CN115730708B - Grid-connected energy storage system optimization operation method based on device-level battery model - Google Patents
Grid-connected energy storage system optimization operation method based on device-level battery model Download PDFInfo
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Abstract
The invention relates to a grid-connected energy storage system optimization operation method based on a device-level battery model, which comprises the following steps: establishing a grid-connected battery energy storage system power model based on a device-level battery model; establishing a relation equation of battery equivalent model parameters; designing an optimized operation method of a grid-connected battery energy storage system; designing a nonlinear and non-convexity equation conversion method; performing parameter estimation; and improving a mathematical model of the optimized operation of the grid-connected battery energy storage system according to the parameter estimation result. The beneficial effects of the invention are as follows: according to the invention, the energy storage optimization operation method of the grid-connected battery energy storage system is provided by using the equivalent model of the first-order circuit of the battery, so that the performance optimization of the grid-connected battery energy storage system is realized.
Description
Technical Field
The invention relates to the field of grid-connected energy storage systems, in particular to an optimized running method of a grid-connected energy storage system based on a device-level battery model.
Background
The grid-connected Battery Energy Storage System (BESS) is widely applied to various power grids, and a common optimal energy storage operation strategy is to establish a simplified circuit model of a single battery and a battery pack, reduce redundancy of a control algorithm and obtain an optimal solution. The remaining available energy of the battery can be calculated from the sum of the net energy input or output in combination with the charge-discharge cycle efficiency. Therefore, when a battery pack is formed using a single battery serial-parallel structure, it is generally defined that the maximum capacity of the battery is approximately equal to the rated capacity. Meanwhile, factors such as unbalanced charge and discharge of the battery, variable maximum capacity of different single batteries, variable loss under different power efficiency conditions and the like can influence the optimal operation method of the BESS. In practice, the simplified circuit model may produce partial failure results. Taylor et al conducted experimental studies on a grid-connected energy storage system rated at 100kW, and FIG. 1 shows a tentative battery state of charge (SOC) based on discharge, rated power/energy relationship. The result shows that the output power of the battery pack is set to zero in an 'unexpected' manner in the discharging process, and the failure reason is that any single battery in the battery pack reaches the lowest voltage threshold value, a stop signal of a Battery Management System (BMS) is triggered, and the residual available power/energy value of the whole battery pack is erroneously judged to be zero. Therefore, the optimal operation method based on the battery simplified equivalent model does not consider the fault event of the battery pack, and unexpected interruption in the operation of the BESS may occur at a key time point, so that the operation performance of the BESS application program is seriously reduced.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides an optimized running method of a grid-connected energy storage system based on a device-level battery model.
In a first aspect, a method for optimizing operation of a grid-connected energy storage system based on a device-level battery model is provided, including:
s1, establishing a grid-connected battery energy storage system power model based on a device-level battery model;
s2, establishing a relation equation of battery equivalent model parameters;
s3, designing an optimized operation method of the grid-connected battery energy storage system;
s4, designing a nonlinear and non-convexity equation conversion method;
s5, parameter estimation is carried out;
and S6, improving a mathematical model of the optimized operation of the grid-connected battery energy storage system according to the parameter estimation result.
Preferably, in S1, let T be the total charge/discharge time of the battery, and the power value consumed by the battery pack at any time T ε T is represented as P BESS [t]，P o [t,n]When the total number of the single batteries is N, P is the power value input/consumed in the nth single battery at the time point t BESS [t]Calculated with formula (1):
P BESS [t]＝∑ n＝N P o [t,n] (1)
wherein P is o [t,n]Taking a positive value indicating the battery charge state or a negative value indicating the battery discharge state.
