CN115986824A - Energy storage configuration method and system considering correlation between load and new energy output - Google Patents
Energy storage configuration method and system considering correlation between load and new energy output Download PDFInfo
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Abstract
The invention discloses an energy storage configuration method and system considering the correlation between load and new energy output, which comprises the following steps: acquiring new energy output data and load demand data of new energy in a target area within a preset time period; determining a scissors difference coefficient corresponding to each moment in each preset period according to the new energy output data and the load demand data, and determining a correlation time period when the new energy output and the load demand in each preset period meet the correlation according to the scissors difference coefficient; and performing energy storage configuration on the new energy according to the correlation time interval and the new energy output data. Compared with an energy storage configuration mode which does not consider the correlation between the new energy and the energy storage device and directly and completely smoothes the new energy output curve, the method ensures that the new energy is not limited by the average output curve but directly participates in power balance in the correlation time period, avoids redundant charging and discharging processes of the energy storage device, and reduces the requirements on energy storage capacity and rated power to a certain extent.
Description
Technical Field
The present invention relates to the field of power system planning and operation technology, and more particularly, to an energy storage configuration method and system considering the correlation between load and new energy output.
Background
The aims of carbon peak reaching and carbon neutralization are provided and the construction of a novel power system taking new energy as a main body, and the energy structure transformation and the power system transformation in China are gradually deepened. In the meantime, new energy has attracted attention and paid attention as a main power source of a new power system in the future, and has been developed. Meanwhile, wind power and photovoltaic power generation are used as main forms of new energy power generation, the output uncertainty and the fluctuation of the wind power and photovoltaic power generation obviously increase the regulation and control pressure of a power grid, the power supply abundance is deeply influenced, and great challenges are brought to the safe and stable operation of the power grid.
The key to solve the problems is to stabilize the output fluctuation of the new energy and improve the output characteristic of the new energy. The energy storage is used as a key means for efficient utilization and flexible conversion of energy, the output characteristic of the new energy power supply can be improved, and a solution is provided for large-scale grid connection of new energy. The energy storage device with certain capacity and rated power is configured on the new energy power generation side, so that the fluctuation of the output power of the energy storage device can be effectively stabilized, and a new energy power supply is converted into a dispatchable power supply to a certain extent.
However, a corresponding power generation side capacity configuration method is proposed for a scene in which new energy is used as a main power source, and the correlation between the output of the new energy and the load demand is not considered in the energy storage configuration process. Therefore, under the background of a novel power system, the output wave of the new energy can not be fully stabilized by the stored energy, so that the new energy power supply can not participate in power balance as an adjustable power supply, and the requirement that the new energy is used as a main power supply to bear basic charge in the future is difficult to meet.
Therefore, there is a need to develop a new energy generation side energy storage configuration method suitable for a new power system.
Disclosure of Invention
The invention provides an energy storage configuration method and system considering the correlation between load and new energy output, and aims to solve the problem of how to configure the energy storage at the new energy power generation side based on the correlation between the new energy output and the load demand.
In order to solve the above problem, according to an aspect of the present invention, there is provided an energy storage configuration method considering a correlation between a load and a new energy output, the method including:
acquiring new energy output data and load demand data of new energy in a target area within a preset time period;
determining a scissors difference coefficient corresponding to each moment in each preset period according to the new energy output data and the load demand data, and determining a correlation time interval when the new energy output and the load demand in each preset period meet the correlation according to the scissors difference coefficient;
and performing energy storage configuration on the new energy according to the correlation time interval and the new energy output data.
Preferably, the determining a scissor difference coefficient corresponding to each moment in each preset period according to the new energy output data and the load demand data includes:
wherein S is d,k The shear difference coefficient of the new energy output and the load demand at the kth moment in the d preset period;
the new energy output at the kth moment in the d preset period is obtained; />
The load demand at the kth moment in the d-th preset period. />
Preferably, the determining, according to the scissors difference coefficient, a correlation period in which the new energy output and the load demand meet the correlation in each preset period includes:
and determining the boundary parameter of the relevant interval as s, and determining the relevant time interval in which the new energy output and the load demand meet the relevance in any preset period according to the corresponding moment when the scissors difference coefficient falls in the relevant interval [1-s,1+s ] for any preset period.
Preferably, the configuring, according to the correlation time period and the new energy output data, the energy storage of the new energy includes:
segmenting the new energy output data according to the correlation time period, determining the non-correlation time period in each preset period, and calculating the new energy output average value of the non-correlation time period in each preset period;
and performing energy storage configuration on the new energy according to the segmented new energy output data and the new energy output average value corresponding to each preset period.
Preferably, the calculating the new energy output average value of the non-correlation time period in each preset period comprises:
wherein the content of the first and second substances,
the new energy output average value of the non-correlation time interval in the d preset period is obtained; />
The new energy output at the kth moment in the d preset period is obtained; />
The stored energy power at the kth moment in the d preset period.
Preferably, the performing energy storage configuration on the new energy according to the segmented new energy output data and the new energy output average value corresponding to each preset period includes:
determining a first energy storage configuration capacity of a new energy power generation side corresponding to each preset period according to the segmented new energy output data and the new energy output average value corresponding to each preset period;
constructing an energy storage configuration capacity probability density function according to the first energy storage configuration capacity of the new energy power generation side corresponding to each preset period;
and determining a second energy storage configuration capacity and an energy storage rated power of the new energy power generation side corresponding to the preset time period according to the energy storage configuration capacity probability density function and a preset confidence level.
