Bottom-up industrial user motivation type demand response potential assessment method and system

Abstract

The invention relates to the technical field of demand response potential assessment, and discloses a bottom-up industrial user motivation type demand response potential assessment method and system, and the method comprises the steps: determining an industrial user potential assessment region, and obtaining the load peak and valley time periods of the assessment region; carrying out dimension reduction clustering on the load data, and identifying a typical power utilization mode of the user; calculating a peak load coefficient of each industry sample user to obtain an average peak load coefficient of each industry; determining the typical interactive response load proportion of each industry, considering different load response characteristics, and evaluating the average peak clipping and valley filling potential of each industry; and calculating the total peak clipping and valley filling potential of each industry by considering the participation willingness and responsivity of the users, and evaluating the total response potential of the industrial users in the region through linear mapping. According to the method, the difference of power utilization characteristics of different industries in the industrial field is taken into consideration, data required for evaluation are easy to obtain, the method can be suitable for evaluation areas of all levels in a larger range, and the valley filling potential evaluation method is further provided for industrial users.

Description

Technical Field

[0001] The present invention relates to the technical field of demand response potential assessment, and in particular to a bottom-up industrial user incentive-type demand response potential assessment method and system. Background Art

[0002] As the proportion of renewable energy generation continues to grow, the new power system faces the problem of balancing supply and demand of multi-time scale flexibility and absorbing renewable energy. Relying solely on the construction of power sources and energy storage to deal with the uncertainty of renewable energy may excessively increase the cost of electricity. Starting from the demand side, tapping into flexibility resources and improving the flexible regulation capability of loads are necessary tasks for grid planning and operation regulation to cope with the large-scale development of new energy. As a high-power-consuming industry, industry is subject to strong control, large electricity consumption, and a high proportion of electricity costs. Users often have considerable adjustable potential and enthusiasm, and are the main force of current demand-side flexibility resources. Therefore, it is necessary to conduct potential assessment research on industrial users' participation in incentive-based demand response and tap the adjustable potential of industrial loads on a large scale.

[0003] At present, the research on the potential assessment of incentive demand response for industrial users of a certain scale is mainly based on the typical load curve of the users, from which the user response characteristics are extracted or the potential assessment results of a single user are obtained by time series simulation from the optimization perspective. By superimposing the assessment results of all users in the region, the adjustable potential of various industries to the entire industrial field is finally obtained. These methods have relatively high requirements on user load data, and the actual statistical workload is large. They are only applicable to areas with a small assessment range, such as the potential assessment of a distribution network area or a substation. In addition, a large number of studies mainly focus on exploring the peak shaving potential of industrial users, which cannot take into account the differences in electricity consumption characteristics and equipment response characteristics of different industries, and fail to explore the valley filling potential of load. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above existing problems, the present invention is proposed. Therefore, the present invention provides a bottom-up industrial user incentive demand response potential assessment method to solve the problem of how to solve the differences in power consumption characteristics and equipment response characteristics of different industries in a large area and tap the potential of load valley filling.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a bottom-up industrial user incentive demand response potential assessment method, comprising: determining an industrial user potential assessment area, obtaining historical load data of the industrial user, and obtaining load peak and valley periods in the assessment area;

[0008] Based on the historical load data of the industrial users, the load data is clustered by dimensionality reduction, the typical power consumption pattern of the users is identified, and the typical load curve of the users during the peak power consumption period is obtained;

[0009] Based on the typical load curve of users, the peak load factor of sample users in each industry is calculated to obtain the average peak load factor of each industry;

[0010] Based on the average peak load factor of each industry and questionnaire survey, determine the typical interactive response load proportion of each industry, take into account different load response characteristics, and evaluate the average peak shaving and valley filling potential of each industry;

[0011] Based on the average peak shaving and valley filling potential of each industry, taking into account the user's willingness to participate and responsiveness, the total peak shaving and valley filling potential of each industry is calculated, and the total response potential of industrial users in the region is evaluated by linear mapping.

