Building micro-grid low-carbon integrated cluster control system

Abstract

The invention provides a building micro-grid low-carbon integrated cluster control system, and the system comprises the steps: determining the accumulated capacity of an energy production micro-grid in a target time period according to an energy production impact factor of a target region in the target time period; according to the energy consumption of each power utilization load in the historical time period, the accumulated energy consumption of the power utilization load in the target time period is determined; determining a target sub-moment and an adjustment time period according to the accumulated energy capacity corresponding to each sub-moment of the target time period and the accumulated energy consumption corresponding to the sub-moment; adjusting the total energy consumption corresponding to the adjustment time period according to the total energy consumption corresponding to the adjustment time period and the difference between the accumulated energy consumption corresponding to the next sub-moment of the target sub-moment and the accumulated energy production corresponding to the next sub-moment of the target sub-moment; and finally, controlling the electricity load to be connected with the commercial power grid in the adjustment time period and to be connected with the energy production micro-grid in the non-adjustment time period so as to realize flexible electricity utilization adjustment of the electricity load.

Description

Background Art

[0002] A building microgrid is a microgrid that generates new energy to supply power to electrical loads in a building. It can be self-sufficient in the electricity consumption of electrical loads in the building. However, when the electricity demand of the electrical loads increases, or the energy production of the building microgrid decreases due to external reasons, the energy supply of the electrical loads may be lower than the energy consumption. Therefore, in this case, the electrical loads need to be connected to the external power supply to maintain the power safety of the electrical loads.

[0003] However, since most of the current building microgrids adjust and switch the power supply end of the power load in real time according to the current power demand of the power load, it is impossible to determine the energy consumption of the power load at the next moment, there may be a risk of power supply disconnection of the power load. Moreover, if the power supply end of the power load is switched frequently, the voltage of the power load may become unstable, which is not conducive to the safe use of electricity by the power load. Summary of the invention

[0004] In view of the above technical problems, the technical solution adopted by the present invention is: According to one aspect of the present application, a building microgrid low-carbon integrated cluster control system is provided, wherein the building microgrid low-carbon integrated cluster control system is connected to a municipal power grid, a plurality of energy production microgrids, and a plurality of power loads; Among them, the building microgrid low-carbon integrated cluster control system is used to execute the following methods: Step S100, according to a number of energy production influencing factors of the target area within the target time period, determine the cumulative energy production of a number of energy production microgrids at each sub-time of the target time period; the target area is the geographical area where the several energy production microgrids are located; the start time of the target time period is 0:00 on the day after the current date, and the end time of the target time period is 24:00 on the day after the current date; the length of the time period between each two adjacent sub-times of the target time period is the same; Step S200: Determine the cumulative energy consumption of a number of electrical loads at each sub-time of the target time period according to the energy consumption of each electrical load in the historical time period; the end time of the historical time period is zero o'clock on the current date, and the length of the historical time period is a preset time length; Step S300, traverse each sub-moment in the target time period in turn, if the cumulative energy production corresponding to any sub-moment is greater than or equal to the cumulative energy consumption corresponding to the sub-moment, and the cumulative energy production corresponding to any sub-moment before the sub-moment in the target time period is greater than the cumulative energy consumption corresponding to any sub-moment before the sub-moment, and the cumulative energy production corresponding to the sub-moment after the sub-moment is less than the cumulative energy consumption corresponding to the sub-moment after the sub-moment, then determine the sub-moment as the target sub-moment; Step S400: Determine the power consumption valley time period before the target sub-time in the target time period as the adjustment time period; the power consumption valley time period is the time period corresponding to the power consumption valley period of the target area; Step S500: If the total energy consumption corresponding to the adjustment time period is greater than or equal to the difference between the cumulative energy consumption corresponding to the next sub-moment after the target sub-moment and the cumulative energy production corresponding to the next sub-moment after the target sub-moment, the total energy consumption corresponding to the adjustment time period is adjusted to zero, and the cumulative energy consumption corresponding to the target time period is recalculated, and the process returns to step S300 until there is no target sub-moment in the target time period. Step S600, control a plurality of power loads to be connected to the city power grid during each adjustment time period of the target time period, and control a plurality of power loads to be connected to each energy production microgrid during the non-adjustment time period of the target time period.

[0005] In an exemplary embodiment of the present application, step S100 includes: Step S110, obtaining several energy production influencing factors of the target area within the target time period; Step S120: classify a plurality of energy production influencing factors according to the energy type corresponding to each energy production microgrid to obtain an energy production influencing factor group corresponding to each energy production microgrid; the energy production influencing factor group corresponding to the energy production microgrid includes a plurality of energy production influencing factors corresponding to the energy type of the energy production microgrid; Step S130: Input each energy production influencing factor group into a preset prediction model to obtain the predicted energy production of each energy production microgrid output by the prediction model at each sub-time of the target time period, and determine the predicted energy production list set A=(A1, A2, ..., A m ,...,A n ), where m=1,2,...,n; n is the number of energy production microgrids; A m A is the predicted energy production list corresponding to the mth energy production microgrid; m =(A m1 ,A m2 ,...,A mi ,...,A mj ), i=1,2,...,j, j is the number of sub-times in the target time period, A mi is the predicted energy production of the mth energy production microgrid at the i-th sub-moment in the target time period; the prediction model is obtained by training the energy production of each energy production microgrid in the historical time period; the first sub-moment of the target time period is the start time of the target time period; the j-th sub-moment of the target time period is the end time of the target time period; Step S140: According to the predicted energy production list set A, determine the total energy production of several energy production microgrids at each sub-time of the target time period, and obtain the total energy production list B = (B1, B2, ..., B i ,...,B j ), where B i B is the total energy production of several energy production microgrids at the i-th sub-time of the target time period; i =∑ m=1 n A mi ; Step S150: According to the total energy production list B, determine the cumulative energy production of several energy production microgrids at each sub-time in the target time period, and obtain the cumulative energy production list C = (C1, C2, ..., C i ,...,C j ), where C i is the cumulative energy production of several energy production microgrids at the i-th sub-time in the target time period; C i =∑ s=1 i B s .

