CN107292768B - Photovoltaic power generation system daily generated energy fuzzy probability calculation method and device - Google Patents
Photovoltaic power generation system daily generated energy fuzzy probability calculation method and device Download PDFInfo
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Abstract
The embodiment of the invention discloses a fuzzy probability calculation method and device for daily generated energy of a photovoltaic power generation system, which are used for solving the technical problems that uncertainty and randomness of influence factors are not fully considered in the daily generated energy calculation method of the distributed photovoltaic power generation system in the prior art, and the applicability, the practicability and the applicability of the calculation method are difficult to meet. The method provided by the embodiment of the invention comprises the following steps: calculating an n-dimensional generalized trapezoidal fuzzy set for determining the fuzzy uncertainty of the daily generated energy of the photovoltaic power generation system according to the daily generated energy data of the photovoltaic power generation system; according to the influence of the sunlight intensity, the sunlight temperature rise, the sunlight shadow and the sunlight deflection angle on the photovoltaic power generation system, calculating an n-dimensional generalized trapezoidal fuzzy set of the time-period power generation amount of the photovoltaic power generation system; calculating the daily generated energy of the photovoltaic power generation system according to the n-dimensional generalized trapezoidal fuzzy set of the time-interval generated energy of the photovoltaic power generation system; and calculating and determining the fuzzy probability of the daily generated energy of the photovoltaic power generation system according to the daily generated energy of the photovoltaic power generation system.
Description
Technical Field
The invention relates to the field of electric power systems and automation thereof, in particular to a fuzzy probability calculation method and device for daily generated energy of a photovoltaic power generation system.
Background
The development of a solar distributed power generation system is the development trend of smart cities, and photovoltaic power generation and photo-thermal power generation are two different forms of solar power generation. In recent years, a photovoltaic-photothermal integrated distributed power generation system becomes a mainstream development direction and a subject of research hot spot.
The principle of photovoltaic power generation is that solar heat energy is directly converted into electric energy by utilizing the temperature difference of semiconductor or metal materials such as vacuum devices, alkali metals, magnetic fluids and the like, so as to realize power generation. The principle of photo-thermal power generation is that working media such as water and the like are heated to high-temperature and high-pressure steam in a light-gathering and heat-collecting mode, the high-temperature and high-pressure steam drives a heat engine such as a steam turbine and the like, the heat engine drives a generator set to generate power, and the power generation is realized by utilizing conversion of various energy sources such as sunlight, heat, a machine and electricity.
At present, photovoltaic power generation has become a very mature technology, and the power generation cost thereof has been reduced to the level of 7000 ten thousand yuan/ten thousand kilowatts. The photothermal power generation mainly comprises four types, namely tower type, groove type, disc type and Fresnel type. The principle of the trough type solar photo-thermal power generation system is that a plurality of series-parallel trough type paraboloid concentrating collectors are used for concentrating solar heat, a working medium is heated to high-temperature high-pressure steam, and then a steam turbine generator set is driven to generate power. The power generation principle of the disc type solar photo-thermal power generation system is that a parabolic reflector is composed of a plurality of mirrors, solar light is focused on the focus of the parabolic reflector, working media in a parabolic receiver are enabled to heat the working media to high-temperature high-pressure steam, and an engine is driven to generate power. The Fresnel type photo-thermal power generation system has the power generation principle that a condenser with a Fresnel structure is adopted to collect solar heat, heat working media to high-temperature high-pressure steam, and drive a steam turbine generator set to generate power, and the Fresnel type photo-thermal power generation system is low in power generation efficiency, simple in structure and low in construction and maintenance cost. The principle of the tower type solar thermal power generation system is that an absorber on the top of a central absorption tower collects solar heat, a working medium is heated to high-temperature high-pressure steam, a steam turbine generator set is driven to generate power, a certain number of heliostats are installed around the tower, sunlight is collected to a cavity of a receiver on the top of the tower through the heliostats to generate high temperature, and then the working medium of the absorber is heated to generate high-temperature steam to push a steam turbine to generate power. The photo-thermal power generation modes are all that the steam turbine is driven to generate power by converting light into heat and then generating steam.
The radiation intensity and the sunshine time of sunlight in different areas have great difference, the sunshine intensity in different time and space also has great difference, randomness and ambiguity due to the fact that the cloud layer shields to form a shadow in the same place, and the uncertain characteristic determines that the output of the photovoltaic and photo-thermal power generation system also has great difference, randomness and ambiguity. Therefore, to determine the output power of the photovoltaic and photothermal power generation system, the solar radiation intensity and the sunshine duration in the area need to be subjected to probability analysis or fuzzy analysis and probability fuzzy analysis, and the sunshine intensity at different time and space needs to be subjected to probability analysis or fuzzy analysis and probability fuzzy analysis.