[0012] As a preferred solution of the bottom-up industrial user incentive demand response potential assessment method of the present invention, the load peak and valley periods of the assessment area include:

[0013] Determine the assessment area for the evaluation of the potential of incentive-based demand response of industrial users, and classify the industrial users in the assessment area by industry based on statistical industry electricity consumption;

[0014] Obtain the annual load data of the assessment area, pre-process the load data, and filter out the peak and valley periods of the load in the area, including:

[0015] Analyze the peak load months in summer and winter, collect statistics on the load in the first X hours of the day with the highest load in the selected month, and obtain peak time information;

[0016] By counting the number of load hours in the assessment area that exceed 85% of the maximum load throughout the year and averaging them over 365 days throughout the year, the number of daily peak hours X is obtained;

[0017] Statistics are performed on the daily load data of the selected month to obtain the top X time values ​​t1, t2, ..., t X , determine X moments as the load peak periods of the selected month in the evaluation area;

[0018] Based on the division of valley time periods by the current time-of-use electricity price policies in various regions and the regional nighttime anti-peak load characteristics, the load valley period of the assessment area is determined.

[0019] As a preferred solution of the bottom-up industrial user incentive demand response potential assessment method of the present invention, the identifying of the typical electricity consumption pattern of the user includes:

[0020] The historical load data of industrial load in summer and winter months are used as sample sets, and the Calinski-Haeabasz index is selected to evaluate the number of clusters;

[0021] Determine the optimal number of clusters, and divide the sample set into k mutually non-overlapping clusters by using a K-means clustering algorithm to identify different power consumption patterns of users;

[0022] Eliminate the load curve of the cluster farthest from other clusters, take the average of the remaining k-1 load curves in the cluster, and obtain the typical load curve of users during the peak electricity consumption period in summer and winter.

[0023] As a preferred solution of the bottom-up industrial user incentive demand response potential assessment method of the present invention, wherein: the average peak load factor of each industry is obtained including:

[0024] The average peak load of the typical load curve of sample users in various industries during the peak load period is calculated and expressed as:

[0025]

[0026] Among them, P y,i,t represents the load of sample user i in industry y at time t, Ω res Indicates the load peak period, N res Indicates the number of periods during the load peak period;

[0027] Get the annual average load P of each sample user avg,y,i , expressed as:

[0028]

[0029] Among them, E y,i represents the total annual electricity consumption of sample user i in industry y;

[0030] Calculate the peak load factor of each sample user, sum and average the peak load factors of all sample users in the industry, and get the average peak load factor of each industry, expressed as:

[0031]

[0032] Among them, N s,y represents the number of sample users in industry y, p y,i Represents the peak load factor of each sample user.

[0033] As a preferred solution of the bottom-up industrial user incentive demand response potential assessment method of the present invention, the assessment of the average peak shaving and valley filling potential of each industry includes:

[0034] Based on the average peak load factor of each industry, the average peak load demand of each industry during the peak load period is calculated, which is expressed as:

[0035]

[0036] Among them, P max,y represents the peak load demand of each industry during the peak load period, P avg,y It represents the annual average load of each industry;

[0037] Design a load adjustable potential questionnaire for industrial users, and obtain data information including enterprise name, annual maximum load, annual total electricity consumption, production load proportion, and adjustable load response characteristics from the questionnaire of each sample user. The adjustable load response characteristics include equipment rated power, interactive response category, adjustable capacity proportion, preparation time, recovery time, and response duration;

[0038] According to the load interactive response category, the user's adjustable load is divided into shiftable, transferable and curtailable loads. According to the interactive response characteristics of different adjustable loads, the user's peak shaving and valley filling potential is obtained.

[0039] As a preferred solution of the bottom-up industrial user incentive demand response potential assessment method of the present invention, the method of obtaining the peak shaving and valley filling potential of the user includes:

[0040] Based on the average peak load demand of the industry Calculate the average peak shaving potential of the industry It is expressed as:

[0041]

[0042] Among them, α, γ, and β represent the proportion of load that can be translated, transferred, and reduced, respectively;

[0043] Based on the average peak-cutting potential of the industry, the average valley-filling potential of the industry is obtained It is expressed as:

[0044]

[0045] As a preferred solution of the bottom-up industrial user incentive demand response potential assessment method of the present invention, the total response potential of industrial users in the assessment area includes:

[0046] The response coefficient is introduced to evaluate the user's response, the number of registered industrial users participating in the grid response is obtained, the total peak-shaving potential and the total valley-filling potential of each industry are calculated, and the response potential evaluation results of each industry are obtained;

[0047] The total peak shaving potential of each industry P shave,y It is expressed as:

[0048]

[0049] Among them, N r,y represents the number of registered industrial users in each industry participating in the grid response, λ shift , trans , cut They represent the response willingness of loads that can be translated, transferred, and reduced, respectively;

[0050] The total valley-filling potential of the industry fill,y It is expressed as:

[0051]

[0052] The response potential assessment results of the above-mentioned industries are superimposed to obtain the total response potential of industrial users in the assessment area.

