CN117200340A - New energy consumption capability assessment method based on uncertainty - Google Patents
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Abstract
The invention relates to a new energy consumption capability assessment method based on uncertainty, and belongs to the technical field of power distribution network analysis methods. The technical scheme is as follows: setting a region to be evaluated, and obtaining basic data information of network load storage in the region to be evaluated and a power grid operation mode; acquiring a source side distributed photovoltaic sunny day unit capacity output curve of an area to be evaluated, and carrying out target annual load value prediction by taking a transformer substation as granularity on a load side; coupling comparison is carried out on the typical load daily forecast time-sharing load trend of the transformer substation and the typical daily output curve of the photovoltaic power station, so that a coupling threshold value is obtained; calculating the medium voltage line digestion capacity under different load characteristics; and combining the power grid topology, and obtaining the combined digestion capacity of the evaluation area by following the principle that the next level is not more than the previous level. The invention converts the uncertainty of the source load into the evaluation of the digestion capability in a specific scene based on the historical running states of the new energy and the power grid, fully utilizes the existing data, and conveniently and efficiently calculates the partition and the whole digestion capability.
Description
Technical Field
The invention relates to a new energy consumption capability assessment method based on uncertainty, and belongs to the technical field of power distribution network analysis methods.
Background
In the background of the construction of a novel power system, the scale of the access of the centralized and distributed new energy into the power grid in the future is rapidly increased, and the installed capacity and the installed speed of the photovoltaic serving as the representatives of the new energy are rapidly developed. However, the new energy output mainly based on wind power and photovoltaic has obvious randomness, volatility and uncontrollability, and large-scale grid-connected digestion is always a difficult problem to be solved.
In the prior art, when the distributed photovoltaic power consumption capacity is evaluated, a simulation model of the power distribution network is generally required to be constructed, the new energy consumption capacity of the power distribution network is continuously tested out by taking the safe operation of the power distribution network as a boundary, but the dynamic modeling and simulation workload is huge, the modeling method is not universally applicable and has low efficiency, and a feasible and rapid evaluation method for the regional photovoltaic power consumption capacity is lacking currently.
Disclosure of Invention
The invention aims to provide a new energy consumption capability assessment method based on uncertainty, which is based on the historical operating states of new energy and a power grid, takes the number as the basis and the transformer substation as the granularity, converts the uncertainty of source load into the consumption capability assessment under a specific scene, fully utilizes the existing data, conveniently and efficiently calculates the regional and overall consumption capability, and effectively solves the problems in the background art.
The technical scheme of the invention is as follows: an uncertainty-based new energy consumption capability assessment method comprises the following steps:
s101, acquiring an area to be evaluated, and acquiring basic data information of the network load storage in the area to be evaluated and a power grid operation mode;
s102, acquiring a source side distributed photovoltaic sunny day unit capacity output curve of an area to be evaluated, and carrying out target annual load value prediction by taking a transformer substation as granularity on a load side;
s103, coupling comparison is carried out on the typical daily load forecast time-sharing load trend of the transformer substation and the typical daily output curve of the photovoltaic power station, and a coupling threshold value is obtained;
s104, calculating the medium voltage line capacity eliminating condition under different load characteristic conditions;
s105, combining the power grid topology, and obtaining the combined digestion capacity of the evaluation area according to the principle that the lower level is not greater than the upper level digestion capacity.
The step S101 specifically includes the following steps:
s201, acquiring an area to be evaluated, and collecting a typical distributed photovoltaic history output curve within one year;
s202, collecting historical annual load and typical daily load curves of the transformer substation in an area to be evaluated by taking the transformer substation as granularity;
and S203, drawing a topological graph of the regional power grid to be evaluated based on the target annual grid structure and the normal running mode of the power grid.