By utilizing the continuous power generation principle of battery energy storage, the photovoltaic power generation system can continuously generate power or continuously generate power in cloudy days or at night. But the continuous power generation or continuous power generation capacity depends on factors such as the energy storage capacity, the efficiency, the control mode and the like of the battery, and the factors influence the output power level of the battery energy storage continuous power generation system. The continuous power generation or the continuous power generation can be realized by utilizing the fused salt energy storage when the photo-thermal power generation is carried out in the cloudy day or at night. Like photovoltaic power generation, the continuous power generation or continuous power generation capacity of the photo-thermal power generation system depends on factors such as fused salt energy storage capacity, energy conversion efficiency, flexible control mode and the like, and the output power level of the photo-thermal power generation system has high randomness and ambiguity due to the influence of various uncertain factors.
Renewable energy sources of all countries around the world have a rapid growth trend in recent years in power grid access. The photovoltaic power generation access is the fastest to increase, and the annual growth rate is 60 percent; secondly, wind power generation and biofuel power generation are carried out, and the annual growth rate is respectively 27% and 18%. The department of industry and informatization predicts that the nationwide electric automobile reserves will reach 6000 million in 2030 years, the peak charging power will reach 0.42TW, accounting for 18% of the expected total installed capacity of 2.32 TW. Therefore, the large-scale access of distributed power generation, energy storage and electric vehicle charging systems to urban power distribution networks is a necessary trend. With the interactive support and promotion of national policies and industrial development, in a certain space, for example, small users such as urban residents and large user groups such as commercial buildings, communities and industrial areas, the distributed photovoltaic power generation system tends to develop rapidly, and the photovoltaic and photothermal power generation integrated system also shows a strong development situation. The distributed energy storage system is a distributed system with fixed access voltage level and access point, and comprises compressed hydrogen energy storage, battery energy storage, super capacitor energy storage and the like, and the energy storage power is flexible and controllable; the distributed charging system of the electric automobile is a distributed system with variable access voltage levels and access points, the charging power can be flexibly controlled, and the randomness is extremely high. The distributed generation volatility, the intermittency, the randomness and the charging uncertainty of the electric automobile enable the single distributed generation, the power utilization and the charging to have more randomness, and the randomness and the ambiguity of the distributed output power can be further increased by the interaction relationship of small users such as urban residents and the like and large user groups such as commercial buildings, communities and industrial areas for distributed generation, energy storage and electric automobile charging systems.
For random uncertainty, probability statistics theory is conventionally used to analyze and process information of random uncertainty, such as constructing a probability model of an uncertainty event or parameter by using a probability density function and a probability distribution function with mean and variance as characteristic values, and describing occurrence probability characteristics of the uncertainty event and fluctuation characteristics of uncertainty parameters such as power, voltage and current.
For ambiguity uncertainty, it is conventional to use ambiguity analysis methods to analyze and process the ambiguity uncertainty information. Simulating and describing inaccurate information of the fuzzy uncertainty event or parameter by adopting a Zadeh fuzzy set or TYPE1 fuzzy set, and mainly simulating the fuzzy uncertainty event or parameter by using a single-layer membership function method to describe the fuzzy uncertainty event or parameter by using a membership value. In an actual application system, uncertain events become more and more complex, the number of uncertain parameters is huge, the relation is complex, the fuzzy degrees of the events or the parameters and the mutual information are greatly increased, a single-layer membership function method based on a Zadeh fuzzy set and a TYPE1 fuzzy set is obviously insufficient, and the fuzzy uncertain events or the parameters are difficult to analyze and process in direct simulation information. Based on the TYPE1 fuzzy set, Zadeh proposes a TYPE2 fuzzy set based on two layers of membership functions, and further enhances the processing capacity of fuzzy uncertain events or parameters.
In a practical application system, random and fuzzy uncertain events or parameters exist simultaneously, and interact and are superposed with each other. The traditional probability analysis method and the fuzzy analysis method are limited by the mechanism thereof, and have obvious defects when the random and fuzzy uncertain events or parameters of the system are processed, and the analysis effect cannot approach to the actual situation. Therefore, in recent years, the fuzzy theory and the probability theory are fused to form a development direction and a trend, and an attractive idea and a method for understanding the problem of uncertainty are provided. One is to introduce fuzzy theory into traditional probability theory, such as random set, fuzzy random variable; another is to introduce probability theory into fuzzy theory, such as unstable fuzzy set, probability set and probabilistic fuzzy set. The method is characterized in that on the basis of the TYPE2 fuzzy set, the probability fuzzy set introduces a random theory into the traditional fuzzy theory, describes the random characteristics of uncertain random and fuzzy events or parameters by fuzzy membership, and forms a fuzzy set form of an n-dimensional membership function.
