A big data analysis system and method for power grid planning

Abstract

The present invention discloses an analysis system and method for big data for power grid planning, which belongs to the technical field of power grid planning. The system includes a data acquisition module, a data analysis module, a power consumption management module and a notification and warning module; the data acquisition module is used to collect meteorological information, power information and account information; the data analysis module is used to predict the power consumption speed of each account in the future period, and judge whether the power consumption speed in each time period exceeds the power supply speed, and if it exceeds, record the time period; the power consumption management module is used to adjust the total power consumption speed of all accounts in the recorded time period, limit the power consumption time or stop the power consumption of some accounts, so that the power consumption speed in each time period does not exceed the power supply speed; the notification and warning module is used to notify and warn the accounts that need to be adjusted; when power resources are scarce, the present invention realizes smoothing of power load, reduces the gap between power supply and demand, and reduces the risk of power outages by controlling the power consumption speed.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid planning, and in particular to a big data analysis system and method for power grid planning. Background Art

[0002] The balance between electricity supply and demand refers to the balance between electricity supply and electricity demand, that is, the power supply can meet the electricity demand. In the case of power shortage, the role of power supply and demand balance is particularly important. If the supply and demand balance is not effectively managed, it may lead to unstable power supply, power outages, power failures and other problems. Through effective supply and demand balance measures, the instability of power supply can be avoided as much as possible to ensure the continuous supply of electricity.

[0003] At present, when power resources are scarce, the main methods to achieve a balance between power supply and demand are flexible electricity price mechanisms and power outage restrictions. The flexible electricity price mechanism analyzes historical power consumption data, conducts time-of-day pricing, and guides users to use electricity at an average speed in each time period. The power outage restriction mechanism analyzes historical power consumption data, limits the power consumption time of some users or stops the power consumption, so that the average power consumption speed in each time period. The above two methods can achieve a good balance between power supply and demand, but they are not detailed enough in the specific implementation process. For example: 1. In terms of predicting power consumption speed, it mainly relies on historical power consumption data, and lacks consideration of changes in power consumption speed caused by external factors; 2. The selection of objects for limiting power consumption time or stopping power consumption is relatively vague, and it is impossible to reasonably select the objects for limiting power consumption time and the objects for stopping power consumption according to the actual situation; 3. The setting of power consumption time and power outage time is not accurate enough, and it is impossible to reasonably set it according to the actual situation of the object, and there is a lack of factual basis; these problems need to be solved urgently. Summary of the invention

[0004] The purpose of the present invention is to provide a big data analysis system and method for power grid planning to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a big data analysis system for power grid planning, the system comprising a data acquisition module, a data analysis module, a power consumption management module and a notification and warning module.

[0006] The data acquisition module is used to collect meteorological information, power information and account information; the data analysis module is used to analyze meteorological information and power information to calculate the predicted power consumption speed of each account, and determine whether the total predicted power consumption speed of all accounts in each time period exceeds the future power supply speed corresponding to the time period. If it exceeds, the corresponding time period is recorded; the power consumption management module is used to adjust the total predicted power consumption speed of the recorded time period, and by analyzing the account information, the power consumption time of some accounts is restricted or the power consumption is stopped, so that the total predicted power consumption speed of each time period does not exceed the future power supply speed corresponding to the time period; the notification and warning module is used to notify and warn the accounts that need to be adjusted.

[0007] Furthermore, the data collection module includes a meteorological information collection unit, a power information collection unit and an account information collection unit.

[0008] The meteorological information collection unit is used to collect meteorological information within the power consumption range, and the meteorological information includes historical temperature and future temperature.

[0009] The power information collection unit is used to collect power information within the power consumption range, the power information including future power supply speed, historical power consumption speed of each account and historical power consumption time period;

[0010] The historical temperature, the historical electricity consumption speed of each account and the historical electricity consumption time period are collected from the records saved by the system, and the future temperature is collected from the weather forecast issued by the Meteorological Bureau. The historical temperature refers to the temperature change information in the past time, the historical electricity consumption speed refers to the change information of the electricity consumption speed of the corresponding account in the past time, and the historical electricity consumption time period refers to the time period information of the daily electricity consumption of the corresponding account in the past time;

[0011] The future power supply speed is obtained from the power generation end, specifically, the change value of the power supply speed over time in the future period of time;

[0012] The account information collection unit is used to collect information of all accounts within the electricity usage range, the account information includes account type and electricity usage priority, and the account type includes production electricity and living electricity.

[0013] An account refers to an electricity usage account. Each electricity usage account has its own historical data, including historical electricity usage speed and historical electricity usage time period. The electricity usage priority of an account represents the degree of dependence of the account on electricity. The higher the dependence, the higher the electricity usage priority.

[0014] There is no electricity usage priority and historical electricity usage time period for household electricity usage accounts, but there is electricity usage priority and historical electricity usage time period for production electricity usage accounts. The electricity usage priority refers to the priority level of electricity resource allocation.

[0015] Furthermore, the data analysis module includes a power consumption prediction unit and a power consumption judgment unit. The power consumption prediction unit is used to calculate the predicted power consumption speed of each account within the predicted duration, and the power consumption judgment unit is used to judge whether the total predicted power consumption speed of each time period within the predicted duration is greater than the future power supply speed corresponding to the time period.

[0016] Furthermore, the calculation of the predicted power consumption speed of each account within the predicted duration specifically includes:

[0017] First, the historical electricity consumption speed of each account and the historical temperature of the corresponding time period are obtained. After preprocessing these data, the historical temperature and historical electricity consumption speed in the same time period are associated, and the associated data in each account are fitted with a logarithmic function to obtain the relationship formula between temperature and electricity consumption speed. Each account corresponds to a relationship formula; secondly, the prediction duration is divided into X time periods, and all time periods are matched with the historical electricity consumption time periods of each account of production type. When the time period intersects with the historical electricity consumption time period, the match is successful. The successfully matched time period is used as the electricity consumption time period of the corresponding account. Accounts of the type of household electricity consumption do not need to be matched, and the electricity consumption time period is all time periods; finally, the future temperature corresponding to the electricity consumption time period of each account is obtained, and substituted into the relationship formula corresponding to each account, and the predicted electricity consumption speed of each account in the corresponding electricity consumption time period is calculated.

