Electric quantity adjusting method and device for coping with extreme weather

Abstract

The invention discloses an electric quantity adjustment method and device for coping with extreme weather, and the method comprises the steps: obtaining the area of a disaster region when the extreme weather occurs, the duration of the extreme weather, and the electric quantity adjustment demand parameter data of the duration, and obtaining a time sequence of electric quantity adjustment demand parameters; performing normalization processing to obtain an electric quantity adjustment demand parameter normalization value; calculating an influence coefficient of the electric quantity adjustment demand index in the next time period based on the area of the affected area, the normalized value and the electric quantity adjustment demand parameter data; and calculating a predicted value of the extreme weather electric quantity adjustment demand index in the next time period to obtain the adjusted output electric quantity. According to the method, the power demand under the extreme weather condition can be predicted, a basis is provided for reasonable configuration and resource scheduling of a power system, and the method is very necessary. The method can effectively improve the adjustment capability of the power system and the multi-energy scheduling capability, promotes the power system to quickly recover stability after extreme weather, and guarantees the stable operation of the power system.

Description

Technical Field

[0001] The present application relates to the field of power regulation, and in particular to a power regulation method and device for coping with extreme weather. Background Art

[0002] Global climate change has become a reality that cannot be ignored. Extreme weather events occur frequently, bringing huge challenges to human society. In the field of energy, the stability and reliability of the power system as a key infrastructure of modern society have attracted much attention. With the development of the economy and the improvement of people's living standards, the demand for electricity continues to grow, and the emergence of extreme weather has further aggravated the imbalance between electricity supply and demand. On the one hand, extreme high temperature weather has become a common climate phenomenon in recent years. In the hot summer, the use of cooling equipment such as air conditioners and fans has increased sharply, resulting in a significant increase in electricity consumption. For example, when there is a high temperature heat wave for many consecutive days, the power load in the city may reach several times or even higher than usual. On the other hand, especially in the northern region, extreme low temperatures may lead to a sudden increase in heating demand. If the power supply cannot be met, it will seriously affect the quality of life of residents and the normal operation of society. Furthermore, heavy rains and floods may damage power infrastructure, causing power outages in some areas, thereby temporarily reducing power demand. Typhoons may cut power lines and damage power facilities such as substations, affecting power supply while also changing the distribution of power demand. Therefore, how to adjust power demand in extreme weather is a technical problem that needs to be solved urgently. Summary of the invention

[0003] The present disclosure provides a method and device for regulating power in response to extreme weather, so as to at least solve the above technical problems existing in the prior art.

[0004] According to a first aspect of the present application, a method for regulating power in response to extreme weather is provided, the method comprising:

[0005] Acquire the area of ​​the disaster-stricken area when extreme weather occurs, the duration of the extreme weather, and the power regulation demand parameter data of the duration; the power regulation demand parameter is used to characterize the power regulation demand index;

[0006] Obtaining a time series of power regulation demand parameters based on the power regulation demand parameter data of the duration;

[0007] Normalizing the time series of the power regulation demand parameter to obtain a normalized value of the power regulation demand parameter;

[0008] Calculating the influence coefficient of the power regulation demand index for the next period based on the area of ​​the disaster-stricken area, the normalized value and the power regulation demand parameter data;

[0009] Calculate the predicted value of the extreme weather power regulation demand index for the next period according to the influence coefficient of the power regulation demand index for the next period;

[0010] The output power is adjusted according to the predicted value of the extreme weather power regulation demand index in the next period.

[0011] In one possible implementation, the obtaining of the time series of the power regulation demand parameter based on the temperature change of the duration and the power regulation demand parameter data includes:

[0012] dividing the duration into a plurality of fixed time intervals;

[0013] Acquire temperature data at multiple fixed time intervals and power regulation demand parameter data at fixed time intervals.

[0014] In one possible implementation manner, the power regulation requirement parameter includes:

[0015] The load fluctuation rate on the day when extreme weather occurs, the average output power of wind stations on the day when extreme weather occurs, the average output power of solar stations on the day when extreme weather occurs, the upper and lower limits of wind and solar station output, the upper and lower limits of photovoltaic station output, the maximum load, minimum load and average load on the day when extreme weather occurs, the average temperature on the day when extreme weather occurs, the maximum and minimum temperatures on the day when extreme weather occurs, the average output power of thermal power units on the day when extreme weather occurs, the upper and lower limits of thermal power unit output, the adjustable energy storage capacity on the day when extreme weather occurs and the upper and lower limits of adjustable energy storage capacity.

