CN113094898B - Power distribution network reliability analysis method based on time domain simulation under regional autonomy - Google Patents

Power distribution network reliability analysis method based on time domain simulation under regional autonomy Download PDF

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CN113094898B
CN113094898B CN202110372578.XA CN202110372578A CN113094898B CN 113094898 B CN113094898 B CN 113094898B CN 202110372578 A CN202110372578 A CN 202110372578A CN 113094898 B CN113094898 B CN 113094898B
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CN113094898A (en
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杨梓俊
荆江平
陈康
周挺
胡伟
吴奕
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State Grid Jiangsu Electric Power Co Ltd
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • 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
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    • G06F2113/00—Details relating to the application field
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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
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Abstract

The invention discloses a power distribution network reliability analysis method based on time domain simulation under regional autonomy, which comprises the following steps: establishing a mathematical model of a typical distributed power supply of a photovoltaic array, a wind driven generator, an energy storage system and a micro gas turbine; respectively building a simulation model of each distributed power supply based on a mathematical model of a typical distributed power supply; carrying out simulation analysis on each simulation model respectively to obtain output characteristic curves of various distributed power supplies; inputting parameters such as load and line impedance based on a distributed power supply simulation model, and building a power distribution network simulation model connected with a main network to enable the power distribution network to work in a grid-connected mode; setting the on-off time of a circuit breaker on a main network connection line, and simulating an area autonomous operation mode of the power distribution network; and judging the reliability of the power distribution network according to indexes such as output power and voltage of each power supply, the rotating speed of the motor, frequency and the like. The reliability of the power distribution network operating in the regional autonomous mode after being disconnected with the main network can be intuitively, quickly and effectively analyzed.

Description

Power distribution network reliability analysis method based on time domain simulation under regional autonomy
Technical Field
The invention belongs to the technical field of power distribution network reliability analysis, and particularly relates to a power distribution network reliability analysis method based on time domain simulation under regional autonomy.
Background
In recent years, due to the occurrence of blackout accidents in various countries, controllable factors such as power grid planning operation, operation of dispatchers and the like, and uncontrollable factors such as equipment faults, natural disasters and the like exist, so that the mode of improving the reliability of a power distribution network through the top-down passive defense is obviously insufficient. Therefore, an area autonomous concept is introduced in planning and operating of the power distribution network, and when sudden breakdown failure of the main network occurs, the power distribution network is actively separated from the main network and operates in an area autonomous mode. Therefore, it is important to analyze the reliability of the distribution network during this short time.
The conventional reliability analysis of the power distribution network mainly adopts a characteristic value analysis method, a Lyapunov method, a nonlinear theory analysis method and the like. However, the power distribution network model constructed by the method is high in complexity, poor in applicability, slow in solving speed and not intuitive enough in analysis result, and is not beneficial to analyzing the reliability of the power distribution network in a short time.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a power distribution network reliability analysis method based on time domain simulation under regional autonomy, which can intuitively, quickly and effectively analyze the reliability of a power distribution network running in a regional autonomy mode in a short time after the power distribution network is disconnected from a main network.
The purpose of the invention can be realized by the following technical scheme:
a power distribution network reliability analysis method based on time domain simulation under regional autonomy comprises the following steps:
s1, establishing a mathematical model of a typical distributed power supply of the photovoltaic array, the wind driven generator, the energy storage system and the micro gas turbine;
s2, respectively building a simulation model of each distributed power supply based on the mathematical model of the typical distributed power supply;
s3, performing simulation analysis on each simulation model respectively to obtain output characteristic curves of various distributed power supplies;
s4, inputting parameters such as load and line impedance based on the distributed power supply simulation model, and building a power distribution network simulation model connected with the main network to enable the power distribution network to work in a grid-connected mode;
s5, setting the on-off time of the circuit breaker on the main network connection line, and simulating the regional autonomous operation mode of the power distribution network;
and S6, judging the reliability of the power distribution network according to indexes such as output power and voltage of each power supply, the rotating speed of the motor, the frequency and the like.
Further, the S1 specifically includes the following steps:
s1.1, establishing a photovoltaic array mathematical model;
Figure BDA0003009917480000021
Figure BDA0003009917480000022
P＝U oc I L (3)
s1.2, establishing a mathematical model of the wind driven generator;
Figure BDA0003009917480000023
Figure BDA0003009917480000024
Figure BDA0003009917480000031
Figure BDA0003009917480000032
s1.3, establishing a mathematical model of the energy storage system;
establishing an energy storage system mathematical model consisting of a storage battery, an inverter, a droop control system and the like,
Figure BDA0003009917480000033
Figure BDA0003009917480000034
Figure BDA0003009917480000035
Figure BDA0003009917480000036
Figure BDA0003009917480000037
Figure BDA0003009917480000038
s1.4, establishing a micro gas turbine mathematical model.
Further, in the formulas (1), (2) and (3), I L Is the output current of the battery pack, I ph Is the short-circuit current with a constant light intensity, I D Is the diode saturation current, I sc Is the short-circuit current under standard test conditions, N p Is the number of parallel-connected components, N s Is the number of series-connected components, U oc Is the terminal voltage of the battery pack, R s Is a constant value resistor with a charge constant q of 1.6 x 10 - 19 C, A is diode polarity factor, boltzmann constant K is 1.38 × 10 -23 J/K, T is the absolute temperature of the environment, K t Is the temperature coefficient, and G is the intensity of light.
Further, the formula (4) is a mathematical model of the wind turbine, p f Mechanical power captured by a wind turbine; r is the blade radius of the wind turbine; ρ is the density in air, in (kg/m) 3 ) (ii) a V is the magnitude of the wind speed, in units of (m/s); c p The wind energy utilization coefficient is used for expressing the conversion efficiency of the wind turbine and is a function of the pitch angle beta of the blades and the tip speed ratio lambda; c i Is the use coefficient of various fans.
Further, equation (5) is a stator voltage equation of the synchronous generator, u d Is the d-axis component, u, of the stator voltage q Is the q-axis component, i, of the stator voltage d Is the d-axis component of the stator current, i q Is stator currentq-axis component, L d Is the equivalent d-axis inductance, L, of a synchronous generator q Is the equivalent q-axis inductance of the synchronous generator, R is the stator resistance, equation (6) is the flux linkage equation of the synchronous generator, and equation (7) is the torque equation of the synchronous generator.
Further, formula (8) is a mathematical model of the battery, V b Is the outlet voltage, SOC is the state of charge, R b Is the internal resistance of the battery, V o Is the open circuit voltage of the battery, i b Is the battery charging current, K is the polarization voltage, Q is the battery capacity, and A, B is the characteristic constant of the battery.
Equation (9) is the three-phase fundamental component of the inverter output voltage, V dc Is the inverter dc side voltage; m is the modulation ratio.
Figure BDA0003009917480000041
Wherein V m Is the amplitude, V, of the modulated signal wave b Is the amplitude of the carrier signal; omega m Is the frequency of the modulated wave.
Equations (10) and (11) are mathematical models of the inverter in a synchronous rotating coordinate system, L 1 Is a filter inductor, C 1 Is a filter capacitor; i.e. i 1k Is the inverter output current i 2k Is a filter capacitor C 1 Current of (i) 3k Is the current after passing through the filter; u. of 1k Is the inverter output voltage u 2k Is the output voltage after passing through the filter.
Equation (12) is a calculation equation of the output power of the inverter in the synchronous rotating coordinate system.
Equation (13) is the droop control system control principle, f is the actual frequency of the inverter, V is the actual output voltage of the inverter, f n Is the rated frequency, V, of the microgrid n Is the rated voltage of the microgrid, P is the actual value of the active power of the inverter, Q is the actual value of the reactive power of the inverter, P n Is the nominal reference value of the active power, Q n The reference value is a rated reference value of active power, a is an inverter frequency droop coefficient, and b is an inverter frequency voltage droop coefficient.
Further, the distributed power supply simulation model established in S2 specifically includes the following contents:
(1) the photovoltaic array simulation model consists of a photovoltaic cell panel, a control system adopting a maximum power tracking control mode and an inverter;
(2) the wind driven generator simulation model comprises a wind turbine, a synchronous generator, an AC-DC-AC converter and a speed regulator;
(3) the energy storage system simulation model comprises a storage battery, a droop control system power control loop and a voltage and current control loop;
(4) and a micro gas turbine simulation model.
The invention has the beneficial effects that:
1. according to the method for analyzing the reliability of the power distribution network based on time domain simulation under regional autonomy, simulation models of a photovoltaic array, a wind driven generator, an energy storage system and a micro gas turbine are established on the basis of a distributed power supply mathematical model, simulation analysis is conducted on the output conditions of various distributed power supplies according to the power characteristics of each distributed power supply, and a foundation is established for model building and reliability analysis of the power distribution network;
2. the invention provides a power distribution network reliability analysis method based on time domain simulation under regional autonomy, which adopts a time domain simulation analysis method to analyze the reliability of a power distribution network, forms a full system model by using corresponding modules according to the topological structure of each element model of a power supply, a load, a line and the like in the power distribution network, and then reflects the time-varying conditions of each power supply output power, voltage, full network frequency and the like after the power distribution network is separated from a main network by simulating the time-varying conditions, thereby providing a criterion for reliability analysis.
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In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present invention, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a schematic overall flow diagram of an embodiment of the present invention;
FIG. 2 is a diagram of a photovoltaic array simulation model according to an embodiment of the present invention;
FIG. 3 is a diagram of a simulation model of a wind turbine according to an embodiment of the present invention;
FIG. 4 is a diagram of an energy storage system simulation model according to an embodiment of the invention;
fig. 5 is a simulation model diagram of a droop control system power control loop of an energy storage system in accordance with an embodiment of the present invention;
fig. 6 is a simulation model diagram of a voltage-current control loop of a droop control system of an energy storage system in accordance with an embodiment of the present invention;
FIG. 7 is a diagram of a micro gas turbine simulation model according to an embodiment of the present invention;
fig. 8 is a simulation model diagram of a distribution network according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, a method for analyzing reliability of a power distribution network based on time domain simulation under regional autonomy includes the following steps:
s1, establishing a mathematical model of a typical distributed power supply of the photovoltaic array, the wind driven generator, the energy storage system and the micro gas turbine;
s1.1, establishing a photovoltaic array mathematical model
Figure BDA0003009917480000071
Figure BDA0003009917480000072
P＝U oc I L (3)
In the above formulas (1), (2) and (3), I L Is the output current of the battery pack, I ph Is the short-circuit current with a constant light intensity, I D Is the diode saturation current, I sc Is the short-circuit current under standard test conditions, N p Is the number of parallel-connected components, N s Is the number of series-connected components, U oc Is the terminal voltage of the battery pack, R s Is a constant value resistor with a charge constant q of 1.6 x 10 -19 C, A is diode polarity factor, boltzmann constant K is 1.38 × 10 -23 J/K, T is the absolute temperature of the environment, K t Is the temperature coefficient, and G is the intensity of light.
S1.2, establishing a mathematical model of the wind driven generator
Figure BDA0003009917480000073
Figure BDA0003009917480000074
Figure BDA0003009917480000075
Figure BDA0003009917480000076
The above formula (4) is the wind turbine mathematical model, p f Mechanical power captured by the wind turbine; r is the blade radius of the wind turbine; ρ is the density in air, in (kg/m) 3 ) (ii) a V is the magnitude of the wind speed, in units of (m/s); c p The wind energy utilization coefficient is used for expressing the conversion efficiency of the wind turbine and is a function of the pitch angle beta of the blades and the tip speed ratio lambda; c i Is the use coefficient of various fans.
The above formula (5) is the stator voltage square of the synchronous generatorDistance u d Is the d-axis component, u, of the stator voltage q Is the q-axis component, i, of the stator voltage d Is the d-axis component of the stator current, i q Is the q-axis component of the stator current, L d Is the equivalent d-axis inductance, L, of a synchronous generator q Is the equivalent q-axis inductance of the synchronous generator and R is the stator resistance.
The above equation (6) is a flux linkage equation of the synchronous generator.
The above equation (7) is a torque equation of the synchronous generator.
S1.3, establishing a mathematical model of the energy storage system
Establishing an energy storage system mathematical model consisting of a storage battery, an inverter, a droop control system and the like,
Figure BDA0003009917480000081
Figure BDA0003009917480000082
Figure BDA0003009917480000083
Figure BDA0003009917480000084
Figure BDA0003009917480000085
Figure BDA0003009917480000091
the above formula (8) is a mathematical model of the storage battery, V b Is the outlet voltage, SOC is the state of charge, R b Is the internal resistance of the battery, V o Is the open circuit voltage of the battery, i b Is a storage tankThe battery charging current, K the polarization voltage, Q the battery capacity, and A, B are characteristic constants of the battery.
The above equation (9) is a three-phase fundamental component of the inverter output voltage, V dc Is the inverter dc side voltage; m is a modulation ratio of the light-emitting diode,
Figure BDA0003009917480000092
wherein V m Is the amplitude, V, of the modulated signal wave b Is the amplitude of the carrier signal; omega m Is the frequency of the modulated wave.
The above equations (10) and (11) are mathematical models of the inverter in a synchronous rotation coordinate system, L 1 Is a filter inductor, C 1 Is a filter capacitor; i.e. i 1k (subscript k denotes d-axis and q-axis) is an inverter output current, i 2k Is a filter capacitor C 1 Current of (i) 3k Is the current after passing through the filter; u. of 1k (subscript k denotes d-axis and q-axis) is inverter output voltage, u 2k Is the output voltage after passing through the filter.
The above formula (12) is a calculation formula of the output power of the inverter in the synchronous rotating coordinate system, so as to realize the control and regulation of the output power of the inverter.
The above equation (13) is the droop control system control principle, f is the actual frequency of the inverter, V is the actual output voltage of the inverter, f n Is the rated frequency, V, of the microgrid n Is the rated voltage of the microgrid, P is the actual value of the active power of the inverter, Q is the actual value of the reactive power of the inverter, P n Is the nominal reference value of the active power, Q n The reference value is a rated reference value of active power, a is an inverter frequency droop coefficient, and b is an inverter frequency voltage droop coefficient.
S1.4, establishing a mathematical model of the micro gas turbine
Synchronous generators are used as micro gas turbines, so equations (5), (6) and (7) are also mathematical models of micro gas turbines.
S2, respectively building a simulation model of each distributed power supply based on the mathematical model of the typical distributed power supply;
the established distributed power supply simulation model specifically comprises the following contents:
(1) a photovoltaic array simulation model, as shown in fig. 2, the photovoltaic array simulation model is composed of a photovoltaic cell panel, a control system adopting a maximum power tracking control mode, and an inverter;
(2) a wind power generator simulation model, as shown in fig. 3, the wind power generator simulation model includes a wind turbine, a synchronous generator, an AC-DC-AC converter and a speed regulator;
(3) the energy storage system simulation model comprises a storage battery, a droop control system power control loop and a voltage and current control loop, which are respectively shown in fig. 4, fig. 5 and fig. 6;
(4) a micro gas turbine simulation model, as shown in fig. 7.
S3, performing simulation analysis on each simulation model respectively to obtain output characteristic curves of various distributed power supplies;
s4, inputting parameters such as load and line impedance based on the distributed power supply simulation model, and building a power distribution network simulation model connected with the main network to enable the power distribution network to work in a grid-connected mode;
as shown in fig. 8, a simulation model of a power distribution grid containing a photovoltaic array, a wind turbine, an energy storage system, and a micro gas turbine is established.
S5, setting the on-off time of the circuit breaker on the main network connection line, and simulating the regional autonomous operation mode of the power distribution network;
and S6, judging the reliability of the power distribution network according to indexes such as output power and voltage of each power supply, the rotating speed of the motor, the frequency and the like.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing shows and describes the general principles, principal features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed.

Claims (2)

1. A power distribution network reliability analysis method based on time domain simulation under regional autonomy is characterized by comprising the following steps:
s1, establishing a mathematical model of a typical distributed power supply of the photovoltaic array, the wind driven generator, the energy storage system and the micro gas turbine;
s2, respectively building a simulation model of each distributed power supply based on the mathematical model of the typical distributed power supply;
s3, performing simulation analysis on each simulation model respectively to obtain output characteristic curves of various distributed power supplies;
s4, inputting load and line impedance parameters based on the distributed power supply simulation model, and building a power distribution network simulation model connected with a main network to enable the power distribution network to work in a grid-connected mode;
s5, setting the on-off time of the circuit breaker on the main network connection line, and simulating the regional autonomous operation mode of the power distribution network;
s6, judging the reliability of the power distribution network through the output power and voltage of each power supply, the rotating speed of the motor and the frequency index;
the S1 specifically includes the following steps:
s1.1, establishing a photovoltaic array mathematical model;
Figure FDA0003726842070000011
Figure FDA0003726842070000012
P＝U oc I L (3)
s1.2, establishing a mathematical model of the wind driven generator;
Figure FDA0003726842070000021
Figure FDA0003726842070000022
Figure FDA0003726842070000023
T e ＝n p [(L d -L q )i d i q +ψ f i q ] (7)
s1.3, establishing a mathematical model of the energy storage system;
establishing an energy storage system mathematical model consisting of a storage battery, an inverter and a droop control system,
Figure FDA0003726842070000024
Figure FDA0003726842070000025
Figure FDA0003726842070000026
Figure FDA0003726842070000027
Figure FDA0003726842070000031
Figure FDA0003726842070000032
s1.4, establishing a mathematical model of the micro gas turbine;
in the formulae (1), (2) and (3), I L Is the output current of the battery pack, I ph Is the short-circuit current with a constant light intensity, I D Is the diode saturation current, I sc Is the short-circuit current under standard test conditions, N p Is the number of parallel-connected components, N s Is the number of series-connected components, U oc Is the terminal voltage of the battery pack, R s Is a constant value resistor with a charge constant q of 1.6 x 10 -19 C, A is diode polarity factor, boltzmann constant K is 1.38 × 10 -23 J/K, T is the absolute temperature of the environment, K t Is the temperature coefficient, G is the illumination intensity;
equation (4) is a mathematical model of the wind turbine, p f Mechanical power captured by the wind turbine; r is the blade radius of the wind turbine; ρ is the density in air in kg/m 3 (ii) a V is the wind speed, and the unit is m/s; c p The wind energy utilization coefficient is used for expressing the conversion efficiency of the wind turbine and is a function of the pitch angle beta of the blades and the tip speed ratio lambda; c i The use coefficients of various different types of fans;
equation (5) is the stator voltage equation of the synchronous generator, u d Is the d-axis component, u, of the stator voltage q Is the q-axis component, i, of the stator voltage d Is the d-axis component of the stator current, i q Is the q-axis component of the stator current, L d Is the equivalent d-axis inductance, L, of a synchronous generator q Is the equivalent q-axis inductance of the synchronous generator, R is the stator resistance, equation (6) is the flux linkage equation of the synchronous generator, and equation (7) is the torque equation of the synchronous generator;
equation (8) is a mathematical model of the battery, V b Is the outlet voltage, SOC is the state of charge，R b Is the internal resistance of the battery, V o Is the open circuit voltage of the battery, i b Is the battery charging current, K is the polarization voltage, Q is the battery capacity, A, B is the characteristic constant of the battery;
equation (9) is the three-phase fundamental component of the inverter output voltage, V dc Is the inverter dc side voltage; m is a modulation ratio of the light-emitting diode,
Figure FDA0003726842070000041
wherein V m Is the amplitude, V, of the modulated signal wave b Is the amplitude of the carrier signal; omega m Is the frequency of the modulated wave;
equations (10) and (11) are mathematical models of the inverter in a synchronous rotating coordinate system, L 1 Is a filter inductor, C 1 Is a filter capacitor; i.e. i 1k Is the inverter output current i 2k Is a filter capacitor C 1 Current of (i) 3k Is the current after passing through the filter; u. of 1k Is the inverter output voltage u 2k Is the output voltage after passing through the filter;
formula (12) is a calculation formula of the output power of the inverter in the synchronous rotating coordinate system;
equation (13) is the droop control system control principle, f is the actual frequency of the inverter, V is the actual output voltage of the inverter, f n Is the rated frequency, V, of the microgrid n Is the rated voltage of the microgrid, P is the actual value of the active power of the inverter, Q is the actual value of the reactive power of the inverter, P n Is the nominal reference value of the active power, Q n The reference value is a rated reference value of active power, a is an inverter frequency droop coefficient, and b is an inverter frequency voltage droop coefficient.
2. The method according to claim 1, wherein the distributed power supply simulation model established in S2 specifically includes the following contents:
(1) the photovoltaic array simulation model consists of a photovoltaic cell panel, a control system adopting a maximum power tracking control mode and an inverter;
(2) the wind driven generator simulation model comprises a wind turbine, a synchronous generator, an AC-DC-AC converter and a speed regulator;
(3) the energy storage system simulation model comprises a storage battery, a droop control system power control loop and a voltage and current control loop;
(4) and a micro gas turbine simulation model.
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CN103870649A (en) * 2014-03-19 2014-06-18 国家电网公司 Active power distribution network autonomous simulation method based on distributive intelligent computing

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