[0018] To ensure the accuracy of subsequent calculation results, the prediction duration should be set reasonably, longer than the normal production power consumption time, and less than or equal to the farthest time of temperature prediction in the meteorological information. The split time periods should also be reasonable, with each time period having the same length, less than the normal production power consumption time, and longer than the temperature change interval in the meteorological information.

[0019] Furthermore, it is determined whether the total predicted electricity consumption speed of each time period within the predicted duration is greater than the future power supply speed corresponding to the time period, specifically including: summing the predicted electricity consumption speed of each account in each time period to obtain the total predicted electricity consumption speed corresponding to the time period, and determining whether the total predicted electricity consumption speed of each time period is greater than the future power supply speed corresponding to the time period. If the result is no, no processing is performed; if the result is yes, the predicted electricity consumption speeds of all accounts of the type of household electricity consumption in the time period are continued to be summed to determine whether they are still greater than the future power supply speed corresponding to the time period. If the result is no, the time period is marked as adjustment; if the result is yes, the corresponding time period is marked as household power restriction, and all accounts of the type of production electricity consumption in the time period are marked as production adjustment.

[0020] Furthermore, the power usage management module includes a power usage time adjustment unit, which is used to adjust the power usage time of the account, specifically including:

[0021] First, the accounts of type production power consumption in the time period marked as adjustment are extracted in order of power consumption priority from low to high, and marked as production adjustment, until the total predicted power consumption speed of all time periods marked as adjustment is not greater than the future power supply speed. Then, all accounts marked as production adjustment are placed in other time periods in order of power consumption priority from high to low. If the total predicted power consumption speed of other time periods does not exceed the future power supply speed and the sum of the consecutive time periods is not less than the predicted power consumption duration of the account, the account is marked as production power restriction, and the earliest time period in the consecutive time period is automatically selected as the power consumption time period of the account; otherwise, the account is marked as production power outage.

[0022] Furthermore, the notification and warning module includes a power limit notification unit and a power outage notification unit.

[0023] The power restriction notification unit is used to issue power restriction notifications to accounts of the type of household electricity use in the time period marked as household power restriction, and limit the total predicted power consumption speed of accounts of the type of household electricity use in this time period to no more than the future power supply speed corresponding to this time period. Power restriction notifications are issued to accounts marked as production power restriction, and the accounts are restricted to use electricity only in the corresponding power consumption time period; power restriction measures are different for different types of accounts, and for accounts of household electricity use, the total predicted power consumption speed in the corresponding time period is only limited to no more than the future power supply speed corresponding to this time period. The specific measures are whether to cut off power to some accounts or limit the power consumption speed of all accounts, which is manually determined. For accounts of production electricity use, their power consumption time is restricted, and there is no restriction on the duration of power consumption.

[0024] The power outage notification unit is used to issue a power outage notification to the account marked as a production power outage, so as to prevent the account from using electricity within the predicted duration.

[0025] A method for analyzing big data for power grid planning, the method comprising the following steps:

[0026] S1. Collect weather information, electricity information and account information;

[0027] S2, analyzing the information collected in step S1 to predict the power consumption rate of the account;

[0028] S3, determining whether the total predicted power consumption speed is greater than the power supply speed within the predicted time period;

[0029] S4. Marking the time period or account where the total predicted power consumption speed is greater than the power supply speed;

[0030] S5. Adjust the electricity usage time of the account within the marked time period and notify an early warning.

[0031] Furthermore, in S1, meteorological information refers to temperature, including historical temperature and future temperature. The historical temperature is collected from the saved records, and the future temperature is collected from the weather forecast issued by the Meteorological Bureau. Electricity information includes future power supply speed, historical electricity consumption speed of each account, and historical electricity consumption time period. Account information includes account type and electricity consumption priority. Account types include production electricity and life electricity. Accounts of type life electricity have no electricity consumption priority and historical electricity consumption time period. Accounts of type production electricity have electricity priority and historical electricity consumption time period. Electricity consumption priority refers to the priority of power resource allocation.

[0032] Furthermore, in S2, the steps of predicting the power consumption rate of the account are as follows:

[0033] S201. Obtain the historical electricity consumption rate of each account and the historical temperature of the corresponding time period, and pre-process these data to remove abnormal values ​​and extreme values.

[0034] S202, correlating the historical temperature and the historical electricity consumption speed in the same time period, respectively fitting the associated data in each account by means of a logarithmic function, and obtaining a relationship formula between the temperature and the electricity consumption speed, wherein each account corresponds to one relationship formula.

[0035] S203, split the predicted duration into X time periods, and put them into a time period set in chronological order, wherein the set includes {T1, T2, ..., T x}, where X represents the number of time periods split within the prediction duration, T x Indicates the Xth time period.

[0036] S204, establish a power usage time period set for each account, obtain the historical power usage time period of each account of type production power usage, match all time periods in the time period set with the historical power usage time period of each account, and successfully match if the time period intersects with the historical power usage time, and put the successfully matched time period into the power usage time period set corresponding to the account in chronological order, and all elements in the power usage time period set are used as the power usage time period of the corresponding account. Accounts of type life power usage do not need to be matched, and all time periods are put into the power usage time period set corresponding to each account of type life power usage.

[0037] S205, collecting the future temperature of each time period, and substituting it into the relationship formula corresponding to each account, respectively, to calculate the predicted power consumption speed of each account in each time period in the corresponding power consumption time period set, and the calculation formula is as follows:

[0038]

[0039] In the formula, T QThe predicted power consumption speed in the time period, season is the seasonal influence coefficient, speed is the power consumption speed constant, a is the temperature influence coefficient, W is T Q Future temperatures for the time period.

[0040] Furthermore, in S3 and S4, the steps of determining the total predicted power consumption speed and marking the time period or account are as follows:

[0041] S401, respectively put the predicted power consumption speed of all accounts of type life power consumption in each time period into a life predicted power consumption set, each time period corresponds to a life predicted power consumption set, and the set includes {H1, H2, ..., H n}, where n represents the number of accounts of all types of household electricity in this time period, H n Indicates the predicted electricity consumption rate of the nth account.

[0042] S402: The predicted power consumption speeds of all accounts of the production type in each time period are put into a production predicted power consumption set in order of the power consumption priority of the accounts from small to large. Each time period corresponds to a production predicted power consumption set, and the set includes {C1, C2, ..., C m}, where m represents the number of accounts of all types of production electricity consumption in this time period, C m Indicates the predicted electricity consumption rate of the mth account.

[0043] S403, summing up all elements in the life predicted electricity consumption set and the production predicted electricity consumption set in each time period to obtain the total predicted electricity consumption speed in each time period;

[0044]

[0045]

[0046]

[0047] In the formula, T Q The sum of the predicted electricity consumption speed of life in the time period, T Q The sum of the production forecast power consumption speed in the time period, T Q The total predicted electricity usage rate for the time period.

[0048] S404, respectively determine whether the total predicted power consumption speed of each time period is greater than the future power supply speed corresponding to the time period. If the result is yes, mark the corresponding time period and proceed to the next step.

[0049] S405. Determine whether the sum of the predicted daily electricity consumption speed for each marked time period is still greater than the future power supply speed corresponding to the time period. If yes, mark the corresponding time period as daily power restriction, and mark all accounts of production electricity consumption in the time period as production adjustment; if no, mark the corresponding time period as adjustment.

[0050] Furthermore, in S5, the steps of adjusting the account electricity usage time and notifying the warning are as follows:

[0051] S501. Control the time period marked as life power restriction, and use the future power supply speed corresponding to the time period as the maximum power consumption speed; restrict power to accounts with life power consumption type in the time period, and control the sum of the predicted life power consumption speed in the time period to be no greater than the maximum power consumption speed; cut off power to accounts with production power consumption type in the time period, and control the sum of the predicted production power consumption speed in the time period to be zero.

[0052] S502: sort the time periods marked for adjustment in chronological order, and sequentially put them into an adjustment time period set.

[0053] S503, respectively calculating the total predicted power consumption speed of the time periods marked for adjustment, and determining whether it is still greater than the future power supply speed corresponding to the time period. If the result is no, canceling the adjustment mark of the corresponding time period and deleting the corresponding time period from the adjustment time period set.

[0054] S504: Determine whether the number of elements in the adjustment time period set is zero. If yes, proceed to step S508; otherwise, proceed to step S505.

[0055] S505: Find the earliest time in the adjustment time period set as the current time period.

[0056] S506. Extract an account of production electricity type and the lowest electricity priority in the current time period, and mark the account as production adjustment.

[0057] S507 , respectively obtain all time periods in each electricity consumption time period set marked as a production adjustment account, subtract the predicted electricity consumption speed marked as a production adjustment account from the total predicted electricity consumption speed of these time periods, and proceed to step S503 .

[0058] S508. Sort the accounts marked for production adjustment according to power usage priority, and select the account with the highest priority as the current account.

[0059] S509: Sum all elements in the electricity consumption time period set corresponding to the current account to obtain the predicted electricity consumption duration.

[0060] S510. Obtain all time periods that are not marked as life power restrictions, as well as the future temperatures of these time periods, substitute them into the relationship formula corresponding to the current account, calculate the predicted power consumption speed of the current account in these time periods, calculate the total predicted power consumption speed of these time periods respectively, and determine whether there are continuous time periods in which the total predicted power consumption speed is not greater than the future power supply speed corresponding to the time period. If the result is no, the current account is marked as production power outage; if the result is yes, sum the continuous time periods to determine whether it is greater than or equal to the predicted power consumption duration of the current account. If the result is yes, mark the current account as production power restrictions and enter step S511; if the result is no, mark the current account as production power outage and enter step S512.

[0061] S511. First, clear the electricity usage time period set corresponding to the current account, and then automatically start selecting from the earliest time period in the consecutive time periods according to the predicted electricity usage duration of the current account. When the sum of the selected time periods is not less than the predicted electricity usage duration of the current account, stop selecting. Put the selected time periods into the electricity usage time period set corresponding to the account in chronological order, and add the predicted electricity usage speed of each time period of the current account in the electricity usage time period set to the total predicted electricity usage speed of each time period.

[0062] S512. Determine whether the number of accounts marked as production adjustments is zero. If yes, proceed to step S513; if no, proceed to step S508.

[0063] S513. Issue a power restriction notification to the account marked as production power restriction, notifying the account to use electricity within the time period in the corresponding power usage time period set; issue a power outage notification to the account marked as production power outage, notifying the account not to use electricity within the predicted duration.

[0064] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0065] 1. In the stage of predicting the power consumption speed, the present invention uses the temperature factor as the influencing condition of the power consumption speed, and calculates the predicted power consumption speed for each power consumption account respectively, which is more in line with the power consumption habits of each account, and the total predicted power consumption speed obtained is more accurate;

[0066] 2. The present invention divides the forecast duration into multiple time periods, divides the accounts into production electricity and life electricity, and extracts the accounts of production electricity in each time period in order from low to high according to the account electricity priority, ensuring that the total forecast electricity consumption speed in each time period is not greater than the future power supply speed, achieving supply and demand balance, and improving the stability and reliability of power supply;

[0067] 3. Under the premise of ensuring that the total predicted power consumption speed in each time period is not greater than the future power supply speed, the present invention adds accounts of production power consumption type to time periods that can meet the power consumption duration in order of account power consumption priority from high to low. This ensures the power consumption duration of the accounts and recalculates the predicted power consumption speed of the accounts in these time periods, thereby improving power consumption efficiency and reducing the number of accounts that require power rationing or power outages. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0069] Figure 1 It is a structural schematic diagram of a big data analysis system for power grid planning according to the present invention.

[0070] Figure 2 It is a flow chart of a method for analyzing big data for power grid planning according to the present invention. DETAILED DESCRIPTION

[0071] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0072] See also Figure 1 The present invention provides an analysis system for big data used in power grid planning, which includes a data acquisition module, a data analysis module, a power consumption management module and a notification and warning module.

