CN111695817B - Method, device and system for calculating required quantity reduction - Google Patents
Method, device and system for calculating required quantity reduction Download PDFInfo
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Abstract
According to the calculation method, the device and the system for the demand reduction, under the condition that a user charges according to the actual maximum demand, the power of the electric meter of the public access point of the power grid is used as the power after the power is supplied by the energy storage device, and the power of the energy storage and grid connection point is used as the power supply power of the energy storage device, the power before the power is supplied by the energy storage device, which is determined by the difference value between the power of the electric meter of the public access point of the power grid and the power of the energy storage and grid connection point, can be accurately obtained, and then the demand before the power is supplied by the energy storage device is accurately calculated for each sampling point according to the power before the power is supplied by the energy storage device, so that the maximum demand in a preset charging period is obtained, and the demand reduction can be accurately calculated.
Description
Technical Field
The invention relates to the technical field of electric power, in particular to a method, a device and a system for calculating a required quantity reduction amount.
Background
With the continuous innovation of the technologies such as distributed photovoltaic, distributed wind power, energy storage technology and micro-grid, more and more users install distributed power supplies such as distributed photovoltaic power generation, distributed wind power, energy storage power stations and the like. The distributed power supplies supply power for users through the energy storage equipment, so that the maximum demand of power consumption of a user power grid is reduced, and benefits generated due to demand reduction are brought to the users.
At present, two methods for charging the maximum demand exist, one is to charge according to the contract maximum demand agreed in advance, and the other is to charge according to the actual maximum demand. For the method of charging according to the maximum demand of the contract, the difference between the maximum demand contracted before the power supply of the energy storage device is applied and the maximum demand contracted after the power supply of the energy storage device is applied can be used as the demand reduction amount, so that the demand reduction income is calculated. However, for the user who uses the actual maximum demand to pay the basic electricity fee, since the maximum demand before the user uses the energy storage device to supply power cannot be directly measured, how to accurately calculate the reduction amount of the demand according to the actual maximum demand is a technical problem to be solved in the art.
Disclosure of Invention
In view of the above, the invention provides a method, a device and a system for calculating the required quantity reduction, which realize accurate calculation of the required quantity reduction.
In order to achieve the above purpose, the specific technical scheme provided by the invention is as follows:
a calculation method of the required quantity reduction comprises the following steps:
Acquiring power of an ammeter of a public access point of a power grid and power of an energy storage grid-connected point of each sampling point in a preset charging period;
respectively determining the difference value between the power of the electric meter of the public access point of the power grid of each sampling point and the power of the energy storage grid-connected point as the power before the power is supplied by the energy storage equipment applied to each sampling point;
according to the power before the sampling points are powered by the energy storage equipment, the demand before the sampling points are powered by the energy storage equipment is calculated, according to the power of the electric network public access point ammeter of each sampling point, the demand after the sampling points are powered by the energy storage equipment is calculated, and the demand reduction amount is obtained.
Optionally, the obtaining the power of the electric network public access point electric meter and the power of the energy storage grid-connected point of each sampling point in the preset charging period includes:
acquiring a power measured value and a time stamp of an ammeter of a public access point of the power grid of each sampling point and a power measured value and a time stamp of an energy storage grid-connected point;
correcting the time stamp of the electric network public access point electric meter of each sampling point and the time stamp of the energy storage grid-connected point according to the hardware measurement correction parameters and the transmission correction parameters to obtain the standard time stamp of the electric network public access point electric meter of each sampling point and the standard time stamp of the energy storage grid-connected point;
When the standard time stamp of the power grid public access point ammeter of each sampling point is inconsistent with the standard time stamp of the energy storage grid-connected point, fitting the power measured value of the power grid public access point ammeter and the power measured value of the energy storage grid-connected point, which are closest to each standard time stamp, to obtain the standard power of the power grid public access point ammeter of each sampling point and the standard power of the energy storage grid-connected point.
Optionally, the fitting the power measurement value of the grid public access point ammeter and the power measurement value of the energy storage grid-connected point with the nearest standard time stamp to obtain the standard power of the grid public access point ammeter and the standard power of the energy storage grid-connected point of each sampling point includes:
the power measurement value and the standard time stamp of the power grid public access point ammeter of each sampling point and the power measurement value and the standard time stamp of the energy storage and grid connection point are input into a BP neural network model for fitting processing, so that the standard power and the standard power of the energy storage and grid connection point ammeter of each sampling point are obtained, and the BP neural network model is obtained after model training and model learning by using the power measurement value and the standard time stamp of the power grid public access point ammeter of each sampling point and the power measurement value and the standard time stamp of the energy storage and grid connection point in a preset charging period before a current preset charging period as training samples and learning samples.
Optionally, the fitting the power measurement value of the grid public access point ammeter and the power measurement value of the energy storage grid-connected point with the nearest standard time stamp to obtain the standard power of the grid public access point ammeter and the standard power of the energy storage grid-connected point of each sampling point includes:
and fitting the power measurement value of the power grid public access point ammeter with the nearest standard time stamp and the power measurement value of the energy storage grid connection point by using a linear two-point method to obtain the standard power of the power grid public access point ammeter and the standard power of the energy storage grid connection point of each sampling point.
Optionally, the calculating the required amount before each sampling point applies the power of the energy storage device according to the power before each sampling point applies the power of the energy storage device, calculating the required amount after each sampling point applies the power of the energy storage device according to the power of the electric network public access point electric meter of each sampling point, and obtaining the required amount reduction amount includes:
calculating the required quantity before each sampling point is supplied with power by using the power before the energy storage equipment is supplied according to the power before the energy storage equipment is supplied by each sampling point, and calculating the required quantity after the energy storage equipment is supplied by each sampling point according to the power of the electric network public access point ammeter of each sampling point;
And determining the difference value between the maximum required amount before the power is supplied by the energy storage equipment and the maximum required amount after the power is supplied by the energy storage equipment in the preset charging period as a required amount reduction amount.
Optionally, the method further comprises:
and calculating the demand reduction benefit according to the demand reduction amount and the demand unit price.
A demand-reduction-amount calculating apparatus comprising:
the power data acquisition unit is used for acquiring the power of the electric network public access point ammeter of each sampling point and the power of the energy storage grid-connected point in a preset charging period;
the power before supply determining unit is used for respectively determining the difference value between the power of the electric network public access point ammeter of each sampling point and the power of the energy storage grid-connected point, and applying the power before the energy storage equipment for each sampling point;
the reduction amount calculation unit is used for calculating the required amount before the energy storage device is applied to each sampling point according to the power before the energy storage device is applied to each sampling point, calculating the required amount after the energy storage device is applied to each sampling point according to the power of the electric network public access point electric meter of each sampling point, and obtaining the reduction amount of the required amount.
Optionally, the power data acquisition unit includes:
The power measurement value acquisition subunit is used for acquiring the power measurement value and the time stamp of the electric meter of the public access point of the power grid of each sampling point and the power measurement value and the time stamp of the energy storage grid-connected point;
the time stamp correction subunit is used for correcting the time stamp of the electric network public access point electric meter and the time stamp of the energy storage networking point of each sampling point according to the hardware measurement correction parameters and the transmission correction parameters to obtain the standard time stamp of the electric network public access point electric meter and the standard time stamp of the energy storage networking point of each sampling point;
and the power correction subunit is used for fitting the power measured value of the power public access point ammeter of the power grid with the nearest standard time stamp and the power measured value of the energy storage grid-connected point to obtain the standard power of the power public access point ammeter of the power grid with the sampling point and the standard power of the energy storage grid-connected point when the standard time stamp of the power public access point ammeter of the power grid with the sampling point is inconsistent with the standard time stamp of the energy storage grid-connected point.
Optionally, the power correction subunit is specifically configured to:
the power measurement value and the standard time stamp of the power grid public access point ammeter of each sampling point and the power measurement value and the standard time stamp of the energy storage and grid connection point are input into a BP neural network model for fitting processing, so that the standard power and the standard power of the energy storage and grid connection point ammeter of each sampling point are obtained, and the BP neural network model is obtained after model training and model learning by using the power measurement value and the standard time stamp of the power grid public access point ammeter of each sampling point and the power measurement value and the standard time stamp of the energy storage and grid connection point in a preset charging period before a current preset charging period as training samples and learning samples.
Optionally, the power correction subunit is specifically configured to:
and fitting the power measurement value of the power grid public access point ammeter with the nearest standard time stamp and the power measurement value of the energy storage grid connection point by using a linear two-point method to obtain the standard power of the power grid public access point ammeter and the standard power of the energy storage grid connection point of each sampling point.
Optionally, the curtailment amount calculation unit is specifically configured to:
calculating the required quantity before each sampling point is supplied with power by using the power before the energy storage equipment is supplied according to the power before the energy storage equipment is supplied by each sampling point, and calculating the required quantity after the energy storage equipment is supplied by each sampling point according to the power of the electric network public access point ammeter of each sampling point;
and determining the difference value between the maximum required amount before the power is supplied by the energy storage equipment and the maximum required amount after the power is supplied by the energy storage equipment in the preset charging period as a required amount reduction amount.
Optionally, the apparatus further includes:
and a reduction profit calculation unit for calculating a demand reduction profit based on the demand reduction amount and the demand unit price.
A demand curtailment computing system, comprising: the energy storage output electric meter is connected to the power grid through an energy storage grid connection point;
The local acquisition device is used for receiving the power data of the power grid public access ammeter and the energy storage output ammeter, determining the power of the energy storage grid-connected point, and executing the calculation method of the demand reduction amount disclosed in the embodiment.
A demand curtailment computing system, comprising: the energy storage output electric meter is connected to the power grid through an energy storage grid connection point;
the local acquisition device is used for receiving the power data of the power grid public access ammeter and the energy storage output ammeter, and packaging and sending the power data of the power grid public access ammeter and the energy storage output ammeter to the cloud platform at regular time;
the cloud platform is used for executing the calculation method of the required quantity reduction quantity disclosed in the embodiment.
Compared with the prior art, the invention has the following beneficial effects:
according to the calculation method of the demand reduction amount, under the condition that a user charges according to the actual maximum demand, the power of the public access point ammeter of the power grid is used as the power after the power is supplied by the energy storage equipment, the power of the energy storage grid-connected point is used as the power supply power of the energy storage equipment, the power before the power is supplied by the energy storage equipment, which is determined by the difference value between the power of the public access point ammeter of the power grid and the power of the energy storage grid-connected point, can be accurately obtained, and then the demand before the power is supplied by the energy storage equipment at each sampling point can be accurately calculated according to the power before the power is supplied by the energy storage equipment at each sampling point, so that the maximum demand in a preset charging period is obtained, and the demand reduction amount can be accurately calculated.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for calculating a required amount according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a user side energy storage power station according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a method for calculating the load power before the user adds the stored energy according to the embodiment of the invention;
fig. 4 is a schematic diagram of a method for obtaining power of an electric meter of a public access point of an electric network and power of an energy storage grid-connected point of each sampling point according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a BP neural network model according to an embodiment of the present invention;
FIG. 6 is a schematic diagram showing data comparison before and after error correction according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a calculating device for a required amount according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. 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.
