A method and system for evaluating multi-dimensional supportability demand index of a power system

Abstract

The application discloses a novel power system multi-dimensional supporting demand index evaluation method and system, belongs to the field of power system demand estimation, and comprises the following steps: based on system load data and new energy output data, analyzing power system net load data conditions; based on the power system net load data conditions, screening extreme weather new energy continuous low output data according to the new energy output data, determining an extreme weather time segment, and acquiring extreme weather period net load data; and based on the extreme weather period net load data and total time sequence net load data, determining a supporting demand index in the time sequence, and supporting new power system power sources for planning. The application more comprehensively constructs a multi-dimensional supporting index system of supporting power sources, and provides a reference basis for new power system supporting power source planning.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system demand estimation, in particular to a novel power system multi-dimensional supporting demand index evaluation method and system. BACKGROUND

[0002] Under the background of the construction of a new power system, the power supply structure in China will change from the traditional one dominated by thermal power to a complex structure dominated by renewable energy power generation and supported by coal-fired power, gas power, nuclear power and energy storage power. With the gradual increase of new energy penetration, the supporting demands of power, electricity, regulation and other types of new power systems are becoming increasingly complex. Therefore, it is more important to study the power supply planning of supporting power sources such as coal-fired power, gas power, nuclear power and energy storage power. Therefore, a novel power system multi-dimensional supporting demand index evaluation method is urgently needed. The existing index system construction is mainly aimed at new energy or power system flexibility, and there is no description of support. At present, there is no supporting demand index. SUMMARY

[0003] In order to solve the above problems, the purpose of the present application is to provide a novel power system multi-dimensional supporting demand index evaluation technology, which aims to construct a supporting demand index system from power support, electricity support, multi-scale regulation support and other supporting demands. Based on the new energy continuous low output identification technology, the supporting index including power and electricity support demand, peak demand and peak shaving demand is proposed, and the multi-dimensional supporting index system of supporting power supply is more comprehensively constructed, which provides a reference for the supporting power supply planning of the new power system.

[0004] In order to achieve the above technical purpose, the present application provides a novel power system multi-dimensional supporting demand index evaluation method, which comprises the following steps:

[0005] Based on the system load data and new energy output data, the net load data of the power system is analyzed;

[0006] Based on the net load data of the power system, the extreme weather new energy continuous low output data is screened according to the new energy output data, the time segment of the extreme weather is determined, and the net load data of the extreme weather period is obtained;

[0007] Based on the extreme weather period net load data and the total time sequence net load data, the supporting demand index in the time sequence is determined, and the supporting planning of the new power system power supply is carried out.

[0008] Preferably, in the process of obtaining the net load condition of the power system, the net load condition of the power system is determined according to the system load data in a certain time sequence and the corresponding time sequence new energy output data.

[0009] Preferably, in the process of acquiring the time segment where the extreme weather is located, the time segment where the extreme weather is located is determined according to the average output of the system in a time segment, the maximum value of the output data, the low output boundary coefficient and the low output duration boundary.

[0010] Preferably, in the process of acquiring the support demand index, the power support demand index, the electricity support demand index, the peak shaving support demand index and the ramping support demand index are taken as the support demand index.

[0011] Preferably, in the process of acquiring the power support demand index, the power support demand index is acquired according to the power support demand and the time period set of the time segment where the extreme weather is located.

[0012] Preferably, in the process of acquiring the electricity support demand index, the electricity support demand index is acquired according to the electricity support demand and the time period set of the time segment where the extreme weather is located.

[0013] Preferably, in the process of acquiring the peak shaving support demand index, the peak shaving support demand index is acquired according to the peak shaving capacity in the mth period, the maximum and minimum values of the net load in the mth period, the peak shaving support demand and the peak shaving support demand coefficient.

[0014] Preferably, in the process of acquiring the ramping support demand index, the ramping support demand index is determined according to the net load change rate at a certain time, the ramping support demand and the ramping support demand coefficient.

[0015] Preferably, based on the power support demand index, the electricity support demand index, the peak shaving support demand index and the ramping support demand index, a power multi-dimensional support index system is constructed to support the power source of the new power system.

[0016] The application discloses a kind of new power system multi-dimensional support demand index evaluation system, for the new power system multi-dimensional support demand index evaluation method mentioned above, comprising:

[0017] Data analysis module, for based on system load data and new energy output data, analysis power system net load data condition;

[0018] Data processing module, for based on power system net load data condition, according to new energy output data filtering extreme weather new energy sustained low output data, determine the time segment where extreme weather is located, acquire extreme weather time period net load data;

[0019] Support planning module, for based on extreme weather time period net load data and total time sequence net load data determine the support demand index in this time sequence, support the power source of new power system.

