CN105184465B - Photovoltaic power station output decomposition method based on clearance model - Google Patents
Photovoltaic power station output decomposition method based on clearance model Download PDFInfo
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Abstract
The invention provides a clearance model-based photovoltaic power station output decomposition method, which comprises the steps of collecting historical photovoltaic output data, and analyzing and sorting the collected historical photovoltaic output data; establishing a clearance model to obtain the clearance theoretical output P of the photovoltaic power stationDCI(i, t) and relative force PN(i, t), completing the resolution of the photovoltaic output. The method can be widely applied to planning and operation analysis of the power system, and provides important technical support for long-term time series modeling in photovoltaic power generation.
Description
Technical Field
The invention relates to a photovoltaic power station output characteristic analysis method, in particular to a photovoltaic power station output decomposition method based on a clearance model.
Background
In recent years, photovoltaic power generation technology is continuously and rapidly developed, the installed capacity of a photovoltaic power generation grid-connected grid is rapidly increased, 10.6GW is additionally added in China by the end of 2014, and the accumulated installed capacity reaches 28.7 GW. However, the photovoltaic power generation has randomness and volatility characteristics, and the uncertainty of power generation of a power system is increased due to large-scale photovoltaic power generation grid connection, so that certain influence is caused on peak load regulation and frequency modulation of a power grid.
The model of photovoltaic output is the basis for planning and operation research of the related power system. The photovoltaic output is influenced by many factors, including natural factors such as the position of the sun, various attenuations of the clean atmosphere, clouds in the air and other sunlight shelters, and photovoltaic equipment factors such as the arrangement of the photovoltaic array and the characteristics of the photovoltaic cells. Under the combined action of the factors, the photovoltaic output has certain regularity and strong randomness. And currently there is less analysis on the medium and long term stochastic properties of photovoltaic power generation.
Disclosure of Invention
In order to make up for the technical defects, the invention provides the photovoltaic power station output decomposition method based on the clearance model, which can be widely applied to power system planning and operation analysis and provides important technical support for long-term time sequence modeling in photovoltaic power generation.
In order to achieve the purpose of the invention, the invention adopts the following technical scheme:
a headroom model-based photovoltaic power plant output decomposition method, comprising the steps of:
(1) collecting historical photovoltaic output data, and analyzing and sorting the collected historical photovoltaic output data;
(2) establishing a clearance model to obtain the clearance theoretical output P of the photovoltaic power stationDCI(i, t) and relative force PN(i, t), completing the resolution of the photovoltaic output.
Preferably, the historical photovoltaic output data collected in step (1) is the photovoltaic output P (i, t) of the photovoltaic power station at a time scale of 15 minutes for 1 year or more than 1 year.
Preferably, the analyzing and sorting the collected historical photovoltaic output data in the step (1) includes deleting the error data and completing the missing data by replacing the missing data with adjacent data.
Further, the error data comprises data exceeding the installed capacity of the photovoltaic power station and being negative; the missing data is data which cannot be collected at a specified time point due to communication faults and is judged according to the time corresponding to the data.
Preferably, the step (2) specifically includes converting the photovoltaic output P (i, t) at each time of day, and decomposing the converted photovoltaic output P (i, t) into a product of a headroom theoretical output and a relative output, where the expression is:
P(i,t)＝PDCI(i,t)·PN(i,t) (1)
in the formula (1), PDCI(i, t) and PN(i, t) respectively representing clearance theoretical force and relative force based on the clearance model at the ith day t.
Further, P is addedN(i, t) converting the power into a power reference value, and accumulating the uncertain output caused by different cloud layers and weather states, wherein the expression is as follows:
PN(i,t)＝PS(i)+ΔPN(i,t) (2)
in the formula (2), Δ PN(i, t) isFluctuation value, P, caused by different cloud layer states and weather states at the moment of i days tS(i) And the power reference value of the ith day reflects the photovoltaic output degree of the current day.
Further, the expression of the power reference value is:
in the formula (3), n is the output time period of photovoltaic power generation.
Compared with the prior art, the invention has the following beneficial effects:
the method comprises the steps of decomposing photovoltaic output into a deterministic part and a stochastic part, and respectively establishing models of the deterministic part and the stochastic part according to the deterministic part and the stochastic part of the photovoltaic output based on a headroom model. A complete model description of the photovoltaic power generation output is thus formed.
The method can be widely applied to planning and operation analysis of the power system, and provides a new idea and an important technical support for long-term time series modeling in photovoltaic power generation.
The established photovoltaic power station clearance model with good universality and universality does not need the fitting of historical data, and is suitable for newly-built photovoltaic power stations.
Drawings
FIG. 1 is a flow chart of a headroom model-based photovoltaic power plant output decomposition method;
FIG. 2 is a graph illustrating a comparison between an actual force and a clearance theoretical force;
fig. 3 is a diagram illustrating a relative force curve based on a headroom model.
Detailed Description
The following detailed description of embodiments of the invention will be made with reference to the accompanying drawings.
As shown in fig. 1, a headroom model-based photovoltaic power plant output decomposition method includes the following steps:
(1) collecting historical photovoltaic output data, and analyzing and sorting the collected historical photovoltaic output data;
in the step (1), the collected historical photovoltaic output data is photovoltaic output P (i, t) of the photovoltaic power station with the time scale of 15 minutes for 1 year or more than 1 year. And analyzing and sorting the collected historical photovoltaic output data, namely deleting the error data and completing missing data by using a mode of replacing adjacent data. Wherein. The error data comprises data which exceeds the installed capacity of the photovoltaic power station and is a negative value; the missing data is data which cannot be collected at a specified time point due to communication faults and is judged according to the time corresponding to the data.
(2) Establishing a clearance model to obtain the clearance theoretical output P of the photovoltaic power stationDCI(i, t) and relative force PN(i, t), completing the resolution of the photovoltaic output. Decomposing the photovoltaic output into a deterministic portion and a stochastic portion based on a headroom model; the product of the headroom theoretical output and the relative output;
the specific method for decomposition comprises the following steps: converting the photovoltaic output P (i, t) at each moment every day, and decomposing the photovoltaic output P (i, t) into the product of the clearance theoretical output and the relative output, wherein the expression is as follows:
P(i,t)＝PDCI(i,t)·PN(i,t) (1)
in the formula (1), PDCI(i, t) and PN(i, t) respectively representing clearance theoretical force and relative force based on the clearance model at the ith day t.
Comparing the theoretical headroom output with the actual output, and obtaining a curve chart as shown in fig. 2; the actual output is the photovoltaic output P (i, t) at each moment every day.
The relative contribution from the headroom model shown in fig. 3 can also be decomposed as a power reference value plus an uncertainty contribution due to different clouds and weather conditions. The method specifically comprises the following steps:
will PN(i, t) converting the power into a power reference value, and accumulating the uncertain output caused by different cloud layers and weather states, wherein the expression is as follows:
PN(i,t)＝PS(i)+ΔPN(i,t) (2)
in the formula (2), Δ PN(i, t) is the fluctuation value caused by different cloud layer states and weather states at the time t of the ith day, PS(i) And the power reference value of the ith day reflects the photovoltaic output degree of the current day.
The expression of the power reference value is as follows:
in the formula (3), n is the output time period of photovoltaic power generation.
Finally, it should be noted that: the above embodiments are only intended to illustrate the technical solution of the present invention and not to limit the same, and a person of ordinary skill in the art can make modifications or equivalents to the specific embodiments of the present invention with reference to the above embodiments, and such modifications or equivalents without departing from the spirit and scope of the present invention are within the scope of the claims of the present invention as set forth in the claims.
Claims (2)
1. A clearance model-based photovoltaic power station output decomposition method is characterized by comprising the following steps:
(1) collecting historical photovoltaic output data, and analyzing and sorting the collected historical photovoltaic output data;
analyzing and sorting the collected historical photovoltaic output data in the step (1) comprises deleting the error data and completing the missing data by using a mode of replacing adjacent data;
the error data comprises data which exceeds the installed capacity of the photovoltaic power station and is a negative value; the missing data cannot be acquired at a specified time point due to communication faults, and therefore the missing data is judged according to the time corresponding to the data;
(2) establishing a clearance model to obtain the clearance theoretical output P of the photovoltaic power stationDCI(i, t) and relative force PN(i, t), completing the resolution of the photovoltaic output;
the historical photovoltaic output data collected in step (1) is light
Photovoltaic output P (i, t) of the photovoltaic power station with the time scale of 15 minutes for 1 year or more than 1 year;
the step (2) specifically includes applying light at each time of day
Converting the volt output P (i, t), and decomposing the volt output into the product of the clearance theoretical output and the relative output, wherein the expression is as follows:
P(i,t)＝PDCI(i,t)·PN(i,t) (1)
in the formula (1), PDCI(i, t) and PN(i, t) respectively representing clearance theoretical output and relative output based on a clearance model at the moment t on the ith day;
will PN(i, t) converting the power into a power reference value, and accumulating the uncertain output caused by different cloud layers and weather states, wherein the expression is as follows:
PN(i,t)＝PS(i)+ΔPN(i,t) (2)
in the formula (2), Δ PN(i, t) is the fluctuation value caused by different cloud layer states and weather states at the time t of the ith day, PS(i) And the power reference value of the ith day reflects the photovoltaic output degree of the current day.
2. The method of claim 1, wherein the power reference value is expressed as:
in the formula (3), n is the output time period of photovoltaic power generation.
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