The step S102 specifically includes the following steps:
s301, obtaining a photoelectric conversion utilization rate, namely a typical daily output curve of unit capacity on a sunny day by utilizing a first calculation formula based on a typical distributed photovoltaic historical output curve within one year;
the first calculation formula is:
wherein P is Gi1 The output value of the unit capacity of the distributed photovoltaic at the moment i is obtained; p (P) Gi0n The actual output value of the distributed photovoltaic at the moment i under the condition of a certain sunny day in one year of history, wherein n is the number of sunny days in one year of history; m is the capacity of the distributed photovoltaic installation;
s302, predicting the target annual load of each transformer substation by adopting a trend extrapolation method by taking the transformer substation as granularity;
s303, obtaining a target annual typical daily load curve by using a second calculation formula based on the photovoltaic typical daily load curve of the substation in the same period;
the second calculation formula is:
wherein P is B2 The method is a target annual transformer substation typical daily maximum electricity load predicted value predicted by adopting a trend extrapolation method; p (P) B1 The current transformer station is a typical daily maximum electricity load value; p (P) Bi2 Load values at various moments of typical days of a target year; p (P) Bi1 The load value is the load value at each time of the typical day of the current year; i is the time of each integral point, and 0-23 is taken.
The step S103 specifically includes the following steps:
s401, formulating a basic principle of the digestion capability: the 110kV or 35kV power grid does not have the phenomenon of power reversal;
s402, coupling the time-sharing load trend of the typical load day of the target year of the transformer substation with the typical daily output curve of the distributed photovoltaic power station one by one, and obtaining a coupling threshold value by using a third calculation formula;
the third calculation formula is:
Y＝min(P Gi2 ＝P Bi2 )
wherein Y is a coupling threshold; p (P) Gi2 The output of the photovoltaic at the moment i is given; p (P) Bi2 The load value is a typical day i moment of a transformer substation target year;
s403, considering existing photovoltaic output of the current annual transformer substation on the basis of a coupling threshold, and obtaining new energy consumption capacity of each transformer substation by using a fourth calculation formula;
the fourth calculation formula is:
P BQ ＝Y-P BGi
wherein P is BQ The capacity is consumed for the target year of the transformer substation Q; y is a coupling threshold; p (P) SQ The existing photovoltaic output of the transformer substation Q.
The step S104 specifically includes the following steps:
s501, aiming at a typical daily load curve of a medium-voltage line in an area, classifying the medium-voltage line by adopting a cluster analysis method, and dividing labels into a residential main line, a commercial main line and an industrial main line;
s502, obtaining the maximum load condition of the medium-voltage line by using a fifth calculation formula based on the load data of the medium-voltage line in the last three years collected by the system;
the fifth calculation formula is:
wherein eta is x Is the line load rate; p (P) xi The load value at the moment of the current line i; l is the maximum current-carrying capacity of the line;
s503, combining the operational years of the medium-voltage line, the maximum load rate of the medium-voltage line and the line label classification, and forming average maximum load rates under different load characteristics and different operational years by utilizing a sixth calculation formula;
the sixth calculation formula is:
wherein eta is xjn The average maximum load rate of medium-voltage lines in n years of operation is the average maximum load rate of medium-voltage lines living as a main label;the kth residence is a main type tag, and the maximum load rate of the medium-voltage line is in operation for n years; k is the number of line in the residence type label in n years of operation; j represents a resident class;
s504, predicting the maximum annual load of the medium-voltage line by using a seventh calculation formula according to line classification labels and combining the average load rates under different operational years;
the seventh calculation formula is:
P xj ＝η xjn ·L
wherein P is xj A target annual maximum load forecast value of the main label line is used for residence; η (eta) xjn The average maximum load rate of the medium-voltage line in n years of operation is the average maximum load rate of the medium-voltage line in which the residence is a main label, and the value of n is the annual distance of the target year from the operation year; l is the maximum current-carrying capacity of the line;
s505, obtaining a typical daily load curve of the medium-voltage line in the target year by utilizing an eighth calculation formula based on the daily load curve of the medium-voltage line in the photovoltaic typical daily same period;
