CN115764979B - Distributed photovoltaic system stability quantitative evaluation method considering communication delay - Google Patents
Distributed photovoltaic system stability quantitative evaluation method considering communication delay Download PDFInfo
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Abstract
The invention relates to the field of distributed photovoltaic power generation frequency modulation, and discloses a distributed photovoltaic system stability quantification evaluation method considering communication delay. Firstly, establishing a frequency response model of an electric power system containing photovoltaic power generation, taking the influence of communication delay into consideration, realizing time-lag linearization based on a Pade approximation method, and constructing a system linear state space model; secondly, analyzing characteristics of the large-scale distributed photovoltaic power generation grid-connected system, and calculating relevant attributes representing system stability in the large-scale distributed photovoltaic power generation grid-connected system to obtain an evaluation index of the stability of the power system; then, respectively obtaining the subjective weight and the objective weight by using an analytic hierarchy process and an entropy weight process, combining the subjective weight and the objective weight into a comprehensive weight to determine an index weight, and calculating to obtain a fuzzy comprehensive judgment matrix; and finally, obtaining the stability evaluation of the large-scale distributed photovoltaic grid-connected system by a fuzzy comprehensive quantitative calculation method. The method can be used for efficiently and accurately quantitatively evaluating the stability of the system, and has higher evaluation scientificity and accuracy.
Description
Technical Field
The invention relates to the field of distributed photovoltaic power generation frequency modulation, in particular to a distributed photovoltaic system stability quantitative evaluation method considering communication delay.
Background
The method continuously cuts down coal power generation while meeting the economic growth and the energy demand increase in China, and greatly develops renewable energy sources such as wind power, solar photovoltaic power generation, hydropower and the like. The photovoltaic power generation is green clean energy, accords with the energy transformation development direction proposed by China, and is hopeful to become the main force for guaranteeing the energy supply safety target of China in the future.
The frequency of the traditional power system is mainly determined by the rotating speed of the rotor of the synchronous machine, when the system is disturbed to enable the frequency to fluctuate, the rotating inertia of the rotor plays a role, active power support is provided for the system, frequency deviation is regulated, and the fluctuation of the power grid frequency is restrained. The photovoltaic power generation system is connected to a power grid through power electronic equipment, has no primary frequency modulation capability, and cannot actively respond to the frequency response of the system. Along with the large-scale access of the distributed photovoltaic power generation, the proportion of the synchronous machine is reduced, the disturbance resistance of the power system is greatly reduced, the frequency stability is poor, and the safety and stability operation of the power grid are threatened. The frequency problem of the photovoltaic power generation system is solved by adopting an additional control strategy to enable the photovoltaic power generation system to participate in system frequency modulation. Meanwhile, in the frequency modulation control of the power system, a large amount of information exchange is needed to be realized by means of a communication network, so that the communication problems such as time delay and the like are unavoidable, and the system frequency stability is also adversely affected.
Disclosure of Invention
In order to solve the problems, the invention constructs a frequency response model of the power system containing photovoltaic power generation aiming at the stability of the large-scale distributed photovoltaic power generation grid-connected system, takes the steady-state error of the system frequency, the sensitivity of a feedback system, the gain margin of a closed-loop system and the phase margin of the closed-loop system as key indexes for evaluating the stability of the model, and quantitatively evaluates the stability of the power grid based on a fuzzy comprehensive evaluation method and the established indexes. The method can be used for efficiently and accurately quantitatively evaluating the system stability, can be used as an objective measurement basis for guiding the practical application of the power system, and has higher evaluation scientificity and accuracy.
A distributed photovoltaic system stability quantitative evaluation method taking communication delay into account, the method comprising the steps of:
s1, establishing a frequency response model of a power system containing photovoltaic power generation, taking the influence of communication delay into consideration, realizing time-lag linearization based on a Pade approximation method, and constructing a system linear state space model;
in order to explore the frequency response characteristic of large-scale distributed photovoltaic power generation, on the basis of a traditional power system load frequency modulation control model, the frequency control of a distributed photovoltaic power generation auxiliary system is considered, and a distributed photovoltaic frequency modulation control strategy with the characteristic outside P-U is combined to construct a power system frequency response (LFC-PV) model containing photovoltaic power generation;
the power balance equation of the traditional LFC power system is as follows:
ΔP T (s)-ΔP L (s)＝2H·s·Δf(s)+D·Δf(s)
wherein DeltaP T (s)-ΔP L (s) is delta power mismatch, ΔP L For system load disturbance, Δf is the system frequency deviation, and H, D is the equivalent inertia time constant and the system damping coefficient, respectively.
Namely:
photovoltaic frequency modulation control strategy based on P-U external characteristics, and transfer functions of the frequency response model corresponding to the distributed photovoltaic are as follows:
where a is the fitting coefficient and k is the control coefficient.
The frequency deviation of the system adding the distributed photovoltaic power generation link to the traditional LFC model can be expressed as:
wherein DeltaP PV For power deviation, Δp of photovoltaic power generation control loop T (s)-ΔP L (s) is increment power mismatch, H, D is equivalent inertia time constant and system damping coefficient respectively;
T g 、T t for the time constant of the power system of the speed regulator and turbine, R is the speed regulating coefficient of the power system, and DeltaP S (s) is the power deviation generated by the main control loop, and Δf is the system frequency deviation;
aiming at the communication delay problem existing in the frequency modulation control process of the system, a Pade approximation method is adopted for time-lag linearization, a linear model of the system is constructed, and linear state space representation of the distributed photovoltaic power generation system is further obtained through deduction.
When the communication delay is T d The model frequency deviation is:
wherein DeltaP PV For power deviation, Δp of photovoltaic power generation control loop T (s)-ΔP L (s) is increment power mismatch, H, D is equivalent inertia time constant, system damping coefficient and T respectively d Is communication delay; fixing deviceThe sense Pade function is:
wherein N is pq And D pq Polynomial of the order p and q respectively
Selecting a fifth-order function to linearize the time lag, wherein the corresponding fifth-order pad approximation function is as follows:
the state space of a single-area power system with PV is realized as follows:
wherein A is a system matrix, B is a control input matrix, Γ is an interference matrix, x-state vectors, u (t) input vectors, w (t) is an interference variable, C is an observation matrix, and y (t) is a system output.
S2, as shown in FIG. 3, analyzing the characteristics of the large-scale distributed photovoltaic power generation grid-connected system, and selecting the steady-state error of the system frequency, the sensitivity of the feedback system, the gain margin of the closed-loop system and the phase margin of the closed-loop system as evaluation indexes; calculating the relevant attribute of the stability of the characterization system in the large-scale distributed photovoltaic power generation grid-connected system to obtain the stability evaluation index of the distributed photovoltaic power generation system;
the system frequency deviation equation is:
wherein,
r is the speed regulation coefficient of the power system, H, D is the equivalent inertia time constant, the system damping coefficient and delta P respectively S (s) is the power deviation, ΔP, generated by the main control loop L G for system load disturbance 0 (s) five-order pad approximation function, ΔP PV Power deviation of a photovoltaic power generation control loop; t (T) g 、 T t Time constant of the power system for the speed governor, turbine; according to the final value theorem, the steady state value of the system frequency deviation is: according to the final value theorem, the steady state value of the system frequency deviation is:
wherein,
r is the speed regulation coefficient of the power system, D is the system damping coefficient, and delta P L ΔP for system load disturbance PV T is the power deviation of a photovoltaic power generation control loop g 、T t Time constant of the power system for the speed governor, turbine;
disturbance of load ΔP L As an input, a system frequency deviation Δf as an output, a closed loop transfer function between the system frequency deviation and the load step change is:
wherein,
the sensitivity function is obtained according to the above equation:
wherein S is R 、S K 、S α Corresponding sensitivity functions of R, K, K and alpha respectively.
And->The open loop transfer functions of the system are respectively:
wherein,
k is gain, R is speed regulation coefficient of the power system, H, D is equivalent inertia time constant and system damping coefficient, alpha is control share, K 1 Fitting coefficient a for photovoltaic control coefficient G 0 (s) a fifth order pad approximation function,and->Respectively open loop transfer functions of the system;
and drawing a Bode diagram based on the open loop transfer function to obtain a gain margin and a phase angle margin.
S3, respectively solving the objective weight and the objective weight by using an analytic hierarchy process and an entropy weight process, combining the objective weight and the objective weight into a comprehensive weight to determine the index weight, and calculating to obtain a fuzzy comprehensive judgment matrix.
(1) Objective weights of the evaluation indexes can be obtained through an entropy weight method.
Firstly, evaluating index data x of stability of a large-scale distributed photovoltaic power generation system ij Processing, calculating to obtain an evaluation index matrix Y, and calculating by adopting a formula 1 when the stability index is larger and better within a certain range; when the stability index is smaller and better within a certain range, calculating by adopting a formula 2;
formula 1:
formula 2:
x ij the measured value, y, of the grid-connected power stability evaluation index of the jth photovoltaic power generation at the ith moment of the system ij The processed standardized data value is obtained; max (x) j )，min(x j ) Respectively obtaining maximum and minimum values of the j-th stability evaