CN-121981530-A - Method, device and system for acquiring optical storage risk prevention strategy and electronic equipment

CN121981530ACN 121981530 ACN121981530 ACN 121981530ACN-121981530-A

Abstract

The application discloses a method, a device and a system for acquiring an optical storage risk prevention strategy and electronic equipment, and relates to the technical field of optical storage systems. The method comprises the steps of obtaining the load rate of the photovoltaic array, various environment parameter values and weight coefficients corresponding to the environment parameters, determining the weight values according to a preset parameter value interval, and determining the correction coefficients corresponding to the load rate based on a preset mapping relation. And then, taking the environmental parameter with the maximum weight coefficient as a first environmental parameter, determining the average value, the maximum peak value and the duration of the maximum peak value in the historical time period, and determining the risk index by combining the weight value, the weight coefficient and the correction coefficient. And finally, determining the risk level based on the preconfigured mapping relation, and selecting a corresponding precaution strategy. Therefore, the risk assessment is carried out on the multidimensional parameters of the photovoltaic array, the influence of different environmental factors on the operation safety of the optical storage system is quantified, and thus the prevention strategy can be determined according to the change of the surrounding environment of the photovoltaic array in extreme weather.

Inventors

LIAO HAOJIE

Assignees

紫光数能(海南)技术有限公司

Dates

Publication Date: 20260505
Application Date: 20251231

Claims (10)

1. The method for acquiring the optical storage risk prevention strategy is characterized by comprising the following steps: Acquiring the load rate of a photovoltaic array, parameter values of various environmental parameters of the environment where the photovoltaic array is located, and weight coefficients respectively corresponding to each environmental parameter; Determining a weight value corresponding to an ith environmental parameter based on a parameter value interval to which the parameter value of the ith environmental parameter belongs and the parameter value of the ith environmental parameter, wherein i is a positive integer; Determining a correction coefficient corresponding to the load factor based on the load factor and a mapping relation between the pre-configured load factor and the correction coefficient; Determining a first environmental parameter with the maximum weight coefficient in each environmental parameter, and acquiring a first environmental parameter mean value, a first environmental parameter maximum peak value and duration of the first environmental parameter maximum peak value of the first environmental parameter in a historical time period; determining a risk index based on the first environmental parameter mean value, the first environmental parameter maximum peak value, the duration, the historical time period, the weight value respectively corresponding to each environmental parameter, the weight coefficient respectively corresponding to each environmental parameter and the correction coefficient; Determining a risk level corresponding to the risk index based on the risk index and a mapping relation between the pre-configured risk index and the risk level; And selecting a target risk prevention strategy corresponding to the risk level from the pre-configured risk prevention strategies.
2. The method of claim 1, wherein the determining a risk index based on the first environmental parameter mean, the first environmental parameter maximum peak, the duration, the historical time period, the weight value, the weight coefficient, and the correction coefficient comprises: Determining a parameter fluctuation coefficient based on the first environmental parameter mean value, the first environmental parameter maximum peak value, the duration and the historical time period; The risk index is determined based on the parameter fluctuation coefficient, the weight value, the weight coefficient, and the correction coefficient.
3. The method of claim 2, wherein the determining a parameter fluctuation coefficient based on the first environmental parameter mean, the first environmental parameter maximum peak, the duration, and the historical time period is represented by: Representing the coefficient of fluctuation of the parameter in question, Representing the maximum peak value of the first environmental parameter, Representing the mean value of the first environmental parameter, Which is indicative of the duration of time in question, Representing the historical time period.
4. The method according to claim 2, wherein the method further comprises: determining the maximum value in the weight values corresponding to the environmental parameters; if the maximum value is greater than or equal to a first weight threshold and less than a second weight threshold, determining a first parameter cooperation coefficient based on a first number of the maximum values according to a first rule, and determining the risk index based on the parameter fluctuation coefficient, the weight value, the weight coefficient, the correction coefficient and the first parameter cooperation coefficient.
5. The method according to claim 4, wherein the method further comprises: And if the maximum value is greater than the second weight threshold value, determining a second parameter cooperative coefficient based on a second number of the maximum values according to a second rule, wherein the second parameter cooperative coefficient is used for determining the risk index based on the parameter fluctuation coefficient, the weight value, the weight coefficient, the correction coefficient and the second parameter cooperative coefficient.
6. The method of claim 5, wherein the risk index is jointly determined based on the parameter fluctuation coefficient, the weight value, the weight coefficient, the correction coefficient, and a parameter synergy coefficient, as represented by the following expression: the risk index is represented by a value of the risk index, Representing the number of said environmental parameters, Represent the first The risk factors corresponding to the individual environmental parameters, Represent the first The preset weight coefficients corresponding to the respective environmental parameters, Representing the coefficient of fluctuation of the parameter in question, Which represents the load factor in question, And representing the parameter cooperative coefficient, wherein the parameter cooperative coefficient is the first parameter cooperative coefficient or the second parameter cooperative coefficient.
7. An optical storage risk prevention policy obtaining device, characterized in that the device comprises: The parameter acquisition module is used for acquiring the load rate of the photovoltaic array, parameter values of various environmental parameters related to the environment where the photovoltaic array is positioned, and weight coefficients respectively corresponding to each environmental parameter; the weight determining module is used for determining a weight value corresponding to the ith environmental parameter based on a parameter value interval to which the parameter value of the ith environmental parameter belongs and the parameter value of the ith environmental parameter, wherein i is a positive integer; The correction coefficient determining module is used for determining a correction coefficient corresponding to the load factor based on the load factor and a mapping relation between the pre-configured load factor and the correction coefficient; The first environmental parameter acquisition module is used for determining a first environmental parameter with the largest weight coefficient in each environmental parameter, and acquiring a first environmental parameter mean value, a first environmental parameter maximum peak value and duration of the first environmental parameter maximum peak value of the first environmental parameter in a historical time period; The risk index determining module is configured to determine a risk index based on the first environmental parameter average value, the first environmental parameter maximum peak value, the duration, the historical time period, the weight value corresponding to each environmental parameter, the weight coefficient corresponding to each environmental parameter, and the correction coefficient; The risk level determining module is used for determining a risk level corresponding to the risk index based on the risk index and a mapping relation between the pre-configured risk index and the risk level; and the strategy determining module is used for selecting a target risk prevention strategy corresponding to the risk level from the pre-configured risk prevention strategies.
8. An optical storage risk prevention policy acquisition system, the system comprising: the sensors are used for collecting various environmental parameters of the environment where the photovoltaic array is located; a controller for executing the optical storage risk protection policy acquisition method according to any one of the preceding claims 1 to 6; and the executor is used for executing corresponding operations based on the target risk prevention strategy determined by the controller.
9. An electronic device, comprising: A memory and a processor, the memory and the processor being communicatively connected to each other, the memory having stored therein computer instructions, the processor executing the computer instructions to perform the optical storage risk protection policy acquisition method of any one of claims 1 to 6.
10. A computer-readable storage medium having stored thereon computer instructions for causing a computer to execute the optical storage risk protection policy acquisition method according to any one of claims 1 to 6.

