Probabilistic power system supply and demand balance state grading evaluation method and device

Abstract

The invention discloses a probabilistic power system supply and demand balance state grading evaluation method and device. The method comprises the following steps: constructing a new energy annual hour-by-hour output scene set based on historical new energy output statistical data of a power system; based on the output scene set and the capacity and output characteristic boundary data of each type of unit, carrying out time sequence generation simulation calculation, and recording a power system supply and demand balance state in each output scene in the output scene set; based on the supply and demand balance state of the power system, counting the statistical result of the occurrence frequency and duration of each power gap; calculating various power gaps in all scenes in the output scene set based on a statistical result, and constructing power gap probability distribution; and dividing the supply and demand tensity level of the power system based on the power gap probability distribution.

Description

Technical Field

[0001] The present invention relates to the technical field of power system planning, and more particularly to a probabilistic power system supply and demand balance state hierarchical evaluation method and device. Background Art

[0002] Time-series production simulation is a technology based on a new model of power generation, grid, load, and storage characteristics. It considers complex constraints during system planning or operation, and determines the operating states of power generation, grid, load, and storage based on objectives such as economic efficiency, optimal reliability, or maximum renewable energy consumption, thereby reflecting the system's balance. Time-series production simulation has various forms. To meet the practical needs of power planning and ensure efficient high-frequency iterative simulation, this paper adopts an integrated power generation, grid, load, and storage production simulation algorithm based on a heuristic framework, widely used in supply and demand balance analysis. Focusing on assessing the supply and demand balance of power systems, it currently includes technical indicators such as monthly and annual power consumption and daily power shortages, as well as reliability indicators such as load loss probability and power shortage expectation. The former primarily uses deterministic assessment methods and indicator systems to assess system power supply shortages or surpluses, but it struggles to account for the diverse system states influenced by the stochastic characteristics of renewable energy. The latter provides a holistic assessment of system supply capacity, but struggles to provide a detailed description of information such as the probability of various load loss events. Furthermore, traditional computational methods are increasingly struggling to balance long-term, fine-grained time-series simulations with efficient solutions. In general, the current supply and demand balance status assessment method cannot fully reflect the system abundance status considering random characteristics, and it is increasingly difficult to meet the actual needs of power system planning and other work for comprehensive and robust demonstration of decision-making plans. Summary of the Invention

[0003] In view of the deficiencies of the prior art, the present invention provides a probabilistic hierarchical evaluation method and device for the supply and demand balance state of a power system.

[0004] According to one aspect of the present invention, a probabilistic hierarchical evaluation method for the supply and demand balance state of a power system is provided, comprising:

[0005] Based on the historical renewable energy output statistics of the power system, a set of renewable energy output scenarios is constructed hour by hour throughout the year.

[0006] Based on the output scenario set and the capacity and output characteristic boundary data of various units, time series generation simulation calculations are carried out to record the supply and demand balance status of the power system under each output scenario in the output scenario set;

[0007] Based on the supply and demand balance of the power system, statistics on the frequency and duration of various power shortages;

[0008] Based on the statistical results, various power gaps under all scenarios in the power scenario set are calculated to construct the power gap probability distribution;

[0009] Based on the probability distribution of power shortage, the supply and demand tension levels of the power system are divided.

[0010] Optionally, based on the historical renewable energy output statistics of the power system, a set of renewable energy output scenarios for each hour throughout the year is constructed, including:

[0011] Based on the statistical data of renewable energy output over the years, the probability distribution of renewable energy output is constructed at different times using the kernel density estimation method.

[0012] Based on the Latin hypercube sampling method, stratified random sampling is performed on the probability distribution of renewable energy output to obtain the renewable energy output data corresponding to each moment;

[0013] Sort the new energy output data at each moment in time and construct an output scenario set.

[0014] Optionally, the calculation expression for the power surplus in the power system supply and demand balance state is:

[0015]

[0016] Where, P plus For system power surplus; is the available capacity of thermal power; The demand for thermal power startup; R cold To meet the system cold standby requirements; System startup requirements; P hdy 、P nuc 、P pum and P sto are hydropower, nuclear power, and pumped storage output respectively; R hdy and R spin are the water and electricity backup and system hot standby requirements respectively; P load is the system load; P line is the tie line power; To ensure output of new energy.