Under the condition that a user charges according to the actual maximum demand, the invention realizes accurate calculation of the demand reduction amount under the mode of charging according to the actual maximum demand by taking the power of the public access point ammeter of the power grid as the power after the power is supplied by the energy storage equipment and taking the power of the energy storage grid-connected point as the power supply power of the energy storage equipment, wherein the energy storage output ammeter of the user is accessed into the power grid through the energy storage grid-connected point, and the number of the energy storage output ammeter is at least one.
Specifically, referring to fig. 1, a method for calculating a required amount of reduction disclosed in the present embodiment includes the following steps:
s101: acquiring power of a power grid public access point ammeter of each sampling point and power of an energy storage grid connection point in a preset charging period, wherein the energy storage grid connection point comprises at least one energy storage output ammeter;
The preset charging period is set according to actual needs, and the domestic power grid generally refers to a natural month.
When the user has an energy storage output ammeter, the power of the energy storage grid-connected point is the power of the energy storage output ammeter.
When the user has a plurality of energy storage output electric meters, the power of the energy storage grid-connected point is the sum of the power of the plurality of energy storage output electric meters.
S102: respectively determining the difference value between the power of the electric meter of the public access point of the power grid and the power of the energy storage grid-connected point of each sampling point as the power before the energy storage equipment is applied to each sampling point;
as shown in fig. 3, the power exchanged by the power grid is the power of the electric meter of the public access point of the power grid in the embodiment, the energy storage output is the power of the energy storage grid-connected point in the embodiment, and the load is the power before the energy storage device is used for supplying power in the embodiment.
S103: calculating the required quantity before the energy storage equipment is applied to each sampling point according to the power before the energy storage equipment is applied to each sampling point, calculating the required quantity after the energy storage equipment is applied to each sampling point according to the power of the electric meter of the public access point of the electric network of each sampling point, and obtaining the required quantity reduction quantity;
specifically, the required amount dmd_load before power supply of the energy storage equipment is applied to each sampling point and the required amount dmd_wc after power supply of the energy storage equipment is applied to each sampling point are calculated according to the definition of the required amount slip, and the method comprises the following steps: according to the definition of the demand slip, the real-time demand dmd_load of any sampling point n can be obtained by using the method of calculating the load average power through the power integration defined by national standards n Is calculated by the following steps:
where dmd_load is the demand for any sample point and pload is the instantaneous power of any n-j to n sample point.
It can be appreciated that the same method can be applied to calculate the required dmd_pcb after each sampling point is powered by the energy storage device.
The method comprises the steps of calculating the required quantity before power is supplied to the application energy storage device and the required quantity after power is supplied to the application energy storage device of each sampling point in a preset charging period, obtaining the maximum required quantity before power is supplied to the application energy storage device and the maximum required quantity after power is supplied to the application energy storage device in the preset charging period, and determining the difference value between the maximum required quantity before power is supplied to the application energy storage device and the maximum required quantity after power is supplied to the application energy storage device in the preset charging period as a required quantity reduction quantity.
Further, after the demand reduction amount is calculated, demand reduction benefits can be calculated from the demand reduction amount and the demand unit price. Because the calculation result of the demand reduction amount is accurate, the demand reduction benefit can be accurately calculated on the basis, and the demand reduction benefit when a user takes time according to the actual maximum demand is realized.
Taking the user side energy storage power station of fig. 2 as an example, a public access Point (PCC) ammeter of an ammeter 2 and an energy storage output ammeter of an ammeter 3 can be collected and respectively read to the metering load and the energy storage output of the ammeter, and after the energy storage is added in month, the maximum demand can be directly read from the ammeter 2, and the curve shown in fig. 3 can be obtained through the verification of an electric charge bill.
The pre-energy storage power is obtained by subtracting the energy storage output from the grid exchange power.
In the example, the local acquisition device can record the power grid exchange power and the energy storage output power with granularity of 10s (sampling time synchronization error is less than or equal to 2 s). With a demand period of 15 minutes and a slip time of 10s, j=90, i.e. 90 points are sampled during the 15 minute period.
Through practical tests, the error between the maximum demand measured by the method and the reading of the ammeter is less than or equal to 0.01 percent.
Therefore, in the calculation method of the demand reduction amount disclosed in the embodiment, under the condition that a user charges according to the actual maximum demand, by taking the power of the electric meter of the public access point of the power grid as the power after the power is supplied by the energy storage device and taking the power of the energy storage and parallel point as the power supply power of the energy storage device, the power before the power is supplied by the energy storage device, which is determined by the difference between the power of the electric meter of the public access point of the power grid and the power of the energy storage and parallel point of the power, can be accurately obtained, the demand before the power is supplied by the energy storage device can be accurately calculated according to the power before the power is supplied by the energy storage device, and the maximum demand reduction amount in the preset charging period can be obtained, so that the demand reduction amount can be accurately calculated, and the demand reduction income of the time consumption of the user according to the actual maximum demand can be accurately calculated.
Further, due to time required for information transmission and hardware measurement, time delay exists in data transmission, time stamps are inaccurate, and data uploading time of the power grid public access point ammeter and the energy storage output ammeter may be asynchronous, in order to reduce errors caused by inconsistent time intervals of sampling points, the time stamps are corrected, and alignment processing is carried out on power measurement values of the power grid public access point ammeter and the power measurement values of the energy storage output ammeter of each sampling point. Specifically, referring to fig. 4, the method for obtaining the power of the electric meter of the public access point of the electric network and the power of the energy storage grid-connected point of each sampling point is as follows:
s201: acquiring a power measured value and a time stamp of an ammeter of a public access point of the power grid of each sampling point and a power measured value and a time stamp of an energy storage grid-connected point;
s202: correcting the time stamp of the electric network public access point electric meter and the time stamp of the energy storage grid-connected point of each sampling point according to the hardware measurement correction parameters and the transmission correction parameters to obtain the standard time stamp of the electric network public access point electric meter and the standard time stamp of the energy storage grid-connected point of each sampling point;
s203: when the standard time stamp of the power grid public access point ammeter of each sampling point is inconsistent with the standard time stamp of the energy storage grid-connected point, fitting the power measured value of the power grid public access point ammeter and the power measured value of the energy storage grid-connected point, which are closest to each other in the standard time stamp, to obtain the standard power of the power grid public access point ammeter of each sampling point and the standard power of the energy storage grid-connected point.
When the data uploading time of the power grid public access point ammeter and the energy storage output ammeter is not synchronous, the standard time stamp of the power grid public access point ammeter of each sampling point is inconsistent with the standard time stamp of the energy storage grid-connected point ammeter, and in order to reduce the error of reduction calculation caused by the asynchronous uploading time of the data of the power grid public access point ammeter and the energy storage output ammeter, the power measurement value of the power grid public access point ammeter with the closest standard time stamp and the power measurement value of the energy storage grid-connected point ammeter are required to be fitted, so that the standard power of the power grid public access point ammeter and the standard power of the energy storage grid-connected point ammeter of each sampling point are obtained. The power measurement value of the power grid public access point ammeter and the power measurement value of the energy storage grid-connected point obtained in the preset charging period correspond to a standard time stamp respectively, and represent uploading time of the power measurement value of the power grid public access point ammeter and uploading time of the power measurement value of the energy storage grid-connected point respectively.
The embodiment provides two ways of fitting the power measured value of the public access point ammeter of the power grid with the nearest standard time stamp and the power measured value of the energy storage grid-connected point:
1. fitting using BP neural network
Assuming that the current time is T0, a preset charging period T0-t_ lrn-t_ sdy to T0 before the current preset charging period, wherein the learning time length is t_ lrn, the training time length is t_ sdy, data of T0-t_ lrn-t_ sdy to T0-t_ lrn segments are training samples, T0-t_ lrn to T0 are learning samples, a BP neural network model is trained, please refer to fig. 5, the number of hidden layer units in the BP neural network model is n= v (n+m) +a, n is the number of input units, m is the number of output units, and a is a constant between [1,10 ].
And inputting the power measured value and the standard time stamp of the power meter of the public access point of the power grid and the power measured value and the standard time stamp of the energy storage and grid connection point of each sampling point into the BP neural network model for fitting processing to obtain the standard power of the power meter of the public access point of the power grid and the standard power of the energy storage and grid connection point of each sampling point.
2. Fitting by two-point method
Linear two-point method: that is, the current time value (t 1, y 1) and the previous time value (t 0, y 0) are used to connect, and the connection is extended in the positive direction of the time axis to obtain the rough next time value (t 2, y 2), wherein y2, t2 are known.
In the embodiment, a linear two-point method is utilized to fit a power measured value of the public access point ammeter of the power grid with the nearest standard time stamp and a power measured value of the energy storage grid-connected point, so that standard power of the public access point ammeter of the power grid and standard power of the energy storage grid-connected point of each sampling point are obtained.
The real-time power data is fitted and aligned through the BP neural network, so that errors caused by inconsistent time intervals of power data sampling points are reduced, and meanwhile, the method is more practical in fit than a common linear two-point method, and more accurate measurement and calculation can be realized.
As shown in fig. 6, assuming that the real data is a parabola, the real data is measured every second, and there is a minute deviation in time due to the data measured by the ammeter.
If the data is directly identified as the data at the corresponding moment without processing, the actually used data is the data which is not processed in the graph, and the deviation from the actual data can be seen to be larger;
meanwhile, if a linear method is directly used, actually used data are lines formed by connecting original data, and the deviation is larger.
The influence is great for users who are often tens of thousands of kW of energy storage, load, etc. As can be seen from fig. 6, the accuracy can be effectively improved after the prediction is added.
Based on the foregoing embodiment, the present embodiment correspondingly discloses a device for calculating a required amount, referring to fig. 7, the device includes:
the power data acquisition unit 101 is configured to acquire power of a power grid public access point ammeter of each sampling point and power of an energy storage grid-connected point in a preset charging period, where the energy storage grid-connected point includes at least one energy storage output ammeter;
a pre-power-supply power determining unit 102, configured to determine, for each sampling point, a difference between power of an electric meter of a public access point of the power grid and power of an energy-storage grid-connected point, where the power is before power is supplied by an energy-storage device;
and the reduction amount calculating unit 103 is configured to calculate, according to the power before the energy storage device is applied to each sampling point, the required amount before the energy storage device is applied to each sampling point, calculate, according to the power of the electric meter of the public access point of the electric network of each sampling point, the required amount after the energy storage device is applied to each sampling point, and obtain a reduction amount of the required amount.
