CN111404177B - Self-adaptive secondary frequency modulation method for micro-grid of multiple virtual synchronous machines - Google Patents
Self-adaptive secondary frequency modulation method for micro-grid of multiple virtual synchronous machines Download PDFInfo
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Abstract
The invention relates to a self-adaptive secondary frequency modulation method for a multi-virtual synchronous machine micro-grid, and belongs to the field of micro-grid control. According to the method, under the condition that communication does not exist among virtual synchronous machines, secondary frequency modulation is achieved by adopting improved virtual synchronous machine control based on PI control, and the frequency modulation power of the virtual synchronous machines is dynamically adjusted through self-adaptive adjustment of secondary frequency modulation parameters, so that the frequency modulation power is in direct proportion to the real-time predicted frequency modulation spare capacity. The invention can avoid the waste of power output and reduce the influence of the limitation of the spare capacity on the completion condition of the frequency modulation task.
Description
Technical Field
The invention belongs to the field of microgrid control, and relates to a self-adaptive secondary frequency modulation strategy for a microgrid with multiple virtual synchronous machines.
Background
When various distributed power generation or energy storage devices exist in the microgrid, such as an electric vehicle, a wind turbine generator set, a photovoltaic set and the like, a traditional cooperative mode is centralized control frequency modulation, namely, a centralized control center exists, and system frequency modulation tasks are distributed to frequency modulation participants by the centralized control center. However, centralized control has the disadvantages of low reliability, high requirements on the computing power and communication lines of the control center, and the like.
A Virtual Synchronous Generator (VSG) is an inverter control technique proposed in documents "q.c. zhong and g.weiss," synchronizers: inverters at mistuning generators, "IEEE trans.ind.electron., vol.58, No.4, pp.1259-1267, apr.2011" which enables an inverter to adjust a system voltage or frequency by simulating external characteristics of a Synchronous Generator. Through the virtual synchronous machine, distributed generation and energy storage in the microgrid can realize distributed cooperative frequency modulation. Documents "z.shuai, h.wen, s.xia, y.li, and j.shen," a Maximum Power Loading Factor (MPLF) Control Strategy for Distributed second Frequency Regulation of island fine grid, "IEEE trans.power electron, vol.34, No.3, pp.2275-2291, and mar.2019" propose adjusting the reference active Power of each virtual synchronizer based on a uniform reference signal, achieving Distributed Secondary Frequency modulation of a Microgrid including a plurality of virtual synchronizers. According to the generalized transient Stability criterion, a particle swarm Optimization algorithm is adopted to optimize inertia and damping coefficients of a virtual synchronizer in documents 'J.Alipo, Y.Miura, and T.ise,' Stability analysis and Optimization Methods for Microgrid with Multiple VSG Units, 'IEEE trans.Smart Grid, vol.9, No.2, pp.1462-1471 and Mar.2018', so that the transient Stability of the Microgrid with Multiple virtual synchronizers is improved. However, in the control strategy of the above document, communication between devices is still necessary, resulting in lack of reliability in frequency modulation thereof; and neglects the limitation of the fm reserve capacity of each virtual synchronous machine, the virtual synchronous machines may not achieve the desired power output. An adaptive droop control strategy that does not require communication for multiple virtual synchronizer frequency modulation is disclosed in the documents "w.ren, l.chen, t.zheng, and s.mei," VSG-based adaptive droop control for frequency and active power regulation in the MTDC system, "CSEE j.power Energy system", vol.3, No.3, pp.260-268, sept.2017 ", where more/less unbalanced power is allocated to virtual synchronizers with smaller/larger frequency deviations. However, this allocation method is not reasonable in view of the fm spare capacity, because the virtual synchronous machine, which may have a small frequency deviation, may be limited by the spare capacity and thus cannot compensate for the excessive unbalanced power.
Disclosure of Invention
In view of the above, an object of the present invention is to provide a method for controlling adaptive secondary frequency modulation of a microgrid with multiple virtual synchronizers, which can implement secondary frequency modulation by using an improved virtual synchronizer control based on Proportional Integral (PI) control under the condition that there is no communication between the virtual synchronizers, and dynamically adjust the frequency modulation power of the virtual synchronizers by adaptive adjustment of secondary frequency modulation parameters so as to make the frequency modulation power in proportion to the real-time predicted frequency modulation spare capacity, thereby avoiding waste of power output and reducing the influence of spare capacity limitation on the completion of frequency modulation tasks.
In order to achieve the purpose, the invention provides the following technical scheme:
a self-adaptive secondary frequency modulation method of a multi-virtual synchronous machine micro-grid is characterized in that under the condition that communication does not exist among virtual synchronous machines, the improved virtual synchronous machine control based on Proportional Integral (PI) control is adopted to realize secondary frequency modulation, and the frequency modulation power of the virtual synchronous machines is dynamically adjusted through self-adaptive adjustment of secondary frequency modulation parameters, so that the frequency modulation power is in direct proportion to real-time predicted frequency modulation spare capacity; the method specifically comprises the following steps:
s1: controlling a virtual synchronizer and carrying out secondary frequency modulation;
s2: self-adaptive adjustment based on the frequency modulation spare capacity comprises self-adaptive adjustment of the frequency modulation output and a secondary frequency modulation coefficient of the virtual synchronous machine;
s3: the traditional unit and the virtual synchronous machine cooperate with frequency modulation.
Further, in step S1, the virtual synchronous machine control specifically includes: the function of simulating the motion equation of the rotor of the synchronous motor is realized by a power frequency controller in the virtual synchronous machine, and the obtained motion equation of the rotor of the virtual synchronous machine is shown as the following formula:
converting the formula (1) to obtain an active frequency control equation of the virtual synchronous machine, wherein the equations are shown in the formulas (2) to (4):
wherein J is moment of inertia, D is damping coefficient, and P ismIs mechanical power, PeFor electromagnetic power, Tm、Te、TdRespectively mechanical torque, electromagnetic torque and damping torque, omega is mechanical angular frequency, omegaNAt a rated angular frequency, delta is the power angle, KJAnd KDRespectively recorded as power inertia coefficient and power damping coefficient.
Further, in step S1, the virtual synchronous machine secondary frequency modulation specifically includes: adding a frequency deviation feedback instruction based on droop control into input mechanical power of a power frequency controller to realize primary frequency modulation, wherein the formula (5) is as follows:
Pm＝Pref+Dp(ωN-ω) (5)
wherein, PrefFor reference to active power, DpIs the sag factor;
in the combination formula (4), the transient relation between the frequency and the active power is derived as follows:
however, droop control does not achieve a uniform control of the system frequency. Therefore, in order to realize the error-free secondary frequency modulation, PI control is introduced into the frequency deviation feedback command of the power frequency controller, as shown in equation (7):
wherein, KpAnd KiProportional coefficient and integral coefficient of the PI controller respectively.
In combination with formula (4) after laplace transformation, the following is derived:
then, the final value theorem yields:
as can be seen from equation (9), the introduction of PI control into the power frequency controller realizes frequency error-free control.
Further, in step S2, the virtual synchronous machine frequency modulation output specifically includes: when n virtual synchronous machines are connected in parallel, similar to equation (6), the frequency offset of each VSG in a steady state after the PI control link is introduced is derived as follows:
wherein, PIiThe active power output by a PI controller of the ith virtual synchronous machine;
converting the equation (10) to obtain the output power of the ith virtual synchronous machine as follows:
Pe,i＝Pref,i+(PIi-KD,iΔω) (11)
as can be seen from the above formula, the frequency modulation output of the ith virtual synchronous machine is:
PFR,i＝PIi-KD,iΔω (12)
in order to enable a plurality of virtual synchronizers to output power according to respective frequency modulation spare capacity, the parameters of a PI controller of each virtual synchronizer are set to be the same, a proportional link is added behind the PI controller, and the proportional coefficient is recorded as a distribution coefficient KaAs shown in formula (13):
the frequency modulation output of the ith virtual synchronous machine is represented as:
PFR,i＝Ka,iPI-KD,iΔω (14)。
further, in step S2, the adaptively adjusting the secondary frequency modulation coefficient specifically includes: the ratio of the proportionality coefficient and the power damping coefficient of each virtual synchronous machine to the respective real-time predicted spare capacity is equal, as shown in formula (15):
Ka,1:Ka,2:…:Ka,n＝KD,1:KD,2:…:KD,n＝R1:R2:…:Rn (15)
wherein R isiPredicting the spare capacity of frequency modulation for the ith virtual synchronous machine in real time;
combining with the equation (14), it is derived that the ratio of the frequency-modulated output of each virtual synchronous machine is equal to the ratio of the respective spare capacity under the condition of equation (15), as shown in equation (16):
PFR,1:PFR,2:…:PFR,n＝R1:R2:…:Rn (16)
by pairing distribution coefficients KaSum power damping coefficient KDThe dynamic adjustment of the virtual synchronous machine can control the frequency modulation power of each virtual synchronous machine to be always in proportion to the frequency modulation reserve capacity of the virtual synchronous machine, thereby realizing more reasonable frequency modulation output distribution;
the secondary frequency modulation coefficient is respectively subjected to self-adaptive adjustment according to the formulas (17) and (18):
wherein the content of the first and second substances,
Rup,i、Rdown,irespectively the distribution coefficient, the power damping coefficient and the real-time predicted frequency modulation reserve capacity of the ith virtual synchronous machine under the conditions of up frequency modulation and down frequency modulation,
the coefficient is assigned to the reference and,
is taken as a reference power damping coefficient,
In order to increase the frequency-modulated reference capacity,
is a lower frequency modulation reference capacity;
it is deduced that the virtual synchronous machine secondary frequency modulation coefficient obtained by the above formula satisfies formula (15), so that the frequency modulation power of each virtual synchronous machine is proportional to the frequency modulation spare capacity under the condition of no communication.
