A method for inter-grid load accommodation based on active distribution network

Abstract

The application discloses a kind of inter-grid load consumption methods based on active distribution network;According to the proportion of date-load and temperature-load, the proportion of load consumption estimation model is adjusted according to the proportion of load consumption estimation model;And according to the load consumption estimation model, preliminary distribution is carried out.According to the comparison between actual load consumption and load consumption estimation model, the control object is determined, and the load power adjustment of each functional area to the control object is determined according to the load comparison between the control objects, and the distribution quota is comprehensively considered to ensure the power consumption adjustment in the interval.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power distribution network, in particular to a grid-to-grid load consumption method based on active distribution network. BACKGROUND

[0002] With the peak of the whole society electricity load breaking records, the power grid peak shaving pressure is growing, in order to develop and construct the multi-high elastic power grid, it is urgent to develop more extensive demand response means. Because at present in the society, the technology development causes the electricity consumption to gradually rise, and in the electricity peak period, the electricity load of some areas is relatively rich, while the electricity load of some areas is seriously insufficient, at the same time, the traditional regulation method cannot consider the characteristics of different functional areas in the region to preliminarily regulate and predict the load power, resulting in complicated subsequent adjustment process and involving multiple complex mobilization, and the power load of school hospital and other power protection areas is also difficult to guarantee, so a load regulation method inside the interval considering various aspects is needed.

[0003] For example, a "microgrid control method of storage and distribution integration design" is disclosed in Chinese patent document, its publication number CN105529712B; it takes the energy storage array distributed in each microgrid as the core control object, realizes the automatic balance control of active and reactive power of the connected microgrid group, and its specific steps are: in the networking and grid-connected state, the energy management module calculates the exchange power set value and distributes it to each microgrid control module; each microgrid control module can independently maintain the power balance in the grid in the isolated grid state, and cooperates with the energy management module to realize the set value distribution of each distributed power generation unit in the networking and grid-connected state. The power is exchanged between the adjacent microgrids without external grid power support through the low-voltage and medium-voltage two-stage distribution network, which improves the microgrid operation reliability; the microgrid can migrate between various working conditions without power failure, automatically maintains the balance of power generation and power consumption, improves the power quality, and meets the safety power consumption requirements. The clean power generation resources such as wind and light are maximized, and the oil and electricity are minimized to reduce the pollution to the environment. However, the distribution of the invention is achieved by intercommunication control between double microgrids to exchange power, which is difficult to consider and improve the internal environment of the microgrid, so it is not suitable for load consumption adjustment in any divided interval. SUMMARY

[0004] The present application mainly aims at the problem that the load distribution in the interval is difficult to be comprehensively considered in the prior art; a grid-to-grid load consumption method based on active distribution network is provided; the proportion comparison between date-load and temperature-load is divided according to the quarterly load growth data, the load consumption estimation model is adjusted according to the proportion, and the initial distribution is carried out according to the load consumption estimation model. The control object is determined according to the comparison between the actual load consumption and the load consumption estimation model, the load power adjustment of the control object by each functional area is determined according to the load comparison between the control objects, the distribution amount is comprehensively considered, and the load consumption adjustment inside the interval is ensured.

[0005] The application divides the proportion comparison between date-load and temperature-load according to the quarter-to-quarter load growth data, adjusts the load consumption estimation model according to the proportion, and performs initial allocation according to the load consumption estimation model.

[0006] The application determines the control object according to the comparison between the actual load consumption and the load consumption estimation model, determines the load power adjustment of each functional area to the control object according to the load comparison between the control objects, comprehensively considers the allocation amount, and ensures the power consumption adjustment in the internal area.

[0007] The above technical problems of the application are mainly solved by the following technical scheme:

[0008] A grid-to-grid load consumption method based on active distribution network, comprising:

[0009] S1, obtaining the topology graph of the active distribution network and dividing the active area; collecting historical load data through a carrier chip and establishing a load consumption estimation model in the active area according to the historical load data; and performing initial power allocation in the active area according to the load consumption estimation model;

[0010] S2, obtaining the real-time power load of each grid area;

[0011] S3, redistributing the load of each functional area in the active area according to the real-time power load;

[0012] S4, collecting the load consumption information of the redistribution day; adjusting the proportion of the load consumption data of the day, and re-planning the next day initial allocation.

[0013] The application divides the proportion comparison between date-load and temperature-load according to the quarter-to-quarter load growth data, adjusts the load consumption estimation model according to the proportion, and performs initial allocation according to the load consumption estimation model. The application determines the control object according to the comparison between the actual load consumption and the load consumption estimation model, determines the load power adjustment of each functional area to the control object according to the load comparison between the control objects, comprehensively considers the allocation amount, and ensures the power consumption adjustment in the internal area.

[0014] As a preferred, the establishment method of the load consumption estimation model is as follows:

[0015] S21: standardizing the load change data of each area in the active distribution network;

[0016] S22: establishing a date-load change curve model and a temperature-load change curve model according to the historical load data;

[0017] S23: comparing the quarter-to-quarter load consumption growth data to adjust the weight value of the date-load change curve model;

[0018] S24: The date-load change curve model and the temperature-load change curve model are weighted and averaged to form a load consumption prediction model.

[0019] The load consumption prediction in the recent period is relatively accurate, that is, the load consumption at each temperature is compared with the load consumption in the same period of the previous year; and the temperature has a greater impact on the load consumption, but the consumption data of the same season in different years still has a certain influence on the load consumption of the current season, so the comparison of the season-on-season comparison can determine whether there is a large change in the load consumption in the current year, thereby affecting the weight proportion of the date-load.

[0020] As a preferred, the standardization process is:

[0021]

[0022] wherein, is the standardized daily load of each functional area load; α i is the standardization coefficient of each functional area load; Q i is the total amount of each functional area load.

[0023] Since the proportion of load consumption in different areas is different, and the load of factories, commercial areas, etc. is almost tens or hundreds of times different from that of schools, residential areas, etc., it is necessary to weight the load of different areas to ensure that the load curves of each data can be displayed on the same coordinate axis.

[0024] As a preferred, the date-load change curve model and the temperature-load change curve model are obtained according to the following steps: S41, obtaining the historical data of the standardized daily load change of the functional area in the past three years and the historical data of the standardized daily load change of the functional area in the past seven days through power carrier communication;

[0025] S42, fitting the date corresponding to the daily load change of the user to form a date-load change curve of different years respectively; fitting the daily load change corresponding to the temperature to form a seven-day temperature-load change curve;

[0026] S43, weighting the years, the sum of the weights of each year is 1, and the weight of the larger year is higher, the date-load change curves of each year are weighted and superimposed to obtain the date-load change curve model;

[0027] S44, the seven-day temperature-load change curve is weighted and averaged, and the process of weighted and averaged is as follows:

[0028]

[0029] wherein, is the average load amount, and a1, a2, a3, a4, a5, a6, and a7 are weighting coefficients from the first day to the seventh day of seven days; the sum of a1, a2, a3, a4, a5, a6, and a7 is 1; Q T1 , Q T2 , Q T3 , Q T4 , Q T5 , Q T6 , Q T7 is the temperature-load change data from the first day to the seventh day of seven days; wherein,

[0030] a1

[0031] The temperature-load change curve obtained after weighted average is the temperature-load change curve model.

[0032] Statistical data of the same period in previous years show that the data of similar years have more representative significance and higher weight coefficients when weighted average is performed on the data in the past three years, because the weather changes of similar years are similar. A data model is obtained by statistically analyzing the temperature-load change in the past three years, which is convenient for obtaining the predicted load change curve. Since the change in temperature is not sudden but a gradual and continuous process, the data in the past seven days are statistically compared, and a weight coefficient is added to the load change of each day. The closer to the current day, the higher the weight coefficient.

[0033] As a preferred embodiment, the weight calculation method of the date-load change curve model is as follows:

[0034] S51, real-time load data of each functional area in the active area is comprehensively measured and calculated:

[0035]

[0036] wherein, P Qi is the real-time load data of the i-th functional area;

[0037] P aj is the real-time load state data of the j-th energy router accessed in the functional area;

[0038] n is the total number of energy routers accessed in the functional area;

[0039] S52, the real-time load data of the functional area and the historical same-season average load data are subtracted to obtain a load difference value;

[0040] S53, if the load difference value compared to the historical same season average load data increases by more than 5%, reduce the date-load change curve weight proportion; if the load difference value compared to the historical same season average load data does not increase by more than 5%, increase the date-load change curve weight proportion.

[0041] Although the same period every year is related to the weather, the specific situation is not definite. Therefore, it is necessary to judge whether the previous year has similar weather conditions and load change state as this year by using the year-on-year growth data of the same season, if the similarity is large, the load change of the previous year needs to have a large proportion in the load estimation of this year, otherwise the date-load proportion needs to be adjusted.

[0042] As a preferred, the step of load initial allocation is as follows:

[0043] S61: calculate the daily load consumption of each functional area according to the load consumption estimation model;

[0044] S62: allocate power to the power protection area first; allocate load power to other areas according to the proportion of daily load consumption.

[0045] As a preferred, the load reallocation process is as follows:

[0046] S71: compare the load consumption estimation model; take the load before and after the peak value as 80% of the peak value load, and the corresponding time period between them as the adjustable time period;

[0047] S72: in the adjustable time period, when the actual daily use load exceeds the predicted daily average load, the functional area is selected as the control object;

[0048] S73, judge the power protection level of the functional area; if the power protection level is higher than the functional area, it does not participate in load reallocation; if the power protection level is lower than the functional area, it is allocated according to the power protection level weighted ratio;

[0049] S74, analyze the energy storage capacity in the grid area participating in this load reallocation; determine the reallocated load capacity according to the energy storage capacity and reallocate the functional area.

[0050] Because the electricity load is related to the near environment, and the environment generally does not change greatly within a few days, it is necessary to consider the historical load consumption data of the recent period to allocate the electricity initially. The power protection area is the priority allocation area.

[0051] As a preferred, the power protection level: hospital > school > factory > commercial area = residential area > other places, the power protection level of the area is divided according to the importance of the area, which is also helpful for the reallocation of the control object of each functional area.

[0052] As a preferred option, the redistribution capacity allocation is as follows:

[0053] S91. Collect load consumption information of each functional area within the active zone; assuming the number of functional areas participating in the allocation is N;

[0054] S92. The allocation of each functional area shall be made according to the following formula:

[0055]

[0056] Where Q is the required load of this functional area; λ1, λ2, λ3, λ4, λ5, and λ6 are the load weighting coefficients for factories, commercial areas, residential areas, schools, hospitals, and other locations, respectively.

[0057] a1, a2, a3, a4, a5, and a6 represent the percentage of remaining load to initial allocated load for factories, commercial areas, residential areas, schools, hospitals, and other locations, respectively.

[0058] Q1, Q2, Q3, Q4, Q5, Q i These are the load values ​​for factories, commercial areas, residential areas, schools, hospitals, and other locations, respectively.

[0059] Where λ j a j Q j The charge is redistributed to each grid interval; j takes values ​​from 1 to N.

[0060] The grid load power is allocated according to the conditions of different grid intervals. The surplus intervals need to provide power to the outside, so the power needs to be adjusted accordingly.

[0061] As a preferred option, during the redistribution process, λ5 < λ4 < λ1 < λ2 = λ3 < λ6. When distributing power externally, the power protection zone needs to retain as much of its own power as possible; therefore, the power protection zone needs to reduce the amount of power distributed externally according to the power protection level.

[0062] The beneficial effects of this invention are:

[0063] According to the proportion comparison between the date-load and the temperature-load according to the quarterly load growth data, the load consumption estimation model is adjusted according to the proportion, and the initial allocation is carried out according to the load consumption estimation model. According to the comparison between the actual load consumption and the load consumption estimation model, the control object is determined, and the load power adjustment of each functional area to the control object is determined according to the load comparison between the control objects, and the allocation amount is comprehensively considered to ensure the power consumption adjustment in the internal area. BRIEF DESCRIPTION OF DRAWINGS

[0064] Figure 1 The method flowchart adopted by the present application. DETAILED DESCRIPTION

[0065] It should be understood that the embodiments are only used to illustrate the present application and not to limit the scope of the present application. In addition, it should be understood that after reading the content taught by the present application, those skilled in the art can make various modifications or modifications to the present application, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0066] The technical solutions of the present application are further specifically described below through examples.

[0067] A kind of active distribution network based on inter-grid load consumption method, comprising:

[0068] I, obtain the topological graph of active distribution network, and divide active interval;Through carrier chip, historical load data is collected, and load consumption estimation model in active interval is established according to historical load data;According to the load consumption estimation model, the power of the active interval is initially allocated.

[0069] Wherein, the establishment of load consumption estimation model needs:

[0070] Step S1, first, the load change data of each interval in active distribution network is standardized; Wherein, is the daily load of each functional area after standardization;α i is the standardization coefficient of each functional area load;Q i is the total amount of each functional area load.

[0071] Step S2, establishing a date-load change curve model and a temperature-load change curve model according to historical load data: obtaining historical data of standardized daily load change of the functional area in the past three years and historical data of standardized daily load change of the functional area in the past seven days through power carrier communication; fitting the date corresponding to the daily load change of the user to form a date-load change curve of different years respectively; fitting the daily load change corresponding to the temperature to form a seven-day temperature-load change curve respectively; weighting the years, the weight of each year is added to 1, and the weight of the older year is higher, and the date-load change curves of each year are weighted and superimposed to obtain the date-load change curve model; the temperature-load change curves of the seven days are weighted and averaged, and the temperature-load change curve obtained after the weighted average is the temperature-load change curve model.

