CN112366726B - Primary frequency modulation coefficient optimization method for thermal power generating unit and related equipment - Google Patents

Primary frequency modulation coefficient optimization method for thermal power generating unit and related equipment Download PDF

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CN112366726B
CN112366726B CN202011139200.7A CN202011139200A CN112366726B CN 112366726 B CN112366726 B CN 112366726B CN 202011139200 A CN202011139200 A CN 202011139200A CN 112366726 B CN112366726 B CN 112366726B
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frequency modulation
coefficient
determining
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optimization
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CN112366726A (en
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盛举
孙建军
贾庆岩
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Wuhan University WHU
Electric Power Research Institute of State Grid Hubei Electric Power Co Ltd
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Wuhan University WHU
Electric Power Research Institute of State Grid Hubei Electric Power Co Ltd
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    • 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
    • H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
    • H02J3/241—The oscillation concerning frequency
    • 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
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • 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
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/48—Controlling the sharing of the in-phase component
    • 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
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • 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]

Abstract

The invention discloses a method, equipment, a storage medium and a device for optimizing primary frequency modulation coefficients of a thermal power generating unit. The method comprises the steps of establishing a power system frequency modulation model, determining a unit slip ratio range according to the power system frequency modulation model, determining an open-loop transfer function according to the power system frequency modulation model, and determining a speed regulator dead zone range based on the open-loop transfer function. Determining a comprehensive fitness function according to a preset coefficient optimization model, a dead zone range of a speed regulator, a unit slip ratio range and a preset coefficient optimization model; and optimizing by a particle swarm optimization algorithm to obtain a final particle position corresponding to the comprehensive fitness function, and then obtaining the optimal frequency modulation coefficient based on the final particle position. According to the technical scheme, the dead zone range of the speed regulator and the slip ratio range of the unit are determined, on the basis, a comprehensive fitness function is calculated by using a preset coefficient optimization model, and finally, the optimal frequency modulation coefficient is obtained through optimization. According to the scheme, the frequency modulation coefficient is optimized, so that the stability of power grid frequency modulation and the economy and flexibility of the unit are improved.

Description

Primary frequency modulation coefficient optimization method for thermal power generating unit and related equipment
Technical Field
The invention relates to the field of internet, in particular to a method for optimizing primary frequency modulation coefficients of a thermal power generating unit and related equipment.
Background
The primary frequency modulation refers to an automatic control process that when the frequency of the power grid deviates from a standard value (50Hz), each unit responsible for frequency modulation automatically controls the output of active power, limits and stabilizes the frequency change of the power grid. The whole power grid is a huge inertia system, according to a rotor motion equation, when the power grid is in active power shortage, a rotor of a grid-connected generator is accelerated, the frequency of the power grid is increased, and otherwise, the frequency of the power grid is reduced. The reasonable optimization setting of the primary frequency modulation control parameters directly determines the effectiveness of the primary frequency modulation control performance and the improvement of the adjustment capability level. As one of the most important primary frequency modulation control parameters, the selection of the unequal rotating speed rate of the speed regulator and the setting size of the frequency modulation dead zone directly relate to the response speed and the output condition of primary frequency modulation.
With the increasing of the output of the new energy in the network, the conventional units are replaced by a large amount, and the frequency modulation capability of the power grid is reduced. Under the interconnection of energy sources, the generated output of new energy sources such as wind power and photovoltaic has strong randomness and volatility, the new energy sources are connected into a network to operate, the complexity of a load fluctuation rule is increased, in a traditional primary frequency modulation experiment, only simple step load disturbance or frequency disturbance is given, and the fluctuation rule of the output of the new energy sources is not considered. At present, the traditional unified simplified setting of +/-0.033 Hz (+/-2 r/min) basically adopted by the setting of the frequency modulation dead zone. In a multi-energy mutual-storage power grid, abnormal fluctuation of power grid frequency is caused by the output characteristics of distributed energy and the complexity of load fluctuation, a frequency modulation unit has frequent primary frequency modulation control action, and the stability of power grid frequency modulation is poor.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a method, equipment, a storage medium and a device for optimizing primary frequency modulation coefficients of a thermal power generating unit, and aims to solve the technical problem of poor stability of power grid frequency modulation in the prior art.