Further, the step S3 specifically includes: when the frequency modulation spare capacity of the virtual synchronous machine is sufficient, in order to avoid unnecessary waste, a traditional machine set does not need to keep a certain frequency modulation output all the time when the system frequency deviates. By adopting a traditional unit and virtual synchronous machine cooperative frequency modulation strategy based on frequency modulation spare capacity day-ahead prediction, the traditional unit can output more reasonable power while assisting the virtual synchronous machine to modulate frequency. The strategy specifically comprises:
1) firstly, predicting the frequency modulation spare capacity of each virtual synchronous machine day ahead to obtain the total predicted frequency modulation spare capacity of the virtual synchronous machines day ahead;
2) setting a frequency modulation total capacity threshold value R of the virtual synchronous machinethWhen the predicted frequency modulation spare capacity in the day ahead is not enough to meet the total capacity threshold, as shown in formula (19) or formula (20), calling the traditional unit to participate in up/down frequency modulation through PI control in the time interval;
wherein the content of the first and second substances,
and
respectively representing the day-ahead predicted up-modulation and down-modulation reserve capacity of the ith virtual synchronous machine;
(3) when the sum of the frequency modulation capacity of each virtual synchronous machine in the period that the traditional unit does not participate in frequency modulation is insufficient, a frequency modulation dead zone of the traditional unit is set, namely, once the frequency deviation | delta f | of the system exceeds the determined frequency modulation periodOver-set frequency modulation dead zone boundary fdbAnd the traditional unit needs frequency modulation output.
The invention has the beneficial effects that: the self-adaptive secondary frequency modulation control strategy applicable to the multi-virtual synchronous machine micro-grid can dynamically adjust the frequency modulation power of the virtual synchronous machines to be in direct proportion to the frequency modulation spare capacity predicted in real time under the condition that communication does not exist among the virtual synchronous machines, so that the problems of low communication reliability in the traditional centralized frequency modulation control mode and unreasonable power distribution mode of system frequency modulation demand in fixed proportion caused by frequency modulation spare capacity change in the frequency modulation process are solved.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the invention may be realized and attained by the means of the instrumentalities and combinations particularly pointed out hereinafter.
Drawings
For the purposes of promoting a better understanding of the objects, aspects and advantages of the invention, reference will now be made to the following detailed description taken in conjunction with the accompanying drawings in which:
FIG. 1 is a functional block diagram of a power frequency controller;
FIG. 2 is a schematic diagram of an adaptive secondary frequency modulation of a virtual synchronous machine;
FIG. 3 is a schematic diagram of a microgrid system model;
FIG. 4 is a diagram of the amount of capacity predicted for frequency modulation at the day ahead;
FIG. 5 is a comparison graph of frequency modulation effects of multiple VSGs and a conventional unit;
FIG. 6 is a schematic diagram of a virtual synchronous machine for predicting frequency modulation reserve capacity in real time;
FIG. 7 is a diagram showing the result of variation of secondary frequency modulation parameters of the virtual synchronous machine;
FIG. 8 is a diagram showing the results of the virtual synchronous machine participating in frequency modulation;
FIG. 9 is a result diagram of the conventional unit participating in frequency modulation;
FIG. 10 is a graph comparing frequency modulation effects of adaptive and fixed ratio frequency modulation methods;
FIG. 11 is a diagram showing the results of the embodiment of the present invention;
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention in a schematic way, and the features in the following embodiments and examples may be combined with each other without conflict.
Referring to fig. 1 to 11, in a self-adaptive secondary frequency modulation method for a multi-virtual synchronous machine micro-grid, in the case that there is no communication between virtual synchronous machines, a secondary frequency modulation is implemented by using an improved virtual synchronous machine control based on Proportional Integral (PI) control, and the frequency modulation power of the virtual synchronous machine is dynamically adjusted by self-adaptive adjustment of secondary frequency modulation parameters so as to be in direct proportion to a real-time predicted frequency modulation spare capacity. The method specifically comprises the following steps:
the method comprises the following steps: frequency modulation principle of virtual synchronous machine
(1) Virtual synchronous machine control
The virtual synchronous machine control means that links such as a synchronous machine rotor motion equation are introduced into a distributed power supply or a distributed energy storage grid-connected controller, so that the virtual synchronous machine control can simulate the external characteristics of the synchronous generator set such as inertia and damping of grid-connected operation, and the operation adaptability and the safety and stability level of the accessed power grid are improved. The function of simulating the motion equation of the rotor of the synchronous motor is realized by a power frequency controller in the virtual synchronous machine, and the schematic block diagram is shown in fig. 1. Wherein J is moment of inertia; d is a damping coefficient; peIs the electromagnetic power; t ism、Te、TdRespectively is mechanical torque, electromagnetic torque and damping torque; omega is mechanical angular frequency;ωNis the rated angular frequency; delta is the power angle.
Therefore, the equation of motion of the rotor of the virtual synchronous machine can be obtained as shown in the following formula:
in order to obtain an active frequency control equation of the virtual synchronous machine, the equation (1) is transformed, as shown in equations (2) to (4):
in the formula, KJAnd KDRespectively recorded as power inertia coefficient and power damping coefficient.
(2) Virtual synchronous machine secondary frequency modulation
The frequency deviation feedback instruction based on droop control is added into the input mechanical power of the power frequency controller, so that the function of primary frequency modulation can be realized, as shown in formula (5):
Pm＝Pref+Dp(ωN-ω) (5)
wherein, PrefFor reference to active power, DpIs the sag factor;
in the combination formula (4), the transient relation between the frequency and the active power is derived as follows:
however, droop control does not achieve a uniform control of the system frequency. Therefore, in order to realize the error-free secondary frequency modulation, PI control is introduced into the frequency deviation feedback command of the power frequency controller, as shown in equation (7):
wherein, KpAnd KiProportional coefficient and integral coefficient of the PI controller respectively.
In combination with formula (4) after laplace transformation, the following is derived:
then, the final value theorem yields:
as can be seen from equation (9), the introduction of PI control into the power frequency controller realizes frequency error-free control.
Step two: adaptive adjustment strategy based on frequency modulation spare capacity
(1) Virtual synchronous machine frequency modulation output
When n virtual synchronous machines are connected in parallel, similar to equation (6), it can be deduced that the frequency offset of each VSG at steady state after the PI control link is introduced is as follows:
wherein, PIiThe active power output by a PI controller of the ith virtual synchronous machine;
converting the equation (10) to obtain the output power of the ith virtual synchronous machine as follows:
Pe,i＝Pref,i+(PIi-KD,iΔω) (11)
as can be seen from the above formula, the frequency modulation output of the ith virtual synchronous machine is:
PFR,i＝PIi-KD,iΔω (12)
in order to enable a plurality of virtual synchronizers to output power according to respective frequency modulation spare capacity, the parameters of a PI controller of each virtual synchronizer are set to be the same, a proportional link is added behind the PI controller, and the proportional coefficient is recorded as a distribution coefficient KaAs shown in equation (13) and fig. 2:
the frequency modulation output of the ith virtual synchronous machine is represented as:
PFR,i＝Ka,iPI-KD,iΔω (14)
(2) secondary frequency modulation coefficient self-adaptive adjustment strategy
Since the angular frequency offset Δ ω of each virtual synchronous machine is the same, the output of the PI controller is the same under the condition that the PI controller parameters are the same. If the ratio of the proportionality coefficient and the power damping coefficient of each virtual synchronous machine to the respective real-time predicted spare capacity is equal, as shown in equation (15):
Ka,1:Ka,2:…:Ka,n＝KD,1:KD,2:…:KD,n＝R1:R2:…:Rn (15)
wherein R isiAnd predicting the frequency modulation spare capacity of the ith virtual synchronous machine in real time.