Description

Method, device and system for acquiring optical storage risk prevention strategy and electronic equipment Technical Field The invention relates to the technical field of optical storage systems, in particular to an optical storage risk prevention strategy acquisition method, an optical storage risk prevention strategy acquisition device, an optical storage risk prevention strategy acquisition system and electronic equipment. Background The photovoltaic energy storage system is widely applied to a distributed energy network due to the characteristics of low cleanness, low carbon and flexible deployment, and has remarkable advantages especially in remote areas and micro-grid scenes. However, with the frequency of extreme weather events, the operational risk faced by photovoltaic energy storage systems increases significantly. At present, early warning for extreme weather is mostly dependent on regional weather station data, dynamic sensing capability of local microclimate is lacking, and quick response to actual environmental changes around a photovoltaic array is difficult. Meanwhile, when the weather is extreme, risks can be avoided only through a power-off shutdown mode, and the capacity of maintaining the minimum power supply on the premise of ensuring the system safety is difficult to improve. Disclosure of Invention The invention provides a method, a device, a system and electronic equipment for acquiring a light storage risk prevention strategy, which at least solve the problem that in the related art, quick response to changes of the surrounding environment of a photovoltaic array is difficult to perform under extreme weather. In a first aspect, the invention provides a photovoltaic extreme weather resistant control method, which comprises the steps of obtaining a load rate of a photovoltaic array, parameter values of a plurality of types of environment parameters related to an environment where the photovoltaic array is located, and respectively corresponding weight coefficients to each environment parameter; Determining a weight value corresponding to the ith environmental parameter based on a parameter value interval to which the parameter value of the ith environmental parameter belongs and the parameter value of the ith environmental parameter, wherein i is a positive integer; Determining a correction coefficient corresponding to the load factor based on the load factor and a mapping relation between the pre-configured load factor and the correction coefficient; Determining a first environmental parameter with the largest weight coefficient in each environmental parameter, and acquiring a first environmental parameter mean value of the first environmental parameter in a historical time period, a first environmental parameter maximum peak value and duration of the first environmental parameter maximum peak value; Determining a risk index based on the first environmental parameter mean value, the first environmental parameter maximum peak value, the duration, the historical time period, the weight value respectively corresponding to each environmental parameter, the weight coefficient respectively corresponding to each environmental parameter and the correction coefficient; determining a risk level corresponding to the risk index based on the risk index and a mapping relation between the pre-configured risk index and the risk level; and selecting a target risk prevention strategy corresponding to the risk level from the pre-configured risk prevention strategies. In a second aspect, the present invention provides a photovoltaic extreme weather resistant control device comprising: the parameter acquisition module is used for acquiring the load rate of the photovoltaic array, parameter values of various environmental parameters related to the environment where the photovoltaic array is positioned, and weight coefficients respectively corresponding to each environmental parameter; the weight determining module is used for determining a weight value corresponding to the ith environmental parameter based on a parameter value interval to which the parameter value of the ith environmental parameter belongs and the parameter value of the ith environmental parameter, wherein i is a positive integer; The correction coefficient determining module is used for determining a correction coefficient corresponding to the load rate based on the load rate and a mapping relation between the pre-configured load rate and the correction coefficient; the first environmental parameter acquisition module is used for determining a first environmental parameter with the largest weight coefficient in all environmental parameters, and acquiring a first environmental parameter mean value, a first environmental parameter maximum peak value and duration of the first environmental parameter maximum peak value of the first environmental parameter in a historical time period; the risk index determining module is used for determining a