[0053] In a second aspect, the present invention provides a bottom-up industrial user incentive demand response potential assessment system, comprising:

[0054] An acquisition module is used to determine the potential assessment area of ​​industrial users, obtain the historical load data of industrial users, and obtain the load peak and valley periods of the assessment area;

[0055] An analysis module, based on the historical load data of the industrial user, performs dimensionality reduction clustering on the load data, identifies the typical power consumption pattern of the user, and obtains a typical load curve during the peak power consumption period of the user;

[0056] A calculation module is used to calculate the peak load factor of sample users in each industry based on the typical load curve of users, and obtain the average peak load factor of each industry;

[0057] An evaluation module is used to determine the typical interactive response load proportion of each industry based on the average peak load factor of each industry and a questionnaire survey, and to evaluate the average peak shaving and valley filling potential of each industry by taking into account different load response characteristics;

[0058] The output module is used to calculate the total peak shaving and valley filling potential of each industry based on the average peak shaving and valley filling potential of each industry, taking into account the user's willingness to participate and responsiveness, and linearly map and evaluate the total response potential of industrial users in the region.

[0059] In a third aspect, the present invention provides an electronic device, comprising:

[0060] Memory and processor;

[0061] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the bottom-up industrial user incentive demand response potential assessment method are implemented.

[0062] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the bottom-up industrial user incentive-based demand response potential assessment method.

[0063] Compared with the prior art, the present invention has the following beneficial effects: the present invention adopts a "bottom-up" framework and proposes a practical method for evaluating the incentive-based demand response potential of industrial users for power grid planning. The method takes into account the differences in electricity consumption characteristics of different industries in the industrial field, and the data required for evaluation are relatively easy to obtain. At the same time, the present invention can be applied to evaluation areas at various levels such as feeders, substations, provinces, and even larger ranges; the present invention designs a universal load adjustable potential questionnaire for industrial users in different industries. The questionnaire covers the necessary information required for evaluation calculations, and also provides certain data support for further research work such as power grid planning and scheduling strategy formulation; based on the information covered in the questionnaire, according to the interactive response characteristics of different adjustable loads, adjustable resources suitable for peak shaving or valley filling are extracted, and on the basis of the existing large-scale demand-side resource peak shaving potential evaluation method, a valley filling potential evaluation method is further proposed for industrial users. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0065] Figure 1 It is a schematic diagram of the overall process of a bottom-up industrial user incentive demand response potential assessment method according to an embodiment of the present invention;

[0066] Figure 2 A schematic diagram of a process flow of evaluating the total response potential of industrial users in a region in a bottom-up method for evaluating the potential of incentive-based demand response of industrial users according to an embodiment of the present invention;

[0067] Figure 3A frequency distribution diagram of load peak periods of a bottom-up industrial user incentive demand response potential assessment method according to an embodiment of the present invention;

[0068] Figure 4 Typical daily load curves of various industries in the bottom-up industrial user incentive demand response potential assessment method according to an embodiment of the present invention;

[0069] Figure 5 A schematic diagram of estimating the peak shaving and valley filling potential of typical industrial loads according to a bottom-up industrial user incentive demand response potential assessment method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0070] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0071] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0072] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0073] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0074] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0075] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0076] Example 1

[0077] Reference Figure 1-Figure 2 , which is an embodiment of the present invention, provides a bottom-up method for evaluating the potential of industrial user incentive demand response, such as Figure 1 ,include:

[0078] S101, determine the potential assessment area for industrial users, obtain historical load data of industrial users, and obtain load peak and valley periods in the assessment area.