[0072] S3: Adjust the weight value of the date-load change curve model by comparing the quarter load consumption growth data: comprehensive measurement of real-time load data of each functional area in the active area: Wherein, P Qi is the real-time load data of the i th functional area; P aj is the real-time load state data of the j th energy router accessed in the functional area; n is the total number of energy routers accessed in the functional area; the difference between the real-time load data and the historical same quarter average load data is obtained; if the load difference value compared with the net value of the same quarter average load data exceeds 5%, the weight proportion of the date-load change curve is reduced; if the load difference value compared with the net value of the same quarter average load data does not exceed 5%, the weight proportion of the date-load change curve is increased.

[0073] S4: Weighted average processing of date-load change curve model and temperature-load change curve model to form load consumption estimation model.

[0074] After determining the load consumption estimation model, the daily load consumption of each functional area is calculated according to the load consumption estimation model; the power protection area is preferentially allocated; the load power of each area is allocated according to the proportion of daily load consumption.

[0075] Two, real-time acquisition of electricity load of each grid area.

[0076] Three, according to the real-time electricity load, the load of each functional area in the active area is redistributed.

[0077] Compare the load consumption estimation model; take the load of 80% of the peak load before and after the peak point as the point, and the corresponding time period as the adjustable time period; in the adjustable time period, when the actual daily load exceeds the predicted daily load, the functional area is selected as the control object.

[0078] The power protection level of the functional area is determined, and if the power protection level is higher than the functional area, the load redistribution is not involved, and if the power protection level is lower than the functional area, the power protection level is weighted and proportioned;

[0079] The energy storage capacity in the grid area participating in the load redistribution is analyzed, and the redistribution load capacity is determined according to the energy storage capacity and the functional area is redistributed.

[0080] The distribution amount of each functional area is allocated according to the following formula:

[0081]

[0082] Wherein, the number of functional areas participating in distribution is N; Q is the required load amount of the functional area; λ1, λ2, λ3, λ4, λ5 and λ6 are respectively the factory load weighting coefficient, the commercial area load weighting coefficient, the residential area load weighting coefficient, the school load weighting coefficient, the hospital load weighting coefficient and the other place load weighting coefficient; a1, a2, a3, a4, a5 and a6 are respectively the proportion of the remaining load amount of the factory to the initial distribution load amount of the factory, the proportion of the remaining load amount of the commercial area to the initial distribution load amount of the commercial area, the proportion of the remaining load amount of the residential area to the initial distribution load amount of the residential area, the proportion of the remaining load amount of the school to the initial distribution load amount of the school, the proportion of the remaining load amount of the hospital to the initial distribution load amount of the hospital and the proportion of the remaining load amount of the other place to the initial distribution load amount of the other place; Q1, Q2, Q3, Q4, Q5 and Q6 are respectively the factory load amount, the commercial area load amount, the residential area load amount, the school load amount, the hospital load amount and the load amount of the i-th other place; wherein λ1<λ2=λ3<λ4<λ5<λ6. i j j j Q is the redistribution load amount of each grid area; j takes the value of 1 to N; λ5<λ4<λ1<λ2=λ3<λ6.

[0083] Four, collect the load consumption information on the redistribution day; adjust the proportion of the load consumption data on the day, and re-plan the next day initial distribution.​​​

Claims

1. An active distribution network-based inter-grid load accommodation method, characterized in that, The method comprises: S1, acquiring a topology graph of an active power distribution network, and dividing an active interval; collecting historical load data through a carrier chip and establishing a load consumption estimation model in the active interval according to the historical load data, including a date-load change curve model and a temperature-load change curve model; and performing initial power distribution in the active interval according to the load consumption estimation model; S2, acquiring real-time power consumption load of each grid interval; The S2 comprises: standardizing load change data of each interval in the active power distribution network, establishing a date-load change curve model and a temperature-load change curve model according to historical load data, adjusting the weight value of the date-load change curve model by comparing the quarterly load consumption growth data, and performing weighted average processing on the date-load change curve model and the temperature-load change curve model to form a load consumption estimation model; S3, performing load redistribution of each functional area in the active interval according to the real-time power consumption load; S4, collecting load consumption information on the day of redistribution; adjusting the proportion of load consumption data on the day, and re-planning the next day initial distribution.

2. The active distribution network-based inter-grid load accommodation method according to claim 1, characterized in that: The standardization process is as follows: Wherein, is the standardized daily load of each functional area; a i is the standardized coefficient of each functional area load; Q i is the total load of each functional area.