Optionally, the power data acquisition unit 101 includes:
the power measurement value acquisition subunit is used for acquiring the power measurement value and the time stamp of the electric meter of the public access point of the power grid of each sampling point and the power measurement value and the time stamp of the energy storage grid-connected point;
The time stamp correction subunit is used for correcting the time stamp of the electric network public access point electric meter and the time stamp of the energy storage networking point of each sampling point according to the hardware measurement correction parameters and the transmission correction parameters to obtain the standard time stamp of the electric network public access point electric meter and the standard time stamp of the energy storage networking point of each sampling point;
and the power correction subunit is used for fitting the power measured value of the power public access point ammeter of the power grid with the nearest standard time stamp and the power measured value of the energy storage grid-connected point to obtain the standard power of the power public access point ammeter of the power grid with the sampling point and the standard power of the energy storage grid-connected point when the standard time stamp of the power public access point ammeter of the power grid with the sampling point is inconsistent with the standard time stamp of the energy storage grid-connected point.
Optionally, the power correction subunit is specifically configured to:
and inputting the power measured value and the standard time stamp of the power meter of the public access point of the power grid and the power measured value and the standard time stamp of the energy storage and grid connection point of each sampling point into the BP neural network model for fitting processing to obtain the standard power of the power meter of the public access point of the power grid and the standard power of the energy storage and grid connection point of each sampling point.
Optionally, the power correction subunit is specifically configured to:
and fitting the power measurement value of the power grid public access point ammeter with the nearest standard time stamp and the power measurement value of the energy storage grid connection point by using a linear two-point method to obtain the standard power of the power grid public access point ammeter and the standard power of the energy storage grid connection point of each sampling point.
Optionally, the curtailment amount calculation unit 103 is specifically configured to:
calculating the required quantity before each sampling point is supplied with power by using the power before the energy storage equipment is supplied according to the power before the energy storage equipment is supplied by each sampling point, and calculating the required quantity after the energy storage equipment is supplied by each sampling point according to the power of the electric network public access point ammeter of each sampling point;
and determining the difference value between the maximum required amount before the power is supplied by the energy storage equipment and the maximum required amount after the power is supplied by the energy storage equipment in the preset charging period as a required amount reduction amount.
Optionally, the apparatus further includes:
and a reduction profit calculation unit for calculating a demand reduction profit based on the demand reduction amount and the demand unit price.
According to the calculation device for the demand reduction amount, under the condition that a user charges according to the actual maximum demand, the power of the electric meter of the public access point of the power grid is used as the power after the power is supplied by the energy storage equipment, the power of the energy storage grid-connected point is used as the power supply power of the energy storage equipment, the power before the power is supplied by the energy storage equipment, which is determined by the difference value between the power of the electric meter of the public access point of the power grid and the power of the energy storage grid-connected point, can be accurately obtained, and further the demand before the power is supplied by the energy storage equipment for each sampling point can be accurately calculated according to the power before the power is supplied by the energy storage equipment for each sampling point, so that the maximum demand in a preset charging period is obtained, and the demand reduction amount can be accurately calculated.
The embodiment also discloses a calculation system of the amount of reduction of the amount of demand, comprising: the energy storage output electric meter is connected to the power grid through an energy storage grid connection point;
the local acquisition device is used for receiving the power data of the public access ammeter and the energy storage output ammeter of the power grid, determining the power of the energy storage grid-connected point, and executing the following calculation method of the required quantity reduction:
acquiring power of a power grid public access point ammeter of each sampling point and power of an energy storage grid connection point in a preset charging period, wherein the energy storage grid connection point comprises at least one energy storage output ammeter;
respectively determining the difference value between the power of the electric meter of the public access point of the power grid of each sampling point and the power of the energy storage grid-connected point as the power before the power is supplied by the energy storage equipment applied to each sampling point;
according to the power before the sampling points are powered by the energy storage equipment, the demand before the sampling points are powered by the energy storage equipment is calculated, according to the power of the electric network public access point ammeter of each sampling point, the demand after the sampling points are powered by the energy storage equipment is calculated, and the demand reduction amount is obtained.
Further, the obtaining the power of the electric meter of the public access point of the electric network and the power of the energy storage grid-connected point of each sampling point in the preset charging period includes:
acquiring a power measured value and a time stamp of an ammeter of a public access point of the power grid of each sampling point and a power measured value and a time stamp of an energy storage grid-connected point;
correcting the time stamp of the electric network public access point electric meter of each sampling point and the time stamp of the energy storage grid-connected point according to the hardware measurement correction parameters and the transmission correction parameters to obtain the standard time stamp of the electric network public access point electric meter of each sampling point and the standard time stamp of the energy storage grid-connected point;
when the standard time stamp of the power grid public access point ammeter of each sampling point is inconsistent with the standard time stamp of the energy storage grid-connected point, fitting the power measured value of the power grid public access point ammeter and the power measured value of the energy storage grid-connected point, which are closest to each standard time stamp, to obtain the standard power of the power grid public access point ammeter of each sampling point and the standard power of the energy storage grid-connected point.