[0016] In one possible implementation, the time series of the power regulation requirement parameter is:

[0017]

[0018] Among them, t1, t2, ..., t n ,...,t m is the duration of m extreme weather events, m is a natural number, m∈1,2,L,n∈{1,2,L,m}, and the time periods of m time intervals are t1,t2,...,t n ,...,t m ; is the measured value of the average wind power output power in m time intervals; is the measured value of the average output power of the photovoltaic station in m time intervals; is the value of load fluctuation rate of extreme weather in m time intervals; is the measured value of the average thermal power output during extreme weather events at m time intervals; is the measured value of the adjustable energy storage capacity for the occurrence of extreme weather at m time intervals; The measured values ​​of the temperature when extreme weather occurs at m time intervals.

[0019] In one possible implementation manner, the time series of the power regulation demand parameter is normalized in the following manner:

[0020]

[0021] in, The duration is t n The normalized value of the average wind power output when extreme weather occurs; P f,max , P f,min They are the upper and lower limits of wind and solar power station output respectively; The duration is t n Normalized value of average output power of photovoltaic stations when extreme weather occurs The duration is t n The average output power of wind and solar power stations on the day when the extreme weather occurs; P g,max , P g,min They are the upper and lower limits of the output of the photovoltaic station respectively; The duration is t n Normalized value of load fluctuation rate when extreme weather occurs; The duration is t n The load fluctuation rate on the day when the extreme weather occurs; B f，max , B f，min are the highest load fluctuation rate and the lowest load fluctuation rate of load fluctuation rate respectively; The duration is t n Normalized value of average thermal power output when extreme weather occurs; is the duration t n The average output power of thermal power units on the day when the extreme weather occurs; c,max , F c,min They are the upper and lower limits of thermal power unit output respectively; The duration is t n Normalized value of adjustable energy storage capacity when extreme weather occurs; The adjustable energy storage capacity on the day when extreme weather occurs; Φ es,max With Φ es,min They are the upper and lower limits of the adjustable energy storage capacity; The duration is t n The normalized value of the average temperature on the day when the extreme weather occurs; The average temperature on the day when extreme weather occurs; They are the highest and lowest temperatures on the day when extreme weather occurs.

[0022] In one possible implementation, the influence coefficient of the power regulation demand index for the next period is calculated in the following manner:

[0023]

[0024] Among them, O iw Δ is the influence coefficient of extreme weather on the power regulation demand index in the next period; area is the area of ​​disaster-affected areas when extreme weather occurs; Δ area,max It is the maximum area of ​​the disaster-stricken area when extreme weather occurs.

[0025] In one possible implementation, the following method is used to calculate the predicted value of the extreme weather power regulation demand index for the next period:

[0026]

[0027] Among them, Y jd is the predicted value of the extreme weather power regulation demand index at the next moment; Δ area,min It is the minimum area of ​​disaster-stricken areas when extreme weather occurs.

[0028] In one possible implementation manner, adjusting the output power according to the predicted value of the extreme weather power demand index in the next period includes:

[0029] Comparing the predicted value of the extreme weather power regulation demand index in the next period with a preset threshold;

[0030] If the predicted value of the extreme weather electricity regulation demand index in the next period is less than the preset threshold, the thermal power output and energy storage discharge are adjusted to the original preset multiples; otherwise, the thermal power output is adjusted to be full and the energy storage discharge is maximized.

[0031] In one possible implementation, the output power is adjusted in the following manner:

[0032]

[0033] Among them, W n+1 Adjustment of thermal power output and energy storage at the next moment; The average output power of thermal power when extreme weather occurs at the next moment; Adjustable energy storage capacity for the next extreme weather event.