[0006] In an exemplary embodiment of the present application, step S200 includes: Step S210: Divide the historical time period into a number of historical sub-time periods, the length of each historical sub-time period is the same as the length of the target time period, and the start time of each historical sub-time period is 0:00 on the date corresponding to the historical sub-time period, and the end time of each historical sub-time period is 24:00 on the date corresponding to the historical sub-time period; the number of historical sub-moments in each historical sub-time period is equal to the number of sub-moments in the target time period, and the length of the time period between each two adjacent historical sub-moments is the same as the length of the time period between each two adjacent sub-moments in the target time period; Step S220: Obtain the historical energy consumption of each power load in each historical sub-time period to obtain a historical energy consumption list set D1, D2, ..., D a ,...,D b ; Where a=1,2,...,b; b is the number of electrical loads; D a is the historical energy consumption list set corresponding to the a-th electrical load; D a =(D a1 ,D a2 ,...,D ak ,...,D ah ), k=1,2,...,h, h is the number of historical sub-periods, D akis a list of historical energy consumption corresponding to the a-th power load in the k-th historical sub-time period; D ak =(D ak1 ,D ak2 ,...,D aki ,...,D akj );D aki is the historical energy consumption of the a-th power load at the i-th historical sub-time in the k-th historical sub-time period; Step S230: determine the total historical energy consumption of a number of power loads in each historical sub-time period to obtain a list set of total historical energy consumption E=(E1, E2, ..., E k ,...,E h ), where E k is a list of the total historical energy consumption of several power loads corresponding to the kth historical sub-time period; E k =(E k1 ,E k2 ,...,E ki ,...,E kj );E ki is the total historical energy consumption of several power loads at the i-th historical sub-time in the k-th historical sub-time period; E ki =∑ a=1 b D aki ; Step S240: Determine the target total energy consumption of a plurality of power loads at each sub-moment of the target time period according to the historical total energy consumption list set E, so as to obtain the target total energy consumption list set F=(F1, F2, ..., F i ,...,F j ), where F i is the target total energy consumption of several power loads at the i-th sub-moment in the target time period; F i =∑ k=1 h E ki / h; Step S250: According to the target total energy consumption list set F, the cumulative energy consumption of several power loads at each sub-time of the target time period is determined to obtain a cumulative energy consumption list G=(G1, G2, ..., G i ,...,G j ), where G i G is the cumulative energy consumption of several power loads at the i-th sub-time in the target time period; i =∑ s=1 i F s .

[0007] In an exemplary embodiment of the present application, step S300 includes: Step S310, traverse each sub-time in the target time period in turn, if C i ≥G i , and C t >G t , C i+1 <G i+1 , then the i-th sub-moment of the target time period is determined as the target sub-moment; where t=1,...,i-1.

[0008] In an exemplary embodiment of the present application, step S310 further includes: Step S311: if C1<G1, then obtain the total amount of remaining energy C0 of several energy production microgrids at the start time of the target time period; Step S312, set B1=B1+C0, and return to step S150.

[0009] In an exemplary embodiment of the present application, step S310 further includes: Step S313: If the cumulative energy production corresponding to each sub-moment of the target time period is greater than the cumulative energy consumption corresponding to the sub-moment, a plurality of power loads are controlled to be connected to each energy production microgrid within the target time period.

[0010] In an exemplary embodiment of the present application, step S400 includes: Step S410, obtaining a number of low-power consumption time periods corresponding to the target area in the target time period; Step S420: If there is a low-power consumption time period in the time period between the start time of the target time period and the target sub-time, the low-power consumption time period before the target sub-time is determined as the adjustment time period.

[0011] In an exemplary embodiment of the present application, step S420 further includes: Step S421: If there is no low-power consumption period in the time period between the start time of the target time period and the target sub-time, obtain the length of each low-power consumption period corresponding to the target area in the target time period, and obtain a list of low-power consumption period lengths H=(H1, H2, ..., H u ,...,H v ), where u=1,2,...,v; v is the number of low-consumption time periods corresponding to the target area in the target time period; H u is the length of the u-th electricity consumption valley time period corresponding to the target area in the target time period; Step S422: determine a time period with the start time of the target time period as the start time and the length of the low-power consumption time period corresponding to MIN(H) as the length of the time period as the adjustment time period; wherein MIN() is a preset minimum value determination function.

