CN108233373B - A Probabilistic Harmonic Analysis Method for Distributed Photovoltaic Access to Distribution Network Considering Weather Scenarios - Google Patents
A Probabilistic Harmonic Analysis Method for Distributed Photovoltaic Access to Distribution Network Considering Weather Scenarios Download PDFInfo
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Abstract
本发明提出的考虑天气场景的分布式光伏接入配电网的概率谐波分析方法，首先由典型天气场景下的分布式光伏系统输出功率曲线通过参数估计方法得到其Beta分布的形状参数，确定光伏系统输出功率的概率分布模型，并进行抽样，得到分布式光伏输出功率值，进行谐波潮流计算，得到配电网的谐波注入电流，进而得到系统各节点的谐波电压,当完成所有抽样次数后，计算得到配电网的谐波电压概率分布和谐波畸变率THD。
The method for probabilistic harmonic analysis of distributed photovoltaics connected to the distribution network considering weather scenarios proposed by the present invention firstly obtains the shape parameters of its Beta distribution from the output power curve of the distributed photovoltaic system under typical weather scenarios through a parameter estimation method, and determines The probability distribution model of the output power of the photovoltaic system, and sampling to obtain the distributed photovoltaic output power value, carry out the harmonic power flow calculation, obtain the harmonic injection current of the distribution network, and then obtain the harmonic voltage of each node of the system. After sampling times, the harmonic voltage probability distribution and harmonic distortion rate THD of the distribution network are calculated.
Description
Technical Field
The invention relates to the technical field of photovoltaic power generation, in particular to a probability harmonic analysis method for a distributed photovoltaic access power distribution network considering a weather scene.
Background
The distributed power supply has the advantages of environmental protection, high efficiency, safety, flexibility, high cost performance, short construction period and small risk, can be used as supplement of centralized energy, is coordinated with a large power grid for development, can save investment, reduce energy consumption and improve the reliability and flexibility of a power system, and becomes an important direction of a world energy strategy.
Common distributed power sources include wind power generation, solar power generation, small hydropower, micro gas turbines, fuel cells, and the like. Most distributed power generation facilities require power frequency ac power to be delivered to the grid or to the users through utility power electronics. These power electronics devices may cause distortion of the current and voltage waveforms of the power grid, resulting in harmonic pollution of the power grid.
On the other hand, the random change of the wind speed and the illumination intensity is the natural property of renewable energy, so that the electric energy generated by wind power generation and photovoltaic power generation also changes randomly, and further, the harmonic waves generated by the distributed power supply also have randomness. Therefore, it is necessary to perform calculation and analysis by using a probability method. Meteorological conditions have a large influence on the photovoltaic output power, so that the harmonic distortion condition of the distributed photovoltaic access power distribution network is analyzed respectively according to different weather meteorological conditions.
Disclosure of Invention
There is a need to provide a probability harmonic analysis method for a distributed photovoltaic access distribution network considering weather scenarios.
A probability harmonic analysis method for a distributed photovoltaic access power distribution network considering weather scenes is characterized by comprising the following steps:
the first step is as follows: photovoltaic power generation output power P of distributed photovoltaic access power distribution network by utilizing K-MEANS clustering analysis methodpvCounting and clustering to obtain a photovoltaic output power curve and distribution probability of the photovoltaic output power curve in a typical weather scene;
the second step is that: according to the photovoltaic output power curve of the first step of typical weather scene, performing parameter estimation by adopting a least square method, and establishing a photovoltaic power generation power output probability density function of the photovoltaic power station under different weather scenes:
in the formula, PPVFor photovoltaic power generation output power, PmaxAlpha and Beta are shape parameters of Beta distribution function, and are the maximum value of the output power of the photovoltaic power generation;
the third step: based on the photovoltaic power generation power output probability density function, the Monte Carlo method is adopted to respectively sample the photovoltaic power generation power under various typical weather scenes, and the photovoltaic output power sampling value under the weather scene is obtained through sampling.
The fourth step: according to the sampling value of the photovoltaic power generation power, carrying out harmonic load flow calculation on the sampling value of the photovoltaic output power of the power distribution network to obtain each subharmonic current and harmonic voltage value injected into the power distribution network;
the fifth step: if the sampling times are less than the sampling set times, returning to the third step to continue sampling calculation, and calculating the average value of the harmonic voltages injected into the power distribution network, otherwise, performing the next step;
and a sixth step: substituting the harmonic voltage mean value of each harmonic into the following harmonic voltage distortion rate formula to calculate the harmonic voltage distortion rate THD of each harmonic under various typical weather scenesu；
Harmonic voltage distortion rate formula:
in the formula: uh: the harmonic voltage amplitude of the h harmonic; u shape1: a fundamental voltage amplitude; n: the highest order of the harmonic considered;
the seventh step: after the harmonic voltage distortion rate analysis and calculation under various typical weather scenes are completed, the probabilities and the harmonic voltage distortion rates corresponding to the various typical weather scenes are substituted into the following formula for calculation and analysis to obtain the harmonic voltage distortion rate THD of the distributed photovoltaic access power distribution network in a certain region,
in the formula: piThe probabilities corresponding to various typical weather scenes; THDUiFor the harmonic voltage distortion rate in various types of typical weather scenes, i is a classification label of various types of typical weather scenes, and S is the number of the typical weather scenes.
According to the method, firstly, the output power curve of the distributed photovoltaic system in a typical weather scene is used for obtaining the Beta distribution shape parameters through a parameter estimation method, a probability distribution model of the output power of the photovoltaic system is determined, sampling is carried out, the distributed photovoltaic output power value is obtained, harmonic load flow calculation is carried out, the harmonic injection current of the power distribution network is obtained, and further the harmonic voltage of each node of the system is obtained. And after all sampling times are finished, calculating to obtain the harmonic voltage probability distribution and the harmonic distortion rate THD of the power distribution network.
Drawings
Fig. 1 is a schematic diagram of photovoltaic power generation.
Fig. 2 is an equivalent circuit of a single harmonic distribution network.
FIG. 3 is a flow chart of the calculation of the present invention.
Fig. 4 shows a medium voltage radiation type distribution network system topology of IEEE33 nodes.
Fig. 5 is a graph of branch circuit parameters and bus load data for an IEEE33 system in an embodiment of the present invention.
FIG. 6 is a graph of the harmonic voltage content of a PCC point for a first type of weather in accordance with an embodiment of the present invention.
FIG. 7 is a graph of the harmonic voltage content of a PCC point on a second typical weather in accordance with an embodiment of the present invention.
FIG. 8 is a graph of the voltage content of each harmonic of a PCC point on a third type of typical weather in accordance with an embodiment of the present invention.
FIG. 9 is a graph of the harmonic voltage content of a PCC point for a fourth type of typical weather in accordance with an embodiment of the present invention.
Fig. 10 is a fifth harmonic voltage probability distribution of PCC during a first typical weather in accordance with an embodiment of the present invention.
Fig. 11 is a seventh harmonic voltage probability distribution of a PCC under a first typical weather in an embodiment of the present invention.
Fig. 12 is a probability distribution of eleven harmonic voltages at the PCC points under a first typical weather condition in accordance with an embodiment of the present invention.
Fig. 13 is a thirteen-harmonic voltage probability distribution of the PCC points under the first typical weather in the embodiment of the present invention.
Fig. 14 is a seventy-seventh harmonic voltage probability distribution of a PCC under a first typical weather in an embodiment of the present invention.
Fig. 15 is a fifth harmonic voltage probability distribution of PCC during a second typical weather in accordance with an embodiment of the present invention.
Fig. 16 is a seventh harmonic voltage probability distribution of a PCC under a second typical weather in an embodiment of the present invention.
Fig. 17 is a probability distribution of eleven harmonic voltages at a PCC in a second typical weather in accordance with an embodiment of the present invention.
Fig. 18 is a thirteen-harmonic voltage probability distribution of a PCC under a second typical weather condition in accordance with an embodiment of the present invention.
Fig. 19 is a seventy-seventh harmonic voltage probability distribution of a PCC under a second typical weather in an embodiment of the present invention.
Fig. 20 is a fifth harmonic voltage probability distribution of PCC during a third typical weather in accordance with an embodiment of the present invention.
Fig. 21 is a seventh harmonic voltage probability distribution of a PCC during a third typical weather in accordance with an embodiment of the present invention.
Fig. 22 is a probability distribution of eleven harmonic voltages at the PCC points under a third typical weather in an embodiment of the present invention.
Fig. 23 is a thirteen-harmonic voltage probability distribution of a PCC under a third typical weather in an embodiment of the present invention.
Fig. 24 is a seventy-seventh harmonic voltage probability distribution of a PCC under a third typical weather in an embodiment of the present invention.
Fig. 25 is a fifth harmonic voltage probability distribution of PCC during a fourth typical weather in accordance with an embodiment of the present invention.
Fig. 26 is a seventh harmonic voltage probability distribution of a PCC under a fourth typical weather in an embodiment of the present invention.
Fig. 27 is a probability distribution of eleven harmonic voltages at the PCC in a fourth exemplary weather in accordance with an embodiment of the present invention.
Fig. 28 is a thirteen-harmonic voltage probability distribution of a PCC under a fourth typical weather in an embodiment of the present invention.
Fig. 29 is a seventy-seventh harmonic voltage probability distribution of a PCC under a fourth typical weather in an embodiment of the present invention.
Detailed Description
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are 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 creative efforts.