[0073] The data acquisition module is used to collect meteorological information, power information and account information; the data analysis module is used to analyze meteorological information and power information to calculate the predicted power consumption speed of each account, and determine whether the total predicted power consumption speed of all accounts in each time period exceeds the future power supply speed corresponding to the time period. If it exceeds, the corresponding time period is recorded; the power consumption management module is used to adjust the total predicted power consumption speed of the recorded time period, and by analyzing the account information, the power consumption time of some accounts is restricted or stopped, so that the total predicted power consumption speed of each time period does not exceed the future power supply speed corresponding to the time period; the notification and warning module is used to notify and warn the accounts that need to be adjusted.

[0074] The data collection module includes a meteorological information collection unit, a power information collection unit and an account information collection unit.

[0075] The meteorological information collection unit is used to collect meteorological information within the power consumption range, and the meteorological information includes historical temperature and future temperature.

[0076] The power information collection unit is used to collect power information within the power consumption range, and the power information includes future power supply speed, historical power consumption speed of each account, and historical power consumption time period.

[0077] The historical temperature, the historical power consumption speed of each account, and the historical power consumption time period are collected from the records saved by the system, and the future temperature is collected from the weather forecast released by the Meteorological Bureau. The historical temperature refers to the change information of the temperature in the past time, the historical power consumption speed refers to the change information of the power consumption speed of the corresponding account in the past time, and the historical power consumption time period refers to the time period information of the daily power consumption of the corresponding account in the past time.

[0078] The future power supply speed is obtained from the power generation end, specifically referring to the change in power supply speed over time within a period of time in the future.

[0079] The account information collection unit is used to collect information of all accounts within the electricity usage range. The account information includes account type and electricity usage priority. The account type includes production electricity and living electricity.

[0080] An account refers to an electricity usage account. Each electricity usage account has its own historical data, including historical electricity usage speed and historical electricity usage time period. The electricity usage priority of an account represents the degree of dependence of the account on electricity. The higher the dependence, the higher the electricity usage priority.

[0081] There is no electricity usage priority and historical electricity usage time period for household electricity usage accounts, but there is electricity usage priority and historical electricity usage time period for production electricity usage accounts. The electricity usage priority refers to the priority level of electricity resource allocation.

[0082] The data analysis module includes a power usage prediction unit and a power usage judgment unit.

[0083] The power consumption prediction unit is used to calculate the predicted power consumption rate of each account within the predicted time period.

[0084] First, the historical electricity consumption speed of each account and the historical temperature of the corresponding time period are obtained. After preprocessing these data, the historical temperature and historical electricity consumption speed in the same time period are associated, and the associated data in each account are fitted with a logarithmic function to obtain the relationship formula between temperature and electricity consumption speed. Each account corresponds to a relationship formula; secondly, the prediction duration is divided into X time periods, and all time periods are matched with the historical electricity consumption time periods of each account of production type. When the time period intersects with the historical electricity consumption time period, the match is successful. The successfully matched time period is used as the electricity consumption time period of the corresponding account. Accounts of the type of household electricity consumption do not need to be matched, and the electricity consumption time period is all time periods; finally, the future temperature corresponding to the electricity consumption time period of each account is obtained, and substituted into the relationship formula corresponding to each account, and the predicted electricity consumption speed of each account in the corresponding electricity consumption time period is calculated.

[0085] To ensure the accuracy of subsequent calculation results, the prediction duration should be set reasonably, longer than the normal production power consumption time, and less than or equal to the farthest time of temperature prediction in the meteorological information. The split time periods should also be reasonable, with each time period having the same length, less than the normal production power consumption time, and longer than the temperature change interval in the meteorological information.

[0086] The power consumption determination unit is used to determine whether the total predicted power consumption speed in each time period within the predicted duration is greater than the future power supply speed corresponding to the time period.

[0087] Sum the predicted electricity consumption speed of each account in each time period to obtain the total predicted electricity consumption speed corresponding to the time period, and determine whether the total predicted electricity consumption speed of each time period is greater than the future power supply speed corresponding to the time period. If the result is no, no processing will be performed; if the result is yes, continue to sum the predicted electricity consumption speed of all accounts of the type of household electricity consumption in the time period, and determine whether it is still greater than the future power supply speed corresponding to the time period. If the result is no, mark the time period as adjustment; if the result is yes, mark the corresponding time period as household power restriction, and mark all accounts of the type of production electricity consumption in the time period as production adjustment.

[0088] The power consumption management module includes a power consumption time adjustment unit.

[0089] The electricity usage time adjustment unit is used to adjust the electricity usage time of an account. First, the accounts of the production electricity usage type in the time period marked as adjustment are extracted in order of electricity usage priority from low to high, and marked as production adjustment, until the total predicted electricity usage speed of all time periods marked as adjustment is not greater than the future power supply speed. Then all accounts marked as production adjustment are placed in other time periods in order of electricity usage priority from high to low. If the total predicted electricity usage speed of other time periods does not exceed the future power supply speed and the sum of the continuous time of the time period is not less than the predicted electricity usage time of the account, the account is marked as production power restriction, and the earliest time period in the continuous time period is automatically selected as the power usage time period of the account; otherwise, the account is marked as production power outage.

[0090] The notification and warning module includes a power limit notification unit and a power outage notification unit.

[0091] The power restriction notification unit is used to issue power restriction notifications to accounts of type living electricity in the time period marked as life power restriction, limiting the total predicted power consumption speed of accounts of type living electricity in the time period to no more than the future power supply speed corresponding to the time period. Power restriction notifications are issued to accounts marked as production power restriction, limiting the accounts to use electricity only in the corresponding power consumption time period.

[0092] Power restriction measures are different for different types of accounts. For accounts that use electricity for daily life, the total predicted power consumption speed in the corresponding time period is limited to no more than the future power supply speed corresponding to the time period. The specific measures are to cut off power to some accounts or limit the power consumption speed of all accounts, which is manually determined. For accounts that use electricity for production, the power consumption time is restricted, but the duration of power consumption is not restricted.

[0093] The power outage notification unit is used to notify the accounts marked as production power outages of power outages, and control the accounts to prevent them from using electricity within the predicted duration.