[0079] Preferably, obtaining the load peak and valley periods of the evaluation area includes:

[0080] Determine the assessment area for the potential assessment of industrial users' incentive-based demand response, and classify the industrial users in the assessment area according to the statistical industry electricity consumption;

[0081] Obtain the annual load data of the assessment area, pre-process the load data, and filter out the peak and valley periods of the load in the area, including:

[0082] Analyze the peak load months in summer and winter, collect statistics on the load in the first X hours of the day with the highest load in the selected month, and obtain peak time information;

[0083] By statistically evaluating the number of load hours in the area that exceed 85% of the maximum load throughout the year, averaged over 365 days throughout the year, we can obtain the number of daily peak hours X;

[0084] Statistics are performed on the daily load data of the selected month to obtain the top X time values ​​t1, t2, ..., t X , determine X moments as the load peak periods of the selected month in the evaluation area;

[0085] Based on the division of valley periods by the current time-of-use electricity price policies in various regions and the regional nighttime anti-peak load characteristics, the load valley period in the assessment area is determined.

[0086] Specifically, the industrial users in the assessed area can be classified according to the “National Economic Industry Electricity Consumption Classification Standard” used by the power grid department to calculate industry electricity consumption, and the annual load data of the assessed area can be obtained from the relevant power grid departments.

[0087] Among them, peak load usually occurs in summer and winter, so we select July to September and November to January, the months when summer and winter peak load may occur, and statistically analyze the daily load data from July to September to obtain the top X time values ​​t1, t2, ..., t X , determine these X moments as the load peak period from July to September in the assessment area, and use the same method to determine the load peak period in winter from November to January; combined with the current time-of-use electricity price policy for valley period division in various places and the prominent "anti-peak regulation" characteristics of many regional systems at night, determine the load valley period of the assessment area as 0:00-7:00 at night.

[0088] S102, based on the historical load data of industrial users, reduce the dimension of the load data and cluster them, identify the typical power consumption pattern of the users, and obtain the typical load curve of the users during the peak power consumption period.

[0089] Preferably, identifying a user's typical electricity usage pattern includes:

[0090] The historical load data of industrial load in summer and winter months (July-September, November-January) are used as the sample set, and the Calinski-Haeabasz (CH) index is selected to evaluate the number of clusters;

[0091] Determine the optimal number of clusters and divide the sample set into k non-overlapping clusters using the K-means clustering algorithm to identify different power consumption patterns of users;

[0092] Eliminate the load curve of the cluster farthest from other clusters, take the average of the remaining k-1 load curves in the cluster, and obtain the typical load curve of users during the peak electricity consumption period in summer and winter.

[0093] S103, based on the typical load curve of users, calculate the peak load factor of sample users in each industry to obtain the average peak load factor of each industry.

[0094] For example, the average peak load of the typical load curve of sample users in each industry during the load peak period is statistically analyzed, and then the peak load factor of each sample user is calculated. The peak load factors of all sample users in the industry are summed and averaged to obtain the average peak load factor of each industry.

[0095] Preferably, obtaining the average peak load factor of each industry includes:

[0096] The average peak load of the typical load curve of sample users in various industries during the peak load period is calculated and expressed as:

[0097]

[0098] Among them, P y,i,t represents the load of sample user i in industry y at time t, Ω res Indicates the load peak period, N res Indicates the number of time periods during the load peak period;

[0099] Get the annual average load P of each sample user avg,y,i , expressed as:

[0100]

[0101] Among them, E y,i represents the total annual electricity consumption of sample user i in industry y, which can be obtained from the energy management system EMS of the sample user;

[0102] Calculate the peak load factor of each sample user, sum and average the peak load factors of all sample users in the industry, and get the average peak load factor of each industry, expressed as:

[0103]

[0104] Among them, N s,y represents the number of sample users in industry y, p y,i Represents the peak load factor of each sample user.

[0105] S104, such as Figure 2 Based on the average peak load factor of each industry and questionnaire survey, the typical interactive response load proportion of each industry is determined, and the average peak shaving and valley filling potential of each industry is evaluated by taking into account different load response characteristics.

[0106] Preferably, the average peak shaving and valley filling potential of each industry is evaluated, including:

[0107] Based on the average peak load factor of each industry obtained in S103, the average peak load demand of each industry during the peak load period is calculated, which is expressed as:

[0108]

[0109] Among them, P max,y represents the peak load demand of each industry during the peak load period, P avg,y It represents the annual average load of each industry;

[0110] Among them, according to the industry electricity consumption data collected by the power grid department, the annual average load P of each industry is first calculated. avg,y , expressed as:

[0111]

[0112] Among them, E y is the total annual electricity consumption of industry y.