In order to achieve the purpose, the invention provides a method for optimizing primary frequency modulation coefficients of a thermal power generating unit, which comprises the following steps:
establishing a power system frequency modulation model;
determining a unit slip ratio range according to the power system frequency modulation model;
determining an open-loop transfer function according to the power system frequency modulation model, and determining a dead zone range of the speed regulator based on the open-loop transfer function;
determining a comprehensive fitness function according to a preset coefficient optimization model, a dead zone range of a speed regulator, a unit slip ratio range and a preset coefficient optimization model;
and finally optimizing to obtain the optimal frequency modulation coefficient according to the comprehensive fitness function and the particle swarm optimization algorithm.
Preferably, the determining an open-loop transfer function according to the power system frequency modulation model, and determining a speed governor dead zone range based on the open-loop transfer function, include:
determining an open-loop transfer function according to the power system frequency modulation model;
acquiring a dead zone description function of the speed regulator, and generating a Nyquist diagram of a corresponding negative inversion characteristic;
and determining a dead zone range of the speed regulator according to the open-loop transfer function and the Nyquist diagram.
Preferably, the determining the unit slip range according to the power system frequency modulation model includes:
obtaining target parameters based on the power system frequency modulation model, wherein the target parameters comprise a speed regulator time constant, a prime mover time constant and an engine-power grid equivalent inertia coefficient;
and determining the range of the slip ratio of the unit according to the target parameters and a preset stability rule.
Preferably, the preset stability rule is:
Figure GDA0003533758020000021
wherein, TsIs the governor time constant, T0As time constant of the prime mover, MsThe equivalent inertia coefficient of the engine and the power grid is shown, and R is the slip ratio of the unit.
Preferably, the comprehensive fitness function is determined according to a preset coefficient optimization model, a speed regulator dead zone range, a unit slip ratio range and a preset coefficient optimization model, and the comprehensive fitness function comprises the following steps of;
determining a comprehensive optimization objective function according to a network side frequency optimization objective function, a power generation side frequency optimization objective function and a unit slip ratio range in a dead zone range of a speed regulator;
and calculating according to the comprehensive optimization objective function to obtain a comprehensive fitness function.
Preferably, the step of finally optimizing to obtain the optimal frequency modulation coefficient according to the comprehensive fitness function and the particle swarm optimization algorithm comprises the following steps:
carrying out iterative solution on the comprehensive fitness function, and calculating to obtain the particle position under the preset constraint condition;
and obtaining the optimal frequency modulation coefficient according to the optimized particle position.
Preferably, the network side frequency optimization objective function is:
Figure GDA0003533758020000031
wherein S isPFRCAs an index for evaluating the static primary frequency modulation capability, DPFRCIs an evaluation index of the dynamic primary frequency modulation capability; sigmaiIs the standard deviation of the tie line power fluctuation. Omega1、ω2、ω3Is a weight coefficient;
the power generation side frequency optimization objective function is as follows:
Figure GDA0003533758020000032
wherein C is the coal consumption level in the primary frequency modulation process; g is the pollutant emission level in the primary frequency modulation process; tau is the ratio of the frequency modulation time of the unit in a period of time and is used for measuring the loss degree of the unit. Omega4、ω5、ω6Are weight coefficients.
To achieve the above object, the present invention also provides an apparatus, comprising: the method comprises the steps of obtaining a primary frequency modulation coefficient optimization program of the thermal power generating unit, and performing the primary frequency modulation coefficient optimization program on the thermal power generating unit.
In order to achieve the above object, the present invention further provides a storage medium, where a thermal power unit primary frequency modulation coefficient optimization program is stored on the storage medium, and when being executed by a processor, the thermal power unit primary frequency modulation coefficient optimization program implements the steps of the thermal power unit primary frequency modulation coefficient optimization method described above.
In order to achieve the above object, the present invention further provides a primary frequency modulation coefficient optimization device for a thermal power generating unit, where the primary frequency modulation coefficient optimization device for the thermal power generating unit includes:
the establishing module is used for establishing a power system frequency modulation model;
the slip calculation module is used for determining the slip range of the unit according to the power system frequency modulation model;
the dead zone calculation module is used for determining an open-loop transfer function according to the power system frequency modulation model and determining a dead zone range of the speed regulator based on the open-loop transfer function;
the comprehensive fitness function calculating module is used for determining a comprehensive fitness function according to a preset coefficient optimization model, a dead zone range of the speed regulator, a unit slip ratio range and a preset coefficient optimization model;
and the frequency modulation coefficient determining module is used for finally optimizing to obtain the optimal frequency modulation coefficient according to the comprehensive fitness function and the particle swarm optimization algorithm.
According to the method, a power system frequency modulation model is established, a unit slip ratio range is determined according to the power system frequency modulation model, an open-loop transfer function is determined according to the power system frequency modulation model, and a speed regulator dead zone range is determined based on the open-loop transfer function. Determining a comprehensive fitness function according to a preset coefficient optimization model, a dead zone range of a speed regulator, a unit slip ratio range and a preset coefficient optimization model; and calculating the particle position corresponding to the comprehensive fitness function, and calculating to obtain the frequency modulation coefficient based on the particle position. According to the technical scheme, the dead zone range of the speed regulator and the slip ratio range of the unit are determined, on the basis, a comprehensive fitness function is calculated by using a preset coefficient optimization model, and finally, the optimal frequency modulation coefficient is obtained through optimization. According to the scheme, the frequency modulation coefficient is optimized, so that the stability of power grid frequency modulation is improved.
Drawings
Fig. 1 is a schematic flow chart of a first embodiment of a method for optimizing primary frequency modulation coefficients of a thermal power generating unit according to the present invention;
FIG. 2 is a schematic view of a detailed flow chart of S300 in FIG. 1;
fig. 3 is a functional block diagram of a first embodiment of the primary frequency modulation coefficient optimization device of a thermal power generating unit according to the present invention;
FIG. 4 is a schematic view of a reheat condensing steam turbine set model according to the present invention;
FIG. 5 is a schematic view of a model of a turbine governor system of the present invention;
FIG. 6 is a schematic diagram of a generator-grid model of the present invention;
FIG. 7 is a schematic view of a load disturbance model according to the present invention;
FIG. 8 is a schematic diagram of a frequency modulation model of the power system of the present invention;
FIG. 9 is a Nyquist plot of the open-loop frequency characteristic and the dead-zone negative inversion characteristic of the present invention;
FIG. 10 is a statistical graph of load fluctuations for three exemplary scenarios of the present invention;
FIG. 11 is a statistical chart of fan and photovoltaic output fluctuations in accordance with the present invention;
FIG. 12 is a hierarchical structure diagram of the integrated optimization model of the present invention;
FIG. 13 is a statistical graph of load fluctuations for three exemplary scenarios of the present invention;
FIG. 14 is a statistical chart of fan and photovoltaic output fluctuations in accordance with the present invention;
FIG. 15 is a hierarchical diagram of the integrated optimization model of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, the invention provides a frequency modulation coefficient optimization method. The method for optimizing the primary frequency modulation coefficient of the thermal power generating unit comprises the following steps:
step S100: and establishing a power system frequency modulation model. In this embodiment, the power system frequency modulation model includes a turbine unit model, a speed governor model, a synchronous generator-grid model, and a load disturbance model.
Referring to fig. 4, in this embodiment, the steam turbine set model adopts a reheat condensing steam turbine set model, and key parameters of the reheat condensing steam turbine set model include a high-pressure steam chamber steam volume time constant TCHTime constant T of reheat steam volumeRHHigh pressure cylinder power coefficient FHPPower coefficient of low pressure cylinder FLPThe parameters are obtained by historical data parameter identification. The valve characteristic curve is obtained by simulating historical record data of the valve opening.
Referring to fig. 5, in this embodiment, the speed regulator model adopts a typical turbine governing system model, and the turbine governing system model key parameters include a speed regulator dead zone, a slip ratio R, and a feedback time constant Ts0And Ts1。
Referring to FIG. 6, in the generator-grid model, MsIs generator-grid equivalent inertia coefficient, DsIs the system damping coefficient.
Referring to fig. 7, the load fluctuation is composed of a random load having a large fluctuation and a long fluctuation period and a random load having a small fluctuation and a small fluctuation period.
Referring to fig. 8, a quadratic frequency modulation coefficient is selected, and each parameter in fig. 8 has a meaning represented by: crosstie exchange coefficient T12、T13，KIIntegral gain KICoefficient of proportionality KPTime constant T of unit feedbacks0、Ts1Slip ratio R of unit1、R2Valve characteristic curve model, high pressure steam chamber steam volume time constant TCHTime constant T of reheat steam volumeRHHigh pressure cylinder power coefficient FHPPower coefficient of low pressure cylinder FLPGenerator-grid equivalent inertia coefficient MsCoefficient of system damping DsPrimary frequency modulation response delay coefficient epsilon1、ε2Coefficient of secondary frequency modulation beta1Degree of participation α1、α2Second order PI coefficient KP1、KI1。
Step S200: and determining the range of the slip ratio of the unit according to the frequency modulation model of the power system.
It should be noted that step S200 specifically includes:
obtaining target parameters based on the power system frequency modulation model, wherein the target parameters comprise a speed regulator time constant, a prime mover time constant and an engine-power grid equivalent inertia coefficient;
and determining the range of the slip ratio of the unit according to the target parameters and a preset stability rule.
The control link of the power system frequency modulation model is further simplified, key parameters such as a speed regulator time constant and a prime motor time constant are obtained, stability analysis is carried out on a primary frequency modulation control system of the unit according to the stability principle, and the preset stability rule for analyzing the stability of the unit is as follows:
Figure GDA0003533758020000061
wherein, TsIs the governor time constant, T0As time constant of the prime mover, MsThe equivalent inertia coefficient of the engine and the power grid is shown, and R is the slip ratio of the unit.
Therefore, the minimum value of the slip ratio of the unit which obtains the stable operation of the frequency modulation control system is as follows:
Figure GDA0003533758020000062
the range of the slip ratio of the unit is as follows: r is more than or equal to 0.04 and less than or equal to 0.06.
Step S300: and determining an open-loop transfer function according to the power system frequency modulation model, and determining a dead zone range of the speed regulator based on the open-loop transfer function.
Referring to fig. 2, specifically, step S300 includes the following:
step S310: determining an open-loop transfer function according to the power system frequency modulation model;
step S320: acquiring a dead zone description function of the speed regulator, and generating a Nyquist diagram of a corresponding negative inversion characteristic;
step S330: and determining a dead zone range of the speed regulator according to the open-loop transfer function and the Nyquist diagram.
Because a system formed by the generator, the turboset and the speed regulator often comprises an inertia link, the system has better low-pass filtering performance and meets the condition of analyzing by adopting a description function method. Wherein, the open loop transfer function formed by the three parts is:
G0(s)＝GGov(s)·GPr(s)·GGen(s)
the dead zone links are represented by description functions:
Figure GDA0003533758020000071
referring to fig. 9, a nyquist plot of the open-loop transfer function frequency characteristic corresponding to the single-machine primary frequency modulation system of the generator set and the negative-inversion characteristic of the dead zone link is drawn by using typical data.
G0(j ω) does not surround-1/N (A), then the entire nonlinear system is stable. The dead zone range is subject to general regulations. Here, it is assumed that: db is more than or equal to 1r/min and less than or equal to 4 r/min.
And further, preparing for subsequent frequency modulation coefficient optimization calculation, selecting active load data, wind power and photovoltaic output data measured in a certain area, and obtaining a step disturbance condition meeting the reality through statistical fluctuation characteristics.
After the load data are normalized, the load data are clustered into three types, namely three typical scenes, by using a K-means clustering method according to the overall characteristics of daily load.
For these three types of scenes, as shown in table 1, the load fluctuation conditions are studied with reference to fig. 10, 11, and 12. And respectively obtaining the probability combination conditions of the primary frequency modulation load step disturbance corresponding to the three typical scenes.
TABLE 1 load Curve scene Classification
Figure GDA0003533758020000072
The probability combination conditions of the primary frequency modulation load step disturbance corresponding to the three typical scenes are respectively obtained from the statistical fitting results, as shown in table 2.
TABLE 2 probability combinations of load step perturbations
Figure GDA0003533758020000073
The load step disturbance with the positive value is similar to the load step disturbance with the negative value, and corresponds to the load disturbance probability with the positive value one by one.
The new energy output fluctuation characteristic: fitting the output fluctuation of the new energy power generation by a non-parametric statistics (non-parametric statistics) method, and referring to fig. 13 and 14; taking 0.01p.u. as an interval, counting the fitting result to obtain the probability combination condition of the new energy output step disturbance, as shown in tables 3 and 4.
TABLE 3 probability combinations of fan output step disturbances
Figure GDA0003533758020000081
TABLE 4 probability combination of photovoltaic power generation output step disturbance
Figure GDA0003533758020000082
Step S400: and determining a comprehensive fitness function according to a preset coefficient optimization model, a speed regulator dead zone range, the unit slip ratio range and the preset coefficient optimization model. It should be noted that, in this embodiment, the preset coefficient optimization model includes a grid-side frequency optimization objective function and a power generation-side frequency optimization objective function.
Step S400 specifically includes;
determining a comprehensive optimization objective function according to a network side frequency optimization objective function, a power generation side frequency optimization objective function, a speed regulator dead zone range and the unit slip range;
and calculating according to the comprehensive optimization objective function to obtain a comprehensive fitness function.
Step S500: and finally optimizing to obtain the optimal frequency modulation coefficient according to the comprehensive fitness function and the particle swarm optimization algorithm.
Specifically, the step of finally optimizing to obtain an optimal frequency modulation coefficient according to the comprehensive fitness function and the particle swarm optimization algorithm includes:
carrying out iterative solution on the comprehensive fitness function, and calculating to obtain a final particle position under a preset constraint condition;
and obtaining the optimal frequency modulation coefficient according to the final particle position obtained by optimization.
It should be noted that, in this embodiment, the network side frequency optimization objective function F1The following were used:
Figure GDA0003533758020000083
in the formula, SPFRCIs a static primary frequency modulation capability evaluation index, DPFRCIs an evaluation index of dynamic primary frequency modulation capability, sigmaiAs standard deviation of the tie line power fluctuation, omega1、ω2、ω3Are weight coefficients.
Wherein, the static primary frequency modulation capability evaluation index SPFRCThe expression is as follows:
SPFRC＝k1Δfmax+k2fk+k3Ts
in the formula,. DELTA.fmaxIs the maximum deviation value of the power system frequency, fkIs the rate of change of frequency, TsFor the time at which the frequency returns to a steady state value, k1、k2、k3The weight value can be assigned according to experience.
In this embodiment, the power generation-side frequency optimization objective function F2The following were used:
Figure GDA0003533758020000091
in the formula, C is the coal consumption level of the fire-electric generating set in the primary frequency modulation process, and G is the pollutant emission level in the primary frequency modulation process. Tau is the ratio of the frequency modulation time of the unit in a period of time and is used for measuring the loss degree of the unit. Omega4、ω5、ω6Are weight coefficients.
Wherein the coal consumption level C is a function of:
c(P)＝αP2+βP+χ
Figure GDA0003533758020000092
in the formula, alpha, beta and chi are coal consumption characteristic coefficients of the unit; p is real-time power (kW) of the unit, c (P) is real-time coal consumption value (T/h) of the unit, and T is primary frequency modulation time.
The function of the pollutant emission level G is:
w(P)＝aP3+bP2+cP+d
Figure GDA0003533758020000093
in the formula, a, b, c and d are the pollutant emission characteristic coefficients of the unit; w (P)i) The real-time pollutant emission amount (mg/h) of the unit, and P is the real-time power (kW) of the unit.
From the above, the comprehensive optimization objective function F is
F＝γ1F1′+γ2F2′
In the formula, F1' optimization of the objective function F for the network side frequency1Result after normalization, F2' optimization of the objective function F for the Power Generation side frequency2Go on to unityThe results after the conversion; gamma ray1、γ2The corresponding weight value is mainly determined by the importance degree of two targets on the grid side and the power generation side.
Further, determining a weight coefficient of a comprehensive optimization objective function, wherein a hierarchical structure diagram of a comprehensive optimization model is shown in fig. 15, and the comprehensive optimization model comprises an optimization parameter layer, an index layer, a secondary objective layer and an objective layer. The dotted arrow indicates that as the parameter increases, the index value decreases; the solid arrows indicate that the index value increases as the parameter decreases. The comprehensive optimization objective function F is subjected to AHP (Analytic Hierarchy Process) to obtain a weight vector ω'.
The comprehensive optimization objective function F can be expressed as:
Figure GDA0003533758020000101
ω′＝[ω′1,ω′2,ω′3,ω′4,ω′5,ω′6]
where ω' is a weight vector.
Further, a comprehensive optimization objective function can be obtained:
Kσ＝μΔP＝-0.01FΔP＝-0.01+μΔP＝-0.02FΔP＝-0.02 +...+μΔP＝-0.05FΔP＝-0.05+μΔP＝0.01FΔP＝0.01 +μΔP＝0.02FΔP＝0.02+...+μΔP＝0.05FΔP＝0.05
wherein FΔP＝-0.01Comprehensively optimizing an objective function when the load disturbance is delta P-0.01; mu.sΔP＝-0.01The probability coefficient at which the load disturbance Δ P is-0.01 is given. Thus, the comprehensive optimization objective function K is obtainedσ。
By synthetically optimising an objective function KσA fitness function may be obtained:
Figure GDA0003533758020000102
wherein theta is a penalty factor, here taking positive infinity; xinIs the probability of occurrence of the nth scene, Kn,σFor the comprehensive optimization of the objective function, K, for the nth scene∑Optimizing the objective function for the final synthesis, for K∑And performing a particle swarm optimization algorithm, wherein the finally obtained particle position corresponding to the optimal objective function is the optimized optimal frequency modulation coefficient.
According to the method, a power system frequency modulation model is established, a unit slip ratio range is determined according to the power system frequency modulation model, an open-loop transfer function is determined according to the power system frequency modulation model, and a speed regulator dead zone range is determined based on the open-loop transfer function. Determining a comprehensive fitness function according to a preset coefficient optimization model, a dead zone range of a speed regulator, a unit slip ratio range and a preset coefficient optimization model; and calculating the particle position corresponding to the comprehensive fitness function, and calculating based on the particle position to obtain the frequency modulation coefficient. According to the technical scheme, the dead zone range of the speed regulator and the slip ratio range of the unit are determined, on the basis, a comprehensive fitness function is calculated by using a preset coefficient optimization model, and finally, the optimal frequency modulation coefficient is obtained through optimization. According to the scheme, the frequency modulation coefficient is optimized, so that the stability of power grid frequency modulation is improved.
In order to verify the feasibility of the parameter optimization strategy and the effectiveness of the parameter optimization selection method, a three-region system is taken as an example for simulation research. The specific regional unit type composition mode is as follows: the area 1 is provided with 2 reheating turbines G1 and G2 with different capacities, and the installed capacities are 300MWA and 100MVA respectively; the area 2 has 2 condensing turbines G3 and G4 with different capacities, and the installed capacities are 600MWA and 300MVA respectively. And the region 3 is provided with 1 photovoltaic set group and 1 wind power set group, wherein the output of the new energy set group accounts for 15%.
The index optimization results are shown in table 1, and several indexes are optimized to different degrees.
Table 1 index optimization results
Figure GDA0003533758020000111
The results of the parameter optimization are shown in Table 2.
TABLE 2 index optimization results
Figure GDA0003533758020000112
When the optimization of the targets of the power generation side and the network side is comprehensively considered, the targets of the power generation side and the network side are optimized to a certain extent. In region 1, the dead zone optimization value of G1 with greater installed capacity is smaller than that of G2 with smaller installed capacity, as are G3 and G4 in region 2. In addition, the slip optimization results of G1-G4 are all reduced compared with 0.05 before optimization, the installed capacity is larger in area 1, G1 with a smaller dead zone set value is smaller than the installed capacity, and the slip optimization value of the former is smaller than that of G2 with a larger dead zone set value, and the G3 and G4 in area 2 are also the same, because the dead zone exists, the primary frequency modulation performance of the system is reduced, the equivalent slip of the unit is increased, and the phenomenon can be improved to a certain extent through the optimization of the slip, so that the negative effect of the dead zone on the primary frequency modulation of the system is offset.
With the increasing of the output of the new energy in the network, the conventional units are replaced by a large amount, and the frequency modulation capability of the power grid is reduced. In a multi-energy mutual-storage power grid, abnormal fluctuation of power grid frequency is caused by the output characteristics of distributed energy and the complexity of load fluctuation, and the primary frequency modulation control action of a frequency modulation unit is frequent, so that the stability of two sides of the power grid is influenced. The reasonable setting of the primary frequency modulation parameters can effectively improve the frequency safety and stability of the power system and simultaneously can also consider the economic and environmental protection performance of the unit. The method has the advantages that the method has double targets of frequency stability of the network side and economy of the power generation side, is different from the conventional method that only single simple load step disturbance is considered, and comprehensively evaluates the primary frequency modulation process under various disturbance conditions based on probability distribution by analyzing the load fluctuation condition; a simulation model of the primary frequency modulation of the power grid is established, the primary frequency modulation parameters of the unit are optimized through a particle swarm algorithm, the optimization of the parameters not only improves the stability, economy and flexibility of the unit, but also improves the frequency stability of the power grid side, and the consumption of new energy is promoted to a certain extent. The parameter is used as an optimization standard for gradient setting of the parameters of the thermal power plant units, and the method has high reference value.
To achieve the above object, the present invention also provides an apparatus, comprising: the method comprises the steps of obtaining a primary frequency modulation coefficient optimization program of the thermal power generating unit, and performing the primary frequency modulation coefficient optimization program on the thermal power generating unit.
In order to achieve the above object, the present invention further provides a storage medium, where a thermal power unit primary frequency modulation coefficient optimization program is stored on the storage medium, and when being executed by a processor, the thermal power unit primary frequency modulation coefficient optimization program implements the steps of the thermal power unit primary frequency modulation coefficient optimization method described above.
Referring to fig. 3, in order to achieve the above object, the present invention further provides a primary frequency modulation coefficient optimization apparatus for a thermal power generating unit, where the primary frequency modulation coefficient optimization apparatus for a thermal power generating unit includes:
the establishing module 10 is used for establishing a power system frequency modulation model;
the slip calculation module 20 is used for determining a unit slip range according to the power system frequency modulation model;
the dead zone calculation module 30 is used for determining an open-loop transfer function according to the power system frequency modulation model and determining a dead zone range of the speed regulator based on the open-loop transfer function;
the comprehensive fitness function calculating module 40 is used for determining a comprehensive fitness function according to a preset coefficient optimization model, a speed regulator dead zone range, the unit slip ratio range and the preset coefficient optimization model;
and the frequency modulation coefficient determining module 50 is used for finally optimizing to obtain the optimal frequency modulation coefficient according to the comprehensive fitness function and the particle swarm optimization algorithm.
It should be noted that the primary frequency modulation coefficient optimization device of the thermal power generating unit is a device item corresponding to the primary frequency modulation coefficient optimization method of the thermal power generating unit, and a specific implementation manner of the primary frequency modulation coefficient optimization method of the thermal power generating unit refers to a specific implementation manner of the primary frequency modulation coefficient optimization method of the thermal power generating unit, and is not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are only for description, and do not represent the advantages and disadvantages of the embodiments. The usage of the words first, second and third, etcetera do not indicate any ordering and these words may be interpreted as names.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention or portions thereof contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (7)

1. A method for optimizing primary frequency modulation coefficients of a thermal power generating unit is characterized by comprising the following steps:
establishing a power system frequency modulation model;
determining a unit slip ratio range according to the power system frequency modulation model;
determining an open-loop transfer function according to the power system frequency modulation model, and determining a dead zone range of the speed regulator based on the open-loop transfer function;
determining a comprehensive fitness function according to a preset coefficient optimization model, a dead zone range of a speed regulator, a unit slip ratio range and a preset coefficient optimization model;
finally, optimizing to obtain an optimal frequency modulation coefficient according to the comprehensive fitness function and the particle swarm optimization algorithm;
the determining of the unit slip ratio range according to the power system frequency modulation model comprises the following steps:
obtaining target parameters based on the power system frequency modulation model, wherein the target parameters comprise a speed regulator time constant, a prime mover time constant and an engine-power grid equivalent inertia coefficient;
determining a unit slip ratio range according to the target parameters and a preset stability rule;
the preset stability rule is as follows:
Figure FDA0003547072080000011
wherein, TsTime constant of speed governor, T0As time constant of the prime mover, MsThe equivalent inertia coefficient of an engine and a power grid is shown, and R is the slip ratio of the unit;
the method for determining the comprehensive fitness function according to the preset coefficient optimization model, the dead zone range of the speed regulator, the unit slip ratio range and the preset coefficient optimization model comprises the following steps:
determining a comprehensive optimization objective function according to a network side frequency optimization objective function, a power generation side frequency optimization objective function, a speed regulator dead zone range and the unit slip range;
and calculating according to the comprehensive optimization objective function to obtain a comprehensive fitness function.
2. The thermal power generating unit primary frequency modulation coefficient optimization method as claimed in claim 1, wherein the determining an open-loop transfer function according to the power system frequency modulation model, and determining a governor dead zone range based on the open-loop transfer function, comprises:
determining an open-loop transfer function according to the power system frequency modulation model;
acquiring a dead zone description function of the speed regulator, and generating a Nyquist diagram of a corresponding negative inversion characteristic;
and determining a dead zone range of the speed regulator according to the open-loop transfer function and the Nyquist diagram.
3. The method for optimizing the primary frequency modulation coefficient of the thermal power generating unit according to claim 1, wherein the step of finally optimizing to obtain the optimal frequency modulation coefficient according to the comprehensive fitness function and the particle swarm optimization algorithm comprises the steps of:
carrying out iterative solution on the comprehensive fitness function, and calculating to obtain the particle position under the preset constraint condition;
and obtaining the optimal frequency modulation coefficient according to the optimized particle position.
4. The method for optimizing the primary frequency modulation coefficient of the thermal power generating unit according to claim 1, wherein the grid-side frequency optimization objective function is:
Figure FDA0003547072080000021
wherein S isPFRCIs a static primary frequency modulation capability evaluation index, DPFRCThe dynamic primary frequency modulation capability evaluation index is obtained; sigmaiThe standard deviation of the tie line power fluctuation is taken as the standard deviation; omega1、ω2、ω3Is a weight coefficient;
the power generation side frequency optimization objective function is as follows:
Figure FDA0003547072080000022
wherein C is the coal consumption level in the primary frequency modulation process; g is the pollutant emission level in the primary frequency modulation process; tau is the ratio of the frequency modulation time of the unit in a period of time and is used for measuring the loss degree of the unit, omega4、ω5、ω6Are weight coefficients.
5. An apparatus, characterized in that the apparatus comprises: the method comprises the steps of a thermal power generating unit primary frequency modulation coefficient optimization method according to any one of claims 1 to 4.
6. A storage medium, wherein the storage medium stores a thermal power unit primary frequency modulation coefficient optimization program, and the thermal power unit primary frequency modulation coefficient optimization program, when executed by a processor, implements the steps of the thermal power unit primary frequency modulation coefficient optimization method according to any one of claims 1 to 4.
7. The utility model provides a thermal power unit primary frequency modulation coefficient optimizing apparatus which characterized in that, thermal power unit primary frequency modulation coefficient optimizing apparatus includes:
the establishing module is used for establishing a power system frequency modulation model;
the slip calculation module is used for determining the slip range of the unit according to the power system frequency modulation model;
the dead zone calculation module is used for determining an open-loop transfer function according to the power system frequency modulation model and determining a dead zone range of the speed regulator based on the open-loop transfer function;
the comprehensive fitness function calculating module is used for determining a comprehensive fitness function according to a preset coefficient optimization model, a speed regulator dead zone range, the unit slip ratio range and the preset coefficient optimization model;
the frequency modulation coefficient determining module is used for finally optimizing to obtain the optimal frequency modulation coefficient according to the comprehensive fitness function and the particle swarm optimization algorithm;
the slip calculation module is further configured to:
obtaining target parameters based on the power system frequency modulation model, wherein the target parameters comprise a speed regulator time constant, a prime mover time constant and an engine-power grid equivalent inertia coefficient;
determining a unit slip ratio range according to the target parameters and a preset stability rule;
the preset stability rule is as follows:
Figure FDA0003547072080000031
wherein, TsIs the governor time constant, T0As time constant of the prime mover, MsThe equivalent inertia coefficient of an engine and a power grid is shown, and R is the slip ratio of the unit;
the method for determining the comprehensive fitness function according to the preset coefficient optimization model, the speed regulator dead zone range, the unit slip ratio range and the preset coefficient optimization model comprises the following steps:
determining a comprehensive optimization objective function according to a network side frequency optimization objective function, a power generation side frequency optimization objective function, a speed regulator dead zone range and the unit slip range;
and calculating according to the comprehensive optimization objective function to obtain a comprehensive fitness function.
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