CN109873439B - Method and device for setting demand control limit - Google Patents
Method and device for setting demand control limit Download PDFInfo
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- CN109873439B CN109873439B CN201910198018.XA CN201910198018A CN109873439B CN 109873439 B CN109873439 B CN 109873439B CN 201910198018 A CN201910198018 A CN 201910198018A CN 109873439 B CN109873439 B CN 109873439B
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Abstract
After acquiring the real-time power historical data of a load side, calculating an energy storage capacity value and an energy storage power value according to the real-time power historical data in the calculation period and an initial value and an increment of a preset target demand value for each calculation period in a preset time period, and obtaining a plurality of energy storage capacity values and energy storage power values in the calculation period along with the increment, on the basis, the optimal energy storage capacity value and the optimal energy storage power value in the calculation period can be accurately calculated by taking the maximum user side profit as an optimization target. And finally, considering the demand control margin coefficient and the optimal energy storage power value in the preset time period, and accurately calculating the optimal demand control limit value.
Description
Technical Field
The invention relates to the technical field of power control, in particular to a method and a device for setting a demand control limit.
Background
In order to configure the charge/discharge power and the energy storage capacity of the energy storage system in the demand control system, a demand control limit value needs to be set for a target load. The selection of the demand control limit value is related to the size of the energy storage capacity and the charge and discharge power, and the size of the system cost, and the success or failure of the energy storage scheme is also influenced.
At present, an engineer mostly sets a demand control limit value for an enterprise by observing historical power consumption data, power consumption prediction data and power price parameters of the enterprise and relying on experience. However, the demand control limit set in this way does not result in an optimum value of the demand control limit, and the load-side user economic efficiency does not meet the intended target.
Disclosure of Invention
In view of this, the present invention provides a method and an apparatus for setting a demand control limit, which accurately calculate an optimal value of an energy storage capacity and the demand control limit, ensure economic benefit of a user, and promote application of energy storage on a load side.
In order to achieve the above purpose, the technical scheme provided by the invention is as follows:
a method for setting a demand control limit value comprises the following steps:
acquiring real-time power historical data of a load side in a preset time period;
for each calculation period in a preset time period, calculating to obtain a plurality of energy storage capacity values and a plurality of energy storage power values in the calculation period according to real-time power historical data in the calculation period and an initial value and an increment of a preset target demand value, and calculating an optimal energy storage capacity value and an optimal energy storage power value in the calculation period according to a maximum user side profit optimization target;
determining an optimal energy storage capacity value and an optimal energy storage power value in the preset time period according to the optimal energy storage capacity value and the optimal energy storage power value of each calculation period in the preset time period;
and setting an optimal demand control limit value according to the optimal energy storage power value and a demand control margin coefficient in the preset time period, wherein the demand control margin coefficient is set according to the ratio of the number of peaks exceeding the maximum energy control demand in the preset time period to the total number of peaks in the preset time period.
Optionally, after the acquiring the real-time power history data within the preset time period of the load side, the method further includes:
and judging whether demand control is needed or not according to the real-time power historical data in the preset time period, and if so, calculating a demand control limit value.
Optionally, the determining whether demand control is required according to the real-time historical power data in the preset time period includes:
determining that demand control is required when the real-time power history data meets all of the following conditions:
the electricity utilization type is large industrial electricity utilization;
executing two power price making processes;
the load has an impact property, and the impact property is greater than a threshold value.
Optionally, the calculating, according to the real-time power historical data in the calculation period and the initial value and the increment of the preset target demand value, a plurality of energy storage capacity values and a plurality of energy storage power values in the calculation period, and calculating, with the maximum user-side profit, the optimal energy storage capacity value and the optimal energy storage power value in the calculation period based on the optimization target includes:
acquiring a maximum power demand value in the calculation period according to the real-time power historical data in the calculation period;
setting an initial value and an increment of a target demand value according to the maximum power demand value, and setting a plurality of target demand values according to the initial value and the increment of the target demand value;
acquiring the actual load power of each sampling point according to the real-time power historical data in the calculation period;
for each target demand value, integrating the difference value between the actual load power of each sampling point in the calculation period and the target demand value to obtain an energy storage capacity value;
for each target demand value, calculating the difference value between the maximum power demand value and the target demand value to obtain an energy storage power value;
and calculating the user side profit by taking the energy storage capacity value and the energy storage power value as variables, and calculating the optimal energy storage capacity value and the optimal energy storage power value in the calculation period by taking the maximum user side profit as an optimization target.
Optionally, the determining the optimal energy storage capacity value and the optimal energy storage power value in the preset time period according to the optimal energy storage capacity value and the optimal energy storage power value in each calculation cycle in the preset time period includes:
sequencing the optimal energy storage capacity value and the optimal energy storage power value of each calculation cycle in the preset time period;
and determining the optimal energy storage capacity value and the optimal energy storage power value which satisfy the preset probability value with the probability greater than other optimal energy storage capacity values and optimal energy storage power values in the sequence as the optimal energy storage capacity value and the optimal energy storage power value in the preset time period.
Optionally, when the optimal energy storage capacity value and/or the optimal energy storage power value in the preset time period do not exist in the preset energy storage product set, the method further includes:
in the energy storage product of the best energy storage capacity value and the energy storage power value that will with best energy storage capacity value and the best energy storage power value in the preset time quantum most approximate in the energy storage product of energy storage capacity value and the energy storage power value in the preset time quantum not less than in the preset energy storage product set, the best energy storage capacity value and the best energy storage power value after the amendment in the preset time quantum are confirmed as.
Optionally, the method further includes:
counting the total peak value and the peak value number exceeding the maximum target demand value according to the real-time historical power data in the preset time period;
calculating the ratio of the number of peaks exceeding the maximum target demand value in the preset time period to the total number of peaks in the preset time period;
when the ratio is within a first preset range, setting the demand control margin coefficient as a first preset value;
and when the ratio is within a second preset range, setting the demand control margin coefficient as a second preset value.
A demand control limit calculation apparatus, comprising:
the acquisition unit is used for acquiring real-time power historical data of a load side in a preset time period;
the calculation unit is used for calculating and obtaining a plurality of energy storage capacity values and a plurality of energy storage power values in a calculation period according to real-time power historical data in the calculation period and initial values and increments of preset target demand values in each calculation period in a preset time period, and calculating the optimal energy storage capacity value and the optimal energy storage power value in the calculation period according to the maximum user-side profit optimization target;
the determining unit is used for determining the optimal energy storage capacity value and the optimal energy storage power value in the preset time period according to the optimal energy storage capacity value and the optimal energy storage power value in each calculation cycle in the preset time period;
and the setting unit is used for setting an optimal demand control limit value according to the optimal energy storage power value and a demand control margin coefficient in the preset time period, wherein the demand control margin coefficient is set according to the ratio of the number of peaks exceeding the maximum energy control demand in the preset time period to the total number of peaks in the preset time period.
Optionally, the apparatus further comprises:
and the judging unit is used for judging whether the demand control is needed or not according to the real-time power historical data in the preset time period, and if so, triggering the calculating unit.
Optionally, the determining unit is specifically configured to determine that demand control needs to be performed when the real-time historical power data meets all of the following conditions:
the electricity utilization type is large industrial electricity utilization;
executing two power price making processes;
the load has an impact property, and the impact property is greater than a threshold value.
Optionally, the computing unit is specifically configured to obtain a maximum power demand value in the computing period according to the real-time historical power data in the computing period; setting an initial value and an increment of a target demand value according to the maximum power demand value, and setting a plurality of target demand values according to the initial value and the increment of the target demand value; acquiring the actual load power of each sampling point according to the real-time power historical data in the calculation period; for each target demand value, integrating the difference value between the actual load power of each sampling point in the calculation period and the target demand value to obtain an energy storage capacity value; for each target demand value, calculating the difference value between the maximum power demand value and the target demand value to obtain an energy storage power value; and calculating the user side profit by taking the energy storage capacity value and the energy storage power value as variables, and calculating the optimal energy storage capacity value and the optimal energy storage power value in the calculation period by taking the maximum user side profit as an optimization target.
Optionally, the determining unit is specifically configured to rank the optimal energy storage capacity value and the optimal energy storage power value of each calculation cycle within the preset time period; and determining the optimal energy storage capacity value and the optimal energy storage power value, of which the probability greater than other optimal energy storage capacity values and optimal energy storage power values in the sequence meets a preset probability value, as the optimal energy storage capacity value and the optimal energy storage power value in the preset time period.