[0113] Design a load adjustable potential questionnaire for industrial users, and obtain data information including enterprise name, annual maximum load, annual total electricity consumption, production load ratio and adjustable load response characteristics from the questionnaire of each sample user. The adjustable load response characteristics include equipment rated power, interactive response category, adjustable capacity ratio, preparation time, recovery time and response duration;

[0114] According to the load interactive response category, the user's adjustable load is divided into shiftable, transferable and curtailable loads. According to the interactive response characteristics of different adjustable loads, the user's peak shaving and valley filling potential is obtained.

[0115] Preferably, obtaining the peak shaving and valley filling potential of the user includes:

[0116] Based on the industry average peak load demand Calculate the average peak shaving potential of the industry It is expressed as:

[0117]

[0118] Among them, α, γ, and β represent the proportion of load that can be translated, transferred, and reduced, respectively;

[0119] Based on the industry average peak shaving potential, the industry average valley filling potential is obtained It is expressed as:

[0120]

[0121] It should be noted that for peak shaving, shiftable, transferable and reducible loads can all participate in the response accordingly during the load peak period to achieve the peak shaving effect; while for the load valley period, only shiftable and transferable loads can be moved in or transferred in from the peak electricity consumption period; combined with the typical interactive response load proportion of each industry obtained from the questionnaire, that is, the sum of the shiftable, transferable and reducible load proportions multiplied by the industry's average peak load demand can be used to calculate the industry's average peak shaving potential, among which the industry's average valley filling potential is approximately equal to the sum of the peak shaving potentials of the shiftable and transferable loads.

[0122] S105, based on the average peak shaving and valley filling potential of each industry, taking into account the user's willingness to participate and responsiveness, calculate the total peak shaving and valley filling potential of each industry, and linearly map and evaluate the total response potential of industrial users in the region.

[0123] It should be noted that for incentive-based demand response projects, not all users are eligible to participate, and not every eligible user will eventually participate in demand response; when calculating the total peak shaving and valley filling potential of each industry, the responsiveness coefficient is introduced on the basis of step S104 to evaluate the user's responsiveness; the number of registered industrial users participating in the grid response is obtained from the power grid department, and then the total response potential of industrial users in the region is evaluated by linear mapping.

[0124] Exemplarily, factors that affect the participation qualifications of each user in the industry and the response willingness of each user include:

[0125] 1) Demand response program design (participation procedures, response times and duration, economic incentives, and default rules);

[0126] 2) the cost-effectiveness of providing the supporting technologies needed for demand response (energy management systems or automated demand response systems);

[0127] 3) Market maturity and user groups’ familiarity and acceptance of demand response.

[0128] The above factors are independent of each other to some extent, yet coupled and complex with each other. When calculating the total peak shaving and valley filling potential of each industry, response coefficients are introduced on the basis of S104 to reflect the comprehensive impact of the above factors, that is, the total peak shaving potential of each industry.

[0129] Preferably, the total response potential of industrial users in the assessment area includes:

[0130] The response coefficient is introduced to evaluate the user's response, the number of registered industrial users participating in the grid response is obtained, the total peak-shaving potential and the total valley-filling potential of each industry are calculated, and the response potential evaluation results of each industry are obtained;

[0131] Total peak shaving potential of each industry P shave,y It is expressed as:

[0132]

[0133] Among them, N r,y represents the number of registered industrial users in each industry participating in the grid response, λ shift , trans , cut They represent the response willingness of loads that can be translated, transferred, and reduced, respectively;

[0134] Total potential of the industry to fill the valley fill,yIt is expressed as:

[0135]

[0136] The response potential assessment results of each industry are superimposed to obtain the total response potential of industrial users in the assessment area.

[0137] Specifically, the total peak shaving potential P ind,shave It is expressed as:

[0138]

[0139] Among them, N ind It is the industry classification number of industrial users in the assessment area in S1.

[0140] Total valley filling potential P ind,shave It is expressed as:

[0141]

[0142] It should be noted that the present invention adopts a "bottom-up" framework and proposes a practical method for evaluating the incentive-based demand response potential of industrial users for power grid planning. The method takes into account the differences in electricity consumption characteristics of different industries in the industrial field, and the data required for evaluation are relatively easy to obtain. At the same time, the present invention can be applied to evaluation areas at various levels such as feeders, substations, provinces, and even larger ranges. The present invention designs a universal load adjustable potential questionnaire for industrial users in different industries. The questionnaire covers the necessary information required for evaluation calculations, and also provides certain data support for further research work such as power grid planning and scheduling strategy formulation. Based on the information covered in the questionnaire, according to the interactive response characteristics of different adjustable loads, adjustable resources suitable for peak shaving or valley filling are extracted. On the basis of the existing large-scale demand-side resource peak shaving potential evaluation method, a valley filling potential evaluation method is further proposed for industrial users.