[0017] Optionally, based on the supply and demand balance of the power system, statistics on the frequency and duration of various power shortages are collected, including:

[0018] Based on the supply and demand balance of the power system, draw the power surplus curve under each output scenario;

[0019] Based on the electricity surplus curve, the frequency and duration of various types of electricity gaps are calculated to determine the statistical results.

[0020] Optionally, the supply and demand tension levels include: Level IV, Level III, Level II and Level I.

[0021] According to another aspect of the present invention, a probabilistic hierarchical evaluation device for supply and demand balance state of a power system is provided, comprising:

[0022] The first building block is used to construct a set of hourly renewable energy output scenarios throughout the year based on the historical renewable energy output statistics of the power system.

[0023] The simulation module is used to perform time series generation simulation calculations based on the output scenario set and the capacity and output characteristic boundary data of various units, and record the supply and demand balance status of the power system under each output scenario in the output scenario set;

[0024] The statistical module is used to collect statistics on the frequency and duration of various power shortages based on the supply and demand balance of the power system;

[0025] The second construction module is used to calculate various power gaps under all scenarios in the power scenario set based on statistical results and construct a power gap probability distribution;

[0026] The division module is used to divide the supply and demand tension level of the power system based on the probability distribution of power gap.

[0027] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the storage medium stores a computer program, and the computer program is used to execute the method according to any one of the above aspects of the present invention.

[0028] According to another aspect of the present invention, an electronic device is provided, comprising: a processor; a memory for storing instructions executable by the processor; and the processor for reading the executable instructions from the memory and executing the instructions to implement the method described in any one of the above aspects of the present invention.

[0029] Therefore, this method combines multiple scenarios of renewable energy output with an 8,760-hour time-series production simulation. Using the scale and duration of power shortfalls as control dimensions, it calculates the system power surplus and probability of occurrence under all renewable energy output scenarios, and categorizes the supply-demand balance accordingly. This assessment method can intuitively characterize various low-probability supply guarantee risks, assist in demonstrating the supply guarantee capability of planning solutions, and facilitate the development of necessary safeguards. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] A more complete understanding of exemplary embodiments of the present invention may be obtained by referring to the following drawings:

[0031] Figure 1 1 is a flow chart of a probabilistic hierarchical evaluation method for the supply and demand balance state of a power system provided by an exemplary embodiment of the present invention;

[0032] Figure 2This is a schematic diagram of a set of 8760-hour new energy output scenarios provided by an exemplary embodiment of the present invention;

[0033] Figure 3 It is a schematic diagram of a power system time sequence production simulation process provided by an exemplary embodiment of the present invention;

[0034] Figure 4 is a schematic diagram of system power surplus in various scenarios provided by an exemplary embodiment of the present invention;

[0035] Figure 5 This is a schematic diagram of the probability distribution of the system power gap scale under all scenarios provided by an exemplary embodiment of the present invention;

[0036] Figure 6 1 is a schematic diagram of the probability distribution of the duration of the system power shortage rule in all scenarios provided by an exemplary embodiment of the present invention;

[0037] Figure 7 is a schematic diagram of the classification of power supply and demand tension provided by an exemplary embodiment of the present invention;

[0038] Figure 8 This is a schematic diagram of a renewable energy output scenario for a regional power grid provided by an exemplary embodiment of the present invention;

[0039] Figure 9 This is a schematic diagram of the annual electricity surplus situation in a certain region in 2030, provided by an exemplary embodiment of the present invention;

[0040] Figure 10 1 is a schematic diagram of the probability distribution of the power gap size provided by an exemplary embodiment of the present invention;

[0041] Figure 11 1 is a schematic diagram of the probability distribution of the duration of a power shortage provided by an exemplary embodiment of the present invention;

[0042] Figure 12 This is a schematic diagram of power supply and demand tension and occurrence probability provided by an exemplary embodiment of the present invention;

[0043] Figure 13 1 is a schematic structural diagram of a probabilistic hierarchical evaluation device for supply and demand balance state of a power system provided by an exemplary embodiment of the present invention;

[0044] Figure 14 This is a structure of an electronic device provided by an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0045] Below, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0046] It should be noted that the relative arrangement of components and steps, the numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

[0047] Those skilled in the art will understand that the terms "first" and "second" in the embodiments of the present invention are only used to distinguish different steps, devices or modules, and neither represent any specific technical meaning nor indicate the necessary logical order between them.