[0012] In an exemplary embodiment of the present application, step S500 includes: Step S510, obtaining the accumulated energy consumption w1 corresponding to the start time of the adjustment time period and the accumulated energy consumption w2 corresponding to the end time of the adjustment time period; Step S520, obtaining the cumulative energy consumption w3 corresponding to the next sub-moment of the target sub-moment and the cumulative energy production w4 corresponding to the next sub-moment of the target sub-moment; Step S530: If (w2-w1)≥(w3-w4), the total energy consumption in the adjustment time period is determined to be zero, and the process returns to step S250.

[0013] In an exemplary embodiment of the present application, step S530 further includes: Step S531, if (w2-w1)<(w3-w4), then obtain the length d1 of the adjustment time period; Step S532: adjust the length of the adjustment time period to d1+(w3-w4-w2+w1)×d1 / (w2-w1).

[0014] The present invention has at least the following beneficial effects: The building microgrid low-carbon integrated cluster control system of the present invention is used to adjust the power supply to the power load. First, the cumulative energy production of several energy production microgrids at each sub-moment of the target time period and the cumulative energy consumption of several power loads at each sub-moment of the target time period are determined, and then each sub-moment is traversed in turn. According to the cumulative energy production corresponding to each sub-moment and the cumulative energy consumption corresponding to the sub-moment, the target sub-moment is determined, and then the power consumption valley time period before the target sub-moment in the target time period is determined as the adjustment time period. According to the total energy consumption corresponding to the adjustment time period, the cumulative energy consumption corresponding to the next sub-moment of the target sub-moment and the cumulative energy consumption corresponding to the next sub-moment of the target sub-moment, the target sub-moment is determined. The difference in cumulative production capacity is used to adjust the total energy consumption corresponding to the adjustment time period, and the cumulative energy consumption corresponding to the target time period is recalculated until there is no target sub-moment in the target time period, so as to predict all adjustment time periods in the target time period, and finally control a number of power loads to be connected to the municipal power grid in each adjustment time period of the target time period, and to be connected to the energy production microgrid in the non-adjustment time period of the target time period, so as to realize flexible power adjustment of power loads, so that the local energy production and energy load in the target area are basically balanced, and the power energy complementarity is realized. When the energy production supply is insufficient to maintain the energy load, the power load and the municipal power grid are flexibly interacted. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 A connection diagram of a building microgrid low-carbon integrated cluster control system provided by an embodiment of the present invention; Figure 2 The present invention provides a flowchart of a method executed by a building microgrid low-carbon integrated cluster control system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0017] 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 those skilled in the art without creative work are within the scope of protection of the present invention.

[0018] The building microgrid low-carbon integrated cluster control system described in this application is an integrated intelligent control system, which mainly targets various energy production microgrids in buildings, including but not limited to distributed solar power generation systems, small wind power generation equipment, energy storage systems (such as batteries) and various power loads in the building, etc., to perform unified power coordination control to achieve the goal of low-carbon operation.

[0019] like Figure 1 As shown in the figure, the building microgrid low-carbon integrated cluster control system is connected to the city power grid, several energy production microgrids and several power loads. Among them, the city power grid is a public power grid, the energy production microgrid is a power grid that produces electricity according to the corresponding energy type (among which, the energy types corresponding to the energy production microgrid are all new energy, such as the energy production microgrid with the energy type of wind energy is used to convert wind energy into electricity, and the energy production microgrid with the energy type of solar energy is used to convert solar energy into electricity, etc.), and the power load is various loads in the building that uses electricity.

[0020] like Figure 2 As shown, the power consumption coordination control method of the building microgrid low-carbon integrated cluster control system for the power load is the following steps: Step S100: determining the cumulative energy production of a plurality of energy production microgrids at each sub-moment in the target time period according to a plurality of energy production influencing factors of the target area in the target time period; The target area is the geographical area where several energy-producing microgrids are located.

[0021] The start time of the target time period is 0:00 on the day after the current date, and the end time of the target time period is 24:00 on the day after the current date, that is, the target time period is the whole day of the day after the current date. If the current day is the 3rd, the target time period is the whole day of the 4th. By determining the energy production and energy consumption of the target time period, the power load within the target time period is predicted and adjusted. The first sub-moment of the target time period is the start time of the target time period, and the last sub-moment of the target time period is the end time of the target time period. The length of the time period between each adjacent sub-moments of the target time period is the same, and the sub-moment can be every hour of the target time period, that is, the length of the time period between each adjacent sub-moments is one hour, wherein the sub-moments can be adjusted automatically according to the power demand.

[0022] The energy production influencing factors are factors that affect the energy production of each type of energy production microgrid. For example, the energy production influencing factors of an energy production microgrid whose energy type is wind energy may be weather factors such as wind speed and wind direction in the target area during the target time period.

[0023] Further, as a feasible embodiment, step S100 includes steps S110 to S150: Step S110, obtaining several energy production influencing factors of the target area within the target time period; Energy production influencing factors can be obtained through weather forecasts and other means.

[0024] Step S120: classify a plurality of energy production influencing factors according to the energy type corresponding to each energy production microgrid to obtain an energy production influencing factor group corresponding to each energy production microgrid; The energy production influencing factor group corresponding to the energy production microgrid includes a plurality of energy production influencing factors corresponding to the energy type of the energy production microgrid.

