CN-121980915-A - Annual photovoltaic load associated scene generation method, equipment and medium considering meteorological influence

CN121980915ACN 121980915 ACN121980915 ACN 121980915ACN-121980915-A

Abstract

The invention discloses a method, equipment and medium for generating a annual photovoltaic load related scene considering meteorological influence, which belong to the technical field of new energy and load related scene generation, and comprise the steps of setting weather types, months, product days and date types of initial dates, randomly extracting a meteorological characteristic point from a meteorological joint probability distribution scattered point set, wherein corresponding air temperature and clear sky indexes are meteorological characteristics of the current day, generating a daily load sequence of the initial date based on the current date types and air temperature and based on load size and load air temperature characteristic coefficients, calculating a corresponding accumulated state transition matrix based on the current months, generating a next day weather type through a Markov chain Monte Carlo method, and iterating until the initial date is the last day of the annual sequence. According to the invention, the photovoltaic output is dynamically associated with the temperature-sensitive load by combining the influence of the air temperature on the load, so that the problem that the traditional method ignores the relevance of the meteorological time sequence is solved, and the physical rationality and the evaluation accuracy of the annual sequence are obviously improved.

Inventors

LUO NING
WANG JIE
LIU JINSEN
CHEN LUDONG
Guo Jianshuai
YANG LISHUN
CHEN BO
Miao mao
ZHAO QINGYU
LIU XICHENG
ZHENG FEI
ZHANG PENGCHENG

Assignees

贵州电网有限责任公司

Dates

Publication Date: 20260505
Application Date: 20251218

Claims (10)