Distributed photovoltaic power generation systems for small users such as urban residents and large user groups such as commercial buildings, communities and industrial areas are systems with random and fuzzy uncertain events or parameters which have complex relationships and interaction. Under the influence of various uncertain random and fuzzy events or parameters, the daily generated energy of new energy small users such as urban residents and the like and new energy large user groups such as commercial buildings, communities and industrial areas with distributed photovoltaic power generation systems becomes more random and fuzzy. The daily generated energy of the traditional distributed photovoltaic power generation system usually adopts a deterministic calculation method, and some systems also adopt an uncertain calculation method of probability analysis. The deterministic calculation method is generally used for calculating the daily generated energy of the distributed photovoltaic power generation system under the condition that the solar radiation intensity, the sunshine time, the sunshine intensity, the sunshine shadow and the sunshine deflection angle of a user location in different time and space are all determined in an assumed region, the influences of factors such as the battery energy storage capacity of the photovoltaic power generation system used for continuous power generation or the fused salt energy storage installed capacity, the energy storage state, the energy conversion efficiency, the power distribution network voltage regulation requirement, the flexible control mode and the like of the photo-thermal power generation system are not considered, and the calculation result is unique and deterministic and can not reflect the actual condition of the daily generated energy of the distributed photovoltaic power generation system. In the calculation method of probability analysis, the daily power generation amount of the distributed photovoltaic power generation system is usually calculated under the condition that only single factors such as sunlight intensity are assumed as uncertainty factors, and the calculation result is a probability value with a certain confidence level. Actually, the daily power generation amount of the distributed photovoltaic power generation system is determined by the solar radiation intensity, the sunshine duration and the probability or ambiguity thereof in the region, the sunshine intensity, the sunshine duration, the sunshine shadow, the sunshine deflection angle and the probability or ambiguity thereof in different time and space at the user location, and also depends on the battery energy storage capacity of the photovoltaic power generation system used for continuous power generation or the fuse salt energy storage installed capacity, the energy storage state, the energy conversion efficiency, the power distribution network voltage regulation requirement, the flexible control mode and other factors of the photo-thermal power generation system. Moreover, these influencing factors are typically random uncertainties or fuzzy uncertainties, or they are random and fuzzy uncertainties, often present as random and fuzzy uncertainty events or quantities. Therefore, the uncertainty and randomness of the influence factors are not considered comprehensively in the prior art of the calculation of the daily generated energy of the distributed photovoltaic power generation system, and the applicability, the practicability and the applicability of the calculation method are difficult to meet.
Disclosure of Invention
The embodiment of the invention provides a fuzzy probability calculation method and device for daily generated energy of a photovoltaic power generation system, and solves the technical problems that uncertainty and randomness of influence factors are not considered comprehensively in the daily generated energy calculation method of the distributed photovoltaic power generation system in the prior art, and the applicability, the practicability and the applicability of the calculation method are difficult to meet.
The embodiment of the invention provides a photovoltaic power generation system daily generated energy fuzzy probability calculation method, which comprises the following steps:
calculating and determining a first n-dimensional generalized trapezoidal fuzzy set of fuzzy uncertainty of daily generated energy of the photovoltaic power generation system according to the acquired daily generated energy data of the photovoltaic power generation system of the user;
calculating a second n-dimensional generalized trapezoidal fuzzy set of the time period generated energy of the photovoltaic power generation system according to the influences of the sunlight intensity, the sunlight temperature rise, the sunlight shadow and the sunlight deflection angle on the photovoltaic power generation system;
calculating the daily generated energy of the photovoltaic power generation system according to a second n-dimensional generalized trapezoidal fuzzy set of the time-period generated energy of the photovoltaic power generation system;
and calculating and determining the fuzzy probability of the daily generated energy of the photovoltaic power generation system according to the daily generated energy of the photovoltaic power generation system.
Preferably, the step of calculating and determining a first n-dimensional generalized trapezoidal fuzzy set of the fuzzy uncertainty of the daily power generation amount of the photovoltaic power generation system according to the acquired daily power generation amount data of the photovoltaic power generation system of the user comprises the following steps:
according to the acquired daily generated energy data of the photovoltaic power generation system of the user, 9 first n-dimensional generalized trapezoidal fuzzy sets with fuzzy uncertainties, namely, the photovoltaic power generation system is determined by a daily generated energy fuzzy set determination formula in a computing mode, wherein the fuzzy uncertainties are 9 fuzzy uncertainties, namely, the daily generated energy fuzzy set determination formula specifically comprises the following steps:
EHi＝(EHiV1,EHiV2,...,EHiVn)＝[(EHiV11,EHiV12,EHiV13,...,EHiV1q；kHiV1),(EHiV21,EHiV22,EHiV23,...,EHiV2q；kHiV2),…(EHiVn1,EHiVn2,EHiVn3,...,EHiVnq；kHiVn)]；
wherein E isHiFor the ith n-dimensional trapezoidal fuzzy set of daily power generation, EHiV1、EHiV2、…、EHiVnAnd kHiV1、kHiV2、…、kHiVnThe value 1, the value 2 and the value … of the ith n-dimensional trapezoidal fuzzy set of the daily generated electricity, the fuzzy set and the membership coefficient of the value n, EHiV1j、EHiV2j、…、EHiVnj(j ═ 1,2,3,. and 9) are the j-th fuzzy numbers of the nth generalized trapezoidal fuzzy set of the fuzzy uncertainty values of the ith daily generated energy respectively.
Preferably, according to the influence of the sunlight intensity, the sunlight temperature rise, the sunlight shadow and the sunlight deflection angle on the photovoltaic power generation system, the second n-dimensional generalized trapezoidal fuzzy set for calculating the period power generation amount of the photovoltaic power generation system comprises:
according to the influence of the sunlight intensity, the sunlight temperature rise, the sunlight shadow and the sunlight deflection angle on the photovoltaic power generation system, a second n-dimensional generalized trapezoidal fuzzy set of the time interval power generation of the photovoltaic power generation system is calculated through a time interval power generation solving formula, and the time interval power generation solving formula specifically comprises the following steps:
wherein the content of the first and second substances,
the historical data and the sunshine intensity in the time period t (t is 1,2SH) The value k is the probability of occurrence of the a (a ═ 1, 2.., n) th trapezoidal blur set b (b ═ 1, 2.., q) th blur number and the blur number,
the probability and the fuzzy number of the occurrence of the fuzzy number of the a-th (a is 1,2,.., n) trapezoidal fuzzy set b (b is 1,2,.., q) in the time period t value k in the historical data and the sunshine temperature rise are respectively,
the probability of occurrence of the fuzzy number of the a (a is 1,2, the.., n) th trapezoidal fuzzy set with the sunshine shadow in the time period t value in the historical data and the fuzzy number are respectively,
the probability and the fuzzy number of the a-th (a is 1,2,.., n) trapezoidal fuzzy set b (b is 1,2,.., q) in the history data and the sunshine deflection angle in the time period t value k are respectively shown,
the probability and the fuzzy number of the occurrence of the fuzzy number of the a-th (a is 1,2,.., n) trapezoidal fuzzy set b (b is 1,2,.., q) in the historical data and the sunshine time at the time period t value k are respectively.
Preferably, calculating the daily power generation amount of the photovoltaic power generation system according to the second n-dimensional generalized trapezoidal fuzzy set of the period power generation amount of the photovoltaic power generation system comprises:
according to a second n-dimensional generalized trapezoidal fuzzy set of the time period power generation amount of the photovoltaic power generation system, the daily power generation amount of the photovoltaic power generation system is calculated through a daily power generation amount calculation formula, wherein the daily power generation amount calculation formula specifically comprises the following steps:
wherein k isPVEIs a photoelectric conversion coefficient of the photovoltaic power generation panel,
represents NSHA union of fuzzy sets.
Preferably, the method further comprises the following steps:
and calculating the similarity of 9 fuzzy quantities, namely the extremely low, the very low, the medium, the high and the extremely high daily power generation quantity of the photovoltaic power generation system and the historical data, and calculating the similarity of the maximum value according to the similarity.
Preferably, the step of determining the fuzzy probability of the daily power generation amount of the photovoltaic power generation system according to the daily power generation amount calculation of the photovoltaic power generation system comprises the following steps:
calculating and determining the day power generation amount fuzzy probability of the photovoltaic power generation system through a day power generation amount fuzzy probability solving formula according to the maximum similarity, wherein the day power generation amount fuzzy probability solving formula specifically comprises the following steps:
wherein the content of the first and second substances,
in order to be the degree of similarity,
the maximum value similarity.
The photovoltaic power generation system day generated energy fuzzy probability calculating device provided by the embodiment of the invention comprises:
the first calculation module is used for calculating and determining a first n-dimensional generalized trapezoidal fuzzy set of the fuzzy uncertainty of the daily generated energy of the photovoltaic power generation system according to the acquired daily generated energy data of the photovoltaic power generation system of the user;
the second calculation module is used for calculating a second n-dimensional generalized trapezoidal fuzzy set of the time-interval power generation amount of the photovoltaic power generation system according to the influence of the sunlight intensity, the sunlight temperature rise, the sunlight shadow and the sunlight deflection angle on the photovoltaic power generation system;
the third calculation module is used for calculating the daily generated energy of the photovoltaic power generation system according to a second n-dimensional generalized trapezoidal fuzzy set of the time-interval generated energy of the photovoltaic power generation system;
and the fourth calculation module is used for calculating and determining the fuzzy probability of the daily generated energy of the photovoltaic power generation system according to the daily generated energy of the photovoltaic power generation system.
Preferably, the first calculation module comprises:
the first calculating unit is used for calculating and determining 9 first n-dimensional generalized trapezoidal fuzzy sets with fuzzy uncertainties, namely, the first n-dimensional generalized trapezoidal fuzzy set with the extremely low, the very low, the medium, the high and the extremely high daily power generation amount of the photovoltaic power generation system through a daily power generation amount fuzzy set determining formula according to the acquired daily power generation amount data of the photovoltaic power generation system of the user.
Preferably, the second calculation module comprises:
and the second calculation unit is used for calculating a second n-dimensional generalized trapezoidal fuzzy set of the time-interval power generation of the photovoltaic power generation system through a time-interval power generation solving formula according to the influence of the sunlight intensity, the sunlight temperature rise, the sunlight shadow and the sunlight deflection angle on the photovoltaic power generation system.
Preferably, the third calculation module comprises:
the third calculation unit is used for calculating the daily generated energy of the photovoltaic power generation system through a daily generated energy calculation formula according to a second n-dimensional generalized trapezoidal fuzzy set of the time-interval generated energy of the photovoltaic power generation system;
the fourth calculation module includes: and the fourth calculating unit is used for calculating and determining the day power generation fuzzy probability of the photovoltaic power generation system through a day power generation fuzzy probability solving formula according to the maximum similarity.