[0025] Step S130: Input each energy production influencing factor group into a preset prediction model to obtain the predicted energy production of each energy production microgrid output by the prediction model at each sub-time of the target time period, and determine the predicted energy production list set A=(A1, A2, ..., A m ,...,A n ), where m=1,2,...,n; n is the number of energy production microgrids; A m A is the predicted energy production list corresponding to the mth energy production microgrid; m =(A m1 ,A m2 ,...,A mi ,...,A mj ), i=1,2,...,j, j is the number of sub-times in the target time period, A mi The predicted energy production of the mth energy production microgrid at the i-th sub-moment of the target time period; The prediction model is obtained by training the energy production of each energy production microgrid in a historical time period, that is, obtaining the energy production of each energy production microgrid in a historical time period and the corresponding energy production influencing factor in the historical time period, and training them as samples to obtain the prediction model, wherein the training method of the prediction model is an existing model training method, so it will not be repeated here.

[0026] Step S140: According to the predicted energy production list set A, determine the total energy production of several energy production microgrids at each sub-time of the target time period, and obtain the total energy production list B = (B1, B2, ..., B i ,...,B j ), where B i B is the total energy production of several energy production microgrids at the i-th sub-time of the target time period; i =∑ m=1 n A mi ; The total energy production is the total amount of electrical energy produced by all energy-producing microgrids in the time period between two adjacent sub-times of the target time period.

[0027] Step S150: According to the total energy production list B, determine the cumulative energy production of several energy production microgrids at each sub-time in the target time period, and obtain the cumulative energy production list C = (C1, C2, ..., C i ,...,C j ), where C i is the cumulative energy production of several energy production microgrids at the i-th sub-time in the target time period; C i =∑ s=1 i B s .

[0028] The cumulative energy production is the total amount of electric energy produced by all energy-producing microgrids during the time period from the start time of the target time period to each sub-time.

[0029] Step S200, determining the accumulated energy consumption of a plurality of electrical loads at each sub-moment in the target time period according to the energy consumption of each electrical load in the historical time period; The end time of the historical time period is midnight of the current date, and the length of the historical time period is the preset time length.

[0030] Further, as a feasible embodiment, step S200 includes steps S210 to S250: Step S210: Divide the historical time period into a number of historical sub-time periods, the length of each historical sub-time period is the same as the length of the target time period, and the start time of each historical sub-time period is 0:00 on the date corresponding to the historical sub-time period, and the end time of each historical sub-time period is 24:00 on the date corresponding to the historical sub-time period; The number of historical sub-moments in each historical sub-time period is equal to the number of sub-moments in the target time period, and the length of the time period between each two adjacent historical sub-moments is the same as the length of the time period between each two adjacent sub-moments in the target time period.

[0031] The historical time period is divided into several historical sub-time periods of the same length as the target time period, and the start time and end time are also similar to the target time period, which are all from 0:00 to 24:00 on the same day, so that the historical sub-time periods become comparison samples of the target time period, making the predicted energy consumption in the target time period more accurate.

[0032] Step S220: Obtain the historical energy consumption of each power load in each historical sub-time period to obtain a historical energy consumption list set D1, D2, ..., Da ,...,D b ; Where a=1,2,...,b; b is the number of electrical loads; D a is the historical energy consumption list set corresponding to the a-th electrical load; D a =(D a1 ,D a2 ,...,D ak ,...,D ah ), k=1,2,...,h, h is the number of historical sub-periods, D ak is a list of historical energy consumption corresponding to the a-th power load in the k-th historical sub-time period; D ak =(D ak1 ,D ak2 ,...,D aki ,...,D akj );D aki is the historical energy consumption of the a-th power load at the i-th historical sub-time in the k-th historical sub-time period; Step S230: determine the total historical energy consumption of a number of power loads in each historical sub-time period to obtain a list set of total historical energy consumption E=(E1, E2, ..., E k ,...,E h ), where E k is a list of the total historical energy consumption of several power loads corresponding to the kth historical sub-time period; E k =(E k1 ,E k2 ,...,E ki ,...,E kj );E ki is the total historical energy consumption of several power loads at the i-th historical sub-time in the k-th historical sub-time period; E ki =∑ a=1 b D aki ; Step S240: Determine the target total energy consumption of a plurality of power loads at each sub-moment of the target time period according to the historical total energy consumption list set E, so as to obtain the target total energy consumption list set F=(F1, F2, ..., F i ,...,F j ), where F i is the target total energy consumption of several power loads at the i-th sub-moment in the target time period; F i =∑ k=1 h E ki / h; The average of the total energy consumption of all electrical loads at each sub-moment is determined as the target total energy consumption corresponding to the sub-moment, so that the cumulative energy consumption within the predicted target time period is more balanced and the prediction error is reduced.

[0033] Step S250: According to the target total energy consumption list set F, the cumulative energy consumption of several power loads at each sub-time of the target time period is determined to obtain a cumulative energy consumption list G=(G1, G2, ..., G i ,...,G j ), where G i G is the cumulative energy consumption of several power loads at the i-th sub-time in the target time period; i =∑ s=1 i F s .

[0034] The units of energy consumption and energy production in this application may be kilowatt-hours or kilowatts of power.

[0035] Step S300, traverse each sub-moment in the target time period in turn, if the cumulative energy production corresponding to any sub-moment is greater than or equal to the cumulative energy consumption corresponding to the sub-moment, and the cumulative energy production corresponding to any sub-moment before the sub-moment in the target time period is greater than the cumulative energy consumption corresponding to any sub-moment before the sub-moment, and the cumulative energy production corresponding to the sub-moment after the sub-moment is less than the cumulative energy consumption corresponding to the sub-moment after the sub-moment, then determine the sub-moment as the target sub-moment; The target sub-time is the time when the power supply is about to fall short of the demand, indicating the time when the energy provider of the power load needs to be switched and adjusted.

[0036] Wherein, step S300 includes step S313-step S312: Step S313, traverse each sub-moment in the target time period in turn, and if the cumulative energy production corresponding to each sub-moment in the target time period is greater than the cumulative energy consumption corresponding to the sub-moment, control a number of power loads to connect to each energy production microgrid in the target time period; If the cumulative energy production corresponding to each sub-moment of the target time period is greater than the cumulative energy consumption corresponding to the sub-moment, it means that within the target time period, the electric energy generated by the energy production microgrid is sufficient to meet the electricity demand of all power loads, and there is no need for the municipal power grid to supply power to the power loads, so the energy production microgrid can achieve self-sufficiency in the power loads. Therefore, a number of power loads are controlled to be connected to each energy production microgrid within the target time period.

[0037] Step S310: If C i ≥G i , and Ct >G t , C i+1 <G i+1 , then the i-th sub-moment of the target time period is determined as the target sub-moment; where t=1,...,i-1; Step S311: If C1<G1, the total amount of remaining energy C0 of several energy production microgrids at the start time of the target time period is obtained, and step S312 is executed; Step S312, set B1=B1+C0, and return to step S150.

[0038] If the cumulative energy production at the start time of the target time period is less than the cumulative energy consumption, it means that the energy production microgrid cannot meet the electricity demand of the power load at the start time of the target time period, and the municipal power grid is required to provide electricity to the power load at the start time of the target time period. In order to reduce the number of switching between the municipal power grid and the energy production microgrid, and reduce carbon emissions, at this time, the total amount of remaining energy of the previous day of the target time period is added to the cumulative energy production at the start time of the target time period. If the sum is still less than the cumulative energy consumption at the start time of the target time period, then it is determined to control the municipal power grid to supply power to the power load at the start time of the target time period.

[0039] Among them, the determination of the target sub-moment can also be determined by setting an energy consumption difference, that is, traversing each moment in the target time period in turn, when the difference between the cumulative energy production and the cumulative energy consumption corresponding to a certain moment is less than or equal to the set energy consumption difference, and the difference between the cumulative energy production and the cumulative energy consumption corresponding to the moments after this moment becomes smaller and smaller, until the cumulative energy production is lower than the cumulative energy consumption, the moment corresponding to the difference between the cumulative energy production and the cumulative energy consumption is less than or equal to the set energy consumption difference is determined as the target sub-moment, so as to leave some adjustment space and error allowance space for the power load, so that when there is still a certain difference between the cumulative energy production and the cumulative energy consumption, it is necessary to determine the adjustment time period and adjust the transmission end of the power load to avoid the influence of the adjustment of the transmission end on the normal power consumption of the power load.

[0040] Step S400: Determine the power consumption valley time period before the target sub-time within the target time period as the adjustment time period; The low electricity consumption period is the period corresponding to the low electricity consumption period of the target area. The low electricity consumption period is assessed by the local power company in the target area, and the low electricity consumption period is determined as the adjustment period. The adjustment period is the period when the municipal power grid adjusts the power supply to the power load, so that the power load is supplied with power during the low electricity consumption period of the municipal power grid, thereby reducing electricity costs while also reducing carbon emissions.

[0041] Wherein, step S400 includes steps S410 to S422: Step S410, obtaining a number of low-power consumption time periods corresponding to the target area in the target time period; Step S420: If there is a low-power consumption time period in the time period between the start time of the target time period and the target sub-time, the low-power consumption time period before the target sub-time is determined as the adjustment time period; Step S421: If there is no low-power consumption period in the time period between the start time of the target time period and the target sub-time, obtain the length of each low-power consumption period corresponding to the target area in the target time period, and obtain a list of low-power consumption period lengths H=(H1, H2, ..., H u ,...,H v ), where u=1,2,...,v; v is the number of low-consumption time periods corresponding to the target area in the target time period; H u is the length of the u-th electricity consumption valley time period corresponding to the target area in the target time period; Step S422: determine a time period with the start time of the target time period as the start time and the length of the low-power consumption time period corresponding to MIN(H) as the length of the time period as the adjustment time period; wherein MIN() is a preset minimum value determination function.

[0042] If there is a period of low electricity consumption before the target sub-moment, the previous period of low electricity consumption will be determined as the adjustment period; if there is no period of low electricity consumption before the target sub-moment, the length of the adjustment period will be determined based on the length of the period of low electricity consumption, and the start time of the target period will be set as the start time of the adjustment period.

[0043] Step S500: If the total energy consumption corresponding to the adjustment time period is greater than or equal to the difference between the cumulative energy consumption corresponding to the next sub-moment after the target sub-moment and the cumulative energy production corresponding to the next sub-moment after the target sub-moment, the total energy consumption corresponding to the adjustment time period is adjusted to zero, and the cumulative energy consumption corresponding to the target time period is recalculated, and the process returns to step S300 until there is no target sub-moment in the target time period. The total energy consumption corresponding to the adjustment time period is adjusted to zero, which means that during the adjustment time period, the power load is connected to the municipal power grid, and the energy production microgrid stores new energy without consuming energy to meet the safe electricity consumption of the power load before the target sub-time.

[0044] Further, as a feasible embodiment, step S500 includes steps S510 to S532: Step S510, obtaining the accumulated energy consumption w1 corresponding to the start time of the adjustment time period and the accumulated energy consumption w2 corresponding to the end time of the adjustment time period; Step S520, obtaining the cumulative energy consumption w3 corresponding to the next sub-moment of the target sub-moment and the cumulative energy production w4 corresponding to the next sub-moment of the target sub-moment; Step S530: If (w2-w1)≥(w3-w4), the total energy consumption in the adjustment time period is determined to be zero, and the process returns to step S250; Step S531: if (w2-w1)<(w3-w4), then obtain the length d1 of the adjustment time period, and execute step S532; Step S532, adjust the length of the adjustment time period to d1+(w3-w4-w2+w1)×d1 / (w2-w1), and determine the total energy consumption in the adjusted adjustment time period to zero, and return to step S250.

[0045] After adjusting the adjustment time period, the cumulative energy consumption corresponding to the target time period is recalculated, that is, steps S300 to S500 are executed again, and in the cumulative energy consumption list corresponding to the new target time period, a new target sub-moment and a new adjustment time period are re-determined, and the total energy consumption of the new adjustment time period is adjusted again. This step is repeated until there is no target sub-moment in the latest target time period (indicating that there is no need to determine the adjustment time period at this time, and within the currently determined target time period, the power load can already meet the standard for safe power use, that is, the cumulative energy consumption within the target time period is always lower than the cumulative energy production), and step S600 is executed.

[0046] In addition, the adjustment time period can also be shortened. For example, when the difference between (w2-w1) and (w3-w4) is too large (greater than the preset difference threshold), it means that the electricity consumption of the municipal power grid during the adjustment time period is too large. Therefore, in order to reduce electricity costs and reduce carbon emissions, it is necessary to shorten the adjustment time period. The method of shortening the time is the same as the method of extending the adjustment time period, that is, adjusting the length of the adjustment time period to d1-(w2-w1-w3+w4)×d1 / (w2-w1).

[0047] Step S600, control a plurality of power loads to be connected to the city power grid during each adjustment time period of the target time period, and control a plurality of power loads to be connected to each energy production microgrid during the non-adjustment time period of the target time period.

[0048] When supplying power to the power load in the target time period, the power supply end can also be adjusted according to the real-time power consumption of the power load. For example, when the power load has a tendency to increase energy consumption and the energy production microgrid cannot meet the demand, it is necessary to recalculate the power consumption of the power load and adjust the power supply end in real time to ensure the power safety of the power load. When the power load consumes electricity and the energy production microgrid produces electricity, a real-time energy consumption curve and a real-time production capacity curve can be drawn, as well as a cumulative energy consumption curve, a cumulative production capacity curve, etc., to statistically analyze the energy consumption of the power load and the production capacity data of the energy production microgrid for real-time viewing by the staff. The cumulative energy consumption data and cumulative production capacity data of the target time period that have been predicted can be corrected and tested based on the real-time energy consumption data and production capacity data in the target time period.

[0049] The building microgrid low-carbon integrated cluster control system of the present invention is used to adjust the power supply to the power load. First, the cumulative energy production of several energy-producing microgrids at each sub-moment of the target time period and the cumulative energy consumption of several power loads at each sub-moment of the target time period are determined, and then each sub-moment is traversed in turn. According to the cumulative energy production corresponding to each sub-moment and the cumulative energy consumption corresponding to the sub-moment, the target sub-moment is determined, and then the power consumption valley time period before the target sub-moment in the target time period is determined as the adjustment time period. According to the total energy consumption corresponding to the adjustment time period, the cumulative energy consumption corresponding to the next sub-moment of the target sub-moment, and the cumulative energy production corresponding to the next sub-moment of the target sub-moment, the target sub-moment is determined. The energy difference is calculated, and the total energy consumption corresponding to the adjustment time period is adjusted, and the cumulative energy consumption corresponding to the target time period is recalculated until there is no target sub-moment in the target time period, so as to predict all adjustment time periods in the target time period, and finally control a number of power loads to be connected to the municipal power grid in each adjustment time period of the target time period, and to be connected to the energy production microgrid in the non-adjustment time period of the target time period, so as to realize flexible power adjustment of power loads, so that the local energy production and energy load in the target area are basically balanced, and the power energy complementarity is realized to reduce carbon emissions, and when the energy production supply is insufficient to maintain the energy load, the power load and the municipal power grid are flexibly interacted.

[0050] An embodiment of the present invention further provides a computer program product, which includes program code. When the program product is run on an electronic device, the program code is used to enable the electronic device to execute the steps of the method according to various exemplary embodiments of the present invention described above in this specification.

[0051] In addition, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0052] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by combining software with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0053] In an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

[0054] It will be appreciated by those skilled in the art that various aspects of the present invention may be implemented as a system, method or program product. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as a "circuit", "module" or "system".

[0055] The electronic device according to this embodiment of the present invention is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0056] The electronic device is presented in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: the at least one processor mentioned above, the at least one storage device mentioned above, and a bus connecting different system components (including storage devices and processors).

