the first feeder current waveform data.
In step 103, a target power supply feed is determined from the set of abnormal waveform data and a plurality of second waveform data sets corresponding to the plurality of power supply feeds.
In some embodiments, the step 103 comprises: determining a plurality of voltage anomaly characteristics according to the abnormal waveform data set, a fourth formula and a plurality of second waveform data sets if the abnormal waveform data set is extracted based on the first feeder voltage waveform data set, wherein the fourth formula is:
UFeature (j) is the voltage abnormality characteristic of the jth power supply feeder, abn (N) is the nth element of the voltage abnormal waveform data set, N is the total number of the elements in the voltage abnormal waveform data set, and U is the total number of the elements in the voltage abnormal waveform data set j (n) is the nth element of the jth second waveform data set;
selecting a power supply feeder line with the voltage abnormal characteristic value exceeding a threshold value as a target power supply feeder line;
if the abnormal waveform data set is extracted based on a first feeder current waveform data set, extracting a plurality of second reactive data sets from a plurality of second waveform data sets and determining a plurality of current abnormality characteristics from the abnormal waveform data set, a fifth formula and a plurality of second reactive data sets, wherein the fifth formula is:
wherein IFeature (j) is the current anomaly characteristic of the jth power feeder, rea (K) is the kth element of the first reactive data set, K is the total number of elements in the first reactive data set, and Rea' (K) is the kth element of the jth second reactive data set;
and selecting the power feeder with the current abnormal characteristic value exceeding the threshold as a target power feeder.
Exemplarily, as can be seen from fig. 2, in general, there are multiple load feeders and multiple power feeders in a power distribution network, and for the problems of voltage fluctuation and power factor reduction in the load feeders, the conventional circuit analysis manner is complex and the calculation cost is high.
The embodiment of the invention adopts a characteristic matching mode, for example, for the problem of voltage abnormity, the voltage abnormity characteristic values of a plurality of power supply feeders are obtained through a fourth formula:
UFeature (j) is the voltage abnormality characteristic of the jth power supply feeder, abn (N) is the nth element of the voltage abnormal waveform data set, N is the total number of the elements in the voltage abnormal waveform data set, and U is the total number of the elements in the voltage abnormal waveform data set j (n) is the n-th element of the j-th second waveform data set.
The above process may be understood as finding one or more power feeders having the largest influence on the anomaly of the anomalous load feeder, if the voltage exceeds the limit, the output or the power factor of the output should be reduced, and if the voltage fluctuates, the output should be reduced.
For the current abnormity problem, firstly, a reactive data set of the power feeder is obtained by analyzing the current waveform in the manner of the current waveform of the load feeder as before, and then a plurality of current abnormity characteristic values of a plurality of power feeders are determined through a fifth formula:
wherein ifefuture (j) is a current anomaly characteristic of the jth power feeder, rea (K) is a kth element of the first reactive data set, K is a total number of elements in the first reactive data set, and Rea' (K) is a kth element of the jth second reactive data set.
The above process is a process of feature matching, and the power feeder whose current anomaly feature value exceeds the threshold value is determined as the power feeder that affects the anomalous load feeder.
In the case of power reduction caused by the power supply, one measure that can be taken is to improve the output of the power supply, e.g. the power factor reduction that is usually caused by the load, by means of phase compensation of the output voltage of the power supply, and thus to increase the power factor of the load feeder.
In step 104, the power supply to the target power supply feed line is adjusted according to the abnormal waveform data set.
Illustratively, as mentioned above, the above process determines the power quality problems of the feeder, such as voltage overrun, voltage fluctuation and power factor reduction, and also finds the power feeder with the highest abnormal relevance to the abnormally loaded feeder by determining the abnormal characteristics, at this time, measures can be taken, such as reducing the output of the power supply, thereby reducing the voltage overrun problem, changing the power factor of the load by changing the phase of the power output, and after adjustment, performing the above analysis and adjustment process again, that is, an iterative process, to achieve the adjustment of the power quality of the distribution network.
The invention relates to an implementation mode of an electric energy quality control method of a distributed power distribution network, which comprises the steps of firstly obtaining a plurality of first feeder waveform data sets corresponding to a plurality of load feeders, wherein a plurality of power feeders and the plurality of load feeders are respectively and electrically connected with a bus, loads are accessed to the bus through the load feeders, and distributed power supplies are subjected to grid-connected power generation through the power feeders; then, extracting an abnormal waveform data set according to the plurality of first feeder waveform data sets, wherein the abnormal waveform data set corresponds to an abnormal feeder with abnormal power supply in the plurality of feeders, and the abnormal waveform data set characterizes abnormal characteristics of the abnormal feeder; then, determining a target power supply feed line based on the abnormal waveform data set and a plurality of second waveform data sets corresponding to the plurality of power supply feed lines; and finally, adjusting the power supply accessed to the target power supply feeder according to the abnormal waveform data set. According to the embodiment of the invention, starting from each load feeder, the point of the electric energy intelligent connection problem of the load feeder and the abnormal load feeder are determined, then, according to the abnormal data of the abnormal load feeder, the abnormal characteristics of a plurality of power feeders are extracted according to the abnormal data, the power feeder with the highest abnormal relevance with the abnormal load feeder is found, and after the targeted adjustment is carried out, the electric energy quality of the power distribution network can be improved.
It should be understood that the sequence numbers of the steps in the above embodiments do not mean the execution sequence, and the execution sequence of each process should be determined by the function and the inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
The following are apparatus embodiments of the invention, and for details not described in detail therein, reference may be made to the corresponding method embodiments described above.
Fig. 4 is a functional block diagram of a power quality evaluation apparatus for a distribution network to which a distributed power supply is connected according to an embodiment of the present invention, and referring to fig. 4, the power quality evaluation apparatus 4 for a distribution network to which a distributed power supply is connected includes: load feeder data acquisition module 401, abnormal waveform data extraction module 402, target power feeder location module 403, and power output adjustment module 404, where:
a load feeder data obtaining module 401, configured to obtain a plurality of first feeder waveform data sets corresponding to a plurality of load feeders, where a plurality of power feeders and the plurality of load feeders are electrically connected to a bus respectively, a load is connected to the bus through a load feeder, and a distributed power source is grid-connected to generate power through a power feeder;
an abnormal waveform data extraction module 402, configured to extract an abnormal waveform data set from the plurality of first feeder waveform data sets, where the abnormal waveform data set corresponds to an abnormal feeder with abnormal power supply among the plurality of feeders, and the abnormal waveform data set characterizes an abnormal feature of the abnormal feeder;
a target power feeder location module 403, configured to determine a target power feeder according to the abnormal waveform data set and a plurality of second waveform data sets corresponding to the plurality of power feeders;
and a power output adjusting module 404, configured to adjust a power source connected to the target power feeder according to the abnormal waveform data set.
Fig. 5 is a functional block diagram of a terminal according to an embodiment of the present invention. As shown in fig. 5, the terminal 5 of this embodiment includes: a processor 500 and a memory 501, the memory 501 having stored therein a computer program 502 executable on the processor 500. The processor 500 executes the computer program 502 to implement the above-described methods and embodiments of the distributed power distribution network power quality control, such as steps 101 to 104 shown in fig. 1.
Illustratively, the computer program 502 may be partitioned into one or more modules/units, which are stored in the memory 501 and executed by the processor 500 to implement the present invention.
The terminal 5 may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The terminal 5 may include, but is not limited to, a processor 500, a memory 501. It will be appreciated by those skilled in the art that fig. 5 is only an example of a terminal 5 and does not constitute a limitation of the terminal 5, and that it may comprise more or less components than those shown, or some components may be combined, or different components, for example, the terminal 5 may further comprise input and output devices, network access devices, buses, etc.
The Processor 500 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 501 may be an internal storage unit of the terminal 5, such as a hard disk or a memory of the terminal 5. The memory 501 may also be an external storage device of the terminal 5, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) and the like provided on the terminal 5. Further, the memory 501 may also include both an internal storage unit and an external storage device of the terminal 5. The memory 501 is used for storing the computer program 502 and other programs and data required by the terminal 5. The memory 501 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit, and the integrated unit may be implemented in a form of hardware, or may be implemented in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. For the specific working processes of the units and modules in the system, reference may be made to the corresponding processes in the foregoing method embodiments, which are not described herein again.
In the above embodiments, the description of each embodiment is focused on, and for parts that are not described or illustrated in detail in a certain embodiment, reference may be made to the description of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal and method may be implemented in other manners. For example, the above-described apparatus/terminal embodiments are merely illustrative, and for example, the division of the modules or units is only one type of logical function division, and other division manners may exist in actual implementation, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may also be implemented in the form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method according to the above embodiments may be implemented by a computer program, which may be stored in a computer readable storage medium and used for implementing the steps of the method and apparatus embodiments when executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like.