According to the technical scheme, the embodiment of the invention has the following advantages:
the embodiment of the invention provides a photovoltaic power generation system daily generated energy fuzzy probability calculation method and device, which comprise the following steps: calculating an n-dimensional generalized trapezoidal fuzzy set for determining the fuzzy uncertainty of the daily generated energy of the photovoltaic power generation system according to the acquired daily generated energy data of the photovoltaic power generation system of the user; according to the influence of the sunlight intensity, the sunlight temperature rise, the sunlight shadow and the sunlight deflection angle on the photovoltaic power generation system, calculating an n-dimensional generalized trapezoidal fuzzy set of the time-period power generation amount of the photovoltaic power generation system; calculating the daily generated energy of the photovoltaic power generation system according to the n-dimensional generalized trapezoidal fuzzy set of the time-interval generated energy of the photovoltaic power generation system; the embodiment of the invention obtains relevant data information of time-interval generated energy of the distributed photovoltaic power generation system through a local monitoring data center, obtains data of power grid operation through a power grid energy management system EMS, mainly introduces a multi-dimensional multi-valued trapezoid fuzzy set concept and a calculation method thereof when the sunshine intensity, the sunshine time, the sunshine shadow, the sunshine deflection angle and the like are considered, supposes the parameters of the sunshine intensity, the sunshine time, the sunshine shadow, the sunshine deflection angle and the like and the energy storage charging event of a user battery to obey a generalized n-dimensional trapezoid fuzzy distribution rule, calculates the daily generated energy of the distributed photovoltaic power generation system on the basis of fuzzy probability analysis, can calculate the generated energy of the one-day photovoltaic power generation system, solves the problem that the calculation method of the daily generated energy of the distributed photovoltaic power generation system in the prior art does not comprehensively consider the uncertainty and the randomness of influence factors, the applicability, the practicability and the applicability of the calculation method are difficult to meet.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a method for calculating a fuzzy probability of a daily power generation amount of a photovoltaic power generation system according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a photovoltaic power generation system daily power generation amount fuzzy probability calculation device provided by an embodiment of the invention.
Detailed Description
The embodiment of the invention provides a fuzzy probability calculation method and device for daily generated energy of a photovoltaic power generation system, which are used for solving the technical problems that uncertainty and randomness of influence factors are not fully considered in the daily generated energy calculation method of the distributed photovoltaic power generation system in the prior art, and the applicability, the practicability and the applicability of the calculation method are difficult to meet.
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a method for calculating a fuzzy probability of a daily power generation amount of a photovoltaic power generation system according to an embodiment of the present invention includes:
101. calculating and determining a first n-dimensional generalized trapezoidal fuzzy set of fuzzy uncertainty of daily generated energy of the photovoltaic power generation system according to the acquired daily generated energy data of the photovoltaic power generation system of the user;
according to the acquired daily generated energy data of the photovoltaic power generation system of the user, 9 first n-dimensional generalized trapezoidal fuzzy sets with fuzzy uncertainties, namely, the photovoltaic power generation system is determined by a daily generated energy fuzzy set determination formula in a computing mode, wherein the fuzzy uncertainties are 9 fuzzy uncertainties, namely, the daily generated energy fuzzy set determination formula specifically comprises the following steps:
EHi＝(EHiV1,EHiV2,...,EHiVn)＝[(EHiV11,EHiV12,EHiV13,...,EHiV1q；kHiV1),(EHiV21,EHiV22,EHiV23,...,EHiV2q；kHiV2),…(EHiVn1,EHiVn2,EHiVn3,...,EHiVnq；kHiVn)]；
wherein E isHiFor the ith n-dimensional trapezoidal fuzzy set of daily power generation, EHiV1、EHiV2、…、EHiVnAnd kHiV1、kHiV2、…、kHiVnThe value 1, the value 2 and the value … of the ith n-dimensional trapezoidal fuzzy set of the daily generated electricity, the fuzzy set and the membership coefficient of the value n, EHiV1j、EHiV2j、…、EHiVnj(j ═ 1,2,3,. and 9) are the j-th fuzzy numbers of the nth generalized trapezoidal fuzzy set of the fuzzy uncertainty values of the ith daily generated energy respectively.
102. Calculating a second n-dimensional generalized trapezoidal fuzzy set of the time period generated energy of the photovoltaic power generation system according to the influences of the sunlight intensity, the sunlight temperature rise, the sunlight shadow and the sunlight deflection angle on the photovoltaic power generation system;
according to the influence of the sunlight intensity, the sunlight temperature rise, the sunlight shadow and the sunlight deflection angle on the photovoltaic power generation system, a second n-dimensional generalized trapezoidal fuzzy set of the time interval power generation of the photovoltaic power generation system is calculated through a time interval power generation solving formula, and the time interval power generation solving formula specifically comprises the following steps:
wherein the content of the first and second substances,
the historical data and the sunshine intensity in the time period t (t is 1,2SH) The value k is the probability of occurrence of the a (a ═ 1, 2.., n) th trapezoidal blur set b (b ═ 1, 2.., q) th blur number and the blur number,
the probability and the fuzzy number of the occurrence of the fuzzy number of the a-th (a is 1,2,.., n) trapezoidal fuzzy set b (b is 1,2,.., q) in the time period t value k in the historical data and the sunshine temperature rise are respectively,
the fuzzy data are respectively trapezoidal fuzzy with sunshine shadow in a time period t value kth (a is 1,2The probability of occurrence of the fuzzy number of the set and the fuzzy number,
the probability and the fuzzy number of the a-th (a is 1,2,.., n) trapezoidal fuzzy set b (b is 1,2,.., q) in the history data and the sunshine deflection angle in the time period t value k are respectively shown,
the probability and the fuzzy number of the occurrence of the fuzzy number of the a-th (a is 1,2,.., n) trapezoidal fuzzy set b (b is 1,2,.., q) in the historical data and the sunshine time at the time period t value k are respectively.
103. Calculating the daily generated energy of the photovoltaic power generation system according to a second n-dimensional generalized trapezoidal fuzzy set of the time-period generated energy of the photovoltaic power generation system;
according to a second n-dimensional generalized trapezoidal fuzzy set of the time period power generation amount of the photovoltaic power generation system, the daily power generation amount of the photovoltaic power generation system is calculated through a daily power generation amount calculation formula, wherein the daily power generation amount calculation formula specifically comprises the following steps:
wherein k isPVEIs a photoelectric conversion coefficient of the photovoltaic power generation panel,
represents NSHA union of fuzzy sets.
104. Calculating the similarity of 9 fuzzy quantities of the daily power generation of the photovoltaic power generation system and the historical data, wherein the 9 fuzzy quantities are very low, medium, high and very high in daily power generation, and calculating the maximum similarity according to the similarity;
calculating the similarity of 9 fuzzy quantities of the solar power generation of the photovoltaic power generation system and the historical data, wherein the 9 fuzzy quantities are very low, medium, high and very high
And calculating the maximum similarity according to the similarity
105. And calculating and determining the fuzzy probability of the daily generated energy of the photovoltaic power generation system according to the daily generated energy of the photovoltaic power generation system.
Calculating and determining the day power generation amount fuzzy probability of the photovoltaic power generation system through a day power generation amount fuzzy probability solving formula according to the maximum similarity, wherein the day power generation amount fuzzy probability solving formula specifically comprises the following steps:
wherein the content of the first and second substances,
in order to be the degree of similarity,
the maximum value similarity.
In the above, a detailed description is provided for the fuzzy probability calculation method for the daily power generation amount of the photovoltaic power generation system according to the embodiment of the present invention, and a detailed description is provided for the fuzzy probability calculation device for the daily power generation amount of the photovoltaic power generation system according to the embodiment of the present invention.
Referring to fig. 2, an apparatus for calculating fuzzy probability of daily power generation of a photovoltaic power generation system according to an embodiment of the present invention includes:
the first calculation module 201 is configured to calculate a first n-dimensional generalized trapezoidal fuzzy set for determining a fuzzy uncertainty of a daily power generation amount of the photovoltaic power generation system according to the acquired daily power generation amount data of the photovoltaic power generation system of the user; the first calculation module 201 includes:
the first calculating unit 2011 is configured to calculate and determine, according to the acquired daily power generation amount data of the photovoltaic power generation system of the user, a first n-dimensional generalized trapezoidal fuzzy set with 9 fuzzy uncertainties, which is very low, medium, high, very high, of the daily power generation amount of the photovoltaic power generation system, by using a daily power generation amount fuzzy set determining formula.
The second calculation module 202 is used for calculating a second n-dimensional generalized trapezoidal fuzzy set of the time-interval power generation amount of the photovoltaic power generation system according to the influence of the sunlight intensity, the sunlight temperature rise, the sunlight shadow and the sunlight deflection angle on the photovoltaic power generation system; the second calculation module 202 includes:
the second calculating unit 2021 is configured to calculate a second n-dimensional generalized trapezoidal fuzzy set of the time-interval power generation amount of the photovoltaic power generation system according to the influence of the sunlight intensity, the sunlight temperature rise, the sunlight shadow, and the sunlight deflection angle on the photovoltaic power generation system through a time-interval power generation amount solving formula.
The third calculating module 203 is used for calculating the daily generated energy of the photovoltaic power generation system according to the second n-dimensional generalized trapezoidal fuzzy set of the time-interval generated energy of the photovoltaic power generation system; the third calculation module 202 includes:
the third calculating unit 2031 is configured to calculate daily power generation of the photovoltaic power generation system according to a daily power generation solving formula in a second n-dimensional generalized trapezoidal fuzzy set of the time-interval power generation of the photovoltaic power generation system;
the fourth calculating module 204 is configured to calculate and determine a daily power generation amount fuzzy probability of the photovoltaic power generation system according to the daily power generation amount of the photovoltaic power generation system. The fourth calculation module 204 includes: the fourth calculating unit 2041 is configured to calculate and determine the daily power generation amount fuzzy probability of the photovoltaic power generation system according to the maximum similarity and the daily power generation amount fuzzy probability solving formula.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, 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 place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution 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 can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (6)
1. A photovoltaic power generation system daily generated energy fuzzy probability calculation method is characterized by comprising the following steps:
calculating and determining a first n-dimensional generalized trapezoidal fuzzy set of fuzzy uncertainty of daily generated energy of the photovoltaic power generation system according to the acquired daily generated energy data of the photovoltaic power generation system of the user;
calculating a second n-dimensional generalized trapezoidal fuzzy set of the time-period generated energy of the photovoltaic power generation system according to the influences of the sunlight intensity, the sunlight temperature rise, the sunlight shadow and the sunlight deflection angle on the photovoltaic power generation system;
calculating the daily generated energy of the photovoltaic power generation system according to a second n-dimensional generalized trapezoidal fuzzy set of the time-period generated energy of the photovoltaic power generation system;
calculating and determining a daily power generation amount fuzzy probability of the photovoltaic power generation system according to the daily power generation amount of the photovoltaic power generation system;
the first n-dimensional generalized trapezoidal fuzzy set for calculating and determining the fuzzy uncertainty of the daily generated energy of the photovoltaic power generation system according to the acquired daily generated energy data of the photovoltaic power generation system of the user comprises:
according to the acquired daily generated energy data of the photovoltaic power generation system of the user, 9 fuzzy uncertainty first n-dimensional generalized trapezoidal fuzzy sets of the photovoltaic power generation system, namely, the first fuzzy uncertainty is calculated and determined according to a daily generated energy fuzzy set determination formula, wherein the first fuzzy uncertainty is as follows:
wherein E isHiFor the ith n-dimensional trapezoidal fuzzy set of daily power generation, EHiV1、EHiV2、…、EHiVnAnd kHiV1、kHiV2、…、kHiVnThe value 1, the value 2 and the value … of the ith n-dimensional trapezoidal fuzzy set of the daily generated electricity, the fuzzy set and the membership coefficient of the value n, EHiV1j、EHiV2j、…、EHiVnjRespectively setting j-th fuzzy numbers of the nth generalized trapezoidal fuzzy set of the fuzzy uncertainty values of the daily generated electricity ith, wherein j is 1,2, 3.
The step of calculating and determining the fuzzy probability of the daily power generation amount of the photovoltaic power generation system according to the daily power generation amount of the photovoltaic power generation system comprises the following steps:
calculating the similarity of 9 fuzzy quantities of the daily power generation of the photovoltaic power generation system and the historical data, wherein the 9 fuzzy quantities are very low, medium, high and extremely high in daily power generation, and calculating the maximum similarity according to the similarity;
calculating and determining the day power generation amount fuzzy probability of the photovoltaic power generation system according to the maximum similarity through a day power generation amount fuzzy probability solving formula, wherein the day power generation amount fuzzy probability solving formula specifically comprises the following steps:
wherein the content of the first and second substances,
in order to be the degree of similarity,
the maximum value similarity.
2. The photovoltaic power generation system daily power generation amount fuzzy probability calculation method according to claim 1, wherein calculating the second n-dimensional generalized trapezoidal fuzzy set of the period power generation amount of the photovoltaic power generation system according to the influence of the solar intensity, the solar temperature rise, the solar shadow and the solar declination on the photovoltaic power generation system comprises:
according to the influence of the sunshine intensity, the sunshine temperature rise, the sunshine shadow and the sunshine deflection angle on the photovoltaic power generation system, a second n-dimensional generalized trapezoidal fuzzy set of the time period power generation of the photovoltaic power generation system is calculated through a time period power generation solving formula, wherein the time period power generation solving formula specifically comprises the following steps:
wherein the content of the first and second substances,
respectively the probability of occurrence of the b-th fuzzy number of the a-th trapezoidal fuzzy set at the time t value k with the sunshine intensity in the historical data and the fuzzy number,
respectively representing the probability of occurrence of the b-th fuzzy number of the a-th trapezoidal fuzzy set at the time t value k with the sunshine temperature rise in the historical data and the fuzzy number,
the probability of occurrence of fuzzy number of the alpha-th trapezoidal fuzzy set in the history data and the sunshine shadow at the time t value k and the fuzzy number are respectively,
respectively the probability of occurrence of the b-th fuzzy number of the a-th trapezoidal fuzzy set at the time t value k with the sunlight deviation angle in the historical data and the fuzzy number,
respectively appearing in historical data and the b-th fuzzy number of the a-th trapezoidal fuzzy set at the time interval t value k with sunshine timeWherein t is 1,2SH；a＝1,2,...,n；b＝1,2,...,q。
3. The photovoltaic power generation system daily power generation amount fuzzy probability calculation method according to claim 2, wherein the calculating the daily power generation amount of the photovoltaic power generation system according to the second n-dimensional generalized trapezoidal fuzzy set of the period power generation amount of the photovoltaic power generation system comprises:
calculating the daily generated energy of the photovoltaic power generation system according to a daily generated energy solving formula according to a second n-dimensional generalized trapezoidal fuzzy set of the time-interval generated energy of the photovoltaic power generation system, wherein the daily generated energy solving formula specifically comprises the following steps:
wherein k isPVEIs a photoelectric conversion coefficient of the photovoltaic power generation panel,
represents NSHA union of fuzzy sets.