Combining with equation (14), it can be derived that the ratio of the frequency-modulated output of each virtual synchronous machine is equal to the ratio of the respective spare capacities under the condition of equation (15), as shown in equation (16):
PFR,1:PFR,2:…:PFR,n＝R1:R2:…:Rn (16)
therefore, by pairing the distribution coefficient KaAnd power damping systemNumber KDThe dynamic adjustment of the virtual synchronous machine can control the frequency modulation power of each virtual synchronous machine to be always proportional to the frequency modulation reserve capacity of the virtual synchronous machine, thereby realizing more reasonable frequency modulation output distribution.
In order to enable each virtual synchronous machine to perform self-adaptive adjustment on respective frequency modulation output under the condition that communication does not exist between the virtual synchronous machines, four reference parameters are set: reference distribution coefficient
Reference power damping coefficient
Upper frequency modulation reference capacity
Lower frequency modulation reference capacity
And (3) the distribution coefficient and the power damping coefficient of each virtual synchronous machine under the conditions of up frequency modulation and down frequency modulation are called as the secondary frequency modulation coefficient of the virtual synchronous machine. If the secondary frequency modulation coefficient is adaptively adjusted according to the following equations (17) and (18):
it can be deduced that the virtual synchronous machine chirp coefficient obtained by the above formula satisfies formula (15), thereby realizing that the chirp power of each virtual synchronous machine is proportional to its chirp reserve capacity in the case of no communication.
Step three: cooperative frequency modulation strategy for traditional unit and virtual synchronous machine
When all frequency modulation functions are borne by the virtual synchronizers in the microgrid, the situation that the frequency modulation spare capacity of each virtual synchronizers is small may occur, so that the frequency modulation power output is insufficient and the frequency modulation effect is poor. Therefore, the frequency modulation is carried out by adopting the traditional unit auxiliary virtual synchronous machine.
When the frequency modulation spare capacity of the virtual synchronous machine is sufficient, in order to avoid unnecessary waste, a traditional machine set does not need to keep a certain frequency modulation output all the time when the system frequency deviates. The invention provides a traditional unit and virtual synchronous machine cooperative frequency modulation strategy based on frequency modulation spare capacity day-ahead prediction, which can enable the traditional unit to output more reasonable power while assisting the virtual synchronous machine in frequency modulation. The specific strategy is as follows:
(1) firstly, predicting the frequency modulation spare capacity of each virtual synchronous machine day ahead to obtain the total predicted frequency modulation spare capacity of the virtual synchronous machines day ahead;
(2) setting a frequency modulation total capacity threshold value R of the virtual synchronous machinethWhen the predicted frequency modulation spare capacity in the day ahead is not enough to meet the total capacity threshold, as shown in formula (19) or formula (20), calling the traditional unit to participate in up/down frequency modulation through PI control in the time interval;
wherein the content of the first and second substances,
and
respectively representing the day-ahead predicted up-modulation and down-modulation reserve capacity of the ith virtual synchronous machine;
(3) due to the difference between the day-ahead prediction and the real-time situation, the situation that the sum of the frequency modulation capacity of each virtual synchronous machine is insufficient when the traditional set does not participate in the frequency modulation period may occur, so that the frequency modulation effect is poor. In order to solve the problem of the above-mentioned problems,setting a frequency modulation dead zone of a traditional unit, namely, once the frequency deviation | delta f | of the system exceeds a set frequency modulation dead zone boundary f outside a determined frequency modulation perioddbAnd the traditional unit needs frequency modulation output.
Example 1:
1. parameter setting
The simulation example is based on a micro-grid system model comprising a wind turbine generator, a photovoltaic generator, an electric vehicle cluster and a traditional generator, and is shown in figure 3. In the system model, EVA stands for electric vehicle aggregator, and M and D are the inertia constant and damping coefficient of the generator, respectively.
The rated installed capacities of the wind turbine generator and the photovoltaic generator are both 5 MW. 1000 electric vehicles are contained in the microgrid, the driving rule of the microgrid refers to Beijing annual traffic development, and the Monte Carlo method is adopted to simulate the driving behavior and SOC change of a single electric vehicle. The environmental data adopts measured data of 5 months in a certain city (43 degrees N and 112 degrees E) in the north of China, and comprises wind speed, solar irradiance and temperature.