the eighth calculation formula is:
wherein P is xji2 Load value P of target annual i time of main label line living xj A target annual maximum load forecast value of the main label line is used for residence; p (P) xj1 The current residential line typical daily maximum electricity load value; p (P) xji1 The load value of each time of the typical day of the living label line in the current year; i is the time of each integral point, and 0 to 23 is taken;
s506, coupling the time-sharing load trend of the typical load day of the target year of the medium-voltage line with the typical daily output curve of the distributed photovoltaic power station one by one, and obtaining a coupling threshold value by using a ninth calculation formula;
the ninth calculation formula is:
Y＝min(P Gi2 ＝P xi2 )+0.8L
wherein Y is a coupling threshold; p (P) Gi2 The output of the photovoltaic at the moment i is given; p (P) xi2 The load value is a typical day i moment load value of a medium-voltage line in a target year, and L is the maximum current-carrying capacity of the line;
s507, considering the existing photovoltaic output of the medium voltage lines in the current year on the basis of the coupling threshold value, and obtaining new energy consumption capacity of each medium voltage line by using a tenth calculation formula;
the tenth calculation formula is:
P Xi ＝Y-P Si
wherein P is Xi The capacity is consumed for the medium-voltage line i in a target year; y is a coupling threshold; p (P) Si The photovoltaic output is already available for the medium-voltage line i.
The step S105 specifically includes the following steps:
s601, marking the digestion capacity of each level of power grid based on a drawn topological graph of the regional power grid to be evaluated;
s602, calculating the total value of the digestion capacity of medium-voltage lines carried by each transformer substation one by one;
s603, comparing the digestion capacity of the transformer substation level with the digestion capacity of the medium-voltage circuit level by utilizing an eleventh calculation formula according to the principle that the lower level is not more than the digestion capacity of the upper level, and finally obtaining the joint digestion capacity of the evaluation area;
the eleventh calculation formula is:
wherein P is B ′ Q The final capacity value P of the power supply range of the transformer substation Q is finally consumed in a target year BQ Calculating a target annual absorption capacity for a substation level;the method is the target annual capacity of the medium-voltage circuit i to which the transformer substation Q belongs.
The beneficial effects of the invention are as follows: based on the historical running states of new energy and the power grid, the method converts the uncertainty of the source load into the evaluation of the digestion capability in a specific scene by taking the number as the basis and the transformer substation as the granularity, and fully utilizes the existing data to conveniently and efficiently calculate the partition and the whole digestion capability.
Drawings
FIG. 1 is a general flow chart of the present invention;
FIG. 2 is a flow chart of the method of step S101 of the present invention;
FIG. 3 is a flow chart of the method of step S102 of the present invention;
FIG. 4 is a flow chart of the method of step S103 of the present invention;
FIG. 5 is a flow chart of the method of step S104 of the present invention;
fig. 6 is a flow chart of the method of step S105 of the present invention.
Detailed Description
The following describes the technical scheme of the present invention in further detail by referring to the accompanying drawings and examples, which are preferred examples of the present invention. It should be understood that the described embodiments are merely some, but not all, embodiments of the present invention; it should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
An uncertainty-based new energy consumption capability assessment method comprises the following steps:
s101, acquiring an area to be evaluated, acquiring basic data information of network load storage in the area to be evaluated, a power grid operation mode and the like;
s102, acquiring a source side distributed photovoltaic sunny unit capacity output curve of an area to be evaluated, and carrying out target annual load value prediction by taking a transformer substation (main transformer) as granularity on a load side;
s103, coupling and comparing the daily forecast time-sharing load trend of the typical load of the transformer substation (main transformer) with a typical daily output curve of the photovoltaic power station to obtain a coupling threshold;
s104, calculating the medium voltage line capacity eliminating condition under different load characteristic conditions;
s105, combining the power grid topology, and obtaining the combined digestion capacity of the evaluation area according to the principle that the lower level is not greater than the upper level digestion capacity.
The step S101 specifically includes the following steps:
s201, acquiring an area to be evaluated, and collecting a typical distributed photovoltaic history output curve within one year;
s202, collecting historical annual load and typical daily load curves of a transformer substation in an area to be evaluated by taking the transformer substation (main transformer) as granularity;
and S203, drawing a topological graph of the regional power grid to be evaluated based on the target annual grid structure and the normal running mode of the power grid.
The step S102 specifically includes the following steps:
s301, obtaining a photoelectric conversion utilization rate, namely a typical daily output curve of unit capacity on a sunny day by utilizing a first calculation formula based on a typical distributed photovoltaic historical output curve within one year;
the first calculation formula is:
wherein P is Gi1 The output value of the unit capacity of the distributed photovoltaic at the moment i is obtained; p (P) Gi0n The actual output value of the distributed photovoltaic at the moment i under the condition of a certain sunny day in one year of history, wherein n is the number of sunny days in one year of history; m is the capacity of the distributed photovoltaic installation;
s302, predicting the target annual load of each transformer substation by adopting a trend extrapolation method by taking the transformer substation (main transformer) as granularity;
s303, obtaining a target annual typical daily load curve by using a second calculation formula based on a photovoltaic typical daily load curve of a substation (main transformer) in the same period;
the second calculation formula is:
wherein P is B2 The method is a target annual transformer substation typical daily maximum electricity load predicted value predicted by adopting a trend extrapolation method; p (P) B1 The current transformer station is a typical daily maximum electricity load value; p (P) Bi2 Load values at various moments of typical days of a target year; p (P) Bi1 The load value is the load value at each time of the typical day of the current year; i is the time of each integral point, and 0-23 is taken.
The step S103 specifically includes the following steps:
s401, formulating a basic principle of the digestion capability: the 110kV or 35kV power grid does not have the phenomenon of power reversal;
s402, coupling the time-sharing load trend of the typical load day of the target year of the transformer substation with the typical daily output curve of the distributed photovoltaic power station one by one, and obtaining a coupling threshold value by using a third calculation formula;
the third calculation formula is:
Y＝min(P Gi2 ＝P Bi2 )
wherein Y is a coupling threshold; p (P) Gi2 The output of the photovoltaic at the moment i is given; p (P) Bi2 The load value is a typical day i moment of a transformer substation target year;
s403, considering existing photovoltaic output of the current annual transformer substation on the basis of a coupling threshold, and obtaining new energy consumption capacity of each transformer substation by using a fourth calculation formula;
the fourth calculation formula is:
P BQ ＝Y-P BGi
wherein P is BQ The capacity is consumed for the target year of the transformer substation Q; y is a coupling threshold; p (P) SQ The existing photovoltaic output of the transformer substation Q.
The step S104 specifically includes the following steps:
s501, aiming at a typical daily load curve of a medium-voltage line in an area, classifying the medium-voltage line by adopting a cluster analysis method, and dividing labels into a residential main line, a commercial main line and an industrial main line;
s502, obtaining the maximum load condition of the medium-voltage line by using a fifth calculation formula based on the load data of the medium-voltage line in the last three years collected by the system;
the fifth calculation formula is:
wherein eta is x Is the line load rate; p (P) xi The load value at the moment of the current line i; l is the maximum current-carrying capacity of the line;
s503, combining the operational years of the medium-voltage line, the maximum load rate of the medium-voltage line and the line label classification, and forming average maximum load rates under different load characteristics and different operational years by utilizing a sixth calculation formula;
the sixth calculation formula is:
wherein eta is xjn The average maximum load rate of medium-voltage lines in n years of operation is the average maximum load rate of medium-voltage lines living as a main label;the kth residence is a main type tag, and the maximum load rate of the medium-voltage line is in operation for n years; k is the number of line in the residence type label in n years of operation; j represents a resident class;
s504, predicting the maximum annual load of the medium-voltage line by using a seventh calculation formula according to line classification labels and combining the average load rates under different operational years;
the seventh calculation formula is:
P xj ＝η xjn ·L
wherein P is xj A target annual maximum load forecast value of the main label line is used for residence; η (eta) xjn The average maximum load rate of the medium-voltage line in n years of operation is the average maximum load rate of the medium-voltage line in which the residence is a main label, and the value of n is the annual distance of the target year from the operation year; l is the maximum current-carrying capacity of the line;
s505, obtaining a typical daily load curve of the medium-voltage line in the target year by utilizing an eighth calculation formula based on the daily load curve of the medium-voltage line in the photovoltaic typical daily same period;
the eighth calculation formula is:
wherein P is xji2 Load value P of target annual i time of main label line living xj A target annual maximum load forecast value of the main label line is used for residence; p (P) xj1 The current residential line typical daily maximum electricity load value; p (P) xji1 The load value of each time of the typical day of the living label line in the current year; i is the time of each integral point, and 0 to 23 is taken;
s506, coupling the time-sharing load trend of the typical load day of the target year of the medium-voltage line with the typical daily output curve of the distributed photovoltaic power station one by one, and obtaining a coupling threshold value by using a ninth calculation formula;
the ninth calculation formula is:
Y＝min(P Gi2 ＝P xi2 )+0.8L
wherein Y is a coupling threshold; p (P) Gi2 The output of the photovoltaic at the moment i is given; p (P) xi2 The load value is a typical day i moment load value of a medium-voltage line in a target year, and L is the maximum current-carrying capacity of the line;
s507, considering the existing photovoltaic output of the medium voltage lines in the current year on the basis of the coupling threshold value, and obtaining new energy consumption capacity of each medium voltage line by using a tenth calculation formula;
the tenth calculation formula is:
P Xi ＝Y-P Si
wherein P is Xi The capacity is consumed for the medium-voltage line i in a target year; y is a coupling threshold; p (P) Si The photovoltaic output is already available for the medium-voltage line i.
The step S105 specifically includes the following steps:
s601, marking the digestion capacity of each level of power grid based on a drawn topological graph of the regional power grid to be evaluated;
s602, calculating the total value of the digestion capacity of medium-voltage lines carried by each transformer substation one by one;
s603, comparing the digestion capacity of the transformer substation level with the digestion capacity of the medium-voltage circuit level by utilizing an eleventh calculation formula according to the principle that the lower level is not more than the digestion capacity of the upper level, and finally obtaining the joint digestion capacity of the evaluation area;
the eleventh calculation formula is:
wherein P is B ′ Q The final capacity value P of the power supply range of the transformer substation Q is finally consumed in a target year BQ Calculating a target annual elimination for a substation levelNano capability;the method is the target annual capacity of the medium-voltage circuit i to which the transformer substation Q belongs.
In the embodiment of the invention, the calculated digestion capacity of each medium-voltage circuit in the region to be evaluated and the digestion capacity of each transformer substation are marked in a power grid topological graph.
In the embodiment of the invention, according to the marked power grid topological graph and the principle that the next level is not more than the previous level of the capacity, the 'transformer substation' is taken as granularity, the total capacity of the transformer substation is not more than the sum of the capacity of the medium-voltage lines, and the capacity of the transformer substation is not needed to be compared and analyzed from the lower level to the upper level. After the consumption capacity data of each transformer substation are obtained, the consumption capacity comparison analysis of different subareas is carried out step by step up one level by combining the power grid topology, and further, the regional joint consumption capacity data are obtained according to the analysis results of the different subareas.
The technical scheme provided by the embodiment of the invention can comprise the following beneficial effects:
according to the method, aiming at the characteristic of uncertainty of the source load, the source side selects the output scene from the historical typical distributed photovoltaic output, the load side considers the load characteristics of different substations, and the typical daily load curve scene is respectively selected by taking the substation as granularity, so that the uncertainty is converted into a deterministic scene.
The invention takes the 'number' as the basis based on the new energy and the historical running state of the power grid, fully utilizes the existing data, can conveniently and efficiently calculate the regional and overall digestion capacity, and has universality.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (6)
1. The new energy consumption capability assessment method based on uncertainty is characterized by comprising the following steps of:
s101, acquiring an area to be evaluated, and acquiring basic data information of the network load storage in the area to be evaluated and a power grid operation mode;
s102, acquiring a source side distributed photovoltaic sunny day unit capacity output curve of an area to be evaluated, and carrying out target annual load value prediction by taking a transformer substation as granularity on a load side;
s103, coupling comparison is carried out on the typical daily load forecast time-sharing load trend of the transformer substation and the typical daily output curve of the photovoltaic power station, and a coupling threshold value is obtained;
s104, calculating the medium voltage line capacity eliminating condition under different load characteristic conditions;
s105, combining the power grid topology, and obtaining the combined digestion capacity of the evaluation area according to the principle that the lower level is not greater than the upper level digestion capacity.
2. The uncertainty-based new energy consumption capability assessment method is characterized by comprising the following steps of: the step S101 specifically includes the following steps:
s201, acquiring an area to be evaluated, and collecting a typical distributed photovoltaic history output curve within one year;
s202, collecting historical annual load and typical daily load curves of the transformer substation in an area to be evaluated by taking the transformer substation as granularity;
and S203, drawing a topological graph of the regional power grid to be evaluated based on the target annual grid structure and the normal running mode of the power grid.
3. The uncertainty-based new energy consumption capability assessment method is characterized by comprising the following steps of: the step S102 specifically includes the following steps:
s301, obtaining a photoelectric conversion utilization rate, namely a typical daily output curve of unit capacity on a sunny day by utilizing a first calculation formula based on a typical distributed photovoltaic historical output curve within one year;
the first calculation formula is:
wherein P is Gi1 The output value of the unit capacity of the distributed photovoltaic at the moment i is obtained; p (P) Gi0n The actual output value of the distributed photovoltaic at the moment i under the condition of a certain sunny day in one year of history, wherein n is the number of sunny days in one year of history; m is the capacity of the distributed photovoltaic installation;
s302, predicting the target annual load of each transformer substation by adopting a trend extrapolation method by taking the transformer substation as granularity;
s303, obtaining a target annual typical daily load curve by using a second calculation formula based on the photovoltaic typical daily load curve of the substation in the same period;
the second calculation formula is:
wherein P is B2 The method is a target annual transformer substation typical daily maximum electricity load predicted value predicted by adopting a trend extrapolation method; p (P) B1 The current transformer station is a typical daily maximum electricity load value; p (P) Bi2 Load values at various moments of typical days of a target year; p (P) Bi1 The load value is the load value at each time of the typical day of the current year; i is the time of each integral point, and 0-23 is taken.
4. The uncertainty-based new energy consumption capability assessment method is characterized by comprising the following steps of: the step S103 specifically includes the following steps:
s401, formulating a basic principle of the digestion capability: the 110kV or 35kV power grid does not have the phenomenon of power reversal;
s402, coupling the time-sharing load trend of the typical load day of the target year of the transformer substation with the typical daily output curve of the distributed photovoltaic power station one by one, and obtaining a coupling threshold value by using a third calculation formula;
the third calculation formula is:
Y＝min(P Gi2 ＝P Bi2 )
wherein Y is a coupling threshold; p (P) Gi2 The output of the photovoltaic at the moment i is given; p (P) Bi2 The load value is a typical day i moment of a transformer substation target year;
s403, considering existing photovoltaic output of the current annual transformer substation on the basis of a coupling threshold, and obtaining new energy consumption capacity of each transformer substation by using a fourth calculation formula;
the fourth calculation formula is:
P BQ ＝Y-P BGi
wherein P is BQ The capacity is consumed for the target year of the transformer substation Q; y is a coupling threshold; p (P) SQ The existing photovoltaic output of the transformer substation Q.
5. The uncertainty-based new energy consumption capability assessment method is characterized by comprising the following steps of: the step S104 specifically includes the following steps:
s501, aiming at a typical daily load curve of a medium-voltage line in an area, classifying the medium-voltage line by adopting a cluster analysis method, and dividing labels into a residential main line, a commercial main line and an industrial main line;
s502, obtaining the maximum load condition of the medium-voltage line by using a fifth calculation formula based on the load data of the medium-voltage line in the last three years collected by the system;
the fifth calculation formula is:
wherein eta is x Is the line load rate; p (P) xi The load value at the moment of the current line i; l is the maximum current-carrying capacity of the line;
s503, combining the operational years of the medium-voltage line, the maximum load rate of the medium-voltage line and the line label classification, and forming average maximum load rates under different load characteristics and different operational years by utilizing a sixth calculation formula;
the sixth calculation formula is:
wherein eta is xjn The average maximum load rate of medium-voltage lines in n years of operation is the average maximum load rate of medium-voltage lines living as a main label;the kth residence is a main type tag, and the maximum load rate of the medium-voltage line is in operation for n years; k is the number of line in the residence type label in n years of operation; j represents a resident class;
s504, predicting the maximum annual load of the medium-voltage line by using a seventh calculation formula according to line classification labels and combining the average load rates under different operational years;
the seventh calculation formula is:
P xj ＝η xjn ·L
wherein P is xj A target annual maximum load forecast value of the main label line is used for residence; η (eta) xjn The average maximum load rate of the medium-voltage line in n years of operation is the average maximum load rate of the medium-voltage line in which the residence is a main label, and the value of n is the annual distance of the target year from the operation year; l is the maximum current-carrying capacity of the line;
s505, obtaining a typical daily load curve of the medium-voltage line in the target year by utilizing an eighth calculation formula based on the daily load curve of the medium-voltage line in the photovoltaic typical daily same period;
the eighth calculation formula is:
wherein P is xji2 Load value P of target annual i time of main label line living xj A target annual maximum load forecast value of the main label line is used for residence; p (P) xj1 The current residential line typical daily maximum electricity load value; p (P) xji1 The load value of each time of the typical day of the living label line in the current year; i is the time of each integral pointTaking 0-23;
s506, coupling the time-sharing load trend of the typical load day of the target year of the medium-voltage line with the typical daily output curve of the distributed photovoltaic power station one by one, and obtaining a coupling threshold value by using a ninth calculation formula;
the ninth calculation formula is:
Y＝min(P Gi2 ＝P xi2 )+0.8L
wherein Y is a coupling threshold; p (P) Gi2 The output of the photovoltaic at the moment i is given; p (P) xi2 The load value is a typical day i moment load value of a medium-voltage line in a target year, and L is the maximum current-carrying capacity of the line;
s507, considering the existing photovoltaic output of the medium voltage lines in the current year on the basis of the coupling threshold value, and obtaining new energy consumption capacity of each medium voltage line by using a tenth calculation formula;
the tenth calculation formula is:
P Xi ＝Y-P Si
wherein P is Xi The capacity is consumed for the medium-voltage line i in a target year; y is a coupling threshold; p (P) Si The photovoltaic output is already available for the medium-voltage line i.
6. The uncertainty-based new energy consumption capability assessment method is characterized by comprising the following steps of: the step S105 specifically includes the following steps:
s601, marking the digestion capacity of each level of power grid based on a drawn topological graph of the regional power grid to be evaluated;
s602, calculating the total value of the digestion capacity of medium-voltage lines carried by each transformer substation one by one;
s603, comparing the digestion capacity of the transformer substation level with the digestion capacity of the medium-voltage circuit level by utilizing an eleventh calculation formula according to the principle that the lower level is not more than the digestion capacity of the upper level, and finally obtaining the joint digestion capacity of the evaluation area;
the eleventh calculation formula is:
wherein P' BQ The final capacity value P of the power supply range of the transformer substation Q is finally consumed in a target year BQ Calculating a target annual absorption capacity for a substation level;the method is the target annual capacity of the medium-voltage circuit i to which the transformer substation Q belongs.
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