[0143] The above is a schematic scheme of a bottom-up industrial user incentive demand response potential assessment method of this embodiment. It should be noted that the technical scheme of the bottom-up industrial user incentive demand response potential assessment system and the technical scheme of the above-mentioned bottom-up industrial user incentive demand response potential assessment method belong to the same concept. The details of the technical scheme of the bottom-up industrial user incentive demand response potential assessment system in this embodiment that are not described in detail can all be referred to the description of the technical scheme of the above-mentioned bottom-up industrial user incentive demand response potential assessment method.

[0144] The bottom-up industrial user incentive demand response potential assessment system in this embodiment includes:

[0145] An acquisition module is used to determine the potential assessment area of ​​industrial users, obtain the historical load data of industrial users, and obtain the load peak and valley periods of the assessment area;

[0146] The analysis module reduces the dimension of load data and clusters it based on the historical load data of industrial users, identifies the typical power consumption patterns of users, and obtains the typical load curves during the peak power consumption period of users;

[0147] A calculation module is used to calculate the peak load factor of sample users in each industry based on the typical load curve of users, and obtain the average peak load factor of each industry;

[0148] The evaluation module is used to determine the proportion of typical interactive response loads in each industry based on the average peak load factor of each industry and questionnaire survey, and to evaluate the average peak shaving and valley filling potential of each industry by taking into account different load response characteristics;

[0149] The output module is used to calculate the total peak shaving and valley filling potential of each industry based on the average peak shaving and valley filling potential of each industry, taking into account the user's willingness to participate and responsiveness, and linearly map the total response potential of industrial users in the region.

[0150] This embodiment also provides an electronic device, which is applicable to the bottom-up evaluation of the potential of industrial user incentive demand response, and includes:

[0151] Memory and processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the bottom-up industrial user incentive demand response potential assessment method proposed in the above embodiment.

[0152] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the bottom-up industrial user incentive demand response potential assessment method proposed in the above embodiment is implemented.

[0153] The storage medium proposed in this embodiment and the bottom-up industrial user incentive demand response potential assessment method proposed in the above embodiment belong to the same inventive concept. The technical details not described in detail in this embodiment can be found in the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0154] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0155] Example 2

[0156] Reference Figure 3-Figure 5 Tables 1 to 3 are an embodiment of the present invention, which provides a bottom-up industrial user incentive demand response potential assessment method. In order to verify its beneficial effects, comparison results of two schemes are provided.

[0157] A certain province was taken as the evaluation area, and three typical industrial loads in the province were selected for example verification: electrolytic aluminum, cement, and monocrystalline silicon.

[0158] 1. Determine the evaluation period

[0159] According to the load data of July, August and September in the summer of 2023, the peak load period in summer is determined. In the historical load data of 2208 hours in summer, the load value exceeds 85% of the maximum load for 254 hours, an average of 2.76 hours per day. Therefore, 3 hours is selected as the peak load period. After data statistics, the frequency distribution of peak load at each time of the day is obtained, such as Figure 3 As shown, Figure 1 Among them, 10:00-11:00, 11:00-12:00, and 12:00-13:00 are the top three periods in terms of frequency of load peak periods. Therefore, it can be determined that these three periods are the peak-shaving potential evaluation time periods for industrial users, and the valley-filling potential evaluation period is 0:00-7:00 at night.

[0160] 2. Determine the typical daily load curve of each industry

[0161] The user's historical load data from July to September 2023 is used as the sample set. The Calinski-Haeabasz (CH) index is selected to evaluate the number of clusters. After determining the optimal number of clusters, the K-means clustering algorithm is used to divide the sample set into k non-intersecting clusters to identify the different power consumption patterns of users. Then, the load curve of the cluster farthest from other clusters is eliminated, and the load curves in the remaining k-1 clusters are averaged to obtain the typical load curve of the user during the peak period of summer power consumption. The clustering results of typical daily load curves of various industries are shown in the following figure. Figure 4 shown.

[0162] 3. Determine the average peak load factor and average peak load demand for each industry

[0163] According to the method of the present invention, the average peak load factor p of each industry is calculated avg,y , and then further calculate the average peak load demand of each industry The results are shown in Table 1.

[0164] Table 1 Industry average peak load factor and average peak load demand

[0165]

[0166] 4. Calculate the peak shaving / valley filling potential of each industry

[0167] (1) Determine the interactive response load proportion of each industry

[0168] The load adjustable potential questionnaire designed by the present invention is used to conduct a questionnaire survey on industrial users, and the electricity consumption process of typical high-energy-consuming industrial loads is comprehensively analyzed to obtain the interactive response load proportions of various industries as shown in Table 2 below.

[0169] Table 2 Proportion of interactive response load in each industry

[0170]

[0171] (2) Assuming the user response coefficients for three scenarios: high / medium / low user response willingness

[0172] Referring to the existing demand-side resource potential assessment research and experience, the user response coefficient is assumed to be as shown in Table 3.

[0173] Table 3 User response coefficients in various industries

[0174]

[0175]

[0176] (3) Calculate the peak shaving / valley filling potential of each industry

[0177] Based on the data in Tables 1 to 3, the peak shaving and valley filling potential of the three industries in 2023 can be roughly estimated according to the formula. The results are as follows: Figure 5 As shown. In the high responsiveness scenario, the three industries can provide 564MW of peak shaving potential and 521MW of valley filling potential, and the peak shaving potential accounts for 1.81% of the maximum load in the province in the previous year; in the medium responsiveness scenario, the three industries can provide 439MW of peak shaving potential and 406MW of valley filling potential, and the peak shaving potential accounts for 1.40% of the maximum load in the province in the previous year; in the low responsiveness scenario, the three industries can provide 314MW of peak shaving potential and 290MW of valley filling potential, and the peak shaving potential accounts for 1.00% of the maximum load in the province in the previous year.

[0178] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A bottom-up industrial user incentive demand response potential assessment method, characterized in that: include: Determine the potential assessment area for industrial users, obtain the historical load data of industrial users, and obtain the peak and valley periods of load in the assessment area; Based on the historical load data of the industrial users, the load data is clustered by dimensionality reduction, the typical power consumption pattern of the users is identified, and the typical load curve of the users during the peak power consumption period is obtained; Based on the typical load curve of users, the peak load factor of sample users in each industry is calculated to obtain the average peak load factor of each industry; Based on the average peak load factor of each industry and questionnaire survey, determine the typical interactive response load proportion of each industry, take into account different load response characteristics, and evaluate the average peak shaving and valley filling potential of each industry; Based on the average peak shaving and valley filling potential of each industry, taking into account the user's willingness to participate and responsiveness, the total peak shaving and valley filling potential of each industry is calculated, and the total response potential of industrial users in the region is evaluated by linear mapping.

2. The bottom-up industrial user incentive demand response potential assessment method according to claim 1, characterized in that: The load peak and valley periods of the evaluation area include: Determine the assessment area for the evaluation of the potential of incentive-based demand response of industrial users, and classify the industrial users in the assessment area by industry based on statistical industry electricity consumption; Obtain the annual load data of the assessment area, pre-process the load data, and filter out the peak and valley periods of the load in the area, including: Analyze the peak load months in summer and winter, collect statistics on the load in the first X hours of the day with the highest load in the selected month, and obtain peak time information; By counting the number of load hours in the assessment area that exceed 85% of the maximum load throughout the year and averaging them over 365 days throughout the year, the number of daily peak hours X is obtained; Statistics are performed on the daily load data of the selected month to obtain the top X time values ​​t1, t2, ..., t X , determine X moments as the load peak periods of the selected month in the evaluation area; Based on the division of valley time periods by the current time-of-use electricity price policies in various regions and the regional nighttime anti-peak load characteristics, the load valley period of the assessment area is determined.

3. The bottom-up industrial user incentive demand response potential assessment method according to claim 1 or 2, characterized in that: The identifying of the typical power usage pattern of the user comprises: The historical load data of industrial load in summer and winter months are used as sample sets, and the Calinski-Haeabasz index is selected to evaluate the number of clusters; Determine the optimal number of clusters, and divide the sample set into k mutually non-overlapping clusters by using a K-means clustering algorithm to identify different power consumption patterns of users; Eliminate the load curve of the cluster farthest from other clusters, take the average of the remaining k-1 load curves in the cluster, and obtain the typical load curve of users during the peak electricity consumption period in summer and winter.