Optionally, when the optimal energy storage capacity value and/or the optimal energy storage power value in the preset time period do not exist in the preset energy storage product set, the apparatus further includes:
and the correcting unit is used for determining the energy storage capacity value and the energy storage power value of the energy storage product which are closest to the optimal energy storage capacity value and the optimal energy storage power value in the preset time period as the corrected optimal energy storage capacity value and the optimal energy storage power value in the preset time period in the energy storage products with the energy storage capacity value not less than the optimal energy storage capacity value in the preset time period and the energy storage power value not less than the optimal energy storage power value in the preset time period.
Optionally, the apparatus further comprises:
the demand control margin coefficient setting unit is used for counting the total peak value and the peak value number exceeding the maximum target demand value according to the real-time power historical data in the preset time period; calculating the ratio of the number of peaks exceeding the maximum target demand value in the preset time period to the total number of peaks in the preset time period; when the ratio is within a first preset range, setting the demand control margin coefficient as a first preset value; and when the ratio is within a second preset range, setting the demand control margin coefficient as a second preset value.
Compared with the prior art, the invention has the following beneficial effects:
the invention discloses a method and a device for calculating a demand control limit value for demand control, which are used for acquiring real-time power historical data of a load side in a preset time period, acquiring a maximum power demand value for each calculation period in the preset time period, setting an initial value and an increment of a target demand value according to the maximum power demand value, calculating an energy storage capacity value and an energy storage power value based on the initial value and the increment of the target demand value, and obtaining a plurality of energy storage capacity values and a plurality of energy storage power values in the calculation period along with the continuous increase of the increment. In the same way, the optimal energy storage capacity value and the optimal energy storage power value of each calculation cycle in the preset time period can be obtained, the optimal energy storage capacity value and the optimal energy storage power value in the preset time period are determined, and the influence of special factors in historical data on the calculation result is further eliminated. And finally, considering the demand control margin coefficient and the optimal energy storage power value in the preset time period, and accurately calculating and setting the optimal demand control limit value.
Therefore, the invention solves the problem that the optimal value of the demand control limit value cannot be obtained due to the fact that the demand control limit value needs to be set by experience in the prior art, improves the accuracy of the demand control limit value, maximizes the economic benefit of a load side user, and promotes the application of stored energy on the load side.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for calculating a demand control limit for demand control according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a device for calculating a demand control limit for demand control according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
The embodiment discloses a method for setting a demand control limit, which is applied to a scene needing demand control, and can judge whether demand control is needed or not after acquiring real-time power historical data of a load side, specifically, when the real-time power historical data meets all the following conditions:
the electricity utilization type is large industrial electricity utilization;
executing two power price making processes;
the load has an impact property, and the impact property is greater than a threshold value.
Wherein, the power consumption of large-scale industrial power consumption is relatively large, such as steel, electrolytic aluminum, power plant self-power consumption, railway transportation.
In general, two electricity prices are used for large-scale industrial electricity, and the two electricity prices are a system for determining electricity prices by combining a basic electricity price corresponding to a capacity and an electricity price corresponding to a used amount of electricity.
Total electricity charge (meter reading electricity quantity, degree electricity price and demand quantity, maximum demand electricity price)
The magnitude of the power change rate is determined according to the real-time power historical data, the magnitude of the power change rate is represented in an impact mode, and the threshold value is preset.
Specifically, referring to fig. 1, the method for setting a demand control limit disclosed in this embodiment includes the following steps:
s101: acquiring real-time power historical data of a load side in a preset time period;
the load side is the load side of the enterprise that needs to perform demand control.
Because the electric charge of enterprises is collected according to one month, the change trend and the increment of the load power of the loads along with different seasons are greatly different, and the duration of historical data, namely the preset time period, preferably reaches one quarter or can be one year or more.
S102: for each calculation period in a preset time period, calculating to obtain a plurality of energy storage capacity values and a plurality of energy storage power values in the calculation period according to real-time power historical data in the calculation period and initial values and increments of preset target demand values, and calculating the optimal energy storage capacity value and the optimal energy storage power value in the calculation period according to the maximum user-side profit optimization target;
wherein, the calculation period may be one day.
For each day of real-time power history data within a preset time period, performing the following steps:
(1) and taking the power data P [ ] of one day to obtain the maximum power demand value Pmax [ j ] [ d ] of one day.
(2) And setting an initial value and an increment of the target demand value according to the maximum power demand value.