[0057] The storage stores program codes, which can be executed by the processor, so that the processor executes the steps according to various exemplary embodiments of the present invention described in the above “Exemplary Method” section of this specification.

[0058] The memory may include readable media in the form of volatile memory, such as random access memory (RAM) and / or cache memory, and may further include read only memory (ROM).

[0059] The storage may also include a program / utility having a set (at least one) of program modules, such program modules including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0060] The bus may represent one or more of several types of bus structures including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures.

[0061] The electronic device may also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device, and / or any device that enables the electronic device to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface. Furthermore, the electronic device may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter.

[0062] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present specification is stored. In some possible implementations, various aspects of the present invention can also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary embodiments of the present invention described in the above "Exemplary Method" section of the present specification.

[0063] The program product may be any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0064] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0065] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0066] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0067] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0068] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.

[0069] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. Building microgrid low-carbon integrated cluster control system, characterized by: The building microgrid low-carbon integrated cluster control system is connected to the city power grid, several energy production microgrids and several power loads; The building microgrid low-carbon integrated cluster control system is used to execute the following method: Step S100, according to a plurality of energy production influencing factors of a target area within a target time period, determine the cumulative energy production of a plurality of energy production microgrids at each sub-moment of the target time period; the target area is a geographical area where the plurality of energy production microgrids are located; the start time of the target time period is 0:00 on the day after the current date, and the end time of the target time period is 24:00 on the day after the current date; the length of the time period between each two adjacent sub-moments of the target time period is the same; Step S200: Determine the cumulative energy consumption of a number of the power loads at each sub-moment of the target time period according to the energy consumption of each power load in the historical time period; the end time of the historical time period is zero o'clock on the current date, and the length of the historical time period is a preset time length; Step S300, traverse each of the sub-moments in the target time period in sequence, if the cumulative energy production corresponding to any of the sub-moments is greater than or equal to the cumulative energy consumption corresponding to the sub-moment, and the cumulative energy production corresponding to any sub-moment before the sub-moment in the target time period is greater than the cumulative energy consumption corresponding to any sub-moment before the sub-moment, and the cumulative energy production corresponding to the sub-moment after the sub-moment is less than the cumulative energy consumption corresponding to the sub-moment after the sub-moment, then determine the sub-moment as the target sub-moment; Step S400: Determine the power consumption valley time period before the target sub-time in the target time period as the adjustment time period; the power consumption valley time period is the time period corresponding to the power consumption valley period of the target area; Step S500: If the total energy consumption corresponding to the adjustment time period is greater than or equal to the difference between the cumulative energy consumption corresponding to the next sub-moment after the target sub-moment and the cumulative energy production corresponding to the next sub-moment after the target sub-moment, the total energy consumption corresponding to the adjustment time period is adjusted to zero, and the cumulative energy consumption corresponding to the target time period is recalculated, and the process returns to step S300 until there is no target sub-moment in the target time period. Step S600, controlling a plurality of the power loads to be connected to the municipal power grid during each adjustment time period of the target time period, and controlling a plurality of the power loads to be connected to each of the energy production microgrids during the non-adjustment time period of the target time period.

2. The building microgrid low-carbon integrated cluster control system according to claim 1 is characterized in that: The step S100 includes: Step S110, obtaining a plurality of energy production influencing factors of the target area within a target time period; Step S120: classify the plurality of energy production influencing factors according to the energy type corresponding to each of the energy production microgrids to obtain an energy production influencing factor group corresponding to each of the energy production microgrids; the energy production influencing factor group corresponding to the energy production microgrid includes a plurality of energy production influencing factors corresponding to the energy type of the energy production microgrid; Step S130: Input each of the energy production influencing factor groups into a preset prediction model to obtain the predicted energy production of each of the energy production microgrids output by the prediction model at each sub-time of the target time period, and determine the predicted energy production list set A=(A1, A2, ..., A m ,...,A n ), where m=1,2,...,n; n is the number of energy production microgrids; A m A is a list of predicted energy production corresponding to the mth energy production microgrid; m =(A m1 ,A m2 ,...,A mi ,...,A mj ); i=1,2,...,j; j is the number of sub-times in the target time period; A mi is the predicted energy production of the mth energy production microgrid at the i-th sub-moment of the target time period; the prediction model is obtained by training the energy production of each energy production microgrid in the historical time period; the first sub-moment of the target time period is the start time of the target time period; the j-th sub-moment of the target time period is the end time of the target time period; Step S140: According to the predicted energy production list set A, determine the total energy production of several energy production microgrids at each sub-time of the target time period, and obtain the total energy production list B = (B1, B2, ..., B i ,...,B j ), where B i The total energy production of the energy production microgrids at the i-th sub-moment of the target time period; B i =∑ m=1 n A mi ; Step S150: According to the total energy production list B, determine the cumulative energy production of several energy production microgrids at each sub-time of the target time period, and obtain the cumulative energy production list C = (C1, C2, ..., C i ,...,C j ), where C i is the cumulative energy production of a number of the energy production microgrids at the i-th sub-moment of the target time period; C i =∑ s=1 i B s .