The above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may be modified or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. A distributed power distribution network power quality control method is characterized by comprising the following steps:
acquiring a plurality of first feeder waveform data sets corresponding to a plurality of load feeders, wherein a plurality of power feeders and the plurality of load feeders are respectively and electrically connected with a bus, a load is accessed to the bus through the load feeders, and a distributed power supply is subjected to grid-connected power generation through the power feeders;
extracting an abnormal waveform data set according to the plurality of first feeder waveform data sets, wherein the abnormal waveform data set corresponds to an abnormal feeder with abnormal power supply in the plurality of feeders, and the abnormal waveform data set characterizes abnormal characteristics of the abnormal feeder;
determining a target power supply feed line from the set of abnormal waveform data and a plurality of sets of second waveform data corresponding to the plurality of power supply feed lines;
and adjusting the power supply accessed to the target power supply feeder according to the abnormal waveform data set.
2. The method of claim 1, wherein the first feeder waveform data set comprises a first feeder voltage waveform data set, and wherein extracting the outlier waveform data set from the plurality of first feeder waveform data sets comprises:
acquiring a bus voltage waveform data set of the bus;
determining the frequency of the voltage according to the bus voltage waveform data set;
according to the frequency of the voltage, fundamental wave extraction is carried out on the multiple first feeder voltage waveform data sets to obtain multiple fluctuation data sets, wherein the fluctuation data sets represent the fluctuation of the load feeder voltage;
determining a target load feeder from the plurality of fluctuation data sets;
and extracting to obtain an abnormal waveform data set according to the fluctuation data set of the target load feeder line and the first feeder line voltage waveform data set of the target load feeder line.
3. The method of claim 2, wherein determining the frequency of the voltage from the bus voltage waveform data set comprises:
determining the number of samples according to the sampling frequency of the bus voltage waveform data set;
a data taking step: according to the number of the samples, taking out a plurality of bus voltage waveform data from the bus voltage waveform data set according to the sequence of sampling time;
accumulating the plurality of taken bus voltage waveform data to obtain an accumulated sum;
if the absolute value of the accumulated sum is larger than a threshold value, adjusting the number of the samples, and skipping to the data taking step;
otherwise, determining the frequency of the voltage according to the number of the samples and the sampling frequency of the bus voltage waveform data set.
4. The method for controlling the power quality of the distributed power distribution network according to claim 2, wherein the performing fundamental wave extraction on the plurality of first feeder voltage waveform data sets according to the frequency of the voltage to obtain a plurality of fluctuation data sets comprises:
for each of the plurality of first feeder voltage waveform data sets, performing the steps of:
dividing the first feeder voltage waveform data set into a plurality of vectors according to the frequency of the voltage, wherein the acquisition periods of a plurality of elements in the vectors correspond to the frequency of the voltage;
obtaining a fluctuation data set according to a first formula and the vectors, wherein the first formula is as follows:
where Vol (k) is the kth element of the wave data set, U k (M) is the mth element of the kth vector, M is the total number of elements in the vector, cos () is a cosine function, ω 0 The frequency of the voltage is delta t, and the sampling interval of the waveform data of the first feeder voltage is delta t;
the extracting and obtaining an abnormal waveform data set according to the fluctuation data set of the target load feeder line and the first feeder line voltage waveform data set of the target load feeder line comprises:
for the plurality of vectors in each first feeder voltage waveform dataset, performing the steps of:
obtaining an abnormal waveform data set according to a second formula, the fluctuation data set and the vectors, wherein the second formula is as follows:
where Abn (n) is the nth element in the set of abnormal waveform data, [ ] is a rounding function, and MOD () is a remainder function.
5. The method of claim 1, wherein the first feeder waveform data set comprises a first feeder current waveform data set, and wherein extracting the outlier waveform data set from the plurality of first feeder waveform data sets comprises:
acquiring a bus voltage waveform data set of the bus;
determining the frequency of the voltage according to the bus voltage waveform data set;
performing reactive power extraction on the plurality of first feeder line current waveform data sets according to the frequency of the voltage to obtain a plurality of first reactive data sets;
determining a target load feeder from the plurality of first reactive data sets;
and taking the first reactive data set of the target load feeder line as an abnormal waveform data set.
6. The method of claim 5, wherein the reactive power extracting the first feeder current waveform data sets according to the frequency of the voltage to obtain first reactive data sets comprises:
for each of the plurality of first feeder current waveform data sets, performing the steps of:
dividing the first feeder voltage waveform data set into a plurality of vectors according to the frequency of the voltage, wherein the acquisition periods of a plurality of elements in the vectors correspond to the frequency of the voltage;
obtaining a first reactive data set according to a third formula and the vectors, wherein the third formula is:
wherein Rea (k) is the first idleKth element of data set, I k (M) is the mth element of the kth vector, M is the total number of elements in the vector, sin () is a sine function, ω 0 At is the frequency of the voltage, Δ t is the sampling interval of the first feeder current waveform data.
7. The method according to any one of claims 1 to 6, wherein determining a target power feeder from the set of abnormal waveform data and a plurality of sets of second waveform data corresponding to the plurality of power feeders comprises:
determining a plurality of voltage anomaly characteristics according to the abnormal waveform data set, a fourth formula and a plurality of second waveform data sets if the abnormal waveform data set is extracted based on the first feeder voltage waveform data set, wherein the fourth formula is:
UFeature (j) is the voltage abnormality characteristic of the jth power supply feeder, abn (N) is the nth element of the voltage abnormal waveform data set, N is the total number of the elements in the voltage abnormal waveform data set, and U is the total number of the elements in the voltage abnormal waveform data set j (n) is the nth element of the jth second waveform data set;
selecting a power feeder line with a voltage anomaly characteristic value exceeding a threshold value as a target power feeder line;
if the abnormal waveform data set is extracted based on a first feeder current waveform data set, extracting a plurality of second reactive data sets from a plurality of second waveform data sets and determining a plurality of current abnormality characteristics from the abnormal waveform data set, a fifth formula and a plurality of second reactive data sets, wherein the fifth formula is:
wherein IFeature (j) is the current anomaly characteristic of the jth power feeder, rea (K) is the kth element of the first reactive data set, K is the total number of elements in the first reactive data set, and Rea' (K) is the kth element of the jth second reactive data set;
and selecting the power feeder with the current abnormal characteristic value exceeding the threshold as a target power feeder.
8. A power quality evaluation device of a distribution network accessed by a distributed power supply, which is used for realizing the power quality control method of the distribution network according to any one of claims 1 to 7, and the power quality evaluation device of the distribution network accessed by the distributed power supply comprises:
the load feeder data acquisition module is used for acquiring a plurality of first feeder waveform data sets corresponding to a plurality of load feeders, wherein the plurality of power feeders and the plurality of load feeders are respectively and electrically connected with a bus, a load is connected into the bus through the load feeders, and a distributed power supply is connected to the power grid through the power feeders for power generation;
an abnormal waveform data extraction module, configured to extract an abnormal waveform data set according to the first feeder waveform data sets, where the abnormal waveform data set corresponds to an abnormal feeder with abnormal power supply among the feeders, and the abnormal waveform data set represents an abnormal feature of the abnormal feeder;
a target power feeder location module to determine a target power feeder based on the set of abnormal waveform data and a plurality of sets of second waveform data corresponding to the plurality of power feeders;
and the number of the first and second groups,
and the power output adjusting module is used for adjusting the power accessed to the target power feeder according to the abnormal waveform data set.
9. A terminal comprising a memory and a processor, the memory having stored therein a computer program operable on the processor, wherein the processor, when executing the computer program, performs the steps of the method according to any of claims 1 to 7.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116231868A (en) * | 2023-03-23 | 2023-06-06 | 北京东华博泰科技有限公司 | Hydropower safety monitoring system based on Internet of things |
| CN116581875A (en) * | 2023-04-24 | 2023-08-11 | 中广核新能源(定远)有限公司 | Distributed power supply power quality monitoring method and device |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116231868A (en) * | 2023-03-23 | 2023-06-06 | 北京东华博泰科技有限公司 | Hydropower safety monitoring system based on Internet of things |
| CN116231868B (en) * | 2023-03-23 | 2023-10-03 | 北京东华博泰科技有限公司 | Hydropower safety monitoring system based on Internet of things |
| CN116581875A (en) * | 2023-04-24 | 2023-08-11 | 中广核新能源(定远)有限公司 | Distributed power supply power quality monitoring method and device |
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