The target demand value represents a target value of the demand value, and the calculation formula of the target demand value is as follows:
Ps[j][d]＝aPmax[j][d]+i*(1/n)*Pmax[j][d]
wherein a is the percentage of the algorithm starting value;
the value a is set up to reduce the calculation amount of the algorithm, and the value a can be set by selecting a percentage from 0 to 99 percent according to the actual impact load condition of an enterprise;
aPmax [ j ] [ d ] represents the initial value of the target demand value;
j is 1, 2, 3, … … n, representing a total of j;
n is the average division of Pmax into n equal parts;
for more refinement, the larger the n value, the better the n value can be determined according to the actual situation;
i (1/n) Pmax [ j ] [ d ] represents the increment of the target demand value, and the larger i is, the larger the increment of the target demand value is;
d represents the number of days of historical data in a preset time period.
(3) Integrating the difference value between the actual load power of each sampling point in one day and the target demand value to obtain an energy storage capacity value;
the actual load power of each sampling point can be obtained according to the real-time power historical data in one day.
Specifically, the calculation formula of the energy storage capacity is as follows:
S[j][d]＝∫(P[k]-Ps[j][d])dt
when P [ k ] -Ps [ j ] [ d ] is 0 or less, P [ k ] is made to be Ps [ j ] [ d ].
The energy storage capacity is the integral of the difference value between the actual load power and the target demand value, the integral duration is one whole day, x represents the number of load sampling points in one day, and k is the increment of the number of sampling points.
And when the P [ k ] -Ps [ j ] [ d ] is less than or equal to 0, the P [ k ] is equal to Ps [ j ] [ d ], the actual power does not exceed the preset required value, and the stored energy does not need to release the power.
(4) Integrating the difference value between the actual load power of each sampling point in the calculation period and the target demand value to obtain an energy storage capacity value;
the calculation formula of the energy storage power is as follows:
PL[j][d]＝Pmax[j][d]-Ps[j][d]
in order to ensure that the energy storage power can reduce the maximum demand of the load, the energy storage rated power is determined by the difference between the maximum power of the load and the target demand value in the day.
(5) And outputting n energy storage capacity values and n energy storage power values in one day according to the initial value and the increment size of the set target demand value along with the continuous increase of the increment of the target demand value.
(6) And calculating the user side income by adopting a cyclic algorithm and taking the energy storage capacity value and the energy storage power value as variables, and calculating the optimal energy storage capacity value and the optimal energy storage power value in the calculation period by taking the maximum user side income as an optimization target.
The maximum benefit obtained by the user side is as follows:
Cymax (profit-cost) max [ b × PL [ j ]][d]-(β*S[j][d]+g*PL[j][d])
Wherein Cy is the maximum gain obtained by the user side;
b is the demand electricity price coefficient;
beta is the cost coefficient of the stored energy power;
g is the inverter cost coefficient;
and when the gain Cy obtained by the user side reaches the maximum, taking the obtained energy storage capacity value and energy storage power value as the optimal energy storage capacity value and the optimal energy storage power value output by the algorithm. Outputting an optimal energy storage capacity value and an optimal energy storage power value in one day through boundary conditions;
s103: determining an optimal energy storage capacity value and an optimal energy storage power value in the preset time period according to the optimal energy storage capacity value and the optimal energy storage power value of each calculation period in the preset time period;
specifically, the method for determining the optimal energy storage capacity value and the optimal energy storage power value in the preset time period according to the optimal energy storage capacity value and the optimal energy storage power value in each calculation cycle in the preset time period includes:
sequencing the optimal energy storage capacity value and the optimal energy storage power value of each calculation cycle in the preset time period;
and determining the optimal energy storage capacity value and the optimal energy storage power value, of which the probability greater than other optimal energy storage capacity values and optimal energy storage power values in the sequence meets a preset probability value, as the optimal energy storage capacity value and the optimal energy storage power value in the preset time period.
For example, the preset probability value can be set to 99%, and the influence of factors such as no working on holidays of enterprises, sudden load change and load faults on the calculation result is eliminated.
It can be understood that if there is no optimal energy storage capacity value and/or optimal energy storage power value within the preset time period calculated in the above steps, the energy storage product on the market needs to correct the optimal energy storage capacity value and/or optimal energy storage power value within the preset time period calculated in the above steps, and the optimal energy storage capacity value and/or optimal energy storage power value may be corrected according to the principle that the energy storage product is not taken down nearby.
Specifically, an energy storage product set is preset, the energy storage product set comprises all energy storage products on the market at present, and each energy storage product has an energy storage capacity value and an energy storage power value. When the optimal energy storage capacity value and/or the optimal energy storage power value in the preset time period do not exist in the preset energy storage product set, in the energy storage product of which the energy storage capacity value is not less than the optimal energy storage capacity value in the preset time period and the energy storage power value is not less than the optimal energy storage power value in the preset time period, the energy storage capacity value and the energy storage power value of the energy storage product which are closest to the optimal energy storage capacity value and the optimal energy storage power value in the preset time period are determined as the corrected optimal energy storage capacity value and the optimal energy storage power value in the preset time period.
Meanwhile, if the enterprise has a load to be planned in the future to be put into operation, the capacity increase and the work expansion of the stored energy are carried out according to the planned value.
S104: and setting an optimal demand control limit value according to the optimal energy storage power value and a demand control margin coefficient in the preset time period, wherein the demand control margin coefficient is set according to the ratio of the number of peaks exceeding the maximum energy control demand in the preset time period to the total number of peaks in the preset time period.
Specifically, the calculation formula of the optimal demand control limit value is as follows:
P1＝h*PL[j][d]
wherein h is a demand control margin coefficient.
The setting method of the demand control margin coefficient comprises the following steps:
counting the total peak value and the peak value number exceeding the maximum target demand value according to the real-time historical power data in the preset time period;
calculating the ratio of the number of peaks exceeding the maximum target demand value in the preset time period to the total number of peaks in the preset time period;
when the ratio is within a first preset range, setting the demand control margin coefficient as a first preset value;
and when the ratio is within a second preset range, setting the demand control margin coefficient to be a second preset value.
Specifically, the ratio of the number of peaks exceeding the maximum target demand value in the preset time period to the total number of peaks in the preset time period is:
w represents the number of peaks exceeding a maximum target demand value (Pmax-PL) within a preset time period
Z represents the total number of peaks in the preset time period.
For example, when V < 5%, the demand control margin coefficient h can be selected between 0.9 and 1;
when 5< V < - > is 10%, the demand control margin coefficient h can be selected between 0.7 and 0.9.
The specific value of the demand control margin coefficient h can be selected according to the actual situation on the basis.
The method for setting the demand control limit value solves the problem that the optimal value of the demand control limit value cannot be obtained due to the fact that the demand control limit value needs to be set by experience in the prior art, reduces the workload of engineers, improves the accuracy of the demand control limit value, maximizes the economic benefit of users on the load side, and promotes the application of stored energy on the load side.
Based on the method for setting the demand control limit disclosed in the above embodiments, this embodiment correspondingly discloses a device for setting the demand control limit, specifically, referring to fig. 2, the device includes:
an obtaining unit 201, configured to obtain real-time power history data of a load side in a preset time period;
a calculating unit 202, configured to calculate, for each calculation cycle in a preset time period, a plurality of energy storage capacity values and a plurality of energy storage power values in the calculation cycle according to the real-time power historical data in the calculation cycle and an initial value and an increment of a preset target demand value, and calculate an optimal energy storage capacity value and an optimal energy storage power value in the calculation cycle with a maximum user-side profit as an optimization target;
a determining unit 203, configured to determine an optimal energy storage capacity value and an optimal energy storage power value in the preset time period according to the optimal energy storage capacity value and the optimal energy storage power value in each calculation cycle in the preset time period;
a setting unit 204, configured to set an optimal demand control limit according to the optimal energy storage power value and a demand control margin coefficient in the preset time period, where the demand control margin coefficient is set according to a ratio of the number of peaks exceeding the maximum energy control demand in the preset time period to the total number of peaks in the preset time period.
Optionally, the apparatus further comprises:
and the judging unit is used for judging whether demand control is required or not according to the real-time power historical data in the preset time period, and if so, triggering the calculating unit.
Optionally, the determining unit is specifically configured to determine that demand control needs to be performed when the real-time historical power data meets all of the following conditions:
the electricity utilization type is large industrial electricity utilization;
executing two power price making processes;
the load has an impact property, and the impact property is greater than a threshold value.
Optionally, the calculating unit 202 is specifically configured to obtain a maximum power demand value in the calculation period according to the real-time historical power data in the calculation period; setting an initial value and an increment of a target demand value according to the maximum power demand value, and setting a plurality of target demand values according to the initial value and the increment of the target demand value; acquiring the actual load power of each sampling point according to the real-time power historical data in the calculation period; for each target demand value, integrating the difference value between the actual load power of each sampling point in the calculation period and the target demand value to obtain an energy storage capacity value; for each target demand value, calculating the difference value between the maximum power demand value and the target demand value to obtain an energy storage power value; and calculating the user side profit by taking the energy storage capacity value and the energy storage power value as variables, and calculating the optimal energy storage capacity value and the optimal energy storage power value in the calculation period by taking the maximum user side profit as an optimization target.