Preferably, S2 includes:
s201, introducing a first-order circuit equivalent model, and establishing a single battery voltage, current and power relation equation as formulas (2) - (7) according to formula (1):
P o [t,n]＝V o [t,n]I[t] (2)
V o [t,n]＝V oc [t,n]+r[n]I[t] (3)
V oc [t,n]＝f(SOC[t,n]) (4)
P in [t,n]＝V oc [t,n]I[t] (7)
wherein V is o Is the end voltage of the single battery, I is the charge-discharge current of the single battery, V oc Is the open circuit voltage of the single battery, r is the initial internal resistance value of the single battery, SOC is the charge state of the single battery, and f (·) is V oc A relation function with C, wherein C is the energy storage of the single battery taking Wh as a unit,
maximum value of energy of single battery in Wh, c 0 For initial energy of single battery, P in The internal power generated/absorbed by the single battery is represented by tau as a time variable and delta t as a sampling time interval;
s202, defining the relation between the energy storage value C and the SOC: defining the SOC as a standardized measure of battery energy storage, and as a proportional value of a current energy storage value and a rated energy storage value; definition of energy maxima
Total energy stored in Wh for a battery from a depleted state to a fully charged state; energy storage value C t, n of single battery n]Using SOC value as SOC [ t ]; n is n]The energy value at that time is expressed, the parameter is expressed as +.>
S203, defining the end voltage V of the single battery o The value range is as follows: the upper and lower values are respectively expressed as
And o vdefining the value range expression as inequality (8):
in the formula, any sampling time T epsilon T and any single battery N epsilon N are satisfied.
Preferably, in S3, according to different objective functions, a mathematical model for optimizing operation of the grid-connected battery energy storage system is established, and the load power value of the building, the distribution feeder line or the transformer substation is minimized, as shown in formula (9):
subject to(1)-(7)
wherein P is load [t]The background load power at the t moment in the peak shaving problem is obtained, and the parameter value is not influenced by the BESS; if P BESS [t]For positive, charging the grid-connected battery energy storage system, P BESS [t]And (3) discharging the grid-connected battery energy storage system.
Preferably, S4 includes:
s401 binary expansion V oc [t,n]: dividing open circuit voltage value range of single battery into
Segments, each of equal length and labeled +.>
Each voltage segment is represented by an index parameter u and satisfies +.>
Let the voltage quantity of the segment point be expressed as +.>
For any time T epsilon T and each single cell n, a binary variable D [ T, n, u ] is defined]Approximately equal to the voltage value V oc [t,n]The formula is as follows:
V oc [t,n]-σ/2≤∑ u∈U α[u]D[t,n,u]≤V oc [t,n]+σ/2 (10)
∑ u∈U D[t,n,u]＝1 (11)
in the formula, the vector alpha [ u ]]Represents the variable V by the nearest-similar value oc [t,n]The method comprises the steps of carrying out a first treatment on the surface of the In the formula (11), for determining the end voltage segment index value u, the binary variable D [ t, n, u ]]The sum value is 1 and satisfies
Combining equation (10) and vector alpha [ u ]]Expression, get the formula sigma u∈U α[u]D[t,n,u]For a value constant equal to alpha u for a determined index value u]；
S402, linear approximation of a function f (.): establishing a nonlinear function f (·) of each single cell n, representing the open circuit voltage V oc A relationship with SOC; let l [ n, u ]]Representing a voltage value alpha u]Under the condition of the charge quantity of the single battery n, the energy value calculation formula of the single battery n at any moment T epsilon T is as follows:
C[t,n]＝∑ u∈U l[n,u]D[t,n,u] (12)
wherein, the parameter pair alpha [ u ]]And l [ n, u ]]Establishing an approximate LUT lookup table to realize linear approximation of a nonlinear function f (°); by decreasing sigma or increasing
Improving the accuracy of the approximation inequality of the formula (10);
s403, defining a new auxiliary variable omega [ T, N, u ] at each moment T epsilon T according to the non-convex bilinear term in the formula (1) -formula (8), and carrying out equation correlation on the current I [ T ], wherein for N epsilon N, the constraint condition is satisfied as follows:
(D[t,n,u]-1)L≤I[t]-Ω[t,n,u]≤(1-D[t,n,u])L (13)
-D[t,n,u]L≤Ω[t,n,u]≤D[t,n,u]L (14)
wherein L is a large value of a Big L binary method;
s404, approximating bilinear constraint conditions in the formula (7) as follows:
P in [t,n]＝∑ u∈U α[u]Ω[t,n,u] (15)
s405, for equation (2), applying the binary expansion term to V o [t,n]And processing parameter V oc [t,n]In the same way, u is respectively calculated,
σ,α[u]u and D [ t, n, U ]]Replaced by w->
ζ,γ[w]W and Ft, n, W]The corresponding constraints translate into:
V o [t,n]-ζ/2≤∑ w∈W γ[w]F[t,n,w]≤V o [t,n]+ζ/2 (16)
∑ w∈W F[t,n,w]＝1 (17)
in the formula, the vector gamma [ w ] is utilized]Represents the variable V by the nearest-most value in (a) o [t,n]By binary variables F [ t, n, w]Selecting; for the determined time t and the cell n, binary variables D [ t, n, u ] according to equation (17)]A value of 1 and satisfies
Combining equation (16) and vector gamma [ w ]]Expression, get the formula sigma w∈W γ[w]F[t,n,u]For a certain index value w, its value is constant equal to gamma [ w ]]；
S406, approximating bilinear constraint conditions in the formula (2) as:
(F[t,n,w]-1)L≤I-Γ[t,n,w]≤(1-F[t,n,w])L (18)
-F[t,n,w]L≤Γ[t,n,w]≤F[t,n,w]L (19)
P o [t,n]＝∑ w∈W γ[w]Γ[t,n,w] (20)。
preferably, S5 includes:
s501, building a battery test platform based on power loop hardware;
s502, estimating an offline battery internal resistance value: recording terminal voltage V in charge-discharge experiment o Open circuit voltage V oc And I, according to formulas (3) and V o ,V oc The measured value of the I is calculated to obtain the internal resistance value of the battery;
s503, on-line parameter estimation is performed by recording the V before and after the change of the current value I o ,V oc I data value calculation r [ n ]]According to the first-order equivalent circuit model, the single battery is represented as a voltage source V oc [t,n]And constant resistance r [ n ]]Series circuit, voltage value V oc [t,n]From C t, n]Determining;
taking two time points t which are close in time according to the formula (3) 1 And t 2 Let C [ t ] 1 ,n]-C[t 2 ,n]Approximately equal to 0, the internal resistance value r [ n ] of the battery]The calculation formula of (2) is as follows:
r[n]＝(V o [t 2 ,n]-V o [t 1 ,n])/(I[t 2 ]-I[t 1 ]) (21)
s504, performing curve fitting on a function f (·) based on the LUT: will V oc [t,n]And C t, n]Is divided into (a) relationship curve
Linear sections. And (3) according to the starting point and the end point information of the SOC curve given by a battery application manufacturer, carrying out least square fitting on the sampled data by using a shape standard curve fitting method (shape prescriptive curve fitting) and a spline interpolation method, and carrying out condition constraint on monotonicity, curvature and value.
Preferably, in S504, the constraint condition includes: the open circuit voltage value of the single battery increases with the increase of the charging current; v (V) oc [t,n]And C t, n]Must pass through certain set points; the minimum open circuit voltage value occurs at zero available energy conditions; presetting a part of parameter values.
Preferably, in S6, according to formulas (1), (3), (5), (7), (15) to (21), in combination with the parameter estimation result, formula (9) is modified, as in formula (22):
in a second aspect, there is provided a grid-connected energy storage system optimizing operation device based on a device-level battery model, for executing the grid-connected energy storage system optimizing operation method based on the device-level battery model according to the first aspect, including:
the first building module is used for building a grid-connected battery energy storage system power model based on the device-level battery model;
the second establishing module is used for establishing a relation equation of the equivalent model parameters of the battery;
the first design module is used for designing an optimized operation method of the grid-connected battery energy storage system;
the second design module is used for designing a nonlinear and non-convexity equation conversion method;
the estimation module is used for carrying out parameter estimation;
and the improvement module is used for improving a mathematical model of the optimized operation of the grid-connected battery energy storage system according to the parameter estimation result.
The beneficial effects of the invention are as follows:
(1) According to the invention, the energy storage optimization operation method of the grid-connected battery energy storage system is provided by using the equivalent model of the first-order circuit of the battery, so that the performance optimization of the grid-connected battery energy storage system is realized.
(2) The invention relates to an improved nonlinear voltage source method (CANVS) method for processing a parameter V oc And C, and compared with the conventional Colomb integration method.
(3) The invention designs a PHIL hardware test platform of a battery pack, trains an energy storage optimization model by using measured data, and estimates the internal resistance value and f (&) fitting curve of the battery on line.
Drawings
FIG. 1 is a schematic diagram of a battery SOC, power rating/energy relationship based on discharge tentative;
FIG. 2 is a schematic diagram of a battery test platform based on power loop hardware;
FIG. 3 is a graph of a LUT-based function f ();
FIG. 4 is a graph showing the comparison of the internal resistance values of 12 single batteries in an off-line method and an on-line method;
FIG. 5 is a schematic diagram of a peak shaving curve based on the PHIL experimental platform.
Detailed Description
The invention is further described below with reference to examples. The following examples are presented only to aid in the understanding of the invention. It should be noted that it will be apparent to those skilled in the art that modifications can be made to the present invention without departing from the principles of the invention, and such modifications and adaptations are intended to be within the scope of the invention as defined in the following claims.
Example 1:
the invention provides a grid-connected energy storage system optimizing operation method based on a device-level battery model, which considers the problems of maximum capacity difference, unbalanced charge and discharge, internal resistance characteristic change and the like of single batteries, designs a nonlinear voltage source equivalent circuit model, realizes continuous estimation and update of model parameters, keeps uninterrupted normal operation of the grid-connected battery energy storage system, and comprises the following steps:
s1, establishing a grid-connected battery energy storage system power model based on a device-level battery model;
s2, establishing a relation equation of battery equivalent model parameters;
s3, designing an optimized operation method of the grid-connected battery energy storage system;
s4, designing a nonlinear and non-convexity equation conversion method;
s5, parameter estimation is carried out;
and S6, improving a mathematical model of the optimized operation of the grid-connected battery energy storage system according to the parameter estimation result.
In S1, let T be the total charge and discharge time of the battery, and at any time T E T, the power value consumed by the battery pack is expressed as P BESS [t]，P o [t,n]When the total number of the single batteries is N, P is the power value input/consumed in the nth single battery at the time point t BESS [t]Using formula (1)And (3) calculating:
P BESS [t]＝∑ n＝N P o [t,n] (1)
wherein P is o [t,n]Taking a positive value indicating the battery charge state or a negative value indicating the battery discharge state.
S2 comprises the following steps:
s201, introducing a first-order circuit equivalent model, and establishing a single battery voltage, current and power relation equation as formulas (2) - (7) according to formula (1):
P o [t,n]＝V o [t,n]I[t] (2)
V o [t,n]＝V oc [t,n]+r[n]I[t] (3)
V oc [t,n]＝f(SOC[t,n]) (4)
P in [t,n]＝V oc [t,n]I[t] (7)
wherein, the definition of specific parameters is shown in Table 1, V o Is the end voltage of the single battery, I is the charge-discharge current of the single battery, V oc Is the open circuit voltage of the single battery, r is the initial internal resistance value of the single battery, SOC is the charge state of the single battery, and f (·) is V oc A relation function with C, wherein C is the energy storage of the single battery taking Wh as a unit,
maximum value of energy of single battery in Wh, c 0 For initial energy of single battery, P in The internal power generated/absorbed by the single battery is represented by tau as a time variable and delta t as a sampling time interval; the system of equations must be adapted to the duration Δt and any time T e T, typically V oc And V o All have positive values, and the value range is 2.5V-4.0V. The above equation setDescription of the output voltage V of the Unit cell o And the discrete state space representation between the input current I. The product term in equation (2) represents the output power P o 。
Table 1 parameter definition table
S202, defining the relation between the energy storage value C and the SOC: defining the SOC as a standardized measure of battery energy storage, and as a proportional value of a current energy storage value and a rated energy storage value; definition of energy maxima
Total energy stored in Wh for a battery from a depleted state to a fully charged state; energy storage value C t, n of single battery n]Using SOC value as SOC [ t ]; n is n]The energy value at that time is expressed, the parameter is expressed as +.>
S203, defining the end voltage V of the single battery o The value range is as follows: the upper and lower values are respectively expressed as
And o vdefining the value range expression as inequality (8):
in the formula, any sampling time T epsilon T and any single battery N epsilon N are satisfied. V according to the formula (2) and the formula (3) oc As a function based on SOC, V o And P o Also a function based on SOC. Due to V oc The relation with SOC is notLinear and non-convex, the equations and inequalities in equations (1) - (8) both have non-linear and non-convex.
In S3, according to different objective functions, a mathematical model for optimizing operation of the grid-connected battery energy storage system is established, and load power values of a building, a distribution feeder line or a transformer substation are minimized, as shown in a formula (9):
subject to(1)-(7)
wherein P is load [t]The background load power at the t moment in the peak shaving problem is obtained, and the parameter value is not influenced by the BESS; if P BESS [t]For positive, charging the grid-connected battery energy storage system, P BESS [t]And (3) discharging the grid-connected battery energy storage system.
S4 comprises the following steps:
s401 binary expansion V oc [t,n]: the invention applies a binary expansion method to the voltage value V oc [t,n]Rather than the current value it]. Dividing open circuit voltage value range of single battery into
Segments, each of equal length and identified as
Each voltage segment is represented by an index parameter u and satisfies +.>
Let the voltage quantity of the segment point be expressed as +.>
For any time T epsilon T and each single cell n, a binary variable D [ T, n, u ] is defined]Approximately equal to the voltage value V oc [t,n]The formula is as follows:
V oc [t,n]-σ/2≤∑ u∈U α[u]D[t,n,u]≤V oc [t,n]+σ/2 (10)
∑ u∈U D[t,n,u]＝1 (11)
in the formula, the vector alpha [ u ]]Represents the variable V by the nearest-similar value oc [t,n]The method comprises the steps of carrying out a first treatment on the surface of the In the formula (11), for determining the end voltage segment index value u, the binary variable D [ t, n, u ]]The sum value is 1 and satisfies
Combining equation (10) and vector alpha [ u ]]Expression, get the formula sigma u∈U α[u]D[t,n,u]For a value constant equal to alpha u for a determined index value u]The method comprises the steps of carrying out a first treatment on the surface of the The step is to use binary optimization algorithm to make non-convex bilinear term V oc [t]Converted into a mathematically processable linear term.
S402, linear approximation of a function f (.): establishing a nonlinear function f (·) of each single cell n, representing the open circuit voltage V oc A relationship with SOC; let l [ n, u ]]Representing a voltage value alpha u]Under the condition of the charge quantity of the single battery n, the energy value calculation formula of the single battery n at any moment T epsilon T is as follows:
C[t,n]＝∑ u∈U l[n,u]D[t,n,u] (12)
wherein, the parameter pair alpha [ u ]]And l [ n, u ]]Establishing an approximate LUT lookup table to realize linear approximation of a nonlinear function f (°); by decreasing sigma or increasing
Improving the accuracy of the approximation inequality of the formula (10);
s403, defining a new auxiliary variable omega [ T, N, u ] at each moment T epsilon T according to the non-convex bilinear term in the formula (1) -formula (8), and carrying out equation correlation on the current I [ T ], wherein for N epsilon N, the constraint condition is satisfied as follows:
(D[t,n,u]-1)L≤I[t]-Ω[t,n,u]≤(1-D[t,n,u])L (13)
-D[t,n,u]L≤Ω[t,n,u]≤D[t,n,u]L (14)
wherein L is a large value of a Big L binary method;
s404, approximating bilinear constraint conditions in the formula (7) as follows:
P in [t,n]＝∑ u∈U α[u]Ω[t,n,u] (15)
s405, for equation (2), applying the binary expansion term to V o [t,n]And processing parameter V oc [t,n]In the same way, u is respectively calculated,
σ,α[u]u and D [ t, n, U ]]Replaced by w->
ζ,γ[w]W and Ft, n, W]The corresponding constraints translate into:
V o [t,n]-ζ/2≤∑ w∈W γ[w]F[t,n,w]≤V o [t,n]+ζ/2 (16)
∑ w∈W F[t,n,w]＝1 (17)
in the formula, the vector gamma [ w ] is utilized]Represents the variable V by the nearest-most value in (a) o [t,n]By binary variables F [ t, n, w]Selecting; for the determined time t and the cell n, binary variables D [ t, n, u ] according to equation (17)]A value of 1 and satisfies
Combining equation (16) and vector gamma [ w ]]Expression, get the formula sigma w∈W γ[w]F[t,n,u]For a certain index value w, its value is constant equal to gamma [ w ]]The method comprises the steps of carrying out a first treatment on the surface of the The step is to use binary optimization algorithm to make non-convex bilinear term V o [t]Converted into a mathematically processable linear term.
S406, approximating bilinear constraint conditions in the formula (2) as:
(F[t,n,w]-1)L≤I-Γ[t,n,w]≤(1-F[t,n,w])L (18)
-F[t,n,w]L≤Γ[t,n,w]≤F[t,n,w]L (19)
P o [t,n]＝∑ w∈W γ[w]Γ[t,n,w] (20)。
s5 comprises the following steps:
s501, building a battery test platform based on power loop hardware (PHIL); as shown in fig. 2, the test platform includes all the critical components that make up the BESS, including hardware devices, RTDS modules, prediction/dispatcher, and data stores. The testing platform comprises N single batteries, and the battery pack array is of a serial structure.
S502, estimating an offline battery internal resistance value: recording terminal voltage V in charge-discharge experiment o Open circuit voltage V oc And I, according to formulas (3) and V o ,V oc The measured value of the I is calculated to obtain the internal resistance value of the battery;
s503, on-line parameter estimation is performed by recording the V before and after the change of the current value I o ,V oc I data value calculation r [ n ]]According to the first-order equivalent circuit model, the single battery is represented as a voltage source V oc [t,n]And constant resistance r [ n ]]Series circuit, voltage value V oc [t,n]From C t, n]Determining;
taking two time points t which are close in time according to the formula (3) 1 And t 2 Let C [ t ] 1 ,n]-C[t 2 ,n]Approximately 0, i.e. open circuit voltage V oc [t,n]Approximately constant, the internal resistance value r [ n ] of the battery]The calculation formula of (2) is as follows:
r[n]＝(V o [t 2 ,n]-V o [t 1 ,n])/(I[t 2 ]-I[t 1 ]) (21)
s504, performing curve fitting on a function f (·) based on the LUT: will V oc [t,n]And C t, n]Is divided into (a) relationship curve
Linear sections. And according to the starting point and the end point information of the SOC curve given by a battery application manufacturer, carrying out least square fitting on the sampling data by using a shape standard curve fitting method and a spline interpolation method, and carrying out conditional constraint on monotonicity, curvature and value.
In S504, the constraint conditions include: the open circuit voltage value of the single battery increases with the increase of the charging current; v (V) oc [t,n]And C t, n]Must pass through certain set points, such as the full voltage threshold point and the empty voltage threshold point indicated in the battery specification; the minimum open circuit voltage value occurs at zero available energy conditions; presetting a part of parameter values.
Assuming that the fitted curve is divided into a plurality of linear portions, a function f (·) curve fit based on measured data points is shown in FIG. 3, with vertical dashed lines in FIG. 3The line represents a piecewise linear portion. The results indicate that the fitted curve can identify any number of V's in the LUT oc [t,n]/C[t,n]Parameter pairs.
In S6, according to formulas (1), (3), (5), (7), (15) to (21), in combination with the parameter estimation result, formula (9) is modified as in formula (22):
example 2:
the internal resistance value experimental results based on the off-line estimation method and the on-line estimation method are shown in fig. 4, the abscissa is the number of 12 single batteries, the ordinate is the internal resistance value of the battery, and the experimental results show that the calculation results of the two methods have insignificant difference. The estimated difference value of the same single cell is substantially the same, about 0.03V/a, using both estimation methods. Fig. 4 shows that the on-line parameter estimation method results in a smaller estimated value of the internal resistance value. Because the overall modeling accuracy is measured according to the closeness of the complete model and the measured data, the estimation inaccuracy of the internal resistance value has a certain noise tolerance value and can be based on V oc [t,n]Is compensated for.
Example 3:
the BESS energy rating and power rating were chosen to be 240kWh and 80kW respectively, and FIG. 5 is a peak shaving curve based on a PHIL experimental platform, and the direct load, CANVS model and CCA model were compared for performance. The results show that: (1) The energy storage maximum value calculated under the three conditions appears in the 19 th hour, and after 12 hours, the energy load value directly loaded keeps the maximum value; (2) The running performance based on the CANVS model preset value is optimal, and the energy load value is kept at about 140kw between 13 hours and 19 hours; (3) The fluctuation conditions of the energy load value based on the measured value of the CCA model and the preset value of the CCA model are more, and fluctuation values of about 20kw exist in the initial 3 hours and the last 5 hours; (4) After the peak energy load at 19 hours, the peak energy load value based on the CCA model was reduced by only 7kW and the peak energy load value based on the CANVS model was reduced by 18kW. The difference in peak energy load value reduction values is caused by model accuracy errors.
Claims (2)
1. The grid-connected energy storage system optimizing operation method based on the device-level battery model is characterized by comprising the following steps of:
s1, establishing a grid-connected battery energy storage system power model based on a device-level battery model;
in S1, let T be the total charge and discharge time of the battery, and at any time T E T, the power value consumed by the battery pack is expressed as P BESS [t]，P o [t，n]When the total number of the single batteries is N, P is the power value input/consumed in the nth single battery at the time point t BESS [t]Calculated with formula (1):
P BESS [t]＝∑ n＝N P o [t，n] (1)
wherein P is o [t，n]Taking a positive value or a negative value, wherein the positive value represents a battery charge state, and the negative value represents a battery discharge state;
s2, establishing a relation equation of battery equivalent model parameters;
s2 comprises the following steps:
s201, introducing a first-order circuit equivalent model, and establishing a single battery voltage, current and power relation equation as formulas (2) - (7) according to formula (1):
P o [t，n]＝V o [t，n]I[t] (2)
V o [t，n]＝V oc [t，n]+r[n]I[t] (3)
V oc [t，n]＝f(SOC[t，n]) (4)
P in [t，n]＝V oc [t，n]I[t] (7)
wherein V is o Is a single electricThe battery end voltage, I is the charge-discharge current of the single battery, V oc Is the open circuit voltage of the single battery, r is the initial internal resistance value of the single battery, SOC is the charge state of the single battery, and f (·) is V oc A relation function with C, wherein C is the energy storage of the single battery taking Wh as a unit,
maximum value of energy of single battery in Wh, c 0 For initial energy of single battery, P in The internal power generated/absorbed by the single battery is represented by tau as a time variable and delta t as a sampling time interval;
s202, defining the relation between the energy storage value C and the SOC: defining the SOC as a standardized measure of battery energy storage, and as a proportional value of a current energy storage value and a rated energy storage value; definition of energy maxima
Total energy stored in Wh for a battery from a depleted state to a fully charged state; energy storage value C t, n of single battery n]Using SOC value as SOC [ t ]; n is n]The energy value at that time is expressed, the parameter is expressed as +.>
S203, defining the end voltage V of the single battery o The value range is as follows: the upper and lower values are respectively expressed as
And o vdefining the value range expression as inequality (8):
in the formula, any sampling time T epsilon T and any single battery N epsilon N are satisfied;
s3, designing an optimized operation method of the grid-connected battery energy storage system;
in S3, according to different objective functions, a mathematical model for optimizing operation of the grid-connected battery energy storage system is established, and load power values of a building, a distribution feeder line or a transformer substation are minimized, as shown in a formula (9):
subject to (1)-(7)
wherein P is load [t]The background load power at the t moment in the peak shaving problem is obtained, and the parameter value is not influenced by the BESS; if P BESS [t]For positive, charging the grid-connected battery energy storage system, P BESS [t]Discharging the grid-connected battery energy storage system if the voltage is negative;
s4, designing a nonlinear and non-convexity equation conversion method;
s4 comprises the following steps:
s401 binary expansion V oc [t，n]: dividing open circuit voltage value range of single battery into
Segments, each of equal length and labeled +.>
Each voltage segment is represented by an index parameter u and satisfies +.>
Let the voltage quantity of the segment point be expressed as +.>
For any time T epsilon T and each single cell n, a binary variable D [ T, n, u ] is defined]Approximately equal to the voltage value V oc [t，n]The formula is as follows:
V oc [t，n]-σ/2≤∑ u∈U α[u]D[t，n，u]≤V oc [t，n]+σ/2 (10)
∑ u∈U D[t，n，u]＝1 (11)
in the formula, the vector alpha [ u ]]Represents the variable V by the nearest-similar value oc [t，n]The method comprises the steps of carrying out a first treatment on the surface of the In the formula (11), for determining the end voltage segment index value u, the binary variable D [ t, n, u ]]The sum value is 1 and satisfies
Combining equation (10) and vector alpha [ u ]]Expression, get the formula sigma u∈U α[u]D[t，n，u]For a value constant equal to alpha u for a determined index value u]；
S402, linear approximation of a function f (.): establishing a nonlinear function f (·) of each single cell n, representing the open circuit voltage V oc A relationship with SOC; let l [ n, u ]]Representing a voltage value alpha u]Under the condition of the charge quantity of the single battery n, the energy value calculation formula of the single battery n at any moment T epsilon T is as follows:
C[t，n]＝∑ u∈U l[n，u]D[t，n，u] (12)
wherein, the parameter pair alpha [ u ]]And l [ n, u ]]Establishing an approximate LUT lookup table to realize linear approximation of a nonlinear function f (°); by decreasing sigma or increasing
Improving the accuracy of the approximation inequality of the formula (10);
s403, defining a new auxiliary variable omega [ T, N, u ] at each moment T epsilon T according to the non-convex bilinear term in the formula (1) -formula (8), and carrying out equation correlation on the current I [ T ], wherein for N epsilon N, the constraint condition is satisfied as follows:
(D[t，n，u]-1)L≤I[t]-Ω[t，n，u]≤(1-D[t，n，u])L (13)
-D[t，n，u]L≤Ω[t，n，u]≤D[t，n，u]L (14)
wherein L is a large value of a Big L binary method;
s404, approximating bilinear constraint conditions in the formula (7) as follows:
P in [t，n]＝∑ u∈U α[u]Ω[t，n，u] (15)
s405, applying the binary expansion term to the formula (2)At V o [t，n]And processing parameter V oc [t，n]In the same way, u is respectively calculated,
σ，α[u]u and D [ t, n, U ]]Replaced by w->
ζ，γ[w]W and Ft, n, W]The corresponding constraints translate into:
V o [t，n]-ζ/2≤∑ w∈W γ[w]F[t，n，w]≤V o [t，n]+ζ/2 (16)
∑ w∈W F[t，n，w]＝1 (17)
in the formula, the vector gamma [ w ] is utilized]Represents the variable V by the nearest-most value in (a) o [t，n]By binary variables F [ t, n, w]Selecting; for the determined time t and the cell n, binary variables D [ t, n, u ] according to equation (17)]A value of 1 and satisfies
Combining equation (16) and vector gamma [ w ]]Expression, get the formula sigma w∈W γ[w]F[t，n，u]For a certain index value w, its value is constant equal to gamma [ w ]]；
S406, approximating bilinear constraint conditions in the formula (2) as:
(F[t，n，w]-1)L≤I-Γ[t，n，w]≤(1-F[t，n，w])L (18)
-F[t，n，w]L≤Γ[t，n，w]≤F[t，n，w]L (19)
P o [t，n]＝∑ w∈W γ[w]Γ[t，n，w] (20)
s5, parameter estimation is carried out;
s5 comprises the following steps:
s501, building a battery test platform based on power loop hardware;
s502, estimating an offline battery internal resistance value: recording terminal voltage V in charge-discharge experiment o Open circuit voltage V oc And I, according to formulas (3) and V o ，V oc Measured value of I, calculatedTo the internal resistance value of the battery;
s503, on-line parameter estimation is performed by recording the V before and after the change of the current value I o ，V oc I data value calculation r [ n ]]According to the first-order equivalent circuit model, the single battery is represented as a voltage source V oc [t，n]And constant resistance r [ n ]]Series circuit, voltage value V oc [t，n]From C t, n]Determining;
taking two time points t which are close in time according to the formula (3) 1 And t 2 Let C [ t ] 1 ，n]-C[t 2 ，n]Approximately equal to 0, the internal resistance value r [ n ] of the battery]The calculation formula of (2) is as follows:
r[n]＝(V o [t 2 ，n]-V o [t 1 ，n])/(I[t 2 ]-I[t 1 ]) (21)
s504, performing curve fitting on a function f (·) based on the LUT: will V oc [t，n]And C t, n]Is divided into (a) relationship curve
Linear sections. According to starting point and end point information of a SOC curve given by a battery application manufacturer, carrying out least square fitting on sampling data by using a shape standard curve fitting method and a spline interpolation method, and carrying out condition constraint on monotonicity, curvature and value;
in S504, the constraint conditions include: the open circuit voltage value of the single battery increases with the increase of the charging current; v (V) oc [t，n]And C t, n]Must pass through certain set points; the minimum open circuit voltage value occurs at zero available energy conditions; presetting a partial parameter value;
s6, improving a mathematical model of the optimized operation of the grid-connected battery energy storage system according to the parameter estimation result;
in S6, according to formulas (1), (3), (5), (7), (15) to (21), in combination with the parameter estimation result, formula (9) is modified as in formula (22):
2. the grid-connected energy storage system optimizing operation device based on the device-level battery model is characterized by comprising the following components:
the first building module is used for building a grid-connected battery energy storage system power model based on the device-level battery model;
the second establishing module is used for establishing a relation equation of the equivalent model parameters of the battery;
the first design module is used for designing an optimized operation method of the grid-connected battery energy storage system;
the second design module is used for designing a nonlinear and non-convexity equation conversion method;
the estimation module is used for carrying out parameter estimation;
and the improvement module is used for improving a mathematical model of the optimized operation of the grid-connected battery energy storage system according to the parameter estimation result.
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