Preferably, the determining the first energy storage configuration capacity of the new energy power generation side corresponding to each preset period according to the segmented new energy output data and the new energy output average value corresponding to each preset period includes:
the method comprises the steps of constructing an energy storage configuration capacity optimization model and solving to obtain a first energy storage configuration capacity of a new energy power generation side corresponding to each preset period;
wherein, the energy storage configuration capacity optimization model comprises:
wherein the content of the first and second substances,
configuring capacity for a first energy storage at a new energy power generation side corresponding to the d-th preset period; />
Storing initial stored electric quantity at the beginning of the d preset period; p d r,e k The new energy output at the kth moment in the d preset period is obtained; />
The energy storage power at the kth moment in the d preset period is obtained; />
The new energy output average value of the non-correlation time interval in the d preset period is obtained; />
And configuring the maximum power of stored energy for the d preset period.
Preferably, the constructing an energy storage configuration capacity probability density function according to the first energy storage configuration capacity at the new energy power generation side corresponding to each preset period includes:
wherein, f (C) sto ) Configuring a capacity probability density function for the energy storage; k (-) is a kernel function; tau is a preset positive number and represents the bandwidth; d is the total number of the preset periods in the statistical range;
configuring capacity for a first energy storage at a new energy power generation side corresponding to the d-th preset period; c sto Capacity is configured for the first energy storage.
Preferably, the determining, according to the energy storage configuration capacity probability density function and a preset confidence level, a second energy storage configuration capacity and an energy storage rated power of the new energy power generation side corresponding to the preset time period includes:
wherein, C sto,α Configuring capacity for the second energy storage; f (-) is the energy storage configuration capacity probability density function F (C) sto ) A primitive function of (a); f -1 (. H) is the inverse of F (-);
configuring a lower bound of capacity for the second energy storage; alpha is a preset significance level parameter; />
Rated power for energy storage; />
Configuring the maximum power of stored energy for the d preset period; d α Configuring a set of capacities for a first energy storage of a new energy generation side corresponding to each preset period under a 1-alpha confidence level
All of them are less than C sto,α The element of (a) corresponds to a set of preset periods; d is the total number of the preset periods in the statistical range.
According to another aspect of the invention, there is provided an energy storage configuration system considering the dependency of load and new energy output, the system comprising:
the data acquisition unit is used for acquiring new energy output data and load demand data of new energy in a target area within a preset time period;
the correlation time interval determining unit is used for determining a scissors difference coefficient corresponding to each moment in each preset period according to the new energy output data and the load demand data, and determining a correlation time interval in which the new energy output and the load demand in each preset period meet correlation according to the scissors difference coefficient;
and the energy storage configuration unit is used for performing energy storage configuration on the new energy according to the correlation time interval and the new energy output data.
Preferably, the determining unit of the correlation period determines the scissors difference coefficient corresponding to each moment in each preset period according to the new energy output data and the load demand data, and includes:
wherein S is d,k The shear difference coefficient is the new energy output and the load demand at the kth moment in the d preset period;
the new energy output at the kth moment in the d preset period is obtained; />
The load demand at the kth moment in the d-th preset period.
Preferably, the determining unit of the correlation period determines the correlation period in which the new energy output and the load demand in each preset cycle meet the correlation according to the scissors difference coefficient, and includes:
and determining the boundary parameter of the relevant interval as s, and determining the relevant time interval in which the new energy output and the load demand meet the relevance in any preset period according to the corresponding moment when the scissors difference coefficient falls in the relevant interval [1-s,1+s ] for any preset period.
Preferably, the energy storage configuration unit performs energy storage configuration on the new energy according to the correlation time period and the new energy output data, and includes:
the new energy output average value determining module is used for segmenting the new energy output data according to the correlation time interval, determining the non-correlation time interval in each preset period and calculating the new energy output average value of the non-correlation time interval in each preset period;
and the energy storage configuration module is used for performing energy storage configuration on the new energy according to the segmented new energy output data and the new energy output average value corresponding to each preset period. 14. The system of claim 13, wherein the new energy output average determining unit calculates the new energy output average for the non-correlation period in each preset period, and comprises:
wherein the content of the first and second substances,
the new energy output average value of the non-correlation time period in the d preset period is obtained; />
The new energy output at the kth moment in the d preset period is obtained; />
The stored energy power at the kth moment in the d preset period.
Preferably, the energy storage configuration module performs energy storage configuration on the new energy according to the segmented new energy output data and the new energy output average value corresponding to each preset period, and includes:
the first energy storage configuration capacity determining submodule is used for determining the first energy storage configuration capacity of the new energy power generation side corresponding to each preset period according to the segmented new energy output data corresponding to each preset period and the new energy output average value;
the probability density function determining submodule is used for constructing an energy storage configuration capacity probability density function according to the first energy storage configuration capacity of the new energy power generation side corresponding to each preset period;
and the second energy storage configuration capacity and rated power determining submodule is used for determining second energy storage configuration capacity and energy storage rated power of the new energy power generation side corresponding to the preset time period according to the energy storage configuration capacity probability density function and a preset confidence level.
Preferably, the determining module of the first energy storage configuration capacity determines the first energy storage configuration capacity of the new energy power generation side corresponding to each preset period according to the segmented new energy output data and the new energy output average value corresponding to each preset period, and includes:
the method comprises the steps of constructing an energy storage configuration capacity optimization model and solving to obtain a first energy storage configuration capacity of a new energy power generation side corresponding to each preset period;
wherein, the energy storage configuration capacity optimization model comprises:
wherein the content of the first and second substances,
configuring capacity for a first energy storage at a new energy power generation side corresponding to the d-th preset period; />
Storing initial stored electric quantity at the beginning of the d preset period; />
The new energy output at the kth moment in the d preset period is obtained;
the stored energy power at the kth moment in the d preset period is obtained; />
The new energy output average value of the non-correlation time interval in the d preset period is obtained; />
And configuring the maximum power of stored energy for the d preset period.
Preferably, the probability density function determining submodule constructs an energy storage configuration capacity probability density function according to the first energy storage configuration capacity at the new energy power generation side corresponding to each preset period, and includes:
wherein, f (C) sto ) Configuring a capacity probability density function for the energy storage; k (-) is a kernel function; tau is a preset positive number and represents the bandwidth; d is the total number of the preset periods in the statistical range;
configuring capacity for a first energy storage at a new energy power generation side corresponding to the d-th preset period; c sto Capacity is configured for the first energy storage.