Optionally, the determining unit 203 is specifically configured to rank the optimal energy storage capacity value and the optimal energy storage power value in each calculation cycle within the preset time period; and determining the optimal energy storage capacity value and the optimal energy storage power value, of which the probability greater than other optimal energy storage capacity values and optimal energy storage power values in the sequence meets a preset probability value, as the optimal energy storage capacity value and the optimal energy storage power value in the preset time period.
Optionally, when the optimal energy storage capacity value and/or the optimal energy storage power value in the preset time period do not exist in the preset energy storage product set, the apparatus further includes:
and the correcting unit is used for determining the energy storage capacity value and the energy storage power value of the energy storage product which are closest to the optimal energy storage capacity value and the optimal energy storage power value in the preset time period as the corrected optimal energy storage capacity value and the optimal energy storage power value in the preset time period in the energy storage products with the energy storage capacity value not less than the optimal energy storage capacity value in the preset time period and the energy storage power value not less than the optimal energy storage power value in the preset time period.
Optionally, the apparatus further comprises:
a demand control margin coefficient setting unit for counting the total peak value and the peak value number exceeding the maximum target demand value according to the real-time power historical data in the preset time period; calculating the ratio of the number of peaks exceeding the maximum target demand value in the preset time period to the total number of peaks in the preset time period; when the ratio is within a first preset range, setting the demand control margin coefficient as a first preset value; and when the ratio is within a second preset range, setting the demand control margin coefficient as a second preset value.
After acquiring real-time power historical data of a load side in a preset time period, the setting device for the demand control limit value disclosed in this embodiment acquires a maximum power demand value for each calculation period in the preset time period, sets an initial value and an increment of a target demand value according to the maximum power demand value, calculates an energy storage capacity value and an energy storage power value based on the initial value and the increment of the target demand value, and obtains a plurality of energy storage capacity values and a plurality of energy storage power values in the calculation period along with the continuous increase of the increment. In the same way, the optimal energy storage capacity value and the optimal energy storage power value of each calculation cycle in the preset time period can be obtained, the optimal energy storage capacity value and the optimal energy storage power value in the preset time period are determined, and the influence of special factors in historical data on the calculation result is further eliminated. And finally, considering the demand control margin coefficient and the optimal energy storage power value in a preset time period, and accurately calculating and setting the optimal demand control limit value. The problem that the optimal value of the demand control limit value cannot be obtained due to the fact that the demand control limit value needs to be set by experience in the prior art is solved, accuracy of the demand control limit value is improved, economic benefits of users on a load side are maximized, and application of stored energy on the load side is promoted.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A method for setting a demand control limit, comprising:
acquiring real-time power historical data of a load side in a preset time period;
for each calculation period in a preset time period, acquiring a maximum power demand value in the calculation period, presetting an initial value and an increment of a target demand value according to the maximum demand value, calculating a plurality of energy storage capacity values and a plurality of energy storage power values in the calculation period according to real-time power historical data in the calculation period and the initial value and the increment of the preset target demand value, and calculating an optimal energy storage capacity value and an optimal energy storage power value in the calculation period by adopting a cyclic algorithm with a user side maximum profit optimization target;
sequencing the optimal energy storage capacity value and the optimal energy storage power value of each calculation cycle in the preset time period; determining the optimal energy storage capacity value and the optimal energy storage power value, of which the probability greater than other optimal energy storage capacity values and optimal energy storage power values in the sequence meets a preset probability value, as the optimal energy storage capacity value and the optimal energy storage power value in the preset time period;
and setting an optimal demand control limit value according to the optimal energy storage power value and a demand control margin coefficient in the preset time period, wherein the demand control margin coefficient is set according to the ratio of the number of peaks exceeding the maximum energy control demand in the preset time period to the total number of peaks in the preset time period.
2. The method of claim 1, wherein after the obtaining of the real-time power history data of the load side within the preset time period, the method further comprises:
and judging whether demand control is required or not according to the real-time power historical data in the preset time period, and if so, calculating a demand control limit value.
3. The method according to claim 2, wherein the determining whether demand control is required according to the real-time historical power data within the preset time period comprises:
determining that demand control is required when the real-time power history data meets all of the following conditions:
the electricity utilization type is large industrial electricity utilization;
executing two electricity-making prices;
the load has an impact property, and the impact property is greater than a threshold value.
4. The method of claim 1, wherein the calculating a plurality of energy storage capacity values and a plurality of energy storage power values in the calculation period according to the real-time power history data in the calculation period and the initial values and increments of the preset target demand values, and calculating the optimal energy storage capacity value and the optimal energy storage power value in the calculation period with the user-side maximum profit as the optimization target comprises:
setting a plurality of target demand values according to the initial values and the increments of the target demand values;
acquiring the actual load power of each sampling point according to the real-time power historical data in the calculation period;
for each target demand value, integrating the difference value between the actual load power of each sampling point in the calculation period and the target demand value to obtain an energy storage capacity value;
for each target demand value, calculating the difference value between the maximum power demand value and the target demand value to obtain an energy storage power value;
and calculating the user side profit by taking the energy storage capacity value and the energy storage power value as variables, and calculating the optimal energy storage capacity value and the optimal energy storage power value in the calculation period by taking the maximum user side profit as an optimization target.
5. The method according to claim 1, wherein when there is no optimal energy storage capacity value and/or optimal energy storage power value within the preset time period in a preset set of energy storage products, the method further comprises:
and in the energy storage products of which the energy storage capacity value is not less than the optimal energy storage capacity value in the preset time period and the energy storage power value is not less than the optimal energy storage power value in the preset time period, determining the energy storage capacity value and the energy storage power value of the energy storage product which are closest to the optimal energy storage capacity value and the optimal energy storage power value in the preset time period as the corrected optimal energy storage capacity value and the optimal energy storage power value in the preset time period.
6. The method of claim 1, further comprising:
counting the total peak value and the peak value number exceeding the maximum target demand value according to the real-time historical power data in the preset time period;
calculating the ratio of the number of peaks exceeding the maximum target demand value in the preset time period to the total number of peaks in the preset time period;
when the ratio is within a first preset range, setting the demand control margin coefficient as a first preset value;
and when the ratio is within a second preset range, setting the demand control margin coefficient to be a second preset value.
7. A demand control limit calculation apparatus, comprising:
the acquisition unit is used for acquiring real-time power historical data of a load side in a preset time period;
the calculation unit is used for acquiring the maximum power demand value in the calculation period for each calculation period in a preset time period, presetting an initial value and an increment of a target demand value according to the maximum demand value, calculating and obtaining a plurality of energy storage capacity values and a plurality of energy storage power values in the calculation period according to real-time power historical data in the calculation period and the preset initial value and the increment of the target demand value, and calculating the optimal energy storage capacity value and the optimal energy storage power value in the calculation period by adopting a cyclic algorithm and optimizing the maximum user-side income target;
the determining unit is used for sequencing the optimal energy storage capacity value and the optimal energy storage power value of each calculation cycle in the preset time period; determining the optimal energy storage capacity value and the optimal energy storage power value which satisfy the preset probability value and have the probability higher than other optimal energy storage capacity values and optimal energy storage power values in the sequence as the optimal energy storage capacity value and the optimal energy storage power value in the preset time period;
and the setting unit is used for setting an optimal demand control limit value according to the optimal energy storage power value and a demand control margin coefficient in the preset time period, wherein the demand control margin coefficient is set according to the ratio of the number of peaks exceeding the maximum energy control demand in the preset time period to the total number of peaks in the preset time period.
8. The apparatus according to claim 7, wherein the computing unit is specifically configured to obtain a maximum power demand value in the computing period according to the real-time historical power data in the computing period; setting an initial value and an increment of a target demand value according to the maximum power demand value, and setting a plurality of target demand values according to the initial value and the increment of the target demand value; acquiring the actual load power of each sampling point according to the real-time power historical data in the calculation period; for each target demand value, integrating the difference value between the actual load power of each sampling point in the calculation period and the target demand value to obtain an energy storage capacity value; for each target demand value, calculating the difference value between the maximum power demand value and the target demand value to obtain an energy storage power value; and calculating the user side profit by taking the energy storage capacity value and the energy storage power value as variables, and calculating the optimal energy storage capacity value and the optimal energy storage power value in the calculation period by taking the maximum user side profit as an optimization target.
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