[0048] It should also be understood that, in the embodiments of the present invention, “a plurality of” may refer to two or more than two, and “at least one” may refer to one, two or more than two.

[0049] It should also be understood that any component, data or structure mentioned in the embodiments of the present invention can generally be understood as one or more, unless explicitly limited or otherwise indicated in the context.

[0050] In addition, the term "and / or" in this invention merely describes an association relationship between related objects, indicating that three possible relationships exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Furthermore, the character " / " in this invention generally indicates that the related objects are in an "or" relationship.

[0051] It should also be understood that the description of the various embodiments of the present invention focuses on the differences between the various embodiments, and the same or similar aspects thereof can be referenced with each other. For the sake of brevity, they will not be described one by one.

[0052] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0053] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0054] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0055] It should be noted that like reference numerals and letters refer to like items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0056] Embodiments of the present invention can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate in conjunction with numerous other general-purpose or specialized computing system environments or configurations. Examples of well-known terminal devices, computing systems, environments, and / or configurations suitable for use with terminal devices, computer systems, servers, and other electronic devices include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, minicomputer systems, mainframe computer systems, and distributed cloud computing technology environments including any of the above.

[0057] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system-executable instructions (such as program modules) executed by a computer system. Generally, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in a distributed cloud computing environment, where tasks are performed by remote processing devices linked via a communication network. In a distributed cloud computing environment, program modules can be located on local or remote computing system storage media, including storage devices.

[0058] Exemplary Methods

[0059] Figure 1 This is a flow chart of a probabilistic power system supply and demand balance state hierarchical evaluation method provided by an exemplary embodiment of the present invention. This embodiment can be applied to electronic devices, such as Figure 1 As shown, the probabilistic power system supply and demand balance state hierarchical assessment method 100 includes the following steps:

[0060] Step 101: construct a set of hourly output scenarios of renewable energy throughout the year based on historical renewable energy output statistics of the power system;

[0061] Step 102: Based on the output scenario set and the capacity and output characteristic boundary data of various units, a time series generation simulation calculation is performed to record the supply and demand balance state of the power system under each output scenario in the output scenario set;

[0062] Step 103: Based on the supply and demand balance of the power system, statistics are collected on the frequency and duration of various power shortages.

[0063] Step 104, calculating various power shortages under all scenarios in the power scenario set based on the statistical results, and constructing a power shortage probability distribution;

[0064] Step 105: Based on the probability distribution of power shortage, the power system is divided into supply and demand tension levels.

[0065] Specifically, in order to solve the technical problems existing in the background technology, the present invention, based on the actual work experience of power planning and combined with the time-series production simulation algorithm, proposes a quantitative hierarchical assessment method for the supply and demand tension of a high-proportion new energy power system, providing an intuitive and referenceable probabilistic margin assessment means for power planning work, so as to meet the needs of planning schemes to demonstrate supply guarantee capabilities and formulate guarantee measures.

[0066] The purpose of this invention is to provide a probabilistic method for grading the supply and demand balance of a power system. Based on the results of a full-year 8760-hour time-series production simulation, the method divides the supply and demand balance tension into four levels: blue, yellow, orange, and red, taking the scale and duration of the power gap as the main dimensions. The method also provides the probability of occurrence of each situation, explores the low-probability risks of power planning schemes, assists in demonstrating the supply guarantee capability of planning schemes, and formulates necessary safeguard measures. The specific implementation includes the following steps:

[0067] Step 1: Construct a scenario set of 8760 hours of new energy output.

[0068] Step 2: Traverse and extract the set of renewable energy output scenarios, conduct production simulation calculations based on boundary data such as renewable energy and other source, grid, load and storage characteristic parameters, and record the supply and demand balance status of the power system under each scenario.

[0069] Step 3: Count the power shortages for 8,760 hours throughout the year in each scenario, and calculate the frequency and duration of each type of power shortage. If the system is multi-zoned, statistics must be calculated zone by zone.

[0070] Step 4: Based on the statistical results of various scenarios, summarize and calculate the various power gaps under all scenarios in the new energy output scenario set, and construct the power gap probability distribution.

[0071] Step 5: Divide the supply and demand tension level based on the probability of the power gap occurring and its duration.

[0072] In step 1:

[0073] The construction of the 8760-hour new energy output scenario set can be based on the statistical data of the renewable energy output over the years, and the probability distribution of renewable energy output can be constructed by the kernel density estimation method at different moments. The stratified random sampling is performed based on the Latin hypercube sampling method to obtain the renewable energy output data corresponding to each moment. The 8760-hour new energy output scenario set for the whole year is constructed in chronological order, which includes N scenarios, and the probability of occurrence of each scenario is equal, that is, 1 / N. The construction diagram is as follows Figure 2 shown.

[0074] In step 2: To carry out the time series production simulation calculation, it is necessary to traverse and extract the new energy output scenario set, based on the boundary data of each new energy output scenario and the capacity and output characteristics of each type of unit, refer to Figure 3 The process shown carries out time-series production simulation calculations, records the supply and demand balance of the power system under various scenarios, and focuses on the power surplus at each moment, as shown in Equations (1) to (3):

[0075]

[0076] Where, P plus For system power surplus; is the available capacity of thermal power; The demand for thermal power startup; R cold To meet the system cold standby requirements; System startup requirements; P hdy 、P nuc 、P pum and P sto are hydropower, nuclear power, and pumped storage output respectively; R hdy and R spin are the water and electricity backup and system hot standby requirements respectively; P load is the system load; P line is the tie line power; To ensure the output of new energy, it can generally be determined by multiplying the predicted output by the proportional coefficient δ, for example δ = 0.05.

[0077] In step 3: Calculate the annual 8760-hour power shortage in each scenario, especially the power surplus P plus Less than zero. The system 8760-hour power surplus curve can be drawn under various renewable energy output scenarios, such as Figure 4 The frequency and duration of each type of power shortage are counted. If the system has multiple zones, statistics need to be collected for each zone.

[0078] In step 4: construct the power gap probability distribution based on the power gap situation of the entire scenario set, that is, the power gap frequency and duration under each scenario described in step 3 are aggregated to construct the power gap dataset of the entire scenario, and the kernel density estimation method is used to construct the probability distribution for the power gap size and duration, as shown in the following example: Figure 5 and Figure 6 As shown, the probability of occurrence of any power gap size and duration can then be determined.

[0079] In step 5: the supply and demand tension level is divided into four levels: blue, yellow, orange and red (IV, III, II, I) according to the classification method of my country's meteorological disaster warning signals. Similar to the classification of rainstorm warnings based on the amount of rainfall and duration in a certain period, the supply and demand tension warning can be continuously and smoothly graded based on the size of the power gap and the duration, such as Figure 7 As shown, it can also reflect the probability of occurrence information.

[0080] In one embodiment of the present invention, a case analysis is carried out based on the development planning data of a regional power grid in eastern China in 2030. The power grid consists of eight sub-regions: FJ, JS1, JS2, SH, ZJ1, ZJ2, AH1 and AH2. The installed capacity of various power sources is shown in Table 1, including 319.4GW of coal-fired power units, 68.5GW of gas-fired power units, 45.5GW of nuclear power units, 20.6GW of hydropower units, 47.9GW of pumped storage units, 24.6GW of energy storage units, 115.7GW of wind power units, and 293.4GW of photovoltaic units, of which wind power and photovoltaic units account for more than 43%. A set of new energy output scenarios for each sub-region in the region is constructed, such as Figure 8 shown.

[0081] Table 1 Installed power capacity of each zone in a regional power grid in 2030

[0082]

[0083]

[0084] Based on the above boundary data, an 8760-hour integrated power generation simulation calculation was carried out. Taking the scenario where renewable energy continuously has low output for more than 7 days as an example, the probability of the scenario is about 0.004. The regional power grid has a large power gap in summer and winter. The extreme value of the power gap in summer is 38.8GW, and the extreme value of the power gap in winter is about 16.8GW, both accounting for about 10% of the load at that time. Figure 9 shown.

[0085] The probability distribution of the size and duration of the power gap in this scenario is as follows: Figure 10 and Figure 11 As shown, all power gaps are showing a rapid downward trend, with approximately 30% of them less than 5GW and 50% less than 11GW. Approximately 50% of these gaps last less than 13 hours, and 84% last less than 24 hours. It is important to note that large power gaps and long durations often occur simultaneously, and their occurrence periods are highly consistent with periods of prolonged low renewable energy output.

[0086] Furthermore, power gap statistics are conducted for each scenario, and the various types of power gaps that may occur in the power system, their duration and their probabilities are obtained in combination with the scenario probabilities. Referring to the supply and demand tension grading system determined in advance based on planning and operation experience, the supply and demand tension levels corresponding to various types of power gaps can be located. Figure 12The supply and demand tension levels and occurrence probabilities corresponding to some power shortage events are displayed. It can be found that the maximum power shortage duration is relatively short, only two hours, but the gap is extremely large, accounting for about 10% of the load. Considering that the probability of occurrence is only 0.01%, it is an extremely low-probability event. Therefore, it is necessary to comprehensively consider the impact of the event and the probability of occurrence to take necessary response measures, such as adding pumped energy storage, preparing for demand-side response, etc.; when the power shortage is small, it can be positioned at blue level IV, yellow level III and orange level II according to the duration, but the probability of occurrence is relatively high, and emergency plans need to be prepared. For example, new energy electricity can be transferred on a large scale through long-term energy storage to alleviate continuous power shortages.

[0087] Therefore, this method combines multiple scenarios of renewable energy output with an 8,760-hour time-series production simulation. Using the scale and duration of power shortfalls as control dimensions, it calculates the system power surplus and probability of occurrence under all renewable energy output scenarios, and categorizes the supply-demand balance accordingly. This assessment method can intuitively characterize various low-probability supply guarantee risks, assist in demonstrating the supply guarantee capability of planning solutions, and facilitate the development of necessary safeguards.

[0088] Exemplary devices

[0089] Figure 13 Schematic diagram of a probabilistic power system supply and demand balance state hierarchical evaluation device provided by an exemplary embodiment of the present invention. Figure 13 As shown, the apparatus 1300 includes:

[0090] The first constructing module 1310 is configured to construct a set of hourly output scenarios of renewable energy throughout the year based on historical renewable energy output statistics of the power system;

[0091] The simulation module 1320 is used to perform time series generation simulation calculations based on the output scenario set and the capacity and output characteristic boundary data of various units, and record the supply and demand balance state of the power system under each output scenario in the output scenario set;

[0092] The statistics module 1330 is used to collect statistics on the frequency and duration of various power shortages based on the supply and demand balance of the power system;

[0093] The second construction module 1340 is used to calculate various power gaps in all scenarios in the power scenario set based on the statistical results and construct a power gap probability distribution;

[0094] The classification module 1350 is used to classify the supply and demand tension level of the power system based on the power shortage probability distribution.

[0095] Optionally, the first building block 1310 includes:

[0096] The first construction submodule is used to construct the probability distribution of new energy output at different times by using the kernel density estimation method based on the statistical data of new energy output available over the years;

[0097] The sampling submodule is used to perform stratified random sampling on the probability distribution of renewable energy output based on the Latin hypercube sampling method to obtain the renewable energy output data corresponding to each moment;

[0098] The second construction submodule is used to sort the new energy output data at each moment in time sequence and construct an output scenario set.

[0099] Optionally, the calculation expression for the power surplus in the power system supply and demand balance state is:

[0100]

[0101] Where, P plus For system power surplus; is the available capacity of thermal power; The demand for thermal power startup; R cold To meet the system cold standby requirements; System startup requirements; P hdy 、P nuc 、P pum and P sto are hydropower, nuclear power, and pumped storage output respectively; R hdy and R spin are the water and electricity backup and system hot standby requirements respectively; P load is the system load; P line is the tie line power; To ensure output of new energy.

[0102] Optionally, the statistics module 1330 includes:

[0103] The drawing submodule is used to draw the power surplus curve under various output scenarios based on the supply and demand balance status of the power system;

[0104] The determination submodule is used to calculate the frequency and duration of various power gaps based on the power surplus curve and determine the statistical results.

[0105] Optionally, the supply and demand tension levels include: Level IV, Level III, Level II and Level I.

[0106] Exemplary electronic devices

[0107] Figure 13 This is the structure of an electronic device provided by an exemplary embodiment of the present invention. Figure 14 As shown, the electronic device 140 includes one or more processors 141 and a memory 142 .

[0108] The processor 141 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0109] The memory 142 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), a hard disk, a flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 141 may execute the program instructions to implement the methods of the software programs of the various embodiments of the present invention described above and / or other desired functions. In one example, the electronic device may further include: an input device 143 and an output device 144, which are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0110] In addition, the input device 143 may also include, for example, a keyboard, a mouse, and the like.

[0111] The output device 144 can output various information to the outside. The output device 144 can include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto.

[0112] Of course, to simplify, Figure 14 Only some of the components related to the present invention in the electronic device are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, the electronic device may further include any other appropriate components according to specific application conditions.

[0113] Exemplary computer program products and computer-readable storage media

[0114] In addition to the above-mentioned methods and devices, an embodiment of the present invention may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to perform the steps of the method according to various embodiments of the present invention described in the above "Exemplary Method" section of this specification.

[0115] The computer program product may be written in any combination of one or more programming languages to implement the operations of embodiments of the present invention, including object-oriented programming languages such as Java, C++, and conventional procedural programming languages such as C or similar programming languages. The program code may be executed entirely on the user's computing device, partially on the user's computing device, as a stand-alone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0116] In addition, an embodiment of the present invention may also be a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, enable the processor to execute the steps of the method according to various embodiments of the present invention described in the above "Exemplary Method" section of this specification.

[0117] The computer-readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can, for example, include but is not limited to a system, system or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable 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 thereof.

[0118] The basic principles of the present invention have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, and effects mentioned in the present invention are merely illustrative and non-limiting, and should not be construed as necessarily possessed by each embodiment of the present invention. Furthermore, the specific details disclosed above are provided for illustrative purposes and to facilitate understanding, and are not intended to be limiting. These details do not necessarily limit the present invention to being implemented using these specific details.

[0119] Each embodiment in this specification is described in a progressive manner, with each embodiment focusing on its differences from the other embodiments. References to the same or similar parts between the various embodiments are sufficient. For system embodiments, since they largely correspond to method embodiments, their description is relatively simple. For relevant parts, references to the description of the method embodiments are sufficient.

[0120] The block diagrams of the devices, systems, equipment, and systems involved in the present invention are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As will be appreciated by those skilled in the art, these devices, systems, equipment, and systems can be connected, arranged, or configured in any manner. Words such as "including," "comprising," "having," and the like are open-ended words, meaning "including but not limited to," and can be used interchangeably therewith. The words "or" and "and" used herein refer to the words "and / or" and can be used interchangeably therewith, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to," and can be used interchangeably therewith.

[0121] The method and system of the present invention may be implemented in many ways. For example, the method and system of the present invention may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above sequence of steps for the method is for illustration only, and the steps of the method of the present invention are not limited to the sequence specifically described above, unless otherwise specified. In addition, in some embodiments, the present invention may also be implemented as a program recorded in a recording medium, which includes machine-readable instructions for implementing the method according to the present invention. Thus, the present invention also covers recording media that store programs for executing the method according to the present invention.

[0122] It should also be noted that, in the system, device and method of the present invention, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present invention. The above description of the disclosed aspects is provided to enable any technician in this field to make or use the present invention. Various modifications to these aspects will be very obvious to those skilled in the art, and the general principles defined here can be applied to other aspects without departing from the scope of the present invention. Therefore, the present invention is not intended to be limited to the aspects shown here, but according to the widest scope consistent with the principles disclosed here and novel features.