1. A method for generating a annual photovoltaic load related scene considering meteorological influence is characterized by comprising the following steps of, Setting a weather type, a month, a date of the product and a date type of the initial date; based on the current month and weather type, selecting a corresponding weather joint probability distribution scattered point set, randomly extracting a weather characteristic point from the weather joint probability distribution scattered point set, wherein the air temperature and clear sky index corresponding to the weather characteristic point are weather characteristics of the current day; Generating a solar photovoltaic sequence of an initial date based on the current product day and clear sky index, based on the extraterrestrial solar irradiance, the surface solar irradiance and the photovoltaic output power; Based on the current date type and air temperature, generating a daily load sequence of an initial date based on the load size and the load air temperature characteristic coefficient; based on the current month, selecting a corresponding weather type transition probability matrix, calculating a corresponding accumulated state transition matrix, and generating a next day weather type through a Markov chain Monte Carlo method; The iteration is performed until the initial date is the last day of the annual sequence.
2. The method for generating an annual photovoltaic load related scene considering meteorological effects according to claim 1, wherein the date type comprises two date type classifications of working days and rest days; Correcting the composite time sequence of the special period; The product day refers to the ordinal number of the date in one year.
3. The method for generating a annual photovoltaic load related scene considering meteorological influences according to claim 2, wherein the method is characterized in that a corresponding meteorological joint probability distribution scattered point set is selected based on the current month and weather type, a meteorological characteristic point is randomly extracted from the set, and the air temperature and clear sky index corresponding to the meteorological characteristic point are the meteorological characteristics of the current day, and the method comprises the following steps of, The daily average clear sky index quantifies the weather condition of one day, namely the ratio of the actual solar radiation quantity received by the earth surface to the radiation quantity which can be received theoretically outside the earth, and the fluctuation index is calculated by taking the average value of the solar irradiance of the earth surface as a reference and is expressed as, Wherein, the For a daily average clear sky index, As an index of the fluctuation to be used, Is that The solar irradiance of the earth's surface at the moment, Is that The solar irradiance outside the earth at the moment, As the number of unit time intervals of a day, Is a constant of the sun and is a constant of the sun, Is taken as the long-term accumulation day, Is that Azimuth angle of sunlight at moment.
4. The method for generating a annual photovoltaic load related scene taking meteorological effects into account of claim 3, wherein the weather type comprises setting a first threshold for clear sky index, a second threshold for clear sky index, a third threshold for clear sky index and a threshold for fluctuation index; If it is If the first threshold value is larger than 0 and smaller than or equal to the first threshold value of the clear sky index, the weather is overcast and rainy, if If the weather is cloudy and the weather is not more than the first threshold value of the clear sky index and not more than the second threshold value of the clear sky index, the weather is cloudy and if the weather is cloudy If the weather is less than the first threshold and less than the second threshold, the weather is cloudless, if the weather is not cloudy If the weather is sunny and clear and the weather is not more than 1; If it is If the fluctuation index is greater than or equal to 0 and smaller than the fluctuation index threshold, the low fluctuation index is classified as low fluctuation, if Is larger than or equal to the fluctuation index threshold value, then divide into high fluctuations; each weather type is subdivided into two fluctuation levels based on fluctuation indexes, and eight weather types are formed.
5. A method for generating a annual photovoltaic load related scene taking into account meteorological effects as defined in claim 4 wherein said surface solar irradiance is expressed as, Wherein, the Is that The amount of solar irradiance fluctuation at the moment; The photovoltaic output power corresponding to the irradiance of the surface sun is expressed as, Wherein, the For the output power of the photovoltaic, For the efficiency of the conversion of the photovoltaic energy, The size of the area of the photovoltaic cell panel.
6. The method for generating a annual photovoltaic load related scene considering meteorological effects according to claim 5, wherein said generating a daily load sequence of an initial date based on a current date type and air temperature, based on a load size and a load air temperature characteristic coefficient, comprises, The daily load sequence is formed by superposing basic load and temperature sensitive load, and is expressed as, Wherein, the Is of the date type Average daily air temperature of Time of day The magnitude of the load at the moment in time, As a type of date it is, Is that Base load typical curve under date type The per-unit value of the time instant, Is that Date type, Typical curve of cooling/heating load under air temperature The per-unit value of the time instant, Random up-down floating coefficients of the base load for periods of unreleased cooling and heating demand, Is that Load air temperature characteristic coefficient under the date type; The load air temperature characteristic coefficient is obtained by fitting historical daily electricity consumption and air temperature data, and is expressed as, Wherein, the Is that The average daily air temperature under the date type is The temperature-sensitive electric quantity obtained by accumulating the temperature-sensitive load curve, Mean daily air temperature The temperature-sensitive electric quantity obtained by accumulation of the heating load typical curve, Mean daily air temperature Typical curve of cooling load at time the temperature-sensitive electric quantity obtained by accumulation, For the lower limit of the air temperature interval in the cooling and heating demand unreleased period, For the upper limit of the air temperature interval in the cooling and heating demand unreleased period, The method is used for describing a mapping relation function between the temperature-sensitive electric quantity proportion and the load air temperature characteristic coefficient.
7. The method for generating a year photovoltaic load-related scene in consideration of meteorological effects according to claim 6, wherein said selecting a corresponding weather type transition probability matrix based on the current month, calculating a corresponding cumulative state transition matrix, generating a next day weather type by Markov chain Monte Carlo method, comprises, Calculating corresponding cumulative state transition matrix The elements are represented as, Wherein, the Is the first to accumulate state transition matrix Line 1 The column elements are arranged in a row, For an intermediate index in the case of cumulative probability computation, For an index of the current weather type, For the index of the type of weather that is the target, To be of the weather type Transition to weather type Probability of (2); Let the next day weather type be Generating random numbers subject to uniform distribution If (if) Then ; Wherein, the Is the first The type of weather that is to be used in the day, For the first The type of the natural qi is Then the first The weather is of the weather type Is a function of the probability of (1), For the first The type of the natural qi is Then the first The weather is of the weather type Is a function of the probability of (1), Is the first Type of heaven and earth.
8. A method of generating a year photovoltaic load related scene in consideration of meteorological effects as recited in claim 7, wherein said iterating until an initial date is a last day of a year sequence comprises, Sampling by a Monte Carlo simulation method to obtain a meteorological joint probability distribution scattered point set; The selection of the joint function is specifically to construct weather joint probability distribution scattered point sets for the month 1 to the month 2 respectively, and the Cryton joint function is adopted when the month is the month ten, and the Frank joint function is adopted for the rest months.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of a method for generating annual photovoltaic load related scenes taking into account meteorological effects according to any of claims 1 to 8.
10. A computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the steps of a method of annual photovoltaic load related scene generation taking into account meteorological effects according to any of claims 1 to 8.