[0020] The present application discloses the following technical effects:

[0021] The present application aims at the few index systems about supporting demand at present, and the deficiency that there is no description about supporting power at present, based on new energy continuous low output identification technology, proposes supporting index including power and electricity supporting demand, peak demand, peak regulation demand, etc., more comprehensively constructs supporting power multi-dimensional supporting index system, and provides reference basis for new type power system supporting power planning. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments. Obviously, the drawings described in the following are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0023] Figure 1 The present application provides a method flowchart. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical scheme and advantages of the embodiments of the present application more clear, the following will combine the drawings in the embodiments of the present application to clearly and completely describe the technical scheme in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of the present application.

[0025] As shown in Figure 1 The present application provides a new type of power system multi-dimensional supporting demand index evaluation method, including the following steps:

[0026] Based on system load data and new energy output data, analyze the power system net load data situation;

[0027] Based on the power system net load data situation, according to the new energy output data, filter the extreme weather new energy continuous low output data, determine the time segment of the extreme weather, and obtain the net load data of the extreme weather period;

[0028] The extreme weather period net load data and the total time sequence net load data are used to determine the supporting demand index in the time sequence, and the new power system power supply is supported and planned.

[0029] Further preferably, the new power system multi-dimensional supporting demand index evaluation method provided by the application determines the power system net load condition according to the system load data in a certain time sequence and the new energy output data corresponding to the time sequence in the process of obtaining the power system net load condition.

[0030] Further preferably, the new power system multi-dimensional supporting demand index evaluation method provided by the application determines the time segment of extreme weather according to the average output of the system in a certain time segment, the maximum value of the output data, the low output boundary coefficient and the low output duration boundary in the process of obtaining the time segment of extreme weather.

[0031] Further preferably, the new power system multi-dimensional supporting demand index evaluation method provided by the application takes the power supporting demand index, the power supporting demand index, the peak shaving supporting demand index and the climbing supporting demand index as the supporting demand index in the process of obtaining the supporting demand index.

[0032] Further preferably, the new power system multi-dimensional supporting demand index evaluation method provided by the application obtains the power supporting demand index according to the power supporting demand and the time segment set of the time segment of extreme weather in the process of obtaining the power supporting demand index.

[0033] Further preferably, the new power system multi-dimensional supporting demand index evaluation method provided by the application obtains the power supporting demand index according to the power supporting demand and the time segment set of the time segment of extreme weather in the process of obtaining the power supporting demand index.

[0034] Further preferably, the new power system multi-dimensional supporting demand index evaluation method provided by the application obtains the peak shaving supporting demand index according to the peak shaving capacity in the mth period, the maximum and minimum values of the net load in the mth period, the peak shaving supporting demand, and the peak shaving supporting demand coefficient in the process of obtaining the peak shaving supporting demand index.

[0035] Further preferably, the new power system multi-dimensional supporting demand index evaluation method provided by the application determines the climbing supporting demand index according to the net load change rate at a certain time, the climbing supporting demand and the climbing supporting demand coefficient in the process of obtaining the climbing supporting demand index.

[0036] Further preferably, the application provides a new power system multi-dimensional support demand index evaluation method, which is based on power support demand index, electricity support demand index, peak regulation support demand index and climbing support demand index, constructs a multi-dimensional support index system of power supply, and plans the support of the new power system power supply.

[0037] The application also discloses a new power system multi-dimensional support demand index evaluation system for the new power system multi-dimensional support demand index evaluation method.

[0038] The data analysis module is used for analyzing the power system net load data based on the system load data and the new energy output data.

[0039] The data processing module is used for filtering extreme weather new energy continuous low output data according to the new energy output data based on the power system net load data, determining an extreme weather time segment, and obtaining extreme weather period net load data.

[0040] The support planning module is used for determining the support demand index in the time sequence based on the extreme weather period net load data and the total time sequence net load data, and planning the support of the new power system power supply.

[0041] Embodiment: The application provides a new (new energy) power system multi-dimensional support demand index evaluation method, which specifically comprises the following steps:

[0042] Step S1: obtaining system load data and new energy output data to determine the power system net load data;

[0043] Step S2: filtering extreme weather new energy continuous low output data according to the new energy output data, and determining an extreme weather time segment;

[0044] Step S3: determining the power support demand index, the electricity support demand index, the peak regulation support demand index and the climbing support demand index in the time sequence based on the extreme weather period net load data and the total time sequence net load data.

[0045] In step 1, the system load data and the new energy output data are obtained to determine the power system net load data, which comprises

[0046] The system load data P (t) and the corresponding time sequence new energy output data P (t) in a certain time sequence are obtained respectively. Load New

[0047] The power system net load is determined, and the calculation formula is as follows:

[0048] P​​Net (t) = P Load (t) - P New (t).

[0049] In step 2, extreme weather new energy continuous low output data is screened according to new energy output data, and the time segment where the extreme weather is located is determined, including:

[0050] The extreme weather new energy continuous low output model is as follows:

[0051]

[0052] In the formula, P represents the average output of the system new energy in the time segment t e t1, t2, P New，max represents the maximum value of the obtained new energy output data, λ represents the new energy low output boundary coefficient, and τ represents the new energy low output duration boundary. The obtained time segment t1, t2 is the time segment where the extreme weather is located.