3. The active distribution network-based inter-grid load accommodation method according to claim 1, characterized in that: The date-load change curve model and the temperature-load change curve model are obtained according to the following steps: S41, obtaining historical data of standardized daily average load change of the functional area in the past three years and historical data of standardized daily average load change of the functional area in the past seven days through power carrier communication; S42, fitting the date-load change curve of different years respectively according to the date corresponding to the daily average load change of the user; and fitting the seven-day temperature-load change curve according to the daily average load change corresponding to the temperature; S43, weighting the years, the sum of the weights of each year is 1, and the weight increases with the year; the date-load change curves of each year are weighted and superimposed to obtain the date-load change curve model; S44, weighted average of the seven-day temperature-load change curve, the process is as follows: wherein, is the average load amount, a1, a2, a3, a4, a5, a6, a7 are weighting coefficients from the first day to the seventh day of seven days; the sum of a1, a2, a3, a4, a5, a6, a7 is 1; Q T1 , Q T2 , Q T3 , Q T4 , Q T5 , Q T6 , Q T7 is the temperature-load change data from the first day to the seventh day of seven days; wherein, α1＜α2＜α3＜α4＜α5＜α6＜α7； The temperature-load change curve obtained after weighted average is the temperature-load change curve model.

4. The active distribution network based inter-grid load accommodation method of claim 1, wherein, The weight calculation method of the date-load change curve model is as follows: S51, comprehensive measurement of real-time load data of each functional area in the active interval: P Qi is the real-time load data of the i-th functional area; P aj real-time load status data of the jth energy router accessed in the functional area; n is the total number of energy routers connected in the functional area; S52, the real-time load data of the functional area and the historical average load data of the same season are subtracted to obtain the load difference value; S53, if the load difference value compared with the net value of the same season average load data exceeds 5%, the weight proportion of the date-load change curve is reduced; if the load difference value compared with the net value of the same season average load data does not exceed 5%, the weight proportion of the date-load change curve is increased.

5. The active distribution network based inter-grid load accommodation method according to claim 1, characterized in that, The steps of the initial load distribution are as follows: S61: calculating the daily load consumption of each functional area according to the load consumption estimation model; S62: preferentially distributing power to the power protection area; and distributing load power to other areas according to the proportion of daily load consumption.

6. The active distribution network based inter-grid load accommodation method of claim 1, wherein, The load redistribution process is as follows: S71: comparing the load consumption estimation model; taking the point 80% of the peak load before and after the peak value as the point, and the corresponding time period as the adjustable time period; S72: In the adjustable time period, when the actual daily use load exceeds the daily predicted average load, the function area is selected as the control object; S73, determine the power protection level of the function area; if the power protection level is higher than the function area, it does not participate in load redistribution; if the power protection level is lower than the function area, it is weighted and proportioned according to the power protection level; S74, analyze the energy storage capacity in the grid area participating in this load redistribution; determine the redistribution load capacity according to the energy storage capacity and redistribute the function area.

7. The active network reconfiguration-based inter-grid load accommodation method according to claim 6, characterized in that, The power protection level: hospital > school > factory > commercial area = residential area > other places.

8. The active distribution network based inter-grid load accommodation method of claim 1, wherein, The redistribution capacity proportioning is as follows: S91, collect the load consumption information of each function area in the active area; set the number of function areas participating in distribution as N; S92, the distribution amount of each function area is allocated according to the following formula: Wherein, Q is the required load of the function area; λ1, λ2, λ3, λ4, λ5, λ6 are factory load weighting coefficient, commercial district load weighting coefficient, residential area load weighting coefficient, school load weighting coefficient, hospital load weighting coefficient and other place load weighting coefficient respectively; a1, a2, a3, a4, a5, a6 are factory residual load and factory initial allocation load proportion, commercial district residual load and commercial district initial allocation load proportion, residential area residual load and residential area initial allocation load proportion, school residual load and school initial allocation load proportion, hospital residual load and hospital initial allocation load proportion, and other place residual load and other place initial allocation load proportion respectively; Q1, Q2, Q3, Q4, Q5, Q i respectively, a factory load, a commercial district load, a residential district load, a school load, a hospital load, and an i-th other place load; where λ j a j Q j redistributes the charge amount for each grid interval; j takes values from 1 to N.

9. The active distribution network based inter-grid load accommodation method of claim 1, wherein, In the redistribution process, λ5< λ4< λ1< λ2= λ3< λ6, wherein λ1, λ2, λ3, λ4, λ5, λ6 are factory load weighting coefficient, commercial district load weighting coefficient, residential area load weighting coefficient, school load weighting coefficient, hospital load weighting coefficient and other place load weighting coefficient respectively.

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