[0034] According to a second aspect of the present application, there is provided a power regulation device for coping with extreme weather, comprising:

[0035] An acquisition module is used to acquire the area of ​​the disaster-stricken area when extreme weather occurs, the duration of the extreme weather, and the power regulation demand parameter data of the duration; the power regulation demand parameter is used to characterize the power regulation demand index;

[0036] A sequence module, used for obtaining a time series of power regulation demand parameters based on the power regulation demand parameter data of the duration;

[0037] A processing module, used for normalizing the time series of the power regulation demand parameter to obtain a normalized value of the power regulation demand parameter;

[0038] A first calculation module, configured to calculate an influence coefficient of an electricity regulation demand index for a next period based on the area of ​​the disaster-stricken area, the normalized value and the electricity regulation demand parameter data;

[0039] A second calculation module is used to calculate the predicted value of the extreme weather power regulation demand index in the next period according to the influence coefficient of the power regulation demand index in the next period;

[0040] The regulating module is used to regulate the output power according to the predicted value of the extreme weather power regulation demand index in the next period.

[0041] According to a third aspect of the present application, an electronic device is provided, including:

[0042] at least one processor; and

[0043] a memory communicatively connected to the at least one processor; wherein,

[0044] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the present application.

[0045] According to a fourth aspect of the present application, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the method described in the present application.

[0046] According to a fifth aspect of the present application, a computer program product is provided, comprising a computer program or instructions, which implement the method described in the present application when executed by a processor.

[0047] By using the technical solution of this application, this application can predict the power demand under extreme weather conditions, which provides a basis for the reasonable configuration and dispatching of resources in the power system, which is very necessary. The technical solution provided by this application can effectively improve the regulation ability and multi-energy dispatching ability of the power system, promote the rapid recovery of the power system after extreme weather, and ensure the stable operation of the power system.

[0048] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present application will become readily understood. In the accompanying drawings, several embodiments of the present application are shown in an exemplary and non-limiting manner, wherein:

[0050] In the drawings, the same or corresponding reference numerals represent the same or corresponding parts.

[0051] Figure 1 A schematic diagram of a flow chart of a method for regulating power in response to extreme weather in an embodiment of the present application is shown;

[0052] Figure 2 A schematic diagram of the structure flow of the power regulation device in an embodiment of the present application is shown;

[0053] Figure 3 A schematic diagram of the structure of an electronic device in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0054] In order to make the purpose, features, and advantages of the present application more obvious and easy to understand, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0055] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0056] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it can be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0057] In the following description, the terms "first\second" involved are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It can be understood that "first\second" can be interchanged with a specific order or sequence where permitted, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0058] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0059] It should be understood that in the various embodiments of the present application, the size of the serial number of each implementation process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0060] A method and device for regulating power in response to extreme weather provided by the present application will be described below in conjunction with the accompanying drawings.

[0061] like Figure 1 As shown, the present application provides a method for regulating power in response to extreme weather, the method comprising:

[0062] S101, obtaining the area of ​​the disaster-stricken area when extreme weather occurs, the duration of the extreme weather, and power regulation demand parameter data of the duration; the power regulation demand parameter is used to characterize the power regulation demand index;

[0063] It is understandable that extreme weather, including cold waves, high temperatures, seasonal gales, etc., is sudden and complex, which has a certain impact on power supply security. In this application, the size of the affected area after extreme weather occurs is first measured. area , Δ area,max , Δ area,min It is the maximum and minimum area of ​​the disaster-stricken area when extreme weather occurs.

[0064] In some embodiments, the power regulation requirement parameter includes:

[0065] The load fluctuation rate on the day when extreme weather occurs, the average output power of wind stations on the day when extreme weather occurs, the average output power of solar stations on the day when extreme weather occurs, the upper and lower limits of wind and solar station output, the upper and lower limits of photovoltaic station output, the maximum load, minimum load and average load on the day when extreme weather occurs, the average temperature on the day when extreme weather occurs, the maximum and minimum temperatures on the day when extreme weather occurs, the average output power of thermal power units on the day when extreme weather occurs, the upper and lower limits of thermal power unit output, the adjustable energy storage capacity on the day when extreme weather occurs and the upper and lower limits of adjustable energy storage capacity.

[0066] It should be noted that the load fluctuation rate on the day when extreme weather occurs can be calculated based on the maximum load, minimum load and average load on the day when extreme weather occurs.

[0067]

[0068] in, The duration is t n The load fluctuation rate on the day when the extreme weather occurs; is the average load; H hi , H l They are the maximum and minimum loads on the day when extreme weather occurs.

[0069] S102, obtaining a time series of power regulation demand parameters based on the power regulation demand parameter data of the duration;

[0070] Specifically, a time series of parameters related to the power regulation demand index in m time periods is established based on the obtained measurement values.

[0071]

[0072] Among them, t1, t2, ..., t n ,...,t m is the duration of m extreme weather events, where m is a natural number.

[0073] is the measured value of the average wind power output in m time intervals; is the measured value of the average output power of the photovoltaic station in m time intervals; is the load fluctuation rate value of extreme weather in m time intervals; is the measured value of the average thermal power output during extreme weather events at m time intervals; is the measured value of the adjustable energy storage capacity for the occurrence of extreme weather at m time intervals; The measured values ​​of the temperature when extreme weather occurs at m time intervals.

[0074] S103, normalizing the time series of the power regulation demand parameter to obtain a normalized value of the power regulation demand parameter;

[0075] In some embodiments, the time series of the power regulation demand parameter is normalized in the following manner:

[0076]

[0077] in, The duration is tn The normalized value of the average wind power output when extreme weather occurs; P f,max , P f,min They are the upper and lower limits of wind and solar power station output respectively; The duration is t n Normalized value of average output power of photovoltaic stations when extreme weather occurs The duration is t n The average output power of wind and solar power stations on the day when the extreme weather occurs; P g,max , P g,min They are the upper and lower limits of the output of the photovoltaic station respectively; The duration is t n Normalized value of load fluctuation rate when extreme weather occurs; The duration is t n The load fluctuation rate on the day when the extreme weather occurs; B f，max , B f，min are the highest load fluctuation rate and the lowest load fluctuation rate of load fluctuation rate respectively; The duration is t n Normalized value of average thermal power output when extreme weather occurs; is the duration t n The average output power of thermal power units on the day when the extreme weather occurs; c,max , F c,min They are the upper and lower limits of thermal power unit output respectively; The duration is t n Normalized value of adjustable energy storage capacity when extreme weather occurs; The adjustable energy storage capacity on the day when extreme weather occurs; Φ es,max With Φ es,min They are the upper and lower limits of the adjustable energy storage capacity; The duration is t n The normalized value of the average temperature on the day when the extreme weather occurs; The average temperature on the day when extreme weather occurs; They are the highest and lowest temperatures on the day when extreme weather occurs.

[0078] S104, calculating the influence coefficient of the power regulation demand index for the next period based on the area of ​​the disaster-stricken area, the normalized value and the power regulation demand parameter data;

[0079] Specifically, the influence coefficient of the power regulation demand index in the next period is calculated in the following way:

[0080]

[0081] Among them, O iwΔ is the influence coefficient of extreme weather on the power regulation demand index in the next period; area is the area of ​​disaster-affected areas when extreme weather occurs; Δ area,max It is the maximum area of ​​the disaster-stricken area when extreme weather occurs.

[0082] S105, calculating a predicted value of the extreme weather power regulation demand index for the next period according to the influence coefficient of the power regulation demand index for the next period;

[0083] The forecast value of the extreme weather power regulation demand index for the next period is calculated in the following way:

[0084]

[0085] according to get

[0086]

[0087] Among them, Y jd is the predicted value of the extreme weather power regulation demand index at the next moment; Δ area,min It is the minimum area of ​​disaster-stricken areas when extreme weather occurs.

[0088] S106, adjusting the output power according to the predicted value of the extreme weather power regulation demand index in the next period.

[0089] In some embodiments, adjusting the output power according to the predicted value of the extreme weather power demand index in the next period includes:

[0090] Comparing the predicted value of the extreme weather power regulation demand index in the next period with a preset threshold;

[0091] If the predicted value of the extreme weather electricity regulation demand index in the next period is less than the preset threshold, the thermal power output and energy storage discharge are adjusted to the original preset multiples; otherwise, the thermal power output is adjusted to be full and the energy storage discharge is maximized.

[0092] In some embodiments, the output power is adjusted in the following manner:

[0093]

[0094] Among them, W n+1 Adjustment of thermal power output and energy storage at the next moment; The average output power of thermal power when extreme weather occurs at the next moment; Adjustable energy storage capacity for the next extreme weather event.

[0095] It is understandable that the preset threshold can be 0.5.jd If it is less than 0.5, it is considered that the power regulation demand is small in extreme weather, and the thermal power output power and energy storage discharge are adjusted to 0.5 times the original. jd If it is greater than or equal to 0.5, the thermal power will be adjusted to full output and the energy storage will be discharged to the maximum to ensure that the power reaches the minimum demand.

[0096] As a specific embodiment, the fixed time interval in the measurement process is set to 5 hours, and 5 measurement time periods are selected, namely t1, t2, t3, t4, and t5 are 5 fixed time intervals; the measured value of the average output power of wind power is obtained in the fixed time intervals t1, t2, t3, t4, and t5. The average output power of the photovoltaic station is measured in the fixed time intervals t1, t2, t3, t4, t5. The load fluctuation rate is measured at fixed time intervals t1, t2, t3, t4, t5. The measured value of the average output power of the thermal power unit is measured in the fixed time interval time period t1, t2, t3, t4, t5 The adjustable energy storage capacity is measured at fixed time intervals t1, t2, t3, t4, t5 Measure the average temperature of the day when extreme weather occurs in fixed time intervals t1, t2, t3, t4, t5 The time series of parameters related to the power regulation demand index for extreme weather is established based on all the above measurements as follows:

[0097]

[0098] The measured data of the parameters related to the power regulation demand index are normalized to obtain

[0099]

[0100] in, is the normalized value of the average wind power output during the extreme weather with duration t6; is the normalized value of the average output power of the photovoltaic station when the extreme weather lasts for t6; is the normalized value of load fluctuation rate caused by extreme weather with duration t6; is the normalized value of the average temperature on the day when the extreme weather occurs with a duration of t6; is the normalized value of the average thermal power output during extreme weather with duration t6, It is the normalized value of the adjustable energy storage capacity when extreme weather occurs with a duration of t6.

[0101] According to the historical data of parameters related to the extreme weather on the power regulation demand index, the influence coefficient of extreme weather on the power regulation demand index in the next period is calculated as follows:

[0102]

[0103] Among them, O iw It is the impact coefficient of extreme weather on the electricity regulation demand index in the next period.

[0104] Then calculate the predicted value of the extreme weather power regulation demand index for the next period.

[0105]

[0106] Among them, Δ area,max , Δ area,min The maximum and minimum areas of disaster-stricken areas on the day when extreme weather occurs.

[0107] The output power of thermal power is adjusted according to the predicted value of the extreme weather power regulation demand index at the next moment. Specifically, the output power of thermal power and the charging and discharging of energy storage are adjusted according to the predicted value of the extreme weather power regulation demand index at the next moment.

[0108]

[0109] Among them, Y jd represents the predicted value of the extreme weather power regulation demand index at the next moment, W n+1 is the adjustment of thermal power output and energy storage at the next moment. jd If it is less than 0.5, it is considered that the power regulation demand is small in extreme weather, and the thermal power output power and energy storage discharge are adjusted to 0.5 times the original. jd If it is greater than or equal to 0.5, the thermal power will be adjusted to full output and the energy storage will be discharged to the maximum to ensure that the power reaches the minimum demand.

[0110] Based on historical data, this application predicts the electricity regulation demand index at the next moment, and adjusts the thermal power output power and adjustable energy storage at the next moment according to the prediction results, thereby reducing the impact of extreme weather on the stability of the power system. It helps to reduce the instability of power system operation caused by changes in electricity regulation demand caused by the volatility of wind and solar stations in extreme weather.

[0111] like Figure 2 As shown, the present application provides a power regulation device for coping with extreme weather, the device comprising:

[0112] The acquisition module 201 is used to acquire the area of ​​the disaster-stricken area when extreme weather occurs, the duration of the extreme weather, and the power regulation demand parameter data of the duration; the power regulation demand parameter is used to characterize the power regulation demand index;

[0113] A sequence module 202, configured to obtain a time series of power regulation demand parameters based on the power regulation demand parameter data of the duration;

[0114] The processing module 203 is used to normalize the time series of the power regulation demand parameter to obtain a normalized value of the power regulation demand parameter;

[0115] A first calculation module 204 is used to calculate the influence coefficient of the power regulation demand index in the next period based on the area of ​​the disaster-stricken area, the normalized value and the power regulation demand parameter data;

[0116] The second calculation module 205 is used to calculate the predicted value of the extreme weather power regulation demand index in the next period according to the influence coefficient of the power regulation demand index in the next period;

[0117] The regulating module 206 is used to regulate the output power according to the predicted value of the extreme weather power regulation demand index in the next period.

[0118] The present application provides an electricity regulation device for coping with extreme weather, wherein an acquisition module 201 acquires the area of ​​the disaster-stricken area when extreme weather occurs, the duration of the extreme weather, and electricity regulation demand parameter data of the duration; the electricity regulation demand parameter is used to characterize the electricity regulation demand index; the sequence module 202 obtains the time series of the electricity regulation demand parameter based on the electricity regulation demand parameter data of the duration; the processing module 203 normalizes the time series of the electricity regulation demand parameter to obtain the normalized value of the electricity regulation demand parameter; the first calculation module 204 calculates the influence coefficient of the electricity regulation demand index for the next period based on the area of ​​the disaster-stricken area, the normalized value and the electricity regulation demand parameter data; the second calculation module 205 calculates the predicted value of the extreme weather electricity regulation demand index for the next period according to the influence coefficient of the electricity regulation demand index for the next period; the regulation module 206 adjusts the output electricity according to the predicted value of the extreme weather electricity regulation demand index for the next period.

[0119] According to an embodiment of the present application, the present application also provides an electronic device and a readable storage medium.

[0120] The electronic device includes at least one processor; and a memory in communication with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the power regulation method for extreme weather described in the present application. The computer instructions are used to enable the computer to execute the power regulation method for extreme weather described in the present application.

[0121] The present application also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the extreme weather power regulation method of the present application.

[0122] Figure 3 A schematic block diagram of an example electronic device 300 that can be used to implement an embodiment of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0123] like Figure 3 As shown, the device 300 includes a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 302 or a computer program loaded from a storage unit 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the device 300 can also be stored. The computing unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0124] A number of components in the device 300 are connected to the I / O interface 305, including: an input unit 306, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the device 300 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0125] The computing unit 301 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 301 performs the various methods and processes described above, such as a power regulation method for dealing with extreme weather. For example, in some embodiments, the power regulation method for dealing with extreme weather may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 300 via the ROM 302 and / or the communication unit 309. When the computer program is loaded into the RAM 303 and executed by the computing unit 301, one or more steps of the power regulation method for dealing with extreme weather described above may be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to execute the power regulation method for coping with extreme weather in any other appropriate manner (for example, by means of firmware).

[0126] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0127] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, implements the functions / operations specified in the flow chart and / or block diagram. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0128] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0129] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0130] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0131] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0132] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for regulating power in response to extreme weather, characterized in that: include: Acquire the area of ​​the disaster-stricken area when extreme weather occurs, the duration of the extreme weather, and the power regulation demand parameter data of the duration; the power regulation demand parameter is used to characterize the power regulation demand index; Obtaining a time series of power regulation demand parameters based on the power regulation demand parameter data of the duration; Normalizing the time series of the power regulation demand parameter to obtain a normalized value of the power regulation demand parameter; Calculating the influence coefficient of the power regulation demand index for the next period based on the area of ​​the disaster-stricken area, the normalized value and the power regulation demand parameter data; Calculate the predicted value of the extreme weather power regulation demand index for the next period according to the influence coefficient of the power regulation demand index for the next period; The output power is adjusted according to the predicted value of the extreme weather power regulation demand index in the next period.

2. The method according to claim 1, characterized in that: The time series of the power regulation demand parameter is obtained based on the temperature change of the duration and the power regulation demand parameter data, including: dividing the duration into a plurality of fixed time intervals; Acquire temperature data at multiple fixed time intervals and power regulation demand parameter data at fixed time intervals.

3. The method according to claim 1, characterized in that The power regulation requirement parameters include: The load fluctuation rate on the day when extreme weather occurs, the average output power of wind stations on the day when extreme weather occurs, the average output power of solar stations on the day when extreme weather occurs, the upper and lower limits of wind and solar station output, the upper and lower limits of photovoltaic station output, the maximum load, minimum load and average load on the day when extreme weather occurs, the average temperature on the day when extreme weather occurs, the maximum and minimum temperatures on the day when extreme weather occurs, the average output power of thermal power units on the day when extreme weather occurs, the upper and lower limits of thermal power unit output, the adjustable energy storage capacity on the day when extreme weather occurs and the upper and lower limits of adjustable energy storage capacity.