[0123] The above description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the present invention to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A probabilistic hierarchical evaluation method for the supply and demand balance state of a power system, characterized by: include: Based on the historical renewable energy output statistics of the power system, a set of renewable energy output scenarios is constructed hour by hour throughout the year. Based on the output scenario set and the capacity and output characteristic boundary data of various units, a time series generation simulation calculation is performed to record the supply and demand balance state of the power system under each output scenario in the output scenario set; Based on the supply and demand balance state of the power system, statistical results of the frequency and duration of various power shortages; Calculate various power gaps under all scenarios in the output scenario set based on the statistical results, and construct a power gap probability distribution; Based on the power shortage probability distribution, the power system is divided into supply and demand tension levels.

2. The method according to claim 1, characterized in that Based on the historical renewable energy output statistics of the power system, a set of renewable energy output scenarios for each hour throughout the year is constructed, including: Based on the statistical data of renewable energy output over the years, the probability distribution of renewable energy output is constructed at different times using the kernel density estimation method. Performing stratified random sampling on the probability distribution of the renewable energy output based on the Latin hypercube sampling method to obtain renewable energy output data corresponding to each moment; The new energy output data at each moment is sorted in time sequence to construct the output scenario set.

3. The method according to claim 1, characterized in that The calculation expression of the power surplus in the power system supply and demand balance state is: Where, P plus For system power surplus; is the available capacity of thermal power; The demand for thermal power startup; R cold To meet the system cold standby requirements; System startup requirements; P hdy 、P nuc 、P pum and P sto They are hydropower, nuclear power, and pumped storage output; Rhdy and Rspin They are water and power backup and system hot standby requirements respectively; Pload is the system load; Pline is the tie line power; To ensure output of new energy.

4. The method according to claim 1, wherein Based on the supply and demand balance of the power system, the frequency and duration of various power shortages are statistically analyzed, including: Based on the supply and demand balance state of the power system, draw a power surplus curve under each output scenario; The frequency and duration of each type of power shortage are calculated based on the power surplus curve to determine the statistical results.

5. The method according to claim 1, wherein The supply and demand tension levels include: Level IV, Level III, Level II and Level I.

6. A probabilistic hierarchical evaluation device for the supply and demand balance state of a power system, characterized in that: include: The first building block is used to construct a set of hourly renewable energy output scenarios throughout the year based on the historical renewable energy output statistics of the power system. A simulation module is used to perform time series generation simulation calculation based on the output scenario set and the capacity and output characteristic boundary data of various units, and record the supply and demand balance state of the power system under each output scenario in the output scenario set; A statistical module is used to calculate the frequency and duration of various power shortages based on the supply and demand balance of the power system; A second construction module is configured to calculate various power gaps in all scenarios in the output scenario set based on the statistical results, and construct a power gap probability distribution; A division module is used to divide the supply and demand tension level of the power system based on the power gap probability distribution.

7. The device according to claim 6, characterized in that The first building block includes: The first construction submodule is used to construct the probability distribution of new energy output at different times by using the kernel density estimation method based on the statistical data of new energy output available over the years; a sampling submodule, configured to perform stratified random sampling on the probability distribution of the renewable energy output based on a Latin hypercube sampling method, and obtain renewable energy output data corresponding to each moment; The second construction submodule is used to sort the new energy output data at each moment in time sequence to construct the output scenario set.

8. The device according to claim 6, characterized in that The calculation expression of the power surplus in the power system supply and demand balance state is: Where, P plus For system power surplus; is the available capacity of thermal power; To meet the demand for thermal power startup; Rcold To meet the system cold standby requirements; System startup requirements; P hdy 、 Pnuc 、P pum and Psto are hydropower, nuclear power, and pumped storage output respectively; R hdy and R spin are the water and electricity backup and system hot standby requirements respectively; P load is the system load; Pline is the tie line power; To ensure output of new energy.

9. The device according to claim 6, characterized in that Statistics module, including: A drawing submodule, configured to draw a power surplus curve under each output scenario based on the supply and demand balance state of the power system; The determination submodule is used to calculate the frequency and duration of various types of power shortages based on the power surplus curve and determine the statistical results.

10. The device according to claim 6, characterized in that The supply and demand tension levels include: Level IV, Level III, Level II and Level I.

11. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and the computer program is used to execute the method according to any one of claims 1 to 5.

12. An electronic device, characterized in that: The electronic device comprises: processor; a memory for storing instructions executable by the processor; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method according to any one of claims 1 to 5.

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