2. Day ahead prediction
The day-ahead prediction is performed on the frequency modulation reserve capacities of the wind turbine generator, the photovoltaic generator and the electric automobile in the microgrid, and the obtained total day-ahead predicted frequency modulation capacity is shown in fig. 4.
Setting a virtual synchronous machine frequency modulation total capacity threshold value RthWith 2MW, the time periods required for the conventional units to participate in frequency modulation can be obtained according to equations (19) and (20) as shown in table 1. In addition, a frequency modulation dead zone boundary f is setdb＝0.3Hz。
TABLE 1 participating in frequency modulation period of a conventional unit
3. Multi-virtual synchronous machine frequency modulation
Four reference parameter settings for adaptive adjustment are shown in table 2, depending on the case of the system model.
TABLE 2 adaptive tuning of reference parameters
In order to verify the frequency modulation effect of the frequency modulation strategy for adaptively adjusting the frequency modulation output of each virtual synchronous machine in the frequency modulation process, a scene I and a scene II are set. In the first scenario, a wind turbine generator, a photovoltaic generator and an electric automobile participate in frequency modulation through the proposed multi-virtual synchronous machine frequency modulation strategy; in the second scenario, the wind and light unit and the electric vehicle cluster do not participate in frequency modulation, and only the traditional unit participates in frequency modulation. The 24h system frequency offset in the two scenarios is shown in fig. 5, where the rms value of the frequency offset in scenario one is 0.0968Hz, and scenario two is 0.1258 Hz. As can be seen from fig. 5, under the proposed frequency modulation strategy, the frequency modulation effect meets the requirement of the power grid, and is superior to the frequency modulation effect of the conventional unit. Compared with the traditional unit with the climbing rate limitation, the wind and light unit and the electric automobile both have the characteristic of quick response and can obtain better frequency modulation effect.
In the first scenario, the change situation of 24h of the frequency modulation reserve capacity of the wind turbine generator, the photovoltaic generator and the electric vehicle cluster is predicted in real time as shown in fig. 6.
In scenario one, the distribution coefficient 24h of each virtual synchronous machine changes as shown in fig. 7. Since the variation law of the power damping coefficient is the same as the distribution coefficient, and only the amplitude is different, it is not described herein. As can be seen from fig. 7, in the frequency modulation process, the distribution coefficient and the power damping coefficient of each virtual synchronous machine are dynamically adjusted along with the real-time prediction of the frequency modulation capacity and the switching between the upper frequency modulation and the lower frequency modulation, so that the frequency modulation power of a plurality of virtual synchronous machines is distributed according to the frequency modulation capacity. When the real-time predicted frequency modulation capacity is larger, the distribution coefficient and the power damping coefficient are larger, otherwise, the distribution coefficient and the power damping coefficient are smaller, and the active power output by the PI controller is the same, so that the frequency modulation power of each virtual synchronous machine is in direct proportion to the real-time predicted frequency modulation capacity.
In scenario one, the comparison between the virtual synchronous machines is shown in fig. 8. The frequency modulation task refers to the frequency modulation power distributed to each virtual synchronous machine according to a proposed self-adaptive adjustment strategy, and the frequency modulation output refers to the actual frequency modulation output of each virtual synchronous machine after the actual output limit is considered. Under the proposed frequency modulation strategy, the frequency modulation task of each virtual synchronous machine is dynamically adjusted along with the adjustment of the secondary frequency modulation coefficient and the change of the system frequency offset. As can be seen from fig. 8, the frequency modulation output of each virtual synchronous machine substantially satisfies the frequency modulation task, because the adaptive adjustment of the frequency modulation task allocation takes into account the real-time predicted frequency modulation capacity of each virtual synchronous machine. Therefore, the unreasonable situation that more/less frequency modulation tasks are distributed when the frequency modulation capacity is smaller/larger cannot occur, so that the resource waste or the frequency modulation tasks cannot be effectively completed is caused.
In scenario one, the comparison between the frequency modulation output of the conventional unit and the frequency modulation task is shown in fig. 9. As can be seen from fig. 9, according to the cooperative frequency modulation strategy of the virtual synchronous machine and the conventional set, the conventional set performs the up-frequency modulation output at the time interval of 7:00-11:00 and 16:00-20:00, and performs the down-frequency modulation output at the time interval of 17:00-20:00, as a supplement when the frequency modulation capacity of the virtual synchronous machine is insufficient.
