CN116845893B - Parameter optimization method for weak current network LCL type grid-connected inversion filter based on NSGA-II algorithm - Google Patents
Parameter optimization method for weak current network LCL type grid-connected inversion filter based on NSGA-II algorithm Download PDFInfo
- Publication number
- CN116845893B CN116845893B CN202310860883.2A CN202310860883A CN116845893B CN 116845893 B CN116845893 B CN 116845893B CN 202310860883 A CN202310860883 A CN 202310860883A CN 116845893 B CN116845893 B CN 116845893B
- Authority
- CN
- China
- Prior art keywords
- grid
- inductance
- nsga
- frequency
- filter
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000004422 calculation algorithm Methods 0.000 title claims abstract description 35
- 238000005457 optimization Methods 0.000 title claims abstract description 31
- 238000000034 method Methods 0.000 title claims abstract description 28
- 239000003990 capacitor Substances 0.000 claims abstract description 18
- 238000013016 damping Methods 0.000 claims abstract description 13
- 238000005259 measurement Methods 0.000 claims description 2
- 230000000694 effects Effects 0.000 abstract description 9
- 238000001914 filtration Methods 0.000 abstract description 6
- 238000013461 design Methods 0.000 description 10
- 230000001965 increasing effect Effects 0.000 description 6
- 230000004044 response Effects 0.000 description 5
- 238000012546 transfer Methods 0.000 description 4
- 230000002068 genetic effect Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000004088 simulation Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000007796 conventional method Methods 0.000 description 2
- 230000008878 coupling Effects 0.000 description 2
- 238000010168 coupling process Methods 0.000 description 2
- 238000005859 coupling reaction Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 238000007792 addition Methods 0.000 description 1
- 230000003321 amplification Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000002146 bilateral effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 230000005764 inhibitory process Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000035772 mutation Effects 0.000 description 1
- 238000003199 nucleic acid amplification method Methods 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/01—Arrangements for reducing harmonics or ripples
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
- H02M1/00—Details of apparatus for conversion
- H02M1/12—Arrangements for reducing harmonics from ac input or output
- H02M1/126—Arrangements for reducing harmonics from ac input or output using passive filters
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
- H02M7/00—Conversion of ac power input into dc power output; Conversion of dc power input into ac power output
- H02M7/42—Conversion of dc power input into ac power output without possibility of reversal
- H02M7/44—Conversion of dc power input into ac power output without possibility of reversal by static converters
- H02M7/48—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode
- H02M7/53—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal
- H02M7/537—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only, e.g. single switched pulse inverters
- H02M7/5387—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only, e.g. single switched pulse inverters in a bridge configuration
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/40—Arrangements for reducing harmonics
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a weak current network LCL type grid-connected inversion filter parameter optimization method based on NSGA-II algorithm, which comprises the following steps: modeling a single-phase inversion system under a weak current network, and taking an inversion side inductance L 1, a network side inductance L 2, a filter capacitor C and a passive damping resistor R as parameters to be optimized; setting limit constraint of an inductance total value L, an inversion side inductance L 1, a network side inductance L 2 and a filter capacitor C; constructing an objective function of a switching frequency harmonic attenuation ratio eta, an inverter end inductance current ripple delta I ripple, damping resistance power consumption P R_loss and a resonance frequency f r; based on an NSGA-II algorithm model, taking parameters to be optimized as decision variables, obtaining a parameter solution set of an optimal solution for a plurality of objective functions through iterative optimization according to limit constraint, and picking a group of typical values from the parameter solution set to serve as the optimal solution. The invention can greatly improve the filtering effect and the weak network resistance of the filter.
Description
Technical Field
The invention belongs to the field of inversion filters, and particularly relates to a parameter optimization method of a weak current network LCL type grid-connected inversion filter based on an NSGA-II algorithm.
Background
The grid-connected inverter is key equipment for supporting new energy grid connection, compared with an L and LC type filter, the LCL type filter has a better inhibition effect on high-frequency harmonic waves, the specific performance of the LCL type filter is mainly dependent on LCL parameters, and therefore the design of the filter parameters is very important. However, the parameter design requirement of the filter is more limited, the calculated amount is larger, and the accuracy is poor; in addition, due to the condition of a weak power grid, the safety and the control robustness of the system under multiple operation conditions are more required to be comprehensively considered.
