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CN-121998299-A - Park peak valley electricity dispatching method based on BMS

CN121998299ACN 121998299 ACN121998299 ACN 121998299ACN-121998299-A

Abstract

The invention discloses a district peak-valley electricity dispatching method based on BMS, which relates to the technical field of electricity dispatching and comprises the steps of obtaining historical electricity data of each district in the district, constructing a historical electricity data change chart, determining peak-valley time periods of each district according to the constructed historical electricity data change chart, setting corresponding district dispatching influence coefficients according to the peak-valley time periods of each district, generating electricity dispatching strategies among the districts according to the peak-valley time periods of each district and the district dispatching influence coefficients, and reflecting peak-valley time period matching degree among different districts by the district dispatching influence coefficients in the period of identifying month, day and hour by analyzing the historical electricity curves of each district.

Inventors

  • CHENG WENJING

Assignees

  • 苏州越禾泰普数据科技有限公司

Dates

Publication Date
20260508
Application Date
20251225

Claims (7)

  1. 1. BMS-based park peak valley electricity scheduling method is characterized by comprising the following steps: acquiring historical electricity utilization data of each area in a park, and constructing a historical electricity utilization data change chart; Determining peak-to-valley time periods of all areas according to the constructed historical electricity data change diagram; setting corresponding regional dispatching influence coefficients according to peak-valley time periods of all the regions; And generating power utilization scheduling strategies among the areas according to the peak-valley time periods of the areas and the area scheduling influence coefficients.
  2. 2. The BMS-based campus peak valley power dispatching method according to claim 1, wherein there are several areas in the campus; Summarizing the electricity consumption data of a period of time in each area to obtain historical electricity consumption data of each area, wherein the historical electricity consumption data comprises input current, input voltage, phase angle and corresponding time; Respectively constructing a time axis of time about historical electricity data for each region; Respectively generating a corresponding current change curve, a voltage change curve and a phase angle change curve according to the historical electricity consumption data; And setting time dimension ranges of different levels in a time axis according to the time in the historical electricity utilization data so as to obtain a historical electricity utilization data change chart, wherein the time dimension ranges comprise a annual time range, a monthly time range and a daily time range.
  3. 3. The BMS-based campus peak to valley power scheduling method of claim 2, wherein the process of determining peak to valley time periods of each region according to the constructed historical power data variation graph comprises: Obtaining the electricity load value of each month time range according to the change curve of each month time range in the annual time range; setting an upper monthly load threshold and a lower monthly load threshold; comparing the electricity load values of the month time ranges of the same area with the month load upper limit threshold value and the month load lower limit threshold value respectively; if the electricity load value is smaller than the month load lower limit threshold value, the corresponding month time range is recorded as the annual electricity consumption valley time period, and if the electricity load value is larger than the month load upper limit threshold value, the corresponding month time range is recorded as the annual electricity consumption peak time period; and similarly, obtaining a month electricity consumption valley time period, a month electricity consumption peak time period, a day electricity consumption valley time period and a day electricity consumption peak time period.
  4. 4. The BMS-based campus peak to valley power scheduling method of claim 3, wherein the process of setting the corresponding regional scheduling influence coefficient according to the peak to valley time period of each region comprises: selecting any area as a reference area, and selecting another area as a comparison area; taking the starting time and the ending time of the annual electricity consumption peak time period of the reference area as the reference annual time period; taking the starting time and the ending time of the annual electricity consumption valley time period of the control area as the control annual time period; Comparing the reference annual time period with the comparison annual time period, if the reference annual time period is the same as the comparison annual time period, marking the comparison area as a scheduling candidate area of the reference area corresponding to the annual electricity peak time period, otherwise, removing the comparison area, selecting other areas as the comparison area, and pushing the comparison area until all the areas are traversed, so as to determine all the scheduling candidate areas of the reference area; If the comparison annual time period of any area does not exist is the same as the reference annual time period, the fact that the scheduling candidate area does not exist in the corresponding annual electricity peak time period of the reference area is indicated; when there is a scheduling candidate region in the reference control region, then: acquiring a difference value between a power consumption load value and an annual load upper limit threshold value of a corresponding comparison annual time period of a scheduling candidate region, and recording the difference value as a schedulable load quantity of the scheduling candidate region; obtaining a month scheduling priority coefficient of the scheduling candidate area corresponding to a reference annual time period of the reference area according to the obtained schedulable load quantity and the electricity load value of the reference area; sequencing the obtained scheduling candidate areas from high to low according to the scheduling priority coefficient of the corresponding reference annual time period; recording a month electricity consumption peak time period in a reference annual time period of a reference area as a reference month time period, and obtaining a month comparison time period corresponding to the reference month time period; And so on, obtaining the daily schedule priority coefficient of each scheduling candidate region corresponding to the reference month time period of the reference region; and summarizing the obtained month scheduling priority coefficient, the date scheduling priority coefficient and the hour scheduling priority coefficient to be used as the regional scheduling influence coefficient between the reference region and the scheduling candidate region.
  5. 5. The BMS-based campus peak to valley power consumption scheduling method of claim 4, wherein the process of generating the inter-region power consumption scheduling policy according to the peak to valley time period and the regional scheduling influence coefficient of each region comprises: Generating a corresponding time tag sequence according to the current moment, wherein the time tag sequence comprises month, day and hour; Setting the area labels of each area according to the time label sequence, wherein the area labels comprise normal labels, reference area labels and dispatch alternative area labels; reading the area labels corresponding to the time sequence labels of each area 'hour', and marking the area with the reference area label as a reference area; Acquiring a scheduling candidate region corresponding to a reference region, wherein a region label corresponding to a time sequence label of 'hour' is a scheduling candidate region label and is used as a power consumption scheduling region corresponding to the reference region; and acquiring regional dispatching influence coefficients corresponding to each power utilization dispatching region, sequencing the regional dispatching influence coefficients from high to low, and generating a power utilization dispatching strategy according to sequencing results.
  6. 6. The BMS-based campus peak valley power consumption scheduling method of claim 5, wherein the power consumption scheduling policy is: Selecting an electricity utilization dispatching area with the highest area dispatching influence coefficient as an electricity utilization dispatching first echelon, and comparing the electricity utilization redundancy amount corresponding to the electricity utilization dispatching first echelon with the electricity utilization demand amount of a reference area; if the electricity redundancy amount is larger than or equal to the electricity demand amount, directly taking the electricity dispatching area as a final execution result; if the electricity redundancy amount is smaller than the electricity demand amount, a difference value between the electricity redundancy amount and the electricity demand amount is obtained and is used as a new electricity demand amount, the electricity dispatching area with the second rank is used as an electricity dispatching second ladder, the electricity redundancy amount of the electricity dispatching second ladder is compared with the new electricity demand amount, and the like until the electricity redundancy amount is more than or equal to the electricity demand amount, or the traversal of all the electricity dispatching areas is completed.
  7. 7. The BMS-based park peak-valley power consumption scheduling method according to claim 6, wherein the power consumption redundancy refers to a difference between a power consumption load value of "hour" corresponding to a current time and an intermediate value of a lower hour load limit threshold and an upper hour load limit threshold, and the power consumption demand refers to a difference between a power consumption load value of "hour" corresponding to a current time and an upper hour load limit threshold.

Description

Park peak valley electricity dispatching method based on BMS Technical Field The invention relates to the technical field of power utilization scheduling, in particular to a garden peak-valley power utilization scheduling method based on BMS. Background With the large-scale development of the park, the internal load composition of the park is more complex, and the park often comprises a plurality of functional areas such as production, office, research and development, life service and the like, and the electric characteristics of the areas have obvious differences, namely continuous operation of the production area, stable load and small peak-valley difference; In actual park operation, there is often an instant power generation surplus that when one region is in a peak of electricity consumption, the other region may be in a low load valley or possess distributed photovoltaic, how to formulate a reasonable and effective cross-region electricity consumption scheduling strategy according to the peak-valley time period of electricity consumption in the park is a problem to be solved, and therefore, a park peak-valley electricity consumption scheduling method based on BMS is provided. Disclosure of Invention The invention aims to provide a park peak valley electricity scheduling method based on BMS. The invention aims at realizing the technical scheme that the park peak valley electricity scheduling method based on the BMS comprises the following steps of: acquiring historical electricity utilization data of each area in a park, and constructing a historical electricity utilization data change chart; Determining peak-to-valley time periods of all areas according to the constructed historical electricity data change diagram; setting corresponding regional dispatching influence coefficients according to peak-valley time periods of all the regions; And generating power utilization scheduling strategies among the areas according to the peak-valley time periods of the areas and the area scheduling influence coefficients. Further, there are several areas in the campus; Summarizing the electricity consumption data of a period of time in each area to obtain historical electricity consumption data of each area, wherein the historical electricity consumption data comprises input current, input voltage, phase angle and corresponding time; Respectively constructing a time axis of time about historical electricity data for each region; Respectively generating a corresponding current change curve, a voltage change curve and a phase angle change curve according to the historical electricity consumption data; And setting time dimension ranges of different levels in a time axis according to the time in the historical electricity utilization data so as to obtain a historical electricity utilization data change chart, wherein the time dimension ranges comprise a annual time range, a monthly time range and a daily time range. Further, the process of determining the peak-to-valley time periods of each region according to the constructed historical electricity data change graph comprises the following steps: Obtaining the electricity load value of each month time range according to the change curve of each month time range in the annual time range; setting an upper monthly load threshold and a lower monthly load threshold; comparing the electricity load values of the month time ranges of the same area with the month load upper limit threshold value and the month load lower limit threshold value respectively; if the electricity load value is smaller than the month load lower limit threshold value, the corresponding month time range is recorded as the annual electricity consumption valley time period, and if the electricity load value is larger than the month load upper limit threshold value, the corresponding month time range is recorded as the annual electricity consumption peak time period; and similarly, obtaining a month electricity consumption valley time period, a month electricity consumption peak time period, a day electricity consumption valley time period and a day electricity consumption peak time period. Further, the process of setting the corresponding regional scheduling influence coefficient according to the peak-to-valley time period of each region includes: selecting any area as a reference area, and selecting another area as a comparison area; taking the starting time and the ending time of the annual electricity consumption peak time period of the reference area as the reference annual time period; taking the starting time and the ending time of the annual electricity consumption valley time period of the control area as the control annual time period; Comparing the reference annual time period with the comparison annual time period, if the reference annual time period is the same as the comparison annual time period, marking the comparison area as a scheduling candidate area of the reference area corresponding t