Referring to fig. 1 to 3, an embodiment of the present invention provides a probability harmonic analysis method for a distributed photovoltaic access distribution network considering a weather scene.
1. Output power probability model for constructing distributed photovoltaic power generation
(1) Photovoltaic power generation power output model
As shown in fig. 1, the principle of solar photovoltaic power generation mainly uses the photoelectric effect to convert the solar light energy into electric energy, and its main components include a photovoltaic array formed by solar panels, and an inverter and a controller used for grid connection. The power output of a photovoltaic cell is mainly related to the intensity of solar radiation, the area of the photovoltaic array and the photoelectric conversion efficiency. The output power of photovoltaic power generation is therefore approximated by
PPV＝r·A·ρ (1)
In the formula, r is solar irradiance, A is the area of the photovoltaic array, and rho is photoelectric conversion efficiency.
The output power of the photovoltaic power generation can be obtained by inquiring or counting according to historical monitoring data of photovoltaic power stations in certain areas.
(2) Probability distribution model for solar illumination radiation intensity under different weather scenes
The solar irradiance is generally most commonly distributed by adopting a Beta distribution, and the probability density function of the Beta distribution is as follows:
wherein r is solar irradiance, rmaxAlpha and Beta are the shape parameters of the Beta distribution for the solar irradiance maximum.
In the same region, there are many factors affecting the intensity of illumination radiation, wherein the weather scene is one of the main factors. The shape parameters of the probability distribution functions of the corresponding illumination radiation intensities in different weather scenes are also different.
(3) Probability distribution model of photovoltaic power generation power
The probability density function of the photovoltaic power generation power output can be obtained by combining the existing photovoltaic power generation power output model and the probability distribution function of the illumination intensity
In the formula, PpvFor photovoltaic power generation output power, PmaxAlpha and Beta are shape parameters of Beta distribution function, and are the maximum value of the output power of the photovoltaic power generation; pmaxCan be calculated by the following formula:
Pmax＝rmax·A·ρ (4)
2. clustering analysis and parameter estimation of typical weather scenes
(1) Typical weather scene clustering analysis
In order to make the analyzed weather condition and photovoltaic output more representative, the invention obtains and obtains a photovoltaic output curve under a typical weather scene by adopting a cluster analysis method.
Clustering is the division of a collection of data units into several subsets called clusters, where the data in each cluster has greater similarity. Clustering is mainly used for finding valuable data distribution and data patterns in potential data, and is an important component in data mining. The clustering process can be defined as follows: given N data points of d-dimensional space, the N data points are divided into k clusters according to the degree of similarity between the data points, i.e. it is satisfied that similar samples are in the same cluster and dissimilar samples are in different clusters, so that objects in the same cluster have as much similarity as possible, while objects in different clusters have as much dissimilarity as possible. If a data set X containing N samples X1, …, xN is clustered into c sub-classes X1, …, Xc, X1, …, Xc is required to satisfy:
classical cluster analysis methods include the following categories: (1) the marking method typically represents algorithms such as K-MEANS, K-MEDOIDS and CLARANS algorithms. (2) The hierarchy method typically represents algorithms such as CURE, Chameleon, ROCK and BRICH algorithms. (3) Typical algorithms for the density-based clustering method include a density algorithm, a DBSCAN algorithm, an OPTIC algorithm, and the like. (4) A grid-based clustering method. Common grid-based clustering algorithms include a statistical information grid method STING, a clustering high-dimensional space method CIQUE, a wavelet transform-based clustering method Wave Cluster and the like. (5) A model-based clustering method. The method mainly comprises a statistical method and a neural network method. (6) A group intelligence algorithm. Typically representing the main ant colony algorithm and the particle swarm optimization algorithm. The invention adopts the most classical K-MEANS clustering method for analysis.
(2) Parameter estimation
The most widely used method in parameter estimation is the least squares method. The invention adopts a least square method to carry out parameter estimation of two parameters.
For given data (x)i,yi) I is 1, …, n, is
Is linearly independent, find
Make an error
Has the smallest sum of squares, i.e.
In a geometric sense, it is sought to associate a given point (x)i,yi) The curve y (p) (x) in which the sum of squared distances of i (1) and … (n) is the minimum, the function p (x) is called a fitting function or a least-squares solution, and the method of obtaining the fitting function p (x) is called a least-squares method of curve fitting.
Is provided with
When in use
Time, error ri＝p(xi)-yiI-1, …, m is the smallest sum of squares, if defined
Then satisfy
The system of linear equations of (1) is:
due to the fact that
The linear independence, the determinant of the coefficient matrix is not equal to 0, and the equation set has a unique solution.
When the least square method is used for parameter estimation, only a given set of data is required to be substituted into the equation set
Obtain the unknown aiThe unknown a can be obtained by left divisioni。
3. Principle of harmonic analysis
(1) Harmonic analysis of distributed photovoltaic power distribution network
When the photovoltaic inverter converts direct current into alternating current, certain harmonic waves are generated. The content of the output harmonic is related to the topological structure, the control strategy and the parameter setting of the inverter. When the photovoltaic output is changed, the content of harmonic current generated by photovoltaic power generation is also changed.
The harmonic model of the power distribution network comprises all power elements, the harmonic model comprises distributed photovoltaic, a transformer, a power transmission line and a load, the harmonic model of the power distribution network containing the distributed photovoltaic is built for researching the harmonic current distribution condition of an ideal power distribution network in a steady state, and an equivalent circuit diagram of the single harmonic power distribution network is shown in fig. 2.
In the power distribution network researched by the invention, except for the distributed photovoltaic inverter, other harmonic sources do not exist, namely, no harmonic exists in the power distribution network. After distributed photovoltaic access, h-order harmonic current I is injected into the power distribution network as a harmonic current sourcesh，
H-harmonic equivalent impedance, I, of a load behind a photovoltaic access Point (PC)LbhFor h-harmonic currents of the load after the point PC, ILahFor h harmonic currents before flowing to the access point,
h-harmonic equivalent impedance of the load before the PC point, ILhFor the h harmonic current flowing into the load before the PC point,
is h-order harmonic equivalent impedance between a Load access Point (PL) and a Common access Point (PCC), which mainly depends on the harmonic impedance of a transformer and a line, IeqhIs the h harmonic current flowing into the PCC point.
(2) Distributed photovoltaic injection harmonic current distribution analysis
H-order harmonic current is injected into a power distribution network from a PC point of distributed photovoltaic system
Ish-ILbh-ILah＝0 (7)
Harmonic current I flowing to PCC pointeqhIs composed of
As can be seen from the formula (9),harmonic current I flowing into PCC pointeqhBy
And
are determined jointly by
Much less than
And
the harmonic currents of the distributed photovoltaic injection distribution network mostly flow into the PCC points.
The most common indicator of voltage waveform is Total Harmonic Distortion (THD), which takes into account the effect of each Harmonic component on the signal. The calculation formula is as follows:
in the formula: uh: the harmonic voltage amplitude of the h harmonic; u shape1: a fundamental voltage amplitude; n: the highest order of the harmonic considered;
4. probability harmonic analysis method framework of distributed photovoltaic access considering typical weather scene
Sampling photovoltaic power generation power in the photovoltaic power generation power output probability density function under various typical weather scenes by adopting a Monte Carlo method, and performing harmonic load flow calculation on the sampling value of the photovoltaic power generation power to obtain a harmonic current injection value and a harmonic voltage of each subharmonic injected into the power distribution network;
if the sampling times are less than the sampling set times, returning to the previous step to continue sampling calculation, and otherwise, performing the next step; substituting the harmonic voltage of each harmonic into the following harmonic voltage distortion rate formula to calculate to obtain each harmonic voltage under each typical weather sceneHarmonic voltage distortion rate THD of harmonicu；
And a sixth step: after the harmonic voltage distortion rate analysis and calculation under various typical weather scenes are completed, the probabilities and the harmonic voltage distortion rates corresponding to the various typical weather scenes are substituted into the following formula for calculation and analysis to obtain the harmonic voltage distortion rate THD of the distributed photovoltaic access power distribution network in a certain region,
in the formula: piThe probabilities corresponding to various typical weather scenes; THDUiAnd i is a classification label of each type of typical weather scene.
[ EXAMPLES ]
An IEEE33 node medium voltage radiation type power distribution network system is adopted, and the topological structure is shown in figure 4. The three-phase power reference value Sb of the power distribution system is 10000kVA, the line voltage reference value UB is 12.66kV, the total active load of the system is 3715.0kW, and the total reactive load is 2300.0 kvar. The load data of each node is shown in the table. In the example, node 0 is considered as the balancing node, and the rest of the load nodes are considered as the PQ nodes. And (3) selecting a node 18 to join the distributed photovoltaic system, wherein the installed capacity is 1MW, and the permeability of the distributed photovoltaic is 23%. The branch parameters and bus load data for the system are shown in figure 5.
(1) The photovoltaic output power curve of a certain area all year round is analyzed, and the results of the alpha and beta parameters under four typical weather scenes are obtained by adopting the least square method as shown in the following table 1.
Table 1:
(2) monte Carlo simulation calculations show the voltage content of each harmonic of the PCC points for four typical days as shown in FIGS. 6-9.
(3) The results of the probability distribution of the respective harmonic voltages at the PCC points under typical weather are shown in fig. 10-29.
(4) The harmonic distortion rate calculation results are shown in table 2 below.
Table 2:
the modules or units in the device of the embodiment of the invention can be combined, divided and deleted according to actual needs.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention.
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