3. The low-carbon integrated cluster control system for building microgrid according to claim 2 is characterized in that: The step S200 includes: Step S210: Divide the historical time period into a plurality of historical sub-time periods, wherein the length of each historical sub-time period is the same as the length of the target time period, and the start time of each historical sub-time period is 0:00 of the date corresponding to the historical sub-time period, and the end time of each historical sub-time period is 24:00 of the date corresponding to the historical sub-time period; the number of historical sub-moments in each historical sub-time period is equal to the number of sub-moments in the target time period, and the length of the time period between each two adjacent historical sub-moments is the same as the length of the time period between each two adjacent sub-moments in the target time period; Step S220: Obtain the historical energy consumption of each of the power loads in each of the historical sub-time periods to obtain a historical energy consumption list set D1, D2, ..., D a ,...,D b ; Wherein, a=1,2,...,b; b is the number of the electrical loads; D a is a list set of historical energy consumption corresponding to the a-th electrical load; D a =(D a1 ,D a2 ,...,D ak ,...,D ah ); k=1,2,...,h; h is the number of the historical sub-time periods; D ak A list of historical energy consumption corresponding to the a-th power load in the k-th historical sub-time period; D ak =(D ak1 ,D ak2 ,...,D aki ,...,D akj );D aki The historical energy consumption of the a-th power load at the i-th historical sub-moment in the k-th historical sub-time period; Step S230: determine the total historical energy consumption of a plurality of the power loads in each of the historical sub-time periods to obtain a list set of total historical energy consumption E=(E1, E2, ..., E k ,...,E h ), where E k is a list of historical total energy consumption of a number of the power loads corresponding to the kth historical sub-time period; E k =(E k1 ,E k2 ,...,E ki ,...,E kj );E ki is the total historical energy consumption of the plurality of power loads at the i-th historical sub-moment in the k-th historical sub-time period; E ki =∑ a= 1 b D aki ; Step S240: Determine the target total energy consumption of a plurality of the power loads at each sub-moment of the target time period according to the historical total energy consumption list set E, so as to obtain a target total energy consumption list set F=(F1, F2, ..., F i ,...,F j ), where F i is the target total energy consumption of the plurality of electrical loads at the i-th sub-moment in the target time period; F i =∑ k=1 h E ki / h; Step S250: According to the target total energy consumption list set F, determine the cumulative energy consumption of a plurality of the power loads at each sub-time of the target time period to obtain a cumulative energy consumption list G=(G1, G2, ..., G i ,...,G j ), where G i G is the cumulative energy consumption of a number of the electrical loads at the i-th sub-moment of the target time period; i =∑ s=1 i F s .

4. The low-carbon integrated cluster control system for building microgrid according to claim 3 is characterized in that: The step S300 includes: Step S310, traverse each of the sub-times in the target time period in turn, if C i ≥G i , and C t >G t , C i+1 <G i+1 , then the i-th sub-moment of the target time period is determined as the target sub-moment; wherein t=1,...,i-1.

5. The low-carbon integrated cluster control system for building microgrid according to claim 4 is characterized in that: The step S310 further includes: Step S311: if C1<G1, obtaining the total remaining energy C0 of the energy production microgrids at the start time of the target time period; Step S312, set B1=B1+C0, and return to step S150.

6. The low-carbon integrated cluster control system for building microgrid according to claim 5 is characterized in that: The step S310 further includes: Step S313: If the cumulative energy production corresponding to each sub-moment of the target time period is greater than the cumulative energy consumption corresponding to the sub-moment, control a plurality of power loads to connect to each energy production microgrid within the target time period.

7. The low-carbon integrated cluster control system for building microgrid according to claim 6 is characterized in that: The step S400 includes: Step S410, obtaining a number of low-power consumption time periods corresponding to the target area in the target time period; Step S420: If there is a low-power consumption time period in the time period between the start time of the target time period and the target sub-time, the low-power consumption time period before the target sub-time is determined as the adjustment time period.

8. The low-carbon integrated cluster control system for building microgrid according to claim 7 is characterized in that: The step S420 further includes: Step S421: If there is no low-power consumption time period in the time period between the start time of the target time period and the target sub-time, obtain the length of each low-power consumption time period corresponding to the target area in the target time period, and obtain a low-power consumption time period length list H=(H1, H2, ..., H u ,...,H v ); where u=1,2,...,v; v is the number of low-power consumption time periods corresponding to the target area in the target time period; H u is the length of the u-th electricity consumption valley time period corresponding to the target area in the target time period; Step S422: determine a time period with the start time of the target time period as the starting time and the length of the low-power consumption time period corresponding to MIN(H) as the length of the time period as the adjustment time period; wherein MIN() is a preset minimum value determination function.

9. The low-carbon integrated cluster control system for building microgrid according to claim 8 is characterized in that: The step S500 includes: Step S510, obtaining the accumulated energy consumption w1 corresponding to the start time of the adjustment time period and the accumulated energy consumption w2 corresponding to the end time of the adjustment time period; Step S520, obtaining the cumulative energy consumption w3 corresponding to the next sub-moment of the target sub-moment and the cumulative energy production w4 corresponding to the next sub-moment of the target sub-moment; Step S530: If (w2-w1)≥(w3-w4), the total energy consumption in the adjustment time period is determined to be zero, and the process returns to step S250.

10. The building microgrid low-carbon integrated cluster control system according to claim 9, characterized in that: The step S530 further includes: Step S531: if (w2-w1)<(w3-w4), then obtain the length d1 of the adjustment time period; Step S532: adjust the length of the adjustment time period to d1+(w3-w4-w2+w1)×d1 / (w2-w1).

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