[0094] See also Figure 2 The present invention provides a method for analyzing big data for power grid planning, the method comprising the following steps:

[0095] S1. Collect weather information, electricity information and account information;

[0096] S2, analyzing the information collected in step S1 to predict the power consumption rate of the account;

[0097] S3, determining whether the total predicted power consumption speed is greater than the power supply speed within the predicted time period;

[0098] S4. Marking the time period or account where the total predicted power consumption speed is greater than the power supply speed;

[0099] S5. Adjust the electricity usage time of the account within the marked time period and notify an early warning.

[0100] In S1, meteorological information refers to temperature, including historical temperature and future temperature. Historical temperature is collected from saved records, and future temperature is collected from weather forecasts issued by the Meteorological Bureau. Electricity information includes future power supply speed, historical electricity consumption speed of each account, and historical electricity consumption time period. Account information includes account type and electricity consumption priority. Account types include production electricity and household electricity. Accounts of type household electricity have no electricity consumption priority and historical electricity consumption time period, while accounts of type production electricity have electricity priority and historical electricity consumption time period. Electricity consumption priority refers to the priority of electricity resource allocation.

[0101] In S2, the steps to predict the electricity consumption rate of an account are as follows:

[0102] S201. Obtain the historical electricity consumption rate of each account and the historical temperature of the corresponding time period, and pre-process these data to remove abnormal values ​​and extreme values.

[0103] S202, correlating the historical temperature and the historical electricity consumption speed in the same time period, respectively fitting the associated data in each account by means of a logarithmic function, and obtaining a relationship formula between the temperature and the electricity consumption speed, wherein each account corresponds to one relationship formula.

[0104] S203, split the predicted duration into X time periods, and put them into a time period set in chronological order, wherein the set includes {T1, T2, ..., T x}, where X represents the number of time periods split within the prediction duration, T x Indicates the Xth time period.

[0105] S204, establish a power usage time period set for each account, obtain the historical power usage time period of each account of type production power usage, match all time periods in the time period set with the historical power usage time period of each account, and successfully match if the time period intersects with the historical power usage time, and put the successfully matched time period into the power usage time period set corresponding to the account in chronological order, and all elements in the power usage time period set are used as the power usage time period of the corresponding account. Accounts of type life power usage do not need to be matched, and all time periods are put into the power usage time period set corresponding to each account of type life power usage.

[0106] S205, collecting the future temperature of each time period, and substituting it into the relationship formula corresponding to each account, respectively, to calculate the predicted power consumption speed of each account in each time period in the corresponding power consumption time period set, and the calculation formula is as follows:

[0107]

[0108] In the formula, TQ The predicted power consumption speed in the time period, season is the seasonal influence coefficient, speed is the power consumption speed constant, a is the temperature influence coefficient, W is T Q Future temperatures for the time period.

[0109] In S3 and S4, the steps of determining the total predicted power consumption speed and marking the time period or account are as follows:

[0110] S401, respectively put the predicted power consumption speed of all accounts of type life power consumption in each time period into a life predicted power consumption set, each time period corresponds to a life predicted power consumption set, and the set includes {H1, H2, ..., H n}, where n represents the number of accounts of all types of household electricity in this time period, H n Indicates the predicted electricity consumption rate of the nth account.

[0111] S402: The predicted power consumption speeds of all accounts of the production type in each time period are put into a production predicted power consumption set in order of the power consumption priority of the accounts from small to large. Each time period corresponds to a production predicted power consumption set, and the set includes {C1, C2, ..., C m}, where m represents the number of accounts of all types of production electricity consumption in this time period, C m Indicates the predicted electricity consumption rate of the mth account.

[0112] S403, summing up all elements in the life predicted electricity consumption set and the production predicted electricity consumption set in each time period to obtain the total predicted electricity consumption speed in each time period;

[0113]

[0114]

[0115]

[0116] In the formula, T Q The sum of the predicted electricity consumption speed of life in the time period, T Q The sum of the production forecast power consumption speed in the time period, T Q The total predicted electricity usage rate for the time period.

[0117] S404, respectively determine whether the total predicted power consumption speed of each time period is greater than the future power supply speed corresponding to the time period. If the result is yes, mark the corresponding time period and proceed to the next step.

[0118] S405. Determine whether the sum of the predicted daily electricity consumption speed for each marked time period is still greater than the future power supply speed corresponding to the time period. If yes, mark the corresponding time period as daily power restriction, and mark all accounts of production electricity consumption in the time period as production adjustment; if no, mark the corresponding time period as adjustment.

[0119] In S5, the steps for adjusting the account electricity usage time and notifying the warning are as follows:

[0120] S501. Control the time period marked as life power restriction, and use the future power supply speed corresponding to the time period as the maximum power consumption speed; restrict power to accounts with life power consumption type in the time period, and control the sum of the predicted life power consumption speed in the time period to be no greater than the maximum power consumption speed; cut off power to accounts with production power consumption type in the time period, and control the sum of the predicted production power consumption speed in the time period to be zero.

[0121] S502: sort the time periods marked for adjustment in chronological order, and sequentially put them into an adjustment time period set.

[0122] S503, respectively calculating the total predicted power consumption speed of the time periods marked for adjustment, and determining whether it is still greater than the future power supply speed corresponding to the time period. If the result is no, canceling the adjustment mark of the corresponding time period and deleting the corresponding time period from the adjustment time period set.

[0123] S504: Determine whether the number of elements in the adjustment time period set is zero. If yes, proceed to step S508; otherwise, proceed to step S505.

[0124] S505: Find the earliest time in the adjustment time period set as the current time period.

[0125] S506. Extract an account of production electricity type and the lowest electricity priority in the current time period, and mark the account as production adjustment.

[0126] S507 , respectively obtain all time periods in each electricity consumption time period set marked as a production adjustment account, subtract the predicted electricity consumption speed marked as a production adjustment account from the total predicted electricity consumption speed of these time periods, and proceed to step S503 .

[0127] S508. Sort the accounts marked for production adjustment according to power usage priority, and select the account with the highest priority as the current account.