Description

Annual photovoltaic load associated scene generation method, equipment and medium considering meteorological influence Technical Field The invention relates to the technical field of new energy and load related scene generation, in particular to a method, equipment and medium for generating a annual photovoltaic load related scene considering meteorological influence. Background As the photovoltaic permeability in electrical power systems increases, the pressure of photovoltaic digestion increases. In a distributed photovoltaic large-scale development scenario, light Fu Xiaona capability assessment is critical to the operation planning of the power grid. Scene time sequence production simulation is an important tool for evaluating the capacity of photovoltaic digestion, and by simulating the power generation characteristics of the photovoltaic and the time sequence of loads, the power balance condition of a power grid is simulated time by time. The annual photovoltaic load scene time sequence is used as key input of an electric power supply and demand simulation link, and the accuracy of the digestion capability evaluation result is directly determined; Currently, studies on the generation of time series of photovoltaic output and load scenes are mostly performed on the generation of series of photovoltaic output and load separately. The learner also considers the source load correlation and uncertainty and adopts a scene reduction method based on a clustering technology to generate a typical operation scene, but the difference of daily source load characteristics under a long time scale cannot be reflected, and comprehensive and accurate reference cannot be provided for power grid planning and operation. Therefore, it is necessary to study the photovoltaic and load annual time sequence scene generation technology considering the source-load correlation, and the accuracy of the generated sequence scene is improved through the correlation analysis of the source-load sequence, so that important support is provided for the power and electricity balance analysis of the power system, the evaluation of the absorption capacity of new energy sources and the like. Disclosure of Invention The present invention has been made in view of the above-described problems. Therefore, the invention solves the technical problems that the conventional method cannot reflect the difference of daily source-load characteristics under a long time scale and cannot provide comprehensive and accurate reference for power grid planning and operation. The technical scheme includes that weather types, months, product days and date types of initial dates are set, a corresponding weather joint probability distribution scattered point set is selected based on the current months and weather types, a weather characteristic point is randomly extracted from the weather joint probability distribution scattered point set, air temperature and clear air index corresponding to the weather characteristic point are weather characteristics of the current day, a solar photovoltaic sequence of the initial date is generated based on the current product days and clear air index and based on the solar irradiance outside the earth, the solar irradiance on the earth and the photovoltaic output power, a daily load sequence of the initial date is generated based on the current date types and the air temperature and based on the load size and the load air temperature characteristic coefficient, a corresponding cumulative state transition matrix is calculated based on the current month, the next day type is generated through Markov chain Monte Carlo method, and iteration is conducted until the initial date is the last day of the annual sequence. The annual photovoltaic load related scene generation method considering meteorological influence is characterized by comprising the steps of classifying date types including workday and rest day, correcting special period composite time sequence, and integrating the date to be the ordinal number of the date in one year. The invention relates to a method for generating a annual photovoltaic load related scene considering meteorological influence, which comprises the following steps of selecting a corresponding meteorological joint probability distribution scattered point set based on the current month and weather type, randomly extracting a meteorological characteristic point from the set, wherein the air temperature and the clear sky index corresponding to the meteorological characteristic point are the meteorological characteristics of the same day, and the daily average clear sky index quantifies the weather condition of the same day, namely the ratio of the actual solar radiation quantity received by the earth surface to the radiation quantity which can be received theoretically outside the earth, calculates the fluctuation index by taking the average value of the solar irradiance of the earth surface as a reference, and