The early filter design method adopts a trial-and-error method to carry out parameter design according to a great deal of engineering experience and electromagnetic characteristics, and forms the traditional filter parameter design method, such as documents, through full experimental results and a graphic method "Xinbo Ruan.Control Techniques for LCL-Type Grid-Connected Inverters.Beijing,CN:Science Press,2015.".
In literature "S.Jayalath and M.Hanif,″An LCL-Filter Design With Optimum Total Inductance and Capacitance,″in IEEE Transactions on Power Electronics,vol.33,no.8,pp.6687-6698,Aug.2018.", individual parameters in the LCL filter are optimized, but the optimal filtering effect of the whole system is not guaranteed.
Disclosure of Invention
The invention provides a weak current network LCL type grid-connected inversion filter parameter optimization method based on NSGA-II algorithm, which greatly improves the filtering effect and weak network resistance of the filter.
A weak current network LCL type grid-connected inversion filter parameter optimization method based on NSGA-II algorithm comprises the following steps:
Modeling a single-phase inversion system under a weak current network, and taking an inversion side inductance L 1, a network side inductance L 2, a filter capacitor C and a passive damping resistor R as parameters to be optimized;
setting limit constraint of an inductance total value L, an inversion side inductance L 1, a network side inductance L 2 and a filter capacitor C;
Constructing an objective function of a switching frequency harmonic attenuation ratio eta, an inverter end inductance current ripple delta I ripple, damping resistance power consumption P R_loss and a resonance frequency f r;
Based on an NSGA-II algorithm model, taking parameters to be optimized as decision variables, obtaining a parameter solution set of an optimal solution for a plurality of objective functions through iterative optimization according to limit constraint, and picking a group of typical values from the parameter solution set to serve as the optimal solution.
The decision variables based on NSGA-II algorithm model are:
X＝[L1,L2,C,R]
in the model, the influence of each parameter on a system is analyzed by adopting a single variable principle on the parameters; the parameter changes are all linear increases and are changed based on the parameters of the traditional trial-and-error method.
In the limit constraint, the total inductance value L needs to satisfy two conditions: first, it is necessary to limit the maximum current generated by the voltage drop across the inductor; secondly, the ripple of the current needs to be reduced to be within an allowable range; i.e. the following inequality constraint needs to be satisfied:
where V g_max、Ig_max is the grid side voltage and current peak, V dc is the dc side voltage, Δi ripple-ma is the inverter side maximum current ripple, f s is the switching frequency, ω 0 is the grid frequency.
The inverter side inductance L 1 and the net side inductance L 2 need to satisfy the following constraints:
L1≥L2
Wherein T s is the switching period, Is the current ripple coefficient,/>For the inductance drop coefficient, ω 0 is the grid frequency, V in represents the filter input voltage (i.e., the inverter side output voltage), I L1 represents the inverter side inductor current, V C represents the filter capacitance node voltage, and V g represents the grid side voltage.
The filter capacitor C needs to satisfy the following constraints:
Wherein: p O is the rated power of the network side output; omega 0 is the grid frequency; lambda C is the power ratio of the reactive power of the capacitor to the rated output; v g is the grid side voltage.
In the objective function, the switching frequency harmonic attenuation ratio eta is the optimization target with the highest priority, and the optimization target is shown as the following formula:
In the formula, I g(s) is a current measurement expression of the power grid in the complex frequency domain, I L1(s) is an inductance current expression of the inverter side in the complex frequency domain, ω s is a switching angular frequency, and s=jω s indicates that the condition is that the frequency is the switching angular frequency.
In the objective function, it is necessary to minimize the inverter-side inductor current ripple:
In the formula, the output voltage V in≈Vdc,Vdc of the inverter is dc voltage, L 1 is the inductance of the inverter side, and f s is the switching frequency.
In the objective function, it is necessary to minimize the damping resistance power consumption P R_loss:
Where V g represents grid side voltage and ω 0 is grid frequency.
In order to satisfy the low-pass characteristic of the LCL filter, the resonant frequency is selected in the objective function:
Wherein, f s、fr is the switching frequency and the resonant frequency, and f 0 is the power grid frequency; since the conditions relating to the three variables are not linear, two objective functions that need to be minimized are used to ensure that the resonant frequency is at the allowable range:
F1＝10f0-fr
F2＝fr-0.5fs
finally, the total objective function is min [ eta, delta I ripple,PR_loss,F1,F2 ]
Compared with the prior art, the invention has the following beneficial effects:
The invention adopts a genetic algorithm (NSGA-II) of multi-objective optimization aiming at the parameter selection of the LCL type filter grid-connected inversion system under the weak power grid condition. Firstly, modeling a single-phase inversion system under a weak current network, analyzing the influence of different filter parameters on the stability of the system, and providing a selection standard of a parameter solution for enhancing the stability of the system. The constraint of the parameter limit is given based on the traditional trial-and-error method, a plurality of optimization targets aiming at the system are given, and a typical solution is selected from the obtained optimization solution set. A large number of trial and error processes are omitted, the resistance of the system to weak network conditions is enhanced, and the harmonic distortion rate is further reduced under the condition of meeting grid-connected requirements.
Drawings
FIG. 1 is a grid-connected inverter topology of an LCL filter in an embodiment of the invention;
FIG. 2 is a closed-loop control block diagram of an LCL grid-connected inverter system in an embodiment of the invention;
FIG. 3 is a flowchart of NSGA-II algorithm in an embodiment of the present invention;
FIG. 4 is a graph showing the trend of pole movement of the closed loop of the system when the filter parameters are increased in the embodiment of the invention;
FIG. 5 is a solution set of optimization parameters in an embodiment of the invention;
FIG. 6 is a system response under conventional parameters in an embodiment of the present invention;
FIG. 7 is a system response under optimized parameters in an embodiment of the invention.
Detailed Description
The invention will be described in further detail with reference to the drawings and examples, it being noted that the examples described below are intended to facilitate the understanding of the invention and are not intended to limit the invention in any way.
The grid-connected inversion topology adopted by the embodiment of the invention is an LCL type circuit with a capacitor connected in series with a resistor, as shown in figure 1. V dc、Cdc is the DC voltage and the filter capacitor; l 1、L2、Lg is the equivalent inductance of the inversion side, the network side and the power grid respectively; r 1、R2、Rg is the corresponding line resistance respectively; v in、vg is the voltage of the output end of the inverter bridge and the voltage of the power grid; i L1、ig、ic、ig_ref is the inverter side current, the grid current, the capacitor current and the grid reference current, respectively. G i(s) is a grid-connected current controller, and H is a capacitance current feedback controller.
In order to more intuitively embody the structure of the system, a closed-loop control block diagram of the inverted system is shown in fig. 2. The current controller G i(s) is a PI controller, H is proportional feedback, K PWM is an equivalent transfer function of the inverter, and is a ratio of the dc voltage to the carrier voltage amplitude. The capacitor series resistance adopted by the embodiment of the invention is a simple and effective method for reducing resonance peak damping, and the capacitor current feedback accelerates the system reaction.
To simplify the transfer function, the smaller line impedance value R 1、R2 is omitted. Therefore, the transfer function of the output voltage of the inversion end to the power grid current and the transfer function of the whole closed loop system can be obtained:
next, the parameters are analytically optimized according to the above model.
In general, the multi-objective optimization algorithm model can obtain a set of solutions according to a specific problem, and the solutions have no coupling relation with each other, which is called Pareto optimal solution set. The invention selects NSGA-II algorithm framework, classifies individuals of the population based on genetic algorithm and sorts the individuals rapidly and nondominately, and prevents excellent individuals from losing through elite strategy.
The main flow of NSGA-II algorithm is shown in FIG. 3. First, an initial population P t of size N is randomly generated, subjected to non-dominant ordering, selection, crossover and mutation to generate a child population Q t, and the two populations are combined together to form a population R t of size 2N. And secondly, carrying out rapid non-dominant ranking, simultaneously carrying out crowding degree calculation on individuals in each non-dominant layer, and selecting proper individuals to form a new parent population P t+1 according to the non-dominant relationship and the crowding degree of the individuals. Finally, a new offspring population Q t+1 is generated by basic operations of the genetic algorithm, P t+1 and Q t+1 are combined to form a new population R t+1, and the above operations are repeated until the condition for ending the program is satisfied.
In the parameter design optimization of this time, the main parameters of the design are filter inductance capacitance L 1、L2 and C and passive damping resistance R, so decision variables based on NSGA-II algorithm model are:
X＝[L1,L2,C,R] (3)
Since the optimal solution set of an algorithm is typically relatively large in number, some additional criteria are needed. In the model, the influence of each parameter on the system can be analyzed by adopting a single variable principle on the parameters. The parameter changes are all linear increases and are changed based on the parameters of the traditional trial-and-error method. On the basis, the respective parameter changes are respectively as follows: l 1(850μH→1200μH),L2 (500. Mu.H. Fwdarw.1200. Mu.H), C (4. Mu.F. Fwdarw.18. Mu.F), R (2Ω. Fwdarw.9Ω).
As can be seen from fig. 4, in the process of increasing the filter inductance L 1、L2, the dominant pole is always close to the virtual axis, and the system stability is degraded; in the process of increasing the capacitance C, the absolute value of the real part of the pole is increased and then decreased; as the resistance R increases, the system stability is enhanced. This results in the selection condition for the optimal solution: ensure that L 1、L2 is smaller, R is larger and C is moderate.
When the filter meets the requirements of harmonic attenuation and the like, limit constraints of an inductance total value L, an inversion side inductance L 1, a network side inductance L 2 and a filter capacitor C are set as constraint conditions of an objective function.
1) Total value of inductance
The total inductance of the LCL filter is larger, and the filtering effect is better; the inductance is smaller and the response capability becomes stronger. The total inductance needs to meet two conditions: on the one hand, it is necessary to limit the maximum current generated by the voltage drop across the inductor; on the other hand, it is necessary to reduce the ripple of the current to be within the allowable range; that is, the following inequality constraint needs to be satisfied:
Wherein: v g_max、Ig_max is the grid side voltage current peak; inverter-side output voltage V inv≈Vdc.
2) Inverter side and network side inductor
In terms of engineering manufacture, in order to reduce cost and volume, the inductance value of the network side is often smaller than the inductance of the inversion side, and the inductance of the inversion side needs to meet the limitations of current ripple and voltage drop on the inductance, so that the following constraints are obtained:
L1≥L2 (6)
wherein: a switching period T s; current ripple coefficient Inductance voltage drop coefficient/>
3) Filter capacitor
The larger the capacitance value is, the smaller the voltage ripple is, but the larger the power consumption is; therefore, the upper limit of the capacitance value needs to be considered:
Wherein: p O is the rated power of the network side output; omega 0 is the grid frequency; the reactive power of the capacitor is approximately equal to 5% of the rated output power ratio lambda C.
The objective functions of the switching frequency harmonic attenuation ratio eta, the inverter end inductance current ripple delta I ripple, the damping resistor power consumption P R_loss and the resonance frequency f r are constructed.
1) Switching frequency harmonic attenuation ratio
The method is an optimization target with highest priority of the optimization design, and the smaller the harmonic attenuation degree is, the better the switching frequency harmonic filtering effect is, as shown in the following formula:
2) Inverter-side inductor current ripple
The inverter switching action can cause dv/dt change of the inverter side current approaching to the switching frequency, namely current ripple, in order to ensure stable and enhanced control effect of the system, reduce loss of the switch and the inductor, and minimize reverse current ripple:
Wherein: the output voltage V in≈Vdc of the inversion terminal; the inverter side inductance L 1.
3) Damping resistor power consumption
LCL filters introduce passive damping to enhance system harmonic rejection performance, but also introduce power consumption, which needs to be minimized:
4) Resonant frequency
In order to meet the low pass characteristics of LCL filters, the resonant frequency is generally selected as follows:
Wherein: f s、fr is the switching frequency and the resonant frequency, respectively. Because the conditions related to the three variables are nonlinear, bilateral constraint is carried out as an optimization target, and the two objective functions needing to be minimized are used for ensuring that the value of the resonant frequency is within the allowable range:
F1＝10f0-fr (12)
F2＝fr-0.5fs (13)
The objective function of such an algorithm is
min[η,ΔIripple,PR_loss,F1,F2] (14)
In summary of the above, the NSGA-II algorithm is used with equation (3) as the optimization variable, equations (4) - (7) as the linear constraint, and equation (14) as the multi-objective function. The basic parameters are set as follows: optimal phylogenetic paretoFraction 0.4.4; population size populationsize 300,300; maximum evolutionary algebraic generations 400; stopping algebra STALLGENLIMIT 300,300; fitness function bias TolFun e-10. Thus, a solution set of the multi-objective Pareto optimal solution is obtained through iterative optimization, as shown in fig. 5.
The resulting solutions are not coupled to each other and are also optimal solutions. However, it can still be seen that the parameters have obvious concentrated intervals, and in the mode intervals of all the four parameters, a group of typical values are selected as an optimization solution according to the parameter selection standard, and the superiority of the algorithm is reflected by comparison with the conventional solution, and the specific parameters are shown in table 1.
Table 1 comparison of conventional methods with optimization algorithms
In order to verify the optimizing effect of a multi-objective optimizing algorithm on a system under the condition of weak current network, the embodiment of the invention builds a simulation model of the grid-connected inverter based on Matlab/Simulink, and the specific parameter environment is shown in Table 2.
TABLE 2 simulation System parameters and Environment
According to the parameters, simulation is carried out on the built model, and the system response under the traditional parameters and the system response under the optimized parameters are respectively shown in fig. 6 and 7, and specifically comprise the voltage at the coupling position, the inversion and network side current, the capacitance current and the harmonic analysis chart.
From the two graphs, the parameters designed by using the optimization algorithm obviously enable the inversion system to have stronger adaptability to the weak network conditions, when the inductance value of the weak current network reaches 2mH, the system of the traditional solution is unstable, but the optimization solution can still keep the stability of the system. The waveform local amplification can show that the ripple wave of the current and the voltage is increased to a certain extent (5.513-6.182A) due to the reduction of the parameter value of the filter, but still is within the allowable range of the grid-connected design requirement; the power consumption of the resistor is obviously increased (0.245 to 4.838W), but the resonance frequency loss change can be almost offset by the reduction of the inductance and capacitance values. The waveform distortion rate under the weak current network condition is obviously reduced, the filtering effect and the weak network resistance of the filter are greatly improved, and the specific parameters of the distortion rate are shown in table 3.
TABLE 3 comparison of conventional methods with optimization algorithms
The foregoing embodiments have described in detail the technical solution and the advantages of the present invention, it should be understood that the foregoing embodiments are merely illustrative of the present invention and are not intended to limit the invention, and any modifications, additions and equivalents made within the scope of the principles of the present invention should be included in the scope of the invention.
Claims (8)
1. A weak current network LCL type grid-connected inversion filter parameter optimization method based on NSGA-II algorithm is characterized by comprising the following steps:
Modeling a single-phase inversion system under a weak current network, and taking an inversion side inductance L 1, a network side inductance L 2, a filter capacitor C and a passive damping resistor R as parameters to be optimized;
Setting limit constraint of an inductance total value L, an inversion side inductance L 1, a network side inductance L 2 and a filter capacitor C; in the limit constraint, the inverter side inductance L 1 and the network side inductance L 2 need to satisfy the following constraints:
L1≥L2
Wherein T s is the switching period, Is the current ripple coefficient,/>For the inductance voltage drop coefficient, ω 0 is the grid frequency, V in represents the filter input voltage, I L1 represents the inverter side inductance current, V C represents the filter capacitance node voltage, and V g represents the grid side voltage;
Constructing an objective function of a switching frequency harmonic attenuation ratio eta, an inverter end inductance current ripple delta I ripple, damping resistance power consumption P R_loss and a resonance frequency f r;
Based on an NSGA-II algorithm model, taking parameters to be optimized as decision variables, obtaining a parameter solution set of an optimal solution for a plurality of objective functions through iterative optimization according to limit constraint, and picking a group of typical values from the parameter solution set to serve as the optimal solution.
2. The method for optimizing parameters of the weak grid LCL grid-connected inverter filter based on the NSGA-II algorithm according to claim 1, wherein decision variables based on a NSGA-II algorithm model are as follows:
X＝[L1,L2,C,R]
in the model, the influence of each parameter on a system is analyzed by adopting a single variable principle on the parameters; the parameter changes are all linear increases and are changed based on the parameters of the traditional trial-and-error method.
3. The method for optimizing parameters of the weak grid-connected inverter filter based on the NSGA-II algorithm according to claim 1, wherein in the limit constraint, the total inductance value L needs to satisfy two conditions: first, it is necessary to limit the maximum current generated by the voltage drop across the inductor; secondly, the ripple of the current needs to be reduced to be within an allowable range; i.e. the following inequality constraint needs to be satisfied:
Where V g_max、Ig_max is the grid side voltage and current peak, V dc is the dc side voltage, Δi ripple-max is the inverter side maximum current ripple, f s is the switching frequency, ω 0 is the grid frequency.
4. The method for optimizing parameters of the weak grid LCL grid-connected inverter filter based on the NSGA-II algorithm according to claim 1, wherein in the limit constraint, the filter capacitor C is required to meet the following constraint:
Wherein: p O is the rated power of the network side output; omega 0 is the grid frequency; lambda C is the power ratio of the reactive power of the capacitor to the rated output; v g is the grid side voltage.
5. The optimization method for parameters of the weak grid LCL grid-connected inverter filter based on the NSGA-II algorithm according to claim 1, wherein in an objective function, a switching frequency harmonic attenuation ratio eta is an optimization target with highest priority, and the optimization target is represented by the following formula:
In the formula, I g(s) is a current measurement expression of the power grid in the complex frequency domain, I L1(s) is an inductance current expression of the inverter side in the complex frequency domain, ω s is a switching angular frequency, and s=jω s indicates that the condition is that the frequency is the switching angular frequency.
6. The method for optimizing parameters of the weak current network LCL grid-connected inversion filter based on NSGA-II algorithm according to claim 1, wherein in the objective function, it is necessary to minimize the inductance current ripple of the inversion end:
In the formula, the output voltage V in≈Vdc,Vdc of the inverter is dc voltage, L 1 is the inductance of the inverter side, and f s is the switching frequency.
7. The method for optimizing parameters of a weak grid LCL grid-connected inverter filter based on NSGA-II algorithm according to claim 1, wherein in the objective function, it is necessary to minimize damping resistance power consumption P R_loss:
Where V g represents grid side voltage and ω 0 is grid frequency.
8. The method for optimizing parameters of a weak grid LCL grid-connected inverter filter based on NSGA-II algorithm according to claim 1, wherein in the objective function, in order to satisfy the low-pass characteristic of the LCL filter, the resonant frequency is selected by:
Wherein, f s、fr is the switching frequency and the resonant frequency, and f 0 is the power grid frequency; since the conditions relating to the three variables are not linear, two objective functions that need to be minimized are used to ensure that the resonant frequency is at the allowable range:
F1＝10f0-fr
F2＝fr-0.5fs
finally, the overall objective function is min [ η, ΔI ripple,PR_loss,F1,F2 ].
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310860883.2A CN116845893B (en) | 2023-07-13 | 2023-07-13 | Parameter optimization method for weak current network LCL type grid-connected inversion filter based on NSGA-II algorithm |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310860883.2A CN116845893B (en) | 2023-07-13 | 2023-07-13 | Parameter optimization method for weak current network LCL type grid-connected inversion filter based on NSGA-II algorithm |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116845893A CN116845893A (en) | 2023-10-03 |
| CN116845893B true CN116845893B (en) | 2024-05-17 |
Family
ID=88159841
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310860883.2A Active CN116845893B (en) | 2023-07-13 | 2023-07-13 | Parameter optimization method for weak current network LCL type grid-connected inversion filter based on NSGA-II algorithm |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116845893B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108649780A (en) * | 2018-05-15 | 2018-10-12 | 国网上海市电力公司 | A kind of LCL filter parameter optimization method considering light current inverter stability off the net |
| CN109787367A (en) * | 2019-03-08 | 2019-05-21 | 重庆大学 | EC-WPT system and its parameter optimization method based on stacked coupling mechanism |
| CN111106676A (en) * | 2020-01-08 | 2020-05-05 | 国网河北省电力有限公司雄安新区供电公司 | Magnetic coupling mechanism parameter multi-objective optimization method of LCC-S type MC-WPT system |