Further, the fitting the power measurement value of the electric network public access point electric meter and the power measurement value of the energy storage grid-connected point with the nearest standard time stamp to obtain the standard power of the electric network public access point electric meter and the standard power of the energy storage grid-connected point of each sampling point comprises the following steps:
The power measurement value and the standard time stamp of the power grid public access point ammeter of each sampling point and the power measurement value and the standard time stamp of the energy storage and grid connection point are input into a BP neural network model for fitting processing, so that the standard power and the standard power of the energy storage and grid connection point ammeter of each sampling point are obtained, and the BP neural network model is obtained after model training and model learning by using the power measurement value and the standard time stamp of the power grid public access point ammeter of each sampling point and the power measurement value and the standard time stamp of the energy storage and grid connection point in a preset charging period before a current preset charging period as training samples and learning samples.
Further, the fitting the power measurement value of the electric network public access point electric meter and the power measurement value of the energy storage grid-connected point with the nearest standard time stamp to obtain the standard power of the electric network public access point electric meter and the standard power of the energy storage grid-connected point of each sampling point comprises the following steps:
and fitting the power measurement value of the power grid public access point ammeter with the nearest standard time stamp and the power measurement value of the energy storage grid connection point by using a linear two-point method to obtain the standard power of the power grid public access point ammeter and the standard power of the energy storage grid connection point of each sampling point.
Further, the calculating the demand before each sampling point applies the energy storage device to supply power according to the power before each sampling point applies the energy storage device to supply power, calculating the demand after each sampling point applies the energy storage device to supply power according to the power of the electric network public access point ammeter of each sampling point, and obtaining the demand reduction, including:
calculating the required quantity before each sampling point is supplied with power by using the power before the energy storage equipment is supplied according to the power before the energy storage equipment is supplied by each sampling point, and calculating the required quantity after the energy storage equipment is supplied by each sampling point according to the power of the electric network public access point ammeter of each sampling point;
and determining the difference value between the maximum required amount before the power is supplied by the energy storage equipment and the maximum required amount after the power is supplied by the energy storage equipment in the preset charging period as a required amount reduction amount.
Further, the method further comprises:
and calculating the demand reduction benefit according to the demand reduction amount and the demand unit price.
The present embodiment also discloses another calculation system for reducing the amount of demand, including: the energy storage output electric meter is connected to the power grid through an energy storage grid connection point;
The local acquisition device is used for receiving the power data of the power grid public access ammeter and the energy storage output ammeter, and packaging and sending the power data of the power grid public access ammeter and the energy storage output ammeter to the cloud platform at regular time;
the cloud platform is used for executing the following calculation method of the required quantity reduction:
acquiring power of a power grid public access point ammeter of each sampling point and power of an energy storage grid connection point in a preset charging period, wherein the energy storage grid connection point comprises at least one energy storage output ammeter;
respectively determining the difference value between the power of the electric meter of the public access point of the power grid of each sampling point and the power of the energy storage grid-connected point as the power before the power is supplied by the energy storage equipment applied to each sampling point;
according to the power before the sampling points are powered by the energy storage equipment, the demand before the sampling points are powered by the energy storage equipment is calculated, according to the power of the electric network public access point ammeter of each sampling point, the demand after the sampling points are powered by the energy storage equipment is calculated, and the demand reduction amount is obtained.
Further, the obtaining the power of the electric meter of the public access point of the electric network and the power of the energy storage grid-connected point of each sampling point in the preset charging period includes:
Acquiring a power measured value and a time stamp of an ammeter of a public access point of the power grid of each sampling point and a power measured value and a time stamp of an energy storage grid-connected point;
correcting the time stamp of the electric network public access point electric meter of each sampling point and the time stamp of the energy storage grid-connected point according to the hardware measurement correction parameters and the transmission correction parameters to obtain the standard time stamp of the electric network public access point electric meter of each sampling point and the standard time stamp of the energy storage grid-connected point;
when the standard time stamp of the power grid public access point ammeter of each sampling point is inconsistent with the standard time stamp of the energy storage grid-connected point, fitting the power measured value of the power grid public access point ammeter and the power measured value of the energy storage grid-connected point, which are closest to each standard time stamp, to obtain the standard power of the power grid public access point ammeter of each sampling point and the standard power of the energy storage grid-connected point.
Further, the fitting the power measurement value of the electric network public access point electric meter and the power measurement value of the energy storage grid-connected point with the nearest standard time stamp to obtain the standard power of the electric network public access point electric meter and the standard power of the energy storage grid-connected point of each sampling point comprises the following steps:
The power measurement value and the standard time stamp of the power grid public access point ammeter of each sampling point and the power measurement value and the standard time stamp of the energy storage and grid connection point are input into a BP neural network model for fitting processing, so that the standard power and the standard power of the energy storage and grid connection point ammeter of each sampling point are obtained, and the BP neural network model is obtained after model training and model learning by using the power measurement value and the standard time stamp of the power grid public access point ammeter of each sampling point and the power measurement value and the standard time stamp of the energy storage and grid connection point in a preset charging period before a current preset charging period as training samples and learning samples.
Further, the fitting the power measurement value of the electric network public access point electric meter and the power measurement value of the energy storage grid-connected point with the nearest standard time stamp to obtain the standard power of the electric network public access point electric meter and the standard power of the energy storage grid-connected point of each sampling point comprises the following steps:
and fitting the power measurement value of the power grid public access point ammeter with the nearest standard time stamp and the power measurement value of the energy storage grid connection point by using a linear two-point method to obtain the standard power of the power grid public access point ammeter and the standard power of the energy storage grid connection point of each sampling point.
Further, the calculating the demand before each sampling point applies the energy storage device to supply power according to the power before each sampling point applies the energy storage device to supply power, calculating the demand after each sampling point applies the energy storage device to supply power according to the power of the electric network public access point ammeter of each sampling point, and obtaining the demand reduction, including:
calculating the required quantity before each sampling point is supplied with power by using the power before the energy storage equipment is supplied according to the power before the energy storage equipment is supplied by each sampling point, and calculating the required quantity after the energy storage equipment is supplied by each sampling point according to the power of the electric network public access point ammeter of each sampling point;
and determining the difference value between the maximum required amount before the power is supplied by the energy storage equipment and the maximum required amount after the power is supplied by the energy storage equipment in the preset charging period as a required amount reduction amount.
Further, the method further comprises:
and calculating the demand reduction benefit according to the demand reduction amount and the demand unit price.
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 (10)
1. A method of calculating a reduction in a demand, comprising:
acquiring power of an ammeter of a public access point of a power grid and power of an energy storage grid-connected point of each sampling point in a preset charging period;
respectively determining the difference value between the power of the electric meter of the public access point of the power grid of each sampling point and the power of the energy storage grid-connected point as the power before the power is supplied by the energy storage equipment applied to each sampling point;
calculating the required quantity before power is supplied to each sampling point by using the energy storage equipment according to the power before power is supplied to each sampling point by using the energy storage equipment, calculating the required quantity after power is supplied to each sampling point by using the energy storage equipment according to the power of the electric network public access point ammeter of each sampling point, and obtaining the required quantity reduction quantity;
the obtaining the power of the electric meter of the public access point of the electric network and the power of the energy storage grid-connected point of each sampling point in the preset charging period comprises the following steps:
acquiring a power measured value and a time stamp of an ammeter of a public access point of the power grid of each sampling point and a power measured value and a time stamp of an energy storage grid-connected point;
correcting the time stamp of the electric network public access point electric meter of each sampling point and the time stamp of the energy storage grid-connected point according to the hardware measurement correction parameters and the transmission correction parameters to obtain the standard time stamp of the electric network public access point electric meter of each sampling point and the standard time stamp of the energy storage grid-connected point;
When the standard time stamp of the power grid public access point ammeter of each sampling point is inconsistent with the standard time stamp of the energy storage grid-connected point, fitting the power measured value of the power grid public access point ammeter and the power measured value of the energy storage grid-connected point, which are closest to each standard time stamp, to obtain the standard power of the power grid public access point ammeter of each sampling point and the standard power of the energy storage grid-connected point.
2. The method according to claim 1, wherein fitting the power measurement value of the grid public access point ammeter and the power measurement value of the energy storage grid-connected point with the closest standard time stamp to obtain the standard power of the grid public access point ammeter and the standard power of the energy storage grid-connected point of each sampling point comprises:
the power measurement value and the standard time stamp of the power grid public access point ammeter of each sampling point and the power measurement value and the standard time stamp of the energy storage and grid connection point are input into a BP neural network model for fitting processing, so that the standard power and the standard power of the energy storage and grid connection point ammeter of each sampling point are obtained, and the BP neural network model is obtained after model training and model learning by using the power measurement value and the standard time stamp of the power grid public access point ammeter of each sampling point and the power measurement value and the standard time stamp of the energy storage and grid connection point in a preset charging period before a current preset charging period as training samples and learning samples.
3. The method according to claim 1, wherein fitting the power measurement value of the grid public access point ammeter and the power measurement value of the energy storage grid-connected point with the closest standard time stamp to obtain the standard power of the grid public access point ammeter and the standard power of the energy storage grid-connected point of each sampling point comprises:
and fitting the power measurement value of the power grid public access point ammeter with the nearest standard time stamp and the power measurement value of the energy storage grid connection point by using a linear two-point method to obtain the standard power of the power grid public access point ammeter and the standard power of the energy storage grid connection point of each sampling point.
4. The method of claim 1, wherein the calculating the demand before each sampling point uses the energy storage device according to the power before each sampling point uses the energy storage device to supply power, calculating the demand after each sampling point uses the energy storage device according to the power of the electric network public access point electric meter of each sampling point, and obtaining the demand reduction amount comprises:
calculating the required quantity before each sampling point is supplied with power by using the power before the energy storage equipment is supplied according to the power before the energy storage equipment is supplied by each sampling point, and calculating the required quantity after the energy storage equipment is supplied by each sampling point according to the power of the electric network public access point ammeter of each sampling point;
And determining the difference value between the maximum required amount before the power is supplied by the energy storage equipment and the maximum required amount after the power is supplied by the energy storage equipment in the preset charging period as a required amount reduction amount.
5. The method according to claim 1, wherein the method further comprises:
and calculating the demand reduction benefit according to the demand reduction amount and the demand unit price.
6. A calculation apparatus for a reduction amount of a demand, comprising:
the power data acquisition unit is used for acquiring the power of the electric network public access point ammeter of each sampling point and the power of the energy storage grid-connected point in a preset charging period;
the power before supply determining unit is used for respectively determining the difference value between the power of the electric network public access point ammeter of each sampling point and the power of the energy storage grid-connected point, and applying the power before the energy storage equipment for each sampling point;
the reduction amount calculation unit is used for calculating the required amount before the power is supplied by the energy storage equipment applied to each sampling point according to the power before the power is supplied by the energy storage equipment applied to each sampling point, calculating the required amount after the power is supplied by the energy storage equipment applied to each sampling point according to the power of the electric network public access point electric meter of each sampling point, and obtaining the reduction amount of the required amount;
Wherein, the power data acquisition unit includes:
the power measurement value acquisition subunit is used for acquiring the power measurement value and the time stamp of the electric meter of the public access point of the power grid of each sampling point and the power measurement value and the time stamp of the energy storage grid-connected point;
the time stamp correction subunit is used for correcting the time stamp of the electric network public access point electric meter and the time stamp of the energy storage networking point of each sampling point according to the hardware measurement correction parameters and the transmission correction parameters to obtain the standard time stamp of the electric network public access point electric meter and the standard time stamp of the energy storage networking point of each sampling point;
and the power correction subunit is used for fitting the power measured value of the power public access point ammeter of the power grid with the nearest standard time stamp and the power measured value of the energy storage grid-connected point to obtain the standard power of the power public access point ammeter of the power grid with the sampling point and the standard power of the energy storage grid-connected point when the standard time stamp of the power public access point ammeter of the power grid with the sampling point is inconsistent with the standard time stamp of the energy storage grid-connected point.
7. The apparatus of claim 6, wherein the power modification subunit is specifically configured to:
The power measurement value and the standard time stamp of the power grid public access point ammeter of each sampling point and the power measurement value and the standard time stamp of the energy storage and grid connection point are input into a BP neural network model for fitting processing, so that the standard power and the standard power of the energy storage and grid connection point ammeter of each sampling point are obtained, and the BP neural network model is obtained after model training and model learning by using the power measurement value and the standard time stamp of the power grid public access point ammeter of each sampling point and the power measurement value and the standard time stamp of the energy storage and grid connection point in a preset charging period before a current preset charging period as training samples and learning samples.
8. The apparatus of claim 6, wherein the power modification subunit is specifically configured to:
and fitting the power measurement value of the power grid public access point ammeter with the nearest standard time stamp and the power measurement value of the energy storage grid connection point by using a linear two-point method to obtain the standard power of the power grid public access point ammeter and the standard power of the energy storage grid connection point of each sampling point.
9. A demand-reduction computing system, comprising: the energy storage output electric meter is connected to the power grid through an energy storage grid connection point;
The local acquisition device is used for receiving the power data of the public access ammeter and the energy storage output ammeter of the power grid, determining the power of an energy storage grid-connected point and executing the calculation method of the demand reduction amount according to any one of claims 1-5.
10. A demand-reduction computing system, comprising: the energy storage output electric meter is connected to the power grid through an energy storage grid connection point;
the local acquisition device is used for receiving the power data of the power grid public access ammeter and the energy storage output ammeter, and packaging and sending the power data of the power grid public access ammeter and the energy storage output ammeter to the cloud platform at regular time;
the cloud platform is configured to execute the method for calculating the demand reduction amount according to any one of claims 1 to 5.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105940584A (en) * | 2014-02-14 | 2016-09-14 | 三菱电机株式会社 | Demand control device and program |
| CN108242820A (en) * | 2016-12-27 | 2018-07-03 | 财团法人工业技术研究院 | Charge-discharge control method of grid-connected electricity storage system and rental service pricing system |
| CN110174623A (en) * | 2019-06-10 | 2019-08-27 | 合肥阳光新能源科技有限公司 | A kind of SOC calibration method of energy-accumulating power station battery |
| CN110601243A (en) * | 2019-10-21 | 2019-12-20 | 合肥阳光新能源科技有限公司 | Energy storage system and peak clipping, valley filling and demand management cooperative control method thereof |
| WO2020056308A1 (en) * | 2018-09-14 | 2020-03-19 | Lancium Llc | Systems and methods for dynamic power routing with behind-the-meter energy storage |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8849715B2 (en) * | 2012-10-24 | 2014-09-30 | Causam Energy, Inc. | System, method, and apparatus for settlement for participation in an electric power grid |
-
2020
- 2020-06-15 CN CN202010542023.0A patent/CN111695817B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105940584A (en) * | 2014-02-14 | 2016-09-14 | 三菱电机株式会社 | Demand control device and program |
| CN108242820A (en) * | 2016-12-27 | 2018-07-03 | 财团法人工业技术研究院 | Charge-discharge control method of grid-connected electricity storage system and rental service pricing system |
| WO2020056308A1 (en) * | 2018-09-14 | 2020-03-19 | Lancium Llc | Systems and methods for dynamic power routing with behind-the-meter energy storage |
| CN110174623A (en) * | 2019-06-10 | 2019-08-27 | 合肥阳光新能源科技有限公司 | A kind of SOC calibration method of energy-accumulating power station battery |
| CN110601243A (en) * | 2019-10-21 | 2019-12-20 | 合肥阳光新能源科技有限公司 | Energy storage system and peak clipping, valley filling and demand management cooperative control method thereof |
Non-Patent Citations (1)
| Title |
|---|
| 基于用户侧可调节资源的售电公司实时市场偏差电量管控策略.《电力建设》.2019,全文. * |
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