4. Comparative examples
In order to embody the superiority of the proposed virtual synchronous machine frequency modulation strategy based on adaptive adjustment, a comparative example is set, and a scenario three is set. In the third scenario, when each virtual synchronous machine participates in the secondary frequency modulation, the load power is shared according to the traditional control mode, that is, according to the fixed proportion. If the values of the distribution coefficient and the power damping coefficient are in a direct proportional relationship with the maximum frequency modulation capacity of each virtual synchronous machine, the parameters of the comparative example are shown in tables 3 and 4.
TABLE 3 comparative example secondary frequency modulation parameters
TABLE 4 secondary frequency modulation parameters for comparative examples
The frequency modulation effect pair ratio of scene one and scene three is shown in fig. 10, wherein the rms value of the system frequency offset in scene one is 0.0968Hz, and scene three is 0.1193 Hz. As can be seen from fig. 10, the proposed frequency modulation strategy based on adaptive adjustment is superior to the frequency modulation strategy using a fixed allocation ratio.
The comparison between the frequency modulation task and the frequency modulation output of each virtual synchronous machine in the third scenario is shown in fig. 11. As can be seen from fig. 11, since the frequency modulation strategy with a fixed allocation ratio does not take into account the variation of the frequency modulation capacity of each virtual synchronous machine, a situation may occur in which the virtual synchronous machine still allocates the frequency modulation task in a fixed ratio when predicting that the frequency modulation capacity is insufficient in real time, so that the frequency modulation task cannot be effectively completed due to the limitation of the frequency modulation capacity. Meanwhile, when the frequency modulation capacity of the virtual synchronous machine is sufficient, more frequency modulation tasks cannot be allocated due to the fixed allocation proportion. Furthermore, the mismatch between the fm task and the fm capacity will result in poor fm effect.
Compared with the traditional frequency modulation strategy with fixed distribution proportion, the self-adaptive frequency modulation strategy ensures that the virtual synchronous machines can automatically share the required frequency modulation power of the system according to the self-real-time predicted frequency modulation capacity, so that the waste of resources is avoided, the frequency modulation capacity of each virtual synchronous machine is fully utilized, and a better frequency modulation effect can be obtained.
Finally, the above embodiments are only intended to illustrate the technical solutions of the present invention and not to limit the present invention, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions, and all of them should be covered by the claims of the present invention.
Claims (5)
1. A self-adaptive secondary frequency modulation method of a multi-virtual synchronous machine micro-grid is characterized in that under the condition that communication does not exist among virtual synchronous machines, the method adopts improved virtual synchronous machine control based on PI control to realize secondary frequency modulation, and dynamically adjusts the frequency modulation power of the virtual synchronous machines through the self-adaptive adjustment of secondary frequency modulation parameters to enable the frequency modulation power to be in direct proportion to the real-time predicted frequency modulation spare capacity; the method specifically comprises the following steps:
s1: controlling a virtual synchronizer and carrying out secondary frequency modulation;
the virtual synchronous machine secondary frequency modulation specifically comprises the following steps: adding a frequency deviation feedback instruction based on droop control into input mechanical power of a power frequency controller to realize primary frequency modulation, wherein the formula (1) is as follows:
Pm＝Pref+Dp(ωN-ω) (1)
wherein, PmIs mechanical power, PrefFor reference to active power, DpIs the sag factor, omega is the mechanical angular frequency, omegaNIs the rated angular frequency;
combined type
The transient relation between the frequency and the active power is deduced as follows:
wherein, PeIs electromagnetic power, KJAnd KDRespectively recording as a power inertia coefficient and a power damping coefficient;
introducing PI control into a frequency deviation feedback instruction of a power frequency controller, wherein the formula (3) is as follows:
wherein, KpAnd KiProportional coefficient and integral coefficient of PI controller;
s2: self-adaptive adjustment based on the frequency modulation spare capacity comprises self-adaptive adjustment of the frequency modulation output and a secondary frequency modulation coefficient of the virtual synchronous machine;
s3: the traditional unit and the virtual synchronous machine cooperate with frequency modulation.
2. The method according to claim 1, wherein in step S1, the virtual synchronous machine control specifically includes: the function of simulating the motion equation of the rotor of the synchronous motor is realized by a power frequency controller in the virtual synchronous machine, and the obtained motion equation of the rotor of the virtual synchronous machine is shown as the following formula:
and (5) converting the formula (4) to obtain an active frequency control equation of the virtual synchronous machine, wherein the equations are shown in the formulas (5) to (7):
wherein J is moment of inertia, D is damping coefficient, and P ismIs mechanical power, PeFor electromagnetic power, Tm、Te、TdRespectively mechanical torque, electromagnetic torque and damping torque, omega is mechanical angular frequency, omegaNAt a rated angular frequency, delta is the power angle, KJAnd KDRespectively recorded as power inertia coefficient and power damping coefficient.
3. The method of claim 2, wherein the adaptive secondary frequency modulation method is applied to a multi-virtual synchronous machine micro-gridIn step S2, the virtual synchronous machine frequency modulation output specifically includes: when n virtual synchronous machines are connected in parallel, firstly, the parameters of the PI controllers of all the virtual synchronous machines are set to be the same, a proportion link is added behind the PI controllers, and the proportion coefficient is recorded as a distribution coefficient KaAs shown in formula (8):
wherein, i is 1,2, …, n, the frequency modulation output of the ith virtual synchronous machine is expressed as:
PFR,i＝Ka,iPI-KD,iΔω (9)。
4. the method according to claim 3, wherein in step S2, the adaptive adjustment of the chirp coefficient specifically includes: the ratio of the proportionality coefficient and the power damping coefficient of each virtual synchronous machine to the respective real-time predicted spare capacity is equal, as shown in formula (10):
Ka,1:Ka,2:…:Ka,n＝KD,1:KD,2:…:KD,n＝R1:R2:…:Rn (10)
wherein R isiPredicting the spare capacity of frequency modulation for the ith virtual synchronous machine in real time;
combining with the equation (9), it is derived that the frequency modulation output ratio of each virtual synchronous machine is equal to the ratio of the respective spare capacity under the condition of equation (10), as shown in equation (11):
PFR,1:PFR,2:…:PFR,n＝R1:R2:…:Rn (11)
by pairing distribution coefficients KaSum power damping coefficient KDThe dynamic adjustment of the virtual synchronous machine can control the frequency modulation power of each virtual synchronous machine to be always in proportion to the frequency modulation reserve capacity of the virtual synchronous machine, thereby realizing more reasonable frequency modulation output distribution;
the secondary frequency modulation coefficients are respectively subjected to adaptive adjustment according to the equations (12) and (13):
wherein the content of the first and second substances,
Rup,i、Rdown,irespectively the distribution coefficient, the power damping coefficient and the real-time predicted frequency modulation reserve capacity of the ith virtual synchronous machine under the conditions of up frequency modulation and down frequency modulation,
the coefficient is assigned to the reference and,
in order to be the reference power damping coefficient,
in order to increase the frequency-modulated reference capacity,
is a lower frequency modulation reference capacity;
it is derived that the virtual synchronous machine secondary frequency modulation coefficients obtained from the formulas (12) to (13) satisfy the formula (10), so that the frequency modulation power of each virtual synchronous machine is proportional to the frequency modulation spare capacity under the condition of no communication.
5. The method according to claim 4, wherein the step S3 specifically includes: when the frequency modulation spare capacity of the virtual synchronous machine is sufficient, a traditional machine set and virtual synchronous machine cooperative frequency modulation strategy based on frequency modulation spare capacity prediction in the day ahead is adopted, and the strategy specifically comprises the following steps:
1) firstly, predicting the frequency modulation spare capacity of each virtual synchronous machine day ahead to obtain the total predicted frequency modulation spare capacity of the virtual synchronous machines day ahead;
2) setting a frequency modulation total capacity threshold value R of the virtual synchronous machinethWhen the predicted frequency modulation spare capacity in the day ahead is not enough to meet the total capacity threshold value, as shown in a formula (14) or a formula (15), calling a traditional unit to participate in up/down frequency modulation through PI control;
wherein the content of the first and second substances,
and
respectively representing the day-ahead predicted up-modulation and down-modulation reserve capacity of the ith virtual synchronous machine;
3) when the sum of the frequency modulation capacity of each virtual synchronous machine of the traditional unit is insufficient in the period that the traditional unit does not participate in frequency modulation, a frequency modulation dead zone of the traditional unit is set, namely, once the frequency deviation | delta f | of the system exceeds the set frequency modulation dead zone boundary f outside the determined frequency modulation perioddbAnd the traditional unit needs frequency modulation output.
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