Preferably, the determining submodule of the second energy storage configuration capacity and the rated power determines the second energy storage configuration capacity and the energy storage rated power of the new energy power generation side corresponding to the preset time period according to the energy storage configuration capacity probability density function and a preset confidence level, and includes:
wherein, C sto,α Configuring capacity for the second energy storage; f (-) is the energy storage configuration capacity probability density function F (C) sto ) A primitive function of (a); f -1 (. Cndot.) is the inverse of F (-);
configuring a lower bound of capacity for the second energy storage; alpha is a preset significance level parameter; />
Rated power for energy storage; />
Configuring the maximum energy storage capacity for the d preset periodPower; d α Configuring a set of capacities for a first energy storage of a new energy generation side corresponding to each preset period under a 1-alpha confidence level
All of them are less than C sto,α The element of (a) corresponds to a set of preset periods; d is the total number of the preset periods in the statistical range.
Based on a further aspect of the invention, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of any of the energy storage configuration methods taking into account the dependency of the load and the new energy contribution.
Based on another aspect of the present invention, the present invention provides an electronic device comprising:
the computer-readable storage medium described above; and
one or more processors to execute the program in the computer-readable storage medium.
The invention provides an energy storage configuration method and system considering the correlation between load and new energy output, which can quantitatively depict the correlation between the new energy output and the load demand through a scissor difference coefficient, determine the correlation time period of the new energy output and the load demand, and perform energy storage configuration on the new energy according to the correlation time period and the new energy output data.
Drawings
A more complete understanding of exemplary embodiments of the present invention may be had by reference to the following drawings in which:
fig. 1 is a flow chart of an energy storage configuration method 100 considering load and new energy output correlations according to an embodiment of the invention;
FIG. 2 is a schematic diagram of the scissor error coefficient and the positive correlation interval of new energy output and load demand at each time of day according to an embodiment of the invention;
FIG. 3 is a schematic diagram of a segment of a new energy output curve and an average value of the new energy output at a certain day according to an embodiment of the invention;
FIG. 4 is a diagram of an energy storage configuration for a day segment new energy output curve, according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of annual energy storage configuration capacity probability statistics according to an embodiment of the invention;
FIG. 6 is a graph of annual output of a wind farm according to an embodiment of the present invention;
FIG. 7 is a graph of normalized annual load according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of determining an energy storage configuration capacity for a wind farm according to an embodiment of the present invention;
fig. 9 is a schematic diagram of an energy storage configuration system 900 considering the correlation between load and new energy output according to an embodiment of the present invention.
Detailed Description
The exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, however, the present invention may be embodied in many different forms and is not limited to the embodiments described herein, which are provided for complete and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention. In the drawings, the same unit/element is denoted by the same reference numeral.
Unless otherwise defined, terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Further, it will be understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense.
The existing energy storage configuration method is rarely used for carrying out power generation side capacity configuration at the angle that new energy is used as a main power supply, and the correlation between the output of the new energy and the load requirement is not considered in the energy storage configuration process. Therefore, the energy storage configuration capacity is difficult to effectively stabilize the output fluctuation of the new energy, the system regulation and control pressure when the new energy is used as a main power supply cannot be relieved, and even the power and electric quantity balance is difficult to ensure. Therefore, in order to meet the development requirements of constructing a novel power system with new energy as a main body, smoothen the output curve of the new energy to the maximum extent, fully consider the correlation between the output of the new energy and the load requirements, avoid redundant charging and discharging processes of an energy storage device as much as possible, reasonably configure the energy storage capacity and set the rated power, the invention provides a new energy power generation side energy storage configuration method considering the correlation between the load and the output of the new energy based on probability statistics.
Fig. 1 is a flow chart of an energy storage configuration method 100 considering load and new energy output correlations according to an embodiment of the invention. As shown in fig. 1, in an energy storage configuration method 100 considering a correlation between a load and a new energy output according to an embodiment of the present invention, starting at step 101, new energy output data and load demand data of a new energy in a target area within a preset time period are obtained at step 101.
In the present invention, a year is used as a preset time period, and a day is used as a preset period. When energy storage configuration is carried out, actual output data and annual load data of new energy in a target area need to be acquired. The actual output data and the annual load data of the new energy at least comprise wind power, photovoltaic actual output curves and contemporaneous load curves of a whole year in a certain area; the sampling period of the above data should be synchronized to 15 minutes or 1 hour, i.e. 96 or 24 time points are included in the collected data per day.
In step 102, according to the new energy output data and the load demand data, a scissors difference coefficient corresponding to each moment in each preset period is determined, and a correlation time period when the new energy output and the load demand meet correlation in each preset period is determined according to the scissors difference coefficient.
Preferably, the determining a scissor difference coefficient corresponding to each moment in each preset period according to the new energy output data and the load demand data includes:
wherein S is d,k The shear difference coefficient is the new energy output and the load demand at the kth moment in the d preset period;
the new energy output at the kth moment in the d preset period is obtained; />
The load demand at the kth moment in the d-th preset period.
Preferably, the determining, according to the scissor difference coefficient, a correlation time period in which the new energy output and the load demand meet the correlation within each preset period includes:
and determining the boundary parameter of the relevant interval as s, and determining the relevant time interval in which the new energy output and the load demand meet the relevance in any preset period according to the corresponding moment when the scissors difference coefficient falls in the relevant interval [1-s,1+s ] for any preset period.
In the invention, a daily new energy output and load demand data set is constructed in a daily period, a daily scissors difference coefficient is calculated according to the daily new energy output and load demand data set, and a correlation time period with correlation between the new energy output and the load demand data set is determined according to a visible coefficient.
In the present invention, the scissors difference coefficient can be calculated by the following formula:
in the formula, S d,k The shear difference coefficient of the new energy output and the load demand at the kth moment of the day d is obtained;
at day d, kOutputting new energy; />
Is the load demand at the kth time of day d. Wherein it is of uniform magnitude for comparison purposes>
And &>
Is normalized data.
Let the boundary parameter of the relevant interval be S, then when the scissors difference coefficient is S d,k Falls in the relevant interval [1-s,1+s ]]In time, the new energy output and the load demand can be determined to have correlation, and the corresponding time period is the correlation time period. The set of all correlation periods on day d can be defined as τ under the correlation interval boundary parameter s d,s . The invention sets the correlation period tau d,s And in addition, the new energy does not directly participate in electric power balance through the energy storage device. In addition, the related interval boundary parameter s can be flexibly set according to the calculation requirement and practical experience.
The shear difference coefficient and the related interval are shown by taking the new energy output and the load demand on the day d as an example, as shown in fig. 2. The closer the scissors difference coefficient is to 1, the more the new energy output and the load demand occupy the same position in the respective data sets, and the two have stronger correlation. The relevant interval [1-a,1+a ] can be constructed by setting the relevant interval boundary parameter s as a and b respectively]And [1-b,1+b]Wherein a is more than 0 and less than b. In FIG. 1, τ d,a Including time periods 1-4, 37-40, 84-86 and time 65; tau is d,b Including periods 1-4, 35-40, 55-57, 59-66, and 82-87.
And 103, performing energy storage configuration on the new energy according to the correlation time interval and the new energy output data.
In the embodiment of the invention, after the correlation time period is determined, the new energy is subjected to energy storage configuration according to the correlation time period and the new energy output data. Compared with an energy storage configuration mode in which the correlation between the new energy and the energy storage device is not considered and the new energy output curve is directly and completely smoothed, the new energy is not limited by the average output curve in the correlation time period and directly participates in power balance, redundant charging and discharging processes of the energy storage device are avoided, and requirements on energy storage capacity and rated power are reduced to a certain extent.
Preferably, the configuring, according to the correlation time period and the new energy output data, the energy storage of the new energy includes:
segmenting the new energy output data according to the correlation time period, determining the non-correlation time period in each preset period, and calculating the new energy output average value of the non-correlation time period in each preset period;
and performing energy storage configuration on the new energy according to the segmented new energy output data and the new energy output average value corresponding to each preset period.
Preferably, the calculating the new energy output average value of the non-correlation time period in each preset period comprises:
wherein the content of the first and second substances,
the new energy output average value of the non-correlation time interval in the d preset period is obtained; />
The new energy output at the kth moment in the d preset period is obtained; />
The stored energy power at the kth moment in the d preset period.
The existing new energy power generation side energy storage configuration method mainly focuses on optimizing capacity configuration, and research level relates to a new energy large-scale grid-connected system, a power distribution network and a microgrid system. The optimization model usually aims at optimizing the economic and technical performance of the system, and simultaneously considers technical indexes and constraints related to output fluctuation, system stability and power and electric quantity balance.
In the invention, according to the correlation time period determined in the step 102, the new energy output curve of each day is segmented, the new energy output average value of the segmented non-correlation time period is calculated, and then the new energy is subjected to energy storage configuration according to the segmented new energy output data and the new energy output average value corresponding to each preset period.
In the present invention, as shown in fig. 3, the result of performing the segmentation processing on the new energy output curve is obtained according to the correlation time period τ obtained in step 102 d,s The new energy output curves are divided into two categories by the boundary of (1). One is the correlation period τ d,s The corresponding new energy is output, and the new energy directly participates in the power balance at the stage and does not participate in the charging and discharging processes of the energy storage device; the second is new energy output corresponding to the non-correlation time period, the new energy output needs to be adjusted by the energy storage device and then participate in power balance, and the adjustment process is shown as the following formula:
in the formula (I), the compound is shown in the specification,
the new energy output is given at the kth moment on the day d; />
The energy storage power is the energy storage power at the kth moment of the day d, wherein the charging is a positive value, and the discharging is a negative value; />
Mean new energy contribution for the non-relevant period of day d.
Preferably, the performing energy storage configuration on the new energy according to the segmented new energy output data and the new energy output average value corresponding to each preset period includes:
determining a first energy storage configuration capacity of a new energy power generation side corresponding to each preset period according to the segmented new energy output data and the new energy output average value corresponding to each preset period;
constructing an energy storage configuration capacity probability density function according to the first energy storage configuration capacity of the new energy power generation side corresponding to each preset period;
and determining a second energy storage configuration capacity and an energy storage rated power of the new energy power generation side corresponding to the preset time period according to the energy storage configuration capacity probability density function and a preset confidence level.
Preferably, the determining the first energy storage configuration capacity of the new energy power generation side corresponding to each preset period according to the segmented new energy output data and the new energy output average value corresponding to each preset period includes:
the method comprises the steps of constructing an energy storage configuration capacity optimization model and solving to obtain a first energy storage configuration capacity of a new energy power generation side corresponding to each preset period;
wherein, the energy storage configuration capacity optimization model comprises:
wherein, the first and the second end of the pipe are connected with each other,
configuring capacity for a first energy storage at a new energy power generation side corresponding to the d-th preset period; />
Storing initial stored electric quantity at the beginning of the d preset period; />
The new energy output at the kth moment in the d preset period is obtained;
the energy storage power at the kth moment in the d preset period is obtained; />
The new energy output average value of the non-correlation time interval in the d preset period is obtained; />
And configuring the maximum power of stored energy for the d preset period.
According to the method, after the new energy output average value of the non-correlation time period is determined, the new energy output curve segmented every day and the new energy output average value are combined, and the first energy storage configuration capacity of the new energy power generation side corresponding every day is obtained by constructing and solving an energy storage configuration capacity optimization model of the new energy power generation side every day.
The energy storage configuration capacity optimization model of the new energy power generation side every day is shown as the following formula:
in the formula (I), the compound is shown in the specification,
the energy storage capacity required to be configured for the d day; />
Initial stored electricity quantity at the beginning of day d for storing energy;
the new energy output is given at the kth moment on the day d; />
The energy storage power is the energy storage power at the kth moment of the day d, wherein the charging is a positive value, and the discharging is a negative value; />
The new energy output average value of the day d in the non-correlation period; />
The maximum power of the stored energy is configured for the d day and can be passed>
And (4) obtaining.
In a physical sense, the optimization model represents the maximum energy storage power
Under the limitation, the minimum energy storage capacity which can meet all charging or discharging requirements from the initial moment to each current moment is searched, and the minimum energy storage capacity is essentially required for realizing the output of the new energy in a completely smooth and non-relevant time period. Here, the energy storage configuration process is shown by taking a segmented new energy output curve of day d as an example, which is specifically shown in fig. 4.
Maximum power of energy storage in fig. 4
The maximum deviation value of the new energy output curve and the average value thereof in the non-relevant time period is obtained. Under the power limitation, the new energy output can be adjusted to the minimum energy storage capacity required by the output average value thereof at any time in the irrelevant period>
(i.e., the first energy storage configuration capacity).
Preferably, the constructing an energy storage configuration capacity probability density function according to the first energy storage configuration capacity at the new energy power generation side corresponding to each preset period includes:
wherein, f (C) sto ) Configuring a capacity probability density function for the energy storage; k (-) is a kernel function; tau is a preset positive number and represents the bandwidth; d is the total number of the preset periods in the statistical range;
configuring capacity for a first energy storage at a new energy power generation side corresponding to the d-th preset period; c sto Capacity is configured for the first energy storage.
According to the method and the device, after the first energy storage configuration capacity corresponding to each day is obtained, the energy storage configuration capacities of all days are collected to construct an energy storage configuration capacity set, and an energy storage configuration capacity probability density function is constructed through kernel density estimation.
Assuming the energy storage configuration capacity set is
Based on the set C, the kernel density estimation of the probability density function corresponding to the energy storage configuration capacity can be constructed, namely the probability density function f (C) of the energy storage configuration capacity sto ) Comprises the following steps:
wherein K (·) is a kernel function; tau is a preset positive number and represents the bandwidth; d is the total number of preset cycles (i.e. total number of days) within the statistical range.
Further order
The above equation can be simplified to:
in theory any function can be used as the kernel function K τ (. Cndot.), but for the convenience and rationality of density function estimation, the kernel function is typically required to satisfy the following equation:
K τ (u)＝K τ (-u)，
wherein u represents a random variable, and in the present invention corresponds to variable C sto . The commonly used kernel functions mainly include gaussian kernel function, uniform kernel function, triangular kernel function, biweight kernel function, triweight kernel function and the like. The method selects the Gaussian kernel function as the kernel function of the probability density estimation of the capacity of the energy storage configuration.
To this end, a kernel density estimation f (C) of a probability density function corresponding to the energy storage configuration capacity can be constructed based on the set C sto ) I.e. the energy storage configuration capacity probability density function.
Preferably, the determining, according to the energy storage configuration capacity probability density function and a preset confidence level, a second energy storage configuration capacity and an energy storage rated power of the new energy power generation side corresponding to the preset time period includes:
wherein, C sto,α Configuring a capacity for the second energy storage; f (-) is the energy storage configuration capacity probability density function F (C) sto ) A primitive function of (a); f -1 (. H) is the inverse of F (-);
configuring a lower bound of capacity for the second energy storage; alpha is a preset significance level parameter; />
Rated power for energy storage; />
Configuring the maximum power of stored energy for the d preset period; d α Configuring a set of capacities for a first energy storage of a new energy generation side corresponding to each preset period under a 1-alpha confidence level
All of them are less than C sto,α The element of (a) corresponds to a set of preset periods; d is the total number of the preset periods in the statistical range.
In the present invention, the capacity probability density function f (C) is configured by using energy storage sto ) And the set confidence level 1-alpha determines the second energy storage configuration capacity C required within the annual statistical range sto,α And rated power of stored energy
The calculation formula is as follows:
wherein, C sto,α Is as followsTwo energy storage configuration capacities; f (-) is the probability density function F (C) of the energy storage configuration capacity sto ) A primitive function of (a); f -1 (. Cndot.) is the inverse of F (-);
configuring a lower bound of capacity for the second energy storage; alpha is a preset significance level parameter; />
Rated power for energy storage; />
Configuring the maximum power of stored energy for the d preset period; d α Configuring a set of capacities for a first energy storage of a new energy generation side corresponding to each preset period under a 1-alpha confidence level
All of them are less than C sto,α The element of (a) corresponds to a set of preset periods; d is the total number of the preset periods in the statistical range.
Fig. 5 visually reflects the annual energy storage configuration capacity at different confidence levels. As shown in fig. 5. Wherein when a =0.95, the energy storage configuration capacity is C sto,α | α＝0.95 This means that the number of days that this capacity can completely smooth out new energy output is more than 95% of the total number of days of the year. Meanwhile, in the statistical range of completely smooth new energy output, the maximum energy storage power is
Namely the energy storage rated power. Also when α =0.8, capacity C is configured sto,α | α＝0.8 Can ensure that the complete smooth new energy output is realized at more than 80 percent of days in the whole year, and the corresponding energy storage rated power is greater or equal to>
According to the method provided by the embodiment of the invention, when energy storage configuration is carried out based on the correlation time interval and new energy output data, the confidence level can be flexibly adjusted to obtain specific unified configuration capacity and rated power according to actual requirements based on the probability density function of the energy storage configuration capacity.
The energy storage configuration method is shown by utilizing annual wind power output data of a certain wind power station and annual load curves of the region where the wind power station is located. The total installed capacity of the wind power plant is 200MW, and the output curve is shown in FIG. 6; the normalized load data is shown in fig. 7.
The method of the invention is adopted to construct the probability density function of the capacity of the energy storage configuration, as shown in figure 8. Let α =0.05, the minimum energy storage capacity (i.e., the second energy storage configuration capacity) that can ensure that the completely smooth new energy output can be realized for more than 95% of the days in the whole year is 229MWh, and the corresponding energy storage rated power is 47MW.
Fig. 9 is a schematic diagram of an energy storage configuration system 900 with consideration of the correlation between the load and the new energy output according to an embodiment of the present invention. As shown in fig. 9, an energy storage configuration system 900 considering the correlation between the load and the new energy output according to an embodiment of the present invention includes: a data acquisition unit 901, a correlation period determination unit 902 and an energy storage configuration unit 903. The energy storage system comprises a new energy output average value determining unit 903, a first energy storage configuration capacity determining unit 904, a probability density function determining unit 905 and a second energy storage configuration capacity and rated power determining unit 906.
Preferably, the data obtaining unit 901 is configured to obtain new energy output data and load demand data of the new energy in the target area within a preset time period.
Preferably, the correlation period determining unit 902 is configured to determine, according to the new energy output data and the load demand data, a scissor difference coefficient corresponding to each moment in each preset period, and determine, according to the scissor difference coefficient, a correlation period in which the new energy output and the load demand in each preset period meet the correlation.
Preferably, the determining unit 902 for the correlation period determines, according to the new energy output data and the load demand data, a scissor difference coefficient corresponding to each time in each preset period, including:
wherein S is d,k The shear difference coefficient of the new energy output and the load demand at the kth moment in the d preset period;
the new energy output at the kth moment in the d preset period is obtained; />
The load demand at the kth moment in the d-th preset period.
Preferably, the determining unit 902 of the correlation period determines, according to the scissors difference coefficient, the correlation period in which the new energy output and the load demand in each preset cycle meet the correlation, including:
and determining the boundary parameter of the relevant interval as s, and determining the relevant time interval in which the new energy output and the load demand meet the relevance in any preset period according to the corresponding moment when the scissors difference coefficient falls in the relevant interval [1-s,1+s ].
Preferably, the energy storage configuration unit 903 is configured to perform energy storage configuration on the new energy according to the correlation time period and the new energy output data.
Preferably, the energy storage configuration unit 903 performs energy storage configuration on the new energy according to the correlation time period and the new energy output data, and includes:
the new energy output average value determining module is used for segmenting the new energy output data according to the correlation time interval, determining the non-correlation time interval in each preset period and calculating the new energy output average value of the non-correlation time interval in each preset period;
and the energy storage configuration module is used for performing energy storage configuration on the new energy according to the segmented new energy output data and the new energy output average value corresponding to each preset period.
Preferably, the new energy output average value determining module is configured to segment the new energy output data according to the correlation time period, determine an uncorrelated time period in each preset period, and calculate a new energy output average value of the uncorrelated time period in each preset period.
Preferably, the new energy output average value determining module calculates the new energy output average value of the non-correlation time period in each preset period, and includes:
wherein the content of the first and second substances,
the new energy output average value of the non-correlation time period in the d preset period is obtained; />
The new energy output at the kth moment in the d preset period is obtained; />
The stored energy power at the kth moment in the d preset period.
Preferably, the energy storage configuration module performs energy storage configuration on the new energy according to the segmented new energy output data and the new energy output average value corresponding to each preset period, and includes:
the first energy storage configuration capacity determining submodule is used for determining the first energy storage configuration capacity of the new energy power generation side corresponding to each preset period according to the segmented new energy output data corresponding to each preset period and the new energy output average value;
the probability density function determining submodule is used for constructing an energy storage configuration capacity probability density function according to the first energy storage configuration capacity of the new energy power generation side corresponding to each preset period;
and the second energy storage configuration capacity and rated power determining submodule is used for determining second energy storage configuration capacity and energy storage rated power of the new energy power generation side corresponding to the preset time period according to the energy storage configuration capacity probability density function and a preset confidence level.
Preferably, the determining module of the first energy storage configuration capacity determines the first energy storage configuration capacity of the new energy power generation side corresponding to each preset period according to the segmented new energy output data and the new energy output average value corresponding to each preset period, and includes:
the method comprises the steps of constructing an energy storage configuration capacity optimization model and solving to obtain a first energy storage configuration capacity of a new energy power generation side corresponding to each preset period;
wherein, the energy storage configuration capacity optimization model comprises:
wherein, the first and the second end of the pipe are connected with each other,
configuring capacity for a first energy storage at a new energy power generation side corresponding to the d-th preset period; />
For storing energyInitial stored power at the beginning of the d-th preset period; />
The new energy output at the kth moment in the d preset period is obtained; />
The energy storage power at the kth moment in the d preset period is obtained; />
The new energy output average value of the non-correlation time interval in the d preset period is obtained; />
And configuring the maximum power of stored energy for the d preset period. />
Preferably, the probability density function determining submodule, configured to construct the energy storage configuration capacity probability density function according to the first energy storage configuration capacity of the new energy power generation side corresponding to each preset period, includes:
wherein, f (C) sto ) Configuring a capacity probability density function for the energy storage; k (-) is a kernel function; tau is a preset positive number and represents the bandwidth; d is the total number of the preset periods in the statistical range;
configuring capacity for a first energy storage at a new energy power generation side corresponding to the d-th preset period; c sto Capacity is configured for the first energy storage.