[0053] In step 3, the power support demand index, the electricity support demand index, the peak regulation support demand index, and the climbing support demand index in the time sequence are determined based on the extreme weather period net load data and the total time sequence net load data, including:

[0054] The power support demand index calculation method is as follows:

[0055]

[0056] In the formula, P Sup,R,max represents the power support demand, K τ represents the period set of the time segment where the extreme weather is located;

[0057] The electricity support demand index calculation method is as follows:

[0058]

[0059] In the formula, E Sup,R,max represents the electricity support demand, K τ represents the period set of the time segment where the extreme weather is located;

[0060] The peak regulation support demand index calculation method is as follows:

[0061]

[0062] In the formula, R Net，peak，m represents the peak regulation capacity in the mth period, P Net，max，m and P Net，min，m respectively represent the maximum and minimum values of the net load in the mth period, P Net，peak，max represents the peak regulation support demand, and βNet，peak indicates the peak support demand coefficient.

[0063] The climbing support demand index is calculated as follows:

[0064]

[0065] In the formula, P Net，ramp (t k +1) indicates the net load change rate at the t k +1 moment, P Net，ramp，max indicates the climbing support demand, and β Net，ramp indicates the climbing support demand coefficient.

[0066] The application proposes the concept of support demand, and based on the extreme weather new energy low output identification technology, proposes a calculation method from the aspects of power and electricity support demand, peak demand and peak shaving demand, thereby providing a reference for new power system support power planning.

[0067] The application is described with reference to flowcharts and / or block diagrams of the method, device (system) and computer program product according to the embodiments of the application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a machine that realizes the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one flow or multiple flows and / or blocks Figure 1 The functions specified in one flow or multiple flows and / or blocks

[0068] In the description of the application, it should be understood that the terms "first", "second" are only used for the purpose of description, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the application, the meaning of "multiple" is two or more, unless otherwise specifically limited.

[0069] Obviously, those skilled in the art can make various modifications and variations to the application without departing from the spirit and scope of the application. Thus, if these modifications and variations of the application fall within the scope of the claims of the application and their equivalent technologies, the application also intends to include these modifications and variations.

Claims

1. A method for evaluating multi-dimensional supportability demand index of a power system, characterized in that, The method comprises the following steps: Step S1: Obtain system load data and new energy output data to determine the power system net load data situation; Comprising obtaining system load data P Load (t) within a certain time series respectively New (t) corresponding to the time series of new energy output data P Determine the power system net load situation, and the calculation formula is as follows: P Net (t) = P Load (t) - P New (t); Step S2: According to the new energy output data, screen the extreme weather new energy continuous low output data, and determine the time segment of the extreme weather; Comprising: The extreme weather new energy continuous low output model is as follows: In the formula R represents the average output of the new energy in the time slice t∈t1, t2, and R New，max R represents the maximum value of the obtained new energy output data, λ represents the low output boundary coefficient of the new energy, τ is the low output duration boundary of the new energy; the obtained time slice t1, t2 is the time slice where the extreme weather is located; Step S3: Based on the extreme weather period net load data and the total time sequence net load data, determine the power support demand index, the electricity support demand index, the peak shaving support demand index, and the climbing support demand index in the time sequence; comprising: The power support demand index calculation method is as follows: where P Sup,R,max represents the power support demand, K τ represents the time period set of the time slice where the extreme weather occurs; The electricity support demand index calculation method is as follows: In the formula, E Sup,R,max represents the power support demand; The peak shaving support demand index calculation method is as follows: where P Net，peak，m denotes the peak shaving capacity in the mth cycle, P Net，max，m and P Net，min，m denote the maximum and minimum values of the net load in the mth cycle, P Net，peak，max denotes the peak shaving support demand, β Net，peak denotes the peak shaving support demand coefficient; Based on the power support demand index, the electricity support demand index, the peak shaving support demand index, and the climbing support demand index, a power source multi-dimensional support index system is constructed to plan the support of the power system power source; The climbing support demand index calculation method is as follows: In the formula, P Net，ramp (t k +1) represents the net load rate at the t k +1 time, P Net，ramp，max represents the climbing support demand, and β Net，ramp represents the climbing support demand coefficient.

2. A power system multi-dimension supportability demand index evaluation system for implementing the power system multi-dimension supportability demand index evaluation method according to claim 1, characterized in that, Comprising: A data analysis module is configured to analyze the power system net load data situation based on the system load data and the new energy output data; A data processing module is configured to screen the extreme weather new energy continuous low output data according to the new energy output data based on the power system net load data situation, determine the time segment of the extreme weather, and obtain the extreme weather period net load data; A support planning module is configured to determine the support demand index in the time sequence based on the extreme weather period net load data and the total time sequence net load data, and plan the support of the power system power source.

Images