[0128] S509: Sum all elements in the electricity consumption time period set corresponding to the current account to obtain the predicted electricity consumption duration.

[0129] S510. Obtain all time periods that are not marked as life power restrictions, as well as the future temperatures of these time periods, substitute them into the relationship formula corresponding to the current account, calculate the predicted power consumption speed of the current account in these time periods, calculate the total predicted power consumption speed of these time periods respectively, and determine whether there are continuous time periods in which the total predicted power consumption speed is not greater than the future power supply speed corresponding to the time period. If the result is no, the current account is marked as production power outage; if the result is yes, sum the continuous time periods to determine whether it is greater than or equal to the predicted power consumption duration of the current account. If the result is yes, mark the current account as production power restrictions and enter step S511; if the result is no, mark the current account as production power outage and enter step S512.

[0130] S511. First, clear the electricity usage time period set corresponding to the current account, and then automatically start selecting from the earliest time period in the consecutive time periods according to the predicted electricity usage duration of the current account. When the sum of the selected time periods is not less than the predicted electricity usage duration of the current account, stop selecting. Put the selected time periods into the electricity usage time period set corresponding to the account in chronological order, and add the predicted electricity usage speed of each time period of the current account in the electricity usage time period set to the total predicted electricity usage speed of each time period.

[0131] S512. Determine whether the number of accounts marked as production adjustments is zero. If yes, proceed to step S513; if no, proceed to step S508.

[0132] S513. Issue a power restriction notification to the account marked as production power restriction, notifying the account to use electricity within the time period in the corresponding power usage time period set; issue a power outage notification to the account marked as production power outage, notifying the account not to use electricity within the predicted duration.

[0133] Embodiment 1:

[0134] Assume that there are three accounts, A1, A2 and A3; the seasonal impact coefficient of A1 is 2.1, the electricity consumption rate constant is 0.2, and the temperature impact coefficient is 1.2; the seasonal impact coefficient of A2 is 2.1, the electricity consumption rate constant is 0.3, and the temperature impact coefficient is 1.3; the seasonal impact coefficient of A3 is 2.1, the electricity consumption rate constant is 0.2, and the temperature impact coefficient is 1.4; the future temperature in a certain time period is 26°, calculate the predicted electricity consumption rates of these three accounts in the time period respectively;

[0135] A1: 2.1×0.2×log 1.2 26≈7.51kWh

[0136] A2: 2.1×0.3×log 1.3 26≈7.82kWh

[0137] A3: 2.1×0.2×log 1.4 26≈4.07kWh

[0138] It is obtained that the predicted electricity consumption rate of A1 is 7.51kWh, the predicted electricity consumption rate of A1 is 7.82kWh, and the predicted electricity consumption rate of A1 is 4.07kWh.

[0139] Embodiment 2:

[0140] Assume that there are 8 accounts, B1, B2, B3, B4, B5, B6, B7 and B8. Among them, B1, B2, B3 and B4 are for household electricity use, and B5, B6, B7 and B8 are for production electricity use. The electricity use priorities are 12, 23, 32 and 45 respectively. The predicted duration is divided into 5 time periods, T1, T2, T3, T4 and T5. The future power supply speed corresponding to each time period is:

[0141] T1:20kWh, T2:30kWh, T3:20kWh, T4:40kWh, T5:40kWh;

[0142] Assume that the predicted electricity consumption speed of each of these 8 accounts during the electricity consumption period is as follows:

[0143] B1: T1: 6kWh, T2: 2kWh, T3: 3kWh, T4: 3kWh, T5: 3kWh;

[0144] B2: T1: 3kWh, T2: 4kWh, T3: 3kWh, T4: 2kWh, T5: 2kWh;

[0145] B3: T1: 8kWh, T2: 2kWh, T3: 2kWh, T4: 3kWh, T5: 4kWh;

[0146] B4, T1: 4kWh, T2: 3kWh, T3: 2kWh, T4: 2kWh, T5: 1kWh;

[0147] B5, T4: 12kWh, T5: 12kWh;

[0148] B6, T2: 12kWh, T3: 5kWh;

[0149] B7, T3: 6kWh, T4: 12kWh, T5: 12kWh;

[0150] B8, T1: 12kWh, T2: 7kWh;

[0151] Then we can get:

[0152] If the sum of the predicted electricity consumption speed for daily life in time period T1 is greater than the future power supply speed corresponding to this time period, time period T1 is marked as power restriction for daily life, and B8 is marked as production adjustment. The B8 account is withdrawn and no longer participates in the calculation of the total predicted electricity consumption speed for time periods T1 and T2;

[0153] The total predicted power consumption speed in the T3 period is greater than the future power supply speed corresponding to the period, and B6 is marked as production adjustment. The B6 account is withdrawn and no longer participates in the calculation of the total predicted power consumption speed in the T2 and T3 periods;

[0154] The future power supply speed in each time period minus the predicted power consumption speed, the remainder is:

[0155] T1:0kWh, T2:19kWh, T3:4kWh, T4:6kWh, T5:6kWh;

[0156] Since B8 has a higher priority than B6, B8 is allocated first. Assume that the predicted power consumption speed of B8 in each time period is:

[0157] T1:12kWh, T2:7kWh, T3:4kWh, T4:5kWh, T5:7kWh;

[0158] Since B8's electricity consumption duration is 2 time periods, it is allocated to the T2 and T3 time periods. B8 is marked as production power restriction, and the power restriction time periods are T2 and T3.

[0159] The future power supply speed in each time period is again subtracted from the predicted power consumption speed, and the remainder is:

[0160] T1:0kWh, T2:12kWh, T3:0kWh, T4:6kWh, T5:6kWh;

[0161] Then allocate B6, assuming that the predicted power consumption speed of B6 in each time period is:

[0162] T1:8kWh, T2:12kWh, T3:5kWh, T4:6kWh, T5:8kWh;

[0163] Since B6's electricity consumption duration is 2 time periods, and there are no consecutive time periods that can meet its allocation, B6 is marked as a production power outage and cannot use electricity within the predicted duration.

[0164] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0165] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A big data analysis system for power grid planning, characterized by: It includes data collection module, data analysis module, power management module and notification and warning module; The data acquisition module is used to collect meteorological information, power information and account information; The data analysis module is used to analyze meteorological information and power information to calculate the predicted power consumption speed of each account, and determine whether the total predicted power consumption speed of all accounts in each time period exceeds the future power supply speed corresponding to the time period, and if it exceeds, record the corresponding time period; The power consumption management module is used to adjust the total predicted power consumption speed of the recorded time period, and to limit the power consumption time or stop the power consumption of some accounts by analyzing the account information, so that the total predicted power consumption speed of each time period does not exceed the future power supply speed corresponding to the time period; The notification and warning module is used to notify and warn accounts that need to be adjusted; The data analysis module includes a power usage prediction unit and a power usage judgment unit; The power consumption prediction unit is used to calculate the predicted power consumption speed of each account within the predicted time period; The power consumption judgment unit is used to judge whether the total predicted power consumption speed in each time period within the predicted duration is greater than the future power supply speed corresponding to the time period; The determination of whether the total predicted electricity consumption speed of each time period within the predicted duration is greater than the future power supply speed corresponding to the time period specifically includes: summing the predicted electricity consumption speed of each account in each time period to obtain the total predicted electricity consumption speed corresponding to the time period, and judging whether the total predicted electricity consumption speed of each time period is greater than the future power supply speed corresponding to the time period. If the result is no, no processing is performed; if the result is yes, continuing to sum the predicted electricity consumption speeds of all accounts of the type of household electricity consumption in the time period, and judging whether it is still greater than the future power supply speed corresponding to the time period. If the result is no, marking the time period as adjustment; if the result is yes, marking the corresponding time period as household power restriction, and marking all accounts of the type of production electricity consumption in the time period as production adjustment.

2. The big data analysis system for power grid planning according to claim 1, characterized in that: The data collection module includes a meteorological information collection unit, a power information collection unit and an account information collection unit; The meteorological information collection unit is used to collect meteorological information within the power consumption range, and the meteorological information includes historical temperature and future temperature; The power information collection unit is used to collect power information within the power consumption range, the power information including future power supply speed, historical power consumption speed of each account and historical power consumption time period; The account information collection unit is used to collect information of all accounts within the electricity usage range, the account information includes account type and electricity usage priority, and the account type includes production electricity and living electricity.

3. The big data analysis system for power grid planning according to claim 1, characterized in that: The calculation of the predicted power consumption speed of each account within the predicted duration specifically includes: First, the historical electricity consumption speed of each account and the historical temperature of the corresponding time period are obtained. After preprocessing these data, the historical temperature and historical electricity consumption speed in the same time period are correlated. The associated data in each account are fitted using a logarithmic function to obtain the relationship formula between temperature and electricity consumption speed. Each account corresponds to a relationship formula. Secondly, the forecast duration is divided into X time periods. All time periods are matched with the historical power consumption time periods of each account of type production power consumption. When the time period intersects with the historical power consumption time period, the match is successful. The successfully matched time period is used as the power consumption time period of the corresponding account. Accounts of type life power consumption do not need to be matched, and the power consumption time period is all time periods. Finally, the future temperature corresponding to the electricity consumption time period of each account is obtained, and is substituted into the relationship formula corresponding to each account to calculate the predicted electricity consumption speed of each account in the corresponding electricity consumption time period.

4. The big data analysis system for power grid planning according to claim 1, characterized in that: The power usage management module includes a power usage time adjustment unit, which is used to adjust the power usage time of the account, specifically including: First, the accounts of type production electricity in the time period marked as adjustment are extracted in order of power usage priority from low to high, and marked as production adjustment, until the total predicted power consumption speed of all time periods marked as adjustment is no greater than the future power supply speed; Then all accounts marked as production adjustments are placed in other time periods in order of power usage priority from high to low. If the total predicted power usage speed in other time periods will not be greater than the future power supply speed and the sum of the consecutive time periods is not less than the predicted power usage duration of the account, the account will be marked as production power restriction, and the earliest time period in the consecutive time periods will be automatically selected as the power usage time period of the account; otherwise, the account will be marked as production power outage.

5. The big data analysis system for power grid planning according to claim 1, characterized in that: The notification and warning module includes a power limit notification unit and a power outage notification unit; The power restriction notification unit is used to notify the account of the type of life electricity use in the time period marked as life power restriction, and limit the total predicted power consumption speed of the account of the type of life electricity use in the time period to no more than the future power supply speed corresponding to the time period; Issue power restriction notifications to accounts marked as production power restrictions, restricting the accounts to use electricity only during the corresponding power usage time period; The power outage notification unit is used to issue a power outage notification to the account marked as a production power outage, so as to prevent the account from using electricity within the predicted duration.

6. A method for analyzing big data for power grid planning implementing the system described in any one of claims 1 to 5, characterized in that: The following steps are involved: S1. Collect weather information, electricity information and account information; S2, analyzing the information collected in step S1 to predict the power consumption rate of the account; S3, determining whether the total predicted power consumption speed is greater than the power supply speed within the predicted time period; S4. Marking the time period or account where the total predicted power consumption speed is greater than the power supply speed; S5. Adjust the electricity usage time of the account within the marked time period and notify an early warning.

7. The method for analyzing big data for power grid planning according to claim 6, characterized in that: In S1, meteorological information refers to temperature, including historical temperature and future temperature. Historical temperature is collected from saved records, and future temperature is collected from weather forecasts issued by the Meteorological Bureau; power information includes future power supply speed, historical power consumption speed of each account, and historical power consumption time period; account information includes account type and power consumption priority. Account types include production power consumption and household power consumption. Accounts of type household power consumption have no power consumption priority and historical power consumption time period, and accounts of type production power consumption have power consumption priority and historical power consumption time period. Power consumption priority refers to the priority of power resource allocation.

8. The method for analyzing big data for power grid planning according to claim 6, characterized in that: In S2, the steps to predict the electricity consumption rate of an account are as follows: S201, obtaining the historical electricity consumption speed of each account and the historical temperature of the corresponding time period, and preprocessing these data to remove abnormal values ​​and extreme values; S202, associating the historical temperature and the historical electricity consumption speed in the same time period, and performing data fitting on the associated data in each account using a logarithmic function to obtain a relationship formula between the temperature and the electricity consumption speed, wherein each account corresponds to one relationship formula; S203, split the predicted duration into X time periods, and put them into a time period set in chronological order, wherein the set includes {T1, T2, ..., T x }, where X represents the number of time periods split within the prediction duration, T x Indicates the Xth time period; S204, establish a power usage time period set for each account, obtain the historical power usage time period of each account of type production power usage, match all time periods in the time period set with the historical power usage time period of each account respectively, and the match is successful if the time period intersects with the historical power usage time, put the successfully matched time period into the power usage time period set corresponding to the account in chronological order, and all elements in the power usage time period set are used as the power usage time period of the corresponding account; accounts of type life power usage do not need to be matched, and all time periods are put into the power usage time period set corresponding to each account of type life power usage; S205, collecting the future temperature of each time period, and substituting it into the relationship formula corresponding to each account, respectively, to calculate the predicted power consumption speed of each account in each time period in the corresponding power consumption time period set, and the calculation formula is as follows: In the formula, T Q The predicted power consumption speed in the time period, season is the seasonal influence coefficient, speed is the power consumption speed constant, a is the temperature influence coefficient, W is T Q Future temperatures for the time period.

9. The method for analyzing big data for power grid planning according to claim 6, characterized in that: In S3 and S4, the steps of determining the total predicted power consumption speed and marking the time period or account are as follows: S401, respectively put the predicted power consumption speed of all accounts of type life power consumption in each time period into a life predicted power consumption set, each time period corresponds to a life predicted power consumption set, and the set includes {H1, H2, ..., H n }, where n represents the number of accounts of all types of household electricity in this time period, H n Indicates the predicted electricity consumption rate of the nth account; S402: The predicted power consumption speeds of all accounts of the production type in each time period are put into a production predicted power consumption set in order of the power consumption priority of the accounts from small to large. Each time period corresponds to a production predicted power consumption set, and the set includes {C1, C2, ..., C m }, where m represents the number of accounts of all types of production electricity in this time period, C m represents the predicted electricity consumption speed of the mth account; S403, summing up all elements in the predicted power consumption set for life and the predicted power consumption set for production in each time period to obtain a total predicted power consumption rate for each time period; In the formula, H TQ T Q The sum of the predicted electricity consumption speed of life in the time period, C TQ T Q The sum of the production forecast power consumption speed in the time period, Z TQ T Q Total predicted electricity consumption rate for the time period; S404, respectively determine whether the total predicted power consumption speed of each time period is greater than the future power supply speed corresponding to the time period, and if the result is yes, mark the corresponding time period and proceed to the next step; S405. Determine whether the sum of the predicted daily electricity consumption speed for each marked time period is still greater than the future power supply speed corresponding to the time period. If yes, mark the corresponding time period as daily power restriction, and mark all accounts of production electricity consumption in the time period as production adjustment; if no, mark the corresponding time period as adjustment.

10. The method for analyzing big data for power grid planning according to claim 6, characterized in that: In S5, the steps for adjusting the account electricity usage time and notifying the warning are as follows: S501, control the time period marked as life power restriction, and use the future power supply speed corresponding to the time period as the maximum power consumption speed; limit the power supply of accounts with life power consumption type in the time period, and control the sum of the life predicted power consumption speed in the time period to be no greater than the maximum power consumption speed; cut off the power supply of accounts with production power consumption type in the time period, and control the sum of the production predicted power consumption speed in the time period to be zero; S502, sorting the time periods marked for adjustment in chronological order, and sequentially putting them into an adjustment time period set; S503, respectively calculating the total predicted power consumption speed of the time periods marked as adjusted, and determining whether it is still greater than the future power supply speed corresponding to the time period, and if the result is no, canceling the adjustment mark of the corresponding time period, and deleting the corresponding time period from the adjustment time period set; S504, determine whether the number of elements in the adjustment time period set is zero, if yes, proceed to step S508, otherwise proceed to step S505; S505, finding the earliest time in the adjustment time period set as the current time period; S506, extracting an account of production electricity type and the lowest electricity priority in the current time period, and marking the account as production adjustment; S507, respectively obtain all time periods in each power consumption time period set marked as a production adjustment account, subtract the predicted power consumption speed marked as a production adjustment account from the total predicted power consumption speed of these time periods, and proceed to step S503; S508, sorting the accounts marked as production adjustment according to the electricity usage priority, and selecting the account with the highest priority as the current account; S509, summing up all elements in the electricity consumption time period set corresponding to the current account to obtain the predicted electricity consumption duration; S510, obtaining all time periods that are not marked as life power restriction and the future temperatures of these time periods, substituting them into the relationship formula corresponding to the current account, calculating the predicted power consumption speed of the current account in these time periods, respectively calculating the total predicted power consumption speed of these time periods, and determining whether there are continuous time periods in which the total predicted power consumption speed is not greater than the future power supply speed corresponding to the time period. If the result is no, marking the current account as production power outage; If the result is yes, the continuous time periods are summed to determine whether they are greater than or equal to the predicted power consumption duration of the current account. If the result is yes, the current account is marked as production power restriction and the process goes to step S511; If the answer is no, the current account is marked as a production power outage and the process goes to step S512; S511, first clear the electricity usage time period set corresponding to the current account, then automatically start selecting from the earliest time period in the consecutive time periods according to the predicted electricity usage duration of the current account, stop selecting when the sum of the selected time periods is not less than the predicted electricity usage duration of the current account, add the selected time periods to the electricity usage time period set corresponding to the account in chronological order, and add the predicted electricity usage speed of each time period in the electricity usage time period set of the current account to the total predicted electricity usage speed of each time period; S512: Determine whether the number of accounts marked as production adjustment is zero. If yes, proceed to step S513; if no, proceed to step S508; S513. Issue a power restriction notification to the account marked as production power restriction, notifying the account to use electricity within the time period in the corresponding power usage time period set; issue a power outage notification to the account marked as production power outage, notifying the account not to use electricity within the predicted duration.

Images