4. The bottom-up industrial user incentive demand response potential assessment method according to claim 1, characterized in that: The average peak load factor of each industry includes: The average peak load of the typical load curve of sample users in various industries during the peak load period is calculated and expressed as: Among them, P y,i,t represents the load of sample user i in industry y at time t, Ω res Indicates the load peak period, N res Indicates the number of time periods during the load peak period; Get the annual average load P of each sample user avg,y,i , expressed as: Among them, E y,i represents the total annual electricity consumption of sample user i in industry y; Calculate the peak load factor of each sample user, sum and average the peak load factors of all sample users in the industry, and get the average peak load factor of each industry, expressed as: Among them, N s,y represents the number of sample users in industry y, p y,i Represents the peak load factor of each sample user.

5. The bottom-up industrial user incentive demand response potential assessment method according to claim 4, characterized in that: The average peak shaving and valley filling potential of each industry evaluated includes: Based on the average peak load factor of each industry, the average peak load demand of each industry during the peak load period is calculated, which is expressed as: Among them, P max,y represents the peak load demand of each industry during the peak load period, P avg,y It represents the annual average load of each industry; Design a load adjustable potential questionnaire for industrial users, and obtain data information including enterprise name, annual maximum load, annual total electricity consumption, production load proportion, and adjustable load response characteristics from the questionnaire of each sample user. The adjustable load response characteristics include equipment rated power, interactive response category, adjustable capacity proportion, preparation time, recovery time, and response duration; According to the load interactive response category, the user's adjustable load is divided into shiftable, transferable and curtailable loads. According to the interactive response characteristics of different adjustable loads, the user's peak shaving and valley filling potential is obtained.

6. The bottom-up industrial user incentive demand response potential assessment method according to claim 5, characterized in that: The peak-cutting and valley-filling potential of obtaining users includes: Based on the average peak load demand of the industry Calculate the average peak shaving potential of the industry It is expressed as: Among them, α, γ, and β represent the proportion of load that can be translated, transferred, and reduced, respectively; Based on the average peak-cutting potential of the industry, the average valley-filling potential of the industry is obtained It is expressed as:

7. The bottom-up industrial user incentive demand response potential assessment method according to claim 6, characterized in that: The total response potential of industrial users in the assessment area includes: The response coefficient is introduced to evaluate the user's response, the number of registered industrial users participating in the grid response is obtained, the total peak-shaving potential and the total valley-filling potential of each industry are calculated, and the response potential evaluation results of each industry are obtained; The total peak shaving potential of each industry P shave,y It is expressed as: Among them, N r,y represents the number of registered industrial users in each industry participating in the grid response, λ shift , trans , cut They represent the response willingness of loads that can be translated, transferred, and reduced, respectively; The total valley-filling potential of the industry fill,y It is expressed as: The response potential assessment results of the above-mentioned industries are superimposed to obtain the total response potential of industrial users in the assessment area.

8. A bottom-up industrial user incentive demand response potential assessment system, characterized in that: include, An acquisition module is used to determine the potential assessment area of ​​industrial users, obtain the historical load data of industrial users, and obtain the load peak and valley periods of the assessment area; An analysis module, based on the historical load data of the industrial user, performs dimensionality reduction clustering on the load data, identifies the typical power consumption pattern of the user, and obtains a typical load curve during the peak power consumption period of the user; A calculation module is used to calculate the peak load factor of sample users in each industry based on the typical load curve of users, and obtain the average peak load factor of each industry; An evaluation module is used to determine the typical interactive response load proportion of each industry based on the average peak load factor of each industry and a questionnaire survey, and to evaluate the average peak shaving and valley filling potential of each industry by taking into account different load response characteristics; The output module is used to calculate the total peak shaving and valley filling potential of each industry based on the average peak shaving and valley filling potential of each industry, taking into account the user's willingness to participate and responsiveness, and linearly map and evaluate the total response potential of industrial users in the region.

9. An electronic device, characterized in that: include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the bottom-up industrial user incentive demand response potential assessment method described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: It stores computer executable instructions, which, when executed by a processor, can implement the steps of the bottom-up industrial user incentive demand response potential assessment method as described in any one of claims 1 to 7.

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