4. The method according to claim 1, characterized in that: The time series of the power regulation demand parameter is: Among them, t1, t2, ..., t n ,...,t m is the duration of m extreme weather events, m is a natural number, m∈1,2,L,n∈{1,2,L,m}, and the time periods of m time intervals are t1,t2,...,t n ,...,t m ; is the measured value of the average wind power output power in m time intervals; is the measured value of the average output power of the photovoltaic station in m time intervals; is the load fluctuation rate value of extreme weather in m time intervals; is the measured value of the average thermal power output during extreme weather events at m time intervals; is the measured value of the adjustable energy storage capacity for the occurrence of extreme weather at m time intervals; The measured values ​​of the temperature when extreme weather occurs at m time intervals.

5. The method according to claim 1, characterized in that The time series of the power regulation demand parameter is normalized in the following manner: in, The duration is t n The normalized value of the average wind power output when extreme weather occurs; P f,max , P f,min They are the upper and lower limits of wind and solar power station output respectively; The duration is t n Normalized value of average output power of photovoltaic stations when extreme weather occurs The duration is t n The average output power of wind and solar power stations on the day when the extreme weather occurs; P g,max , P g,min They are the upper and lower limits of the output of the photovoltaic station respectively; The duration is t n Normalized value of load fluctuation rate when extreme weather occurs; The duration is t n The load fluctuation rate on the day when the extreme weather occurs; B f，max , B f，min They are the highest load fluctuation rate and the lowest load fluctuation rate of load fluctuation rate respectively; The duration is t n Normalized value of average thermal power output when extreme weather occurs; is the duration t n The average output power of thermal power units on the day when the extreme weather occurs; c,max , F c,min They are the upper and lower limits of thermal power unit output respectively; The duration is t n Normalized value of adjustable energy storage capacity when extreme weather occurs; The adjustable energy storage capacity on the day when extreme weather occurs; Φ es,max With Φ es,min They are the upper and lower limits of the adjustable energy storage capacity; The duration is t n The normalized value of the average temperature on the day when the extreme weather occurs; The average temperature on the day when extreme weather occurs; They are the highest and lowest temperatures on the day when extreme weather occurs.

6. The method according to claim 5, characterized in that The influence coefficient of the power regulation demand index for the next period is calculated in the following way: Among them, O iw Δ is the influence coefficient of extreme weather on the power regulation demand index in the next period; area is the area of ​​disaster-affected areas when extreme weather occurs; Δ area,max It is the maximum area of ​​the disaster-stricken area when extreme weather occurs.

7. The method according to claim 6, characterized in that The forecast value of the extreme weather power regulation demand index for the next period is calculated in the following way: Among them, Y jd is the predicted value of the extreme weather power regulation demand index at the next moment; Δ area,min It is the minimum area of ​​disaster-stricken areas when extreme weather occurs.

8. The method according to claim 1, characterized in that The step of adjusting the output power according to the predicted value of the extreme weather power demand index in the next period includes: Comparing the predicted value of the extreme weather power regulation demand index in the next period with a preset threshold; If the predicted value of the extreme weather electricity regulation demand index in the next period is less than the preset threshold, the thermal power output and energy storage discharge are adjusted to the original preset multiples; otherwise, the thermal power output is adjusted to be full and the energy storage discharge is maximized.

9. The method according to claim 8, characterized in that The output power is adjusted in the following ways: Among them, W n+1 Adjustment of thermal power output and energy storage at the next moment; The average output power of thermal power when extreme weather occurs at the next moment; Adjustable energy storage capacity for the next extreme weather event.

10. A power regulation device for dealing with extreme weather, characterized in that: The device comprises: An acquisition module is used to acquire the area of ​​the disaster-stricken area when extreme weather occurs, the duration of the extreme weather, and the power regulation demand parameter data of the duration; the power regulation demand parameter is used to characterize the power regulation demand index; A sequence module, used for obtaining a time series of power regulation demand parameters based on the power regulation demand parameter data of the duration; A processing module, used for normalizing the time series of the power regulation demand parameter to obtain a normalized value of the power regulation demand parameter; A first calculation module, configured to calculate an influence coefficient of an electricity regulation demand index for a next period based on the area of ​​the disaster-stricken area, the normalized value and the electricity regulation demand parameter data; A second calculation module is used to calculate the predicted value of the extreme weather power regulation demand index in the next period according to the influence coefficient of the power regulation demand index in the next period; The regulating module is used to regulate the output power according to the predicted value of the extreme weather power regulation demand index in the next period.

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