Preferably, the determining submodule of the second energy storage configuration capacity and the rated power determines the second energy storage configuration capacity and the energy storage rated power of the new energy power generation side corresponding to the preset time period according to the energy storage configuration capacity probability density function and a preset confidence level, and includes:
wherein, C sto,α Configuring capacity for the second energy storage; f (-) is the energy storage configuration capacity probability density function F (C) sto ) A primitive function of (a); f -1 (. H) is the inverse of F (-);
configuring a lower bound of capacity for the second energy storage; alpha is a preset significance level parameter; />
Rated power for energy storage; />
Configuring the maximum power of stored energy for the d preset period; d α Configuring a set of capacities for a first energy storage of a new energy generation side corresponding to each preset period under a 1-alpha confidence level
All of them are less than C sto,α The element of (a) corresponds to a set of preset periods; d is the total number of the preset periods in the statistical range.
The energy storage configuration system 900 considering the correlation between the load and the new energy output according to the embodiment of the present invention corresponds to the energy storage configuration method 100 considering the correlation between the load and the new energy output according to another embodiment of the present invention, and is not described herein again.
The invention provides a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of any of the energy storage configuration methods taking into account the dependency of the load and the new energy contribution.
The present invention provides an electronic device, including:
the computer-readable storage medium described above; and
one or more processors to execute the program in the computer-readable storage medium.
The invention has been described with reference to a few embodiments. However, other embodiments of the invention than the one disclosed above are equally possible within the scope of the invention, as would be apparent to a person skilled in the art from the appended patent claims.
Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to "a/an/the [ means, component, etc ]" are to be interpreted openly as referring to at least one instance of said means, component, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (20)
1. An energy storage configuration method considering the correlation between load and new energy output, characterized in that the method comprises:
acquiring new energy output data and load demand data of new energy in a target area within a preset time period;
determining a scissors difference coefficient corresponding to each moment in each preset period according to the new energy output data and the load demand data, and determining a correlation time interval when the new energy output and the load demand in each preset period meet the correlation according to the scissors difference coefficient;
and performing energy storage configuration on the new energy according to the correlation time interval and the new energy output data.
2. The method according to claim 1, wherein determining the scissors difference coefficient corresponding to each moment in each preset period according to the new energy output data and the load demand data comprises:
wherein S is d,k The shear difference coefficient is the new energy output and the load demand at the kth moment in the d preset period;
the new energy output at the kth moment in the d preset period is obtained; />
The load demand at the kth moment in the d-th preset period.
3. The method according to claim 1, wherein determining the correlation period in which the new energy output and the load demand meet the correlation in each preset period according to the scissors difference coefficient comprises:
and determining the boundary parameter of the relevant interval as s, and determining the relevant time interval in which the new energy output and the load demand meet the relevance in any preset period according to the corresponding moment when the scissors difference coefficient falls in the relevant interval [1-s,1+s ] for any preset period.
4. The method of claim 1, wherein the configuring the new energy source according to the correlation period and the new energy output data comprises:
segmenting the new energy output data according to the correlation time period, determining the non-correlation time period in each preset period, and calculating the new energy output average value of the non-correlation time period in each preset period;
and performing energy storage configuration on the new energy according to the segmented new energy output data and the new energy output average value corresponding to each preset period.
5. The method of claim 4, wherein calculating the new energy output average for the non-correlation period in each predetermined period comprises:
wherein, the first and the second end of the pipe are connected with each other,
the new energy output average value of the non-correlation time period in the d preset period is obtained; />
The new energy output at the kth moment in the d preset period is obtained; />
The stored energy power at the kth moment in the d preset period.
6. The method according to claim 4, wherein the configuring the new energy according to the segmented new energy output data and the new energy output average value corresponding to each preset period includes:
determining a first energy storage configuration capacity of a new energy power generation side corresponding to each preset period according to the segmented new energy output data and the new energy output average value corresponding to each preset period;
constructing an energy storage configuration capacity probability density function according to the first energy storage configuration capacity of the new energy power generation side corresponding to each preset period;
and determining a second energy storage configuration capacity and an energy storage rated power of the new energy power generation side corresponding to the preset time period according to the energy storage configuration capacity probability density function and a preset confidence level.
7. The method according to claim 6, wherein the determining the first energy storage configuration capacity of the new energy generation side corresponding to each preset period according to the segmented new energy output data and the new energy output average value corresponding to each preset period comprises:
the method comprises the steps of constructing an energy storage configuration capacity optimization model and solving to obtain a first energy storage configuration capacity of a new energy power generation side corresponding to each preset period;
wherein, the energy storage configuration capacity optimization model comprises:
wherein the content of the first and second substances,
configuring capacity for a first energy storage at a new energy power generation side corresponding to the d-th preset period; />
Storing initial stored electric quantity at the beginning of the d preset period; />
The new energy output at the kth moment in the d preset period is obtained; />
The energy storage power at the kth moment in the d preset period is obtained; />
The new energy output average value of the non-correlation time interval in the d preset period is obtained; />
And configuring the maximum power of stored energy for the d preset period.
8. The method according to claim 6, wherein constructing the probability density function of the energy storage configuration capacity according to the first energy storage configuration capacity of the new energy power generation side corresponding to each preset period comprises:
wherein, f (C) sto ) Configuring a capacity probability density function for the energy storage; k (-) is a kernel function; tau is a preset positive number and represents the bandwidth; d is the total number of the preset periods in the statistical range;
configuring capacity for a first energy storage at a new energy power generation side corresponding to the d-th preset period; c sto A capacity is configured for the first energy storage.
9. The method according to claim 6, wherein the determining a second energy storage configuration capacity and an energy storage rated power of a new energy generation side corresponding to the preset time period according to the energy storage configuration capacity probability density function and a preset confidence level comprises:
wherein, C sto,α Configuring capacity for the second energy storage; f (-) is the energy storage configuration capacity probability density function F (C) sto ) A primitive function of (a); f -1 (. H) is the inverse of F (-);
configuring a lower bound of capacity for the second energy storage; alpha is a preset significance level parameter; />
Rated power for energy storage; />
Configuring the maximum power of stored energy for the d preset period; d α Configuring a set of capacities for the first energy storage of the new energy generation side corresponding to each preset period under the 1-alpha confidence level
All of them are less than C sto,α The element of (a) corresponds to a set of preset periods; d is the total number of the preset periods in the statistical range.
10. An energy storage configuration system that considers load and new energy output dependencies, the system comprising:
the data acquisition unit is used for acquiring new energy output data and load demand data of new energy in a target area within a preset time period;
the correlation time interval determining unit is used for determining a scissors difference coefficient corresponding to each moment in each preset period according to the new energy output data and the load demand data, and determining a correlation time interval in which the new energy output and the load demand in each preset period meet correlation according to the scissors difference coefficient;
and the energy storage configuration unit is used for performing energy storage configuration on the new energy according to the correlation time interval and the new energy output data.
11. The system according to claim 10, wherein the correlation period determining unit determines the scissors difference coefficient corresponding to each moment in each preset period according to the new energy output data and the load demand data, and includes:
wherein S is d,k The shear difference coefficient of the new energy output and the load demand at the kth moment in the d preset period;
the new energy output at the kth moment in the d preset period is obtained; />
The load demand at the kth moment in the d-th preset period.
12. The system according to claim 10, wherein the correlation period determination unit determines the correlation period in which the new energy output and the load demand satisfy the correlation in each preset period according to the scissors difference coefficient, and comprises:
and determining the boundary parameter of the relevant interval as s, and determining the relevant time interval in which the new energy output and the load demand meet the relevance in any preset period according to the corresponding moment when the scissors difference coefficient falls in the relevant interval [1-s,1+s ] for any preset period.
13. The system according to claim 10, wherein the energy storage configuration unit performs energy storage configuration on the new energy according to the correlation period and the new energy output data, and includes:
the new energy output average value determining module is used for segmenting the new energy output data according to the correlation time interval, determining the non-correlation time interval in each preset period and calculating the new energy output average value of the non-correlation time interval in each preset period;
and the energy storage configuration module is used for performing energy storage configuration on the new energy according to the segmented new energy output data and the new energy output average value corresponding to each preset period.
14. The system of claim 13, wherein the new energy output average determining unit calculates the new energy output average for the non-correlation period in each preset period, and comprises:
wherein the content of the first and second substances,
the new energy output average value of the non-correlation time interval in the d preset period is obtained; />
Is the d thThe new energy output at the kth moment in a preset period is output; />
The stored energy power at the kth moment in the d preset period.
15. The system according to claim 13, wherein the energy storage configuration module performs energy storage configuration on the new energy according to the segmented new energy output data and the new energy output average value corresponding to each preset period, and includes:
the first energy storage configuration capacity determining submodule is used for determining the first energy storage configuration capacity of the new energy power generation side corresponding to each preset period according to the segmented new energy output data corresponding to each preset period and the new energy output average value;
the probability density function determining submodule is used for constructing an energy storage configuration capacity probability density function according to the first energy storage configuration capacity of the new energy power generation side corresponding to each preset period;
and the second energy storage configuration capacity and rated power determining submodule is used for determining second energy storage configuration capacity and second energy storage rated power of the new energy power generation side corresponding to the preset time period according to the energy storage configuration capacity probability density function and the preset confidence level.
16. The system of claim 15, wherein the first energy storage configuration capacity determining submodule determines the first energy storage configuration capacity of the new energy generation side corresponding to each preset period according to the segmented new energy output data and the new energy output average value corresponding to each preset period, and includes:
the method comprises the steps of constructing an energy storage configuration capacity optimization model and solving to obtain a first energy storage configuration capacity of a new energy power generation side corresponding to each preset period;
wherein, the energy storage configuration capacity optimization model comprises:
wherein the content of the first and second substances,
configuring capacity for a first energy storage at a new energy power generation side corresponding to the d-th preset period; />
Storing initial stored electric quantity at the beginning of the d preset period for energy storage; />
The new energy output at the kth moment in the d preset period is obtained; />
The energy storage power at the kth moment in the d preset period is obtained; />
The new energy output average value of the non-correlation time interval in the d preset period is obtained; />
And configuring the maximum power of stored energy for the d preset period.
17. The system according to claim 15, wherein the probability density function determining submodule constructs an energy storage configuration capacity probability density function according to the first energy storage configuration capacity at the new energy power generation side corresponding to each preset period, and includes:
wherein, f (C) sto ) Configuring a capacity probability density function for the energy storage; k (-) is a kernel function; tau is a preset positive number and represents the bandwidth; d is the total number of the preset periods in the statistical range;
configuring capacity for a first energy storage at a new energy power generation side corresponding to the d-th preset period; c sto A capacity is configured for the first energy storage.
18. The system according to claim 15, wherein the second energy storage configuration capacity and rated power determining submodule determines, according to the energy storage configuration capacity probability density function and a preset confidence level, a second energy storage configuration capacity and an energy storage rated power of a new energy generation side corresponding to the preset time period, and includes:
wherein, C sto,α Configuring a capacity for the second energy storage; f (-) is the energy storage configuration capacity probability density function F (C) sto ) A primitive function of (a); f -1 (. H) is the inverse of F (-);
configuring a lower bound of capacity for the second energy storage; alpha is a preset significance level parameter; />
Rated power for energy storage; />
Configuring the maximum power of stored energy for the d preset period; d α Configuring a set of capacities for the first energy storage of the new energy generation side corresponding to each preset period under the 1-alpha confidence level
All of them are less than C sto,α The element of (a) corresponds to a set of preset periods; d is the total number of the preset periods in the statistical range.
19. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 9.
20. An electronic device, comprising:
the computer-readable storage medium recited in claim 19; and
one or more processors to execute the program in the computer-readable storage medium.
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