4. The photovoltaic power generation system daily generated energy fuzzy probability calculation device is characterized by comprising:
the first calculation module is used for calculating and determining a first n-dimensional generalized trapezoidal fuzzy set of the fuzzy uncertainty of the daily generated energy of the photovoltaic power generation system according to the acquired daily generated energy data of the photovoltaic power generation system of the user;
the second calculation module is used for calculating a second n-dimensional generalized trapezoidal fuzzy set of the time-period generated energy of the photovoltaic power generation system according to the influence of the sunlight intensity, the sunlight temperature rise, the sunlight shadow and the sunlight deflection angle on the photovoltaic power generation system;
the third calculation module is used for calculating the daily generated energy of the photovoltaic power generation system according to a second n-dimensional generalized trapezoidal fuzzy set of the time-interval generated energy of the photovoltaic power generation system;
the fourth calculation module is used for calculating and determining the day power generation fuzzy probability of the photovoltaic power generation system according to the day power generation of the photovoltaic power generation system;
the first computing module includes:
the first calculating unit is used for calculating and determining a first n-dimensional generalized trapezoidal fuzzy set with 9 fuzzy uncertainties, namely, a very low, a medium, a high, a very high and a very high daily power generation amount of the photovoltaic power generation system through a daily power generation amount fuzzy set determining formula according to the acquired daily power generation amount data of the photovoltaic power generation system of the user, wherein the daily power generation amount fuzzy set determining formula specifically comprises the following steps:
wherein E isHiFor the ith n-dimensional trapezoidal fuzzy set of daily power generation, EHiV1、EHiV2、…、EHiVnAnd kHiV1、kHiV2、…、kHiVnThe value 1, the value 2 and the value … of the ith n-dimensional trapezoidal fuzzy set of the daily generated electricity, the fuzzy set and the membership coefficient of the value n, EHiV1j、EHiV2j、…、EHiVnjRespectively setting j-th fuzzy numbers of the nth generalized trapezoidal fuzzy set of the fuzzy uncertainty values of the daily generated electricity ith, wherein j is 1,2, 3.
The fourth calculation module includes: the fourth calculating unit is used for calculating the similarity of 9 fuzzy quantities, namely the daily power generation quantity of the photovoltaic power generation system and the daily power generation quantity in historical data, and calculating the maximum value similarity according to the similarity, and calculating and determining the daily power generation quantity fuzzy probability of the photovoltaic power generation system according to the maximum value similarity through a daily power generation quantity fuzzy probability solving formula, wherein the daily power generation quantity fuzzy probability solving formula specifically comprises the following steps:
wherein the content of the first and second substances,
in order to be the degree of similarity,
the maximum value similarity.
5. The photovoltaic power generation system daily power generation amount fuzzy probability calculation device according to claim 4, wherein the second calculation module comprises:
the second calculation unit is used for calculating a second n-dimensional generalized trapezoidal fuzzy set of the time interval power generation amount of the photovoltaic power generation system through the time interval power generation amount calculation formula according to the influence of the sunshine intensity, the sunshine temperature rise, the sunshine shadow and the sunshine deflection angle on the photovoltaic power generation system, wherein the time interval power generation amount calculation formula specifically comprises the following steps:
wherein the content of the first and second substances,
respectively the probability of occurrence of the b-th fuzzy number of the a-th trapezoidal fuzzy set at the time t value k with the sunshine intensity in the historical data and the fuzzy number,
respectively representing the probability of occurrence of the b-th fuzzy number of the a-th trapezoidal fuzzy set at the time t value k with the sunshine temperature rise in the historical data and the fuzzy number,
respectively, the time of sunshine shadow in the historical dataThe segment t value k is the probability of occurrence of the fuzzy number of the a-th trapezoidal fuzzy set and the fuzzy number,
respectively the probability of occurrence of the b-th fuzzy number of the a-th trapezoidal fuzzy set at the time t value k with the sunlight deviation angle in the historical data and the fuzzy number,
the probability and the fuzzy number of the occurrence of the b-th fuzzy number of the a-th trapezoidal fuzzy set at the time interval t value k in the historical data and the sunshine time are respectively, wherein t is 1,2SH；a＝1,2,...,n；b＝1,2,...,q。
6. The photovoltaic power generation system daily power generation amount fuzzy probability calculation device according to claim 4, wherein the third calculation module comprises:
the third calculating unit is configured to calculate the daily power generation amount of the photovoltaic power generation system according to a daily power generation amount solving formula according to a second n-dimensional generalized trapezoidal fuzzy set of the time-interval power generation amount of the photovoltaic power generation system, where the daily power generation amount solving formula specifically includes:
wherein k isPVEIs a photoelectric conversion coefficient of the photovoltaic power generation panel,
represents NSHA union of fuzzy sets.
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