| EP3805999A1 (en) * | 2019-10-10 | 2021-04-14 | Accenture Global Solutions Limited | Resource-aware automatic machine learning system |
| CN114512986A (en) * | 2022-02-23 | 2022-05-17 | 合肥工业大学 | Passive LCL filter parameter optimization design method for grid-connected inverter |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8041545B2 (en) * | 2005-04-28 | 2011-10-18 | Vladimir Sevastyanov | Gradient based methods for multi-objective optimization |
-
2023
- 2023-07-13 CN CN202310860883.2A patent/CN116845893B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108649780A (en) * | 2018-05-15 | 2018-10-12 | 国网上海市电力公司 | A kind of LCL filter parameter optimization method considering light current inverter stability off the net |
| CN109787367A (en) * | 2019-03-08 | 2019-05-21 | 重庆大学 | EC-WPT system and its parameter optimization method based on stacked coupling mechanism |
| EP3805999A1 (en) * | 2019-10-10 | 2021-04-14 | Accenture Global Solutions Limited | Resource-aware automatic machine learning system |
| CN111106676A (en) * | 2020-01-08 | 2020-05-05 | 国网河北省电力有限公司雄安新区供电公司 | Magnetic coupling mechanism parameter multi-objective optimization method of LCC-S type MC-WPT system |
| CN114512986A (en) * | 2022-02-23 | 2022-05-17 | 合肥工业大学 | Passive LCL filter parameter optimization design method for grid-connected inverter |
Non-Patent Citations (2)
| Title |
|---|
| A multi-objective optimized design of LCL filters for grid-connected voltage source inverters considering discrete components;Oscar Hernandez等;《International Transactions on Electrical Energy Systems》;20210421;第31卷(第10期);第1-18页 * |
| 基于NSGAIII多目标优化算法的并网逆变器LLCL滤波器参数优化设计;王应德等;《电气与能效管理技术》;20181230(第24期);第53-59页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116845893A (en) | 2023-10-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108649780B (en) | LCL filter parameter optimization method considering inverter stability under weak grid | |
| CN104953875B (en) | A kind of repetition sliding-mode control of off-network inverter | |
| CN114512986B (en) | Parameter optimization design method for passive LCL filter of grid-connected inverter | |
| CN108631361A (en) | A kind of LC types three-phase grid-connected inverter control method | |
| CN111832158A (en) | Improved particle swarm algorithm-based multi-level inverter harmonic suppression optimization strategy | |
| CN110829485A (en) | LCL filter parameter and control parameter global optimization design method, system and medium based on particle swarm optimization | |
| CN110912135A (en) | Grid-connected inversion LLCL hybrid damping filter design method | |
| CN115534715B (en) | Constant-current constant-voltage IPT system capable of configuring charging voltage and charging current | |
| Zhang et al. | Switching ripple suppressor design of the grid-connected inverters: A perspective of many-objective optimization with constraints handling | |
| CN110867856A (en) | LCL filter parameter optimization method under condition of considering VSC system harmonic stability | |
| CN109861226B (en) | LCL filter design method for comprehensively optimizing harmonic stability and damping loss | |
| Straś et al. | Design of fractional delay repetitive control with a dead-beat compensator for a grid-tied converter under distorted grid voltage conditions | |
| CN116845893B (en) | Parameter optimization method for weak current network LCL type grid-connected inversion filter based on NSGA-II algorithm | |
| CN110429835A (en) | A kind of RBFNN segmentation on-line optimization Passive Shape Control system and method based on LCL filtering | |
| CN111740632B (en) | quasi-Z-source inverter discrete time average model prediction control device and method | |
| CN105978018B (en) | A kind of LC types control method of grid-connected inverter | |
| CN109149981B (en) | A kind of Multipurpose Optimal Method based on genetic algorithm suitable for MMC | |
| Dhaneria et al. | Design of AC side filter for grid tied solar inverter | |
| CN115378259A (en) | Topology of passive resonant converter based on optimization parameter calculation and control method thereof | |
| El-Khazali | Fractional-order LC α L filter-based grid connected PV systems | |
| Thuyen | A new approach in design for hybrid active power filter | |
| Xue et al. | Feedforward phase compensation method of LCL grid‐connected inverter based on all‐pass filter in weak grid | |
| Liu et al. | Parameter optimization of LCL-type grid-connected inverter filter in weak power grid using NSGA-II algorithm | |
| CN112994004A (en) | Hybrid active filter resonance suppression strategy considering control delay | |
| Huang et al. | Switching harmonic suppression design based on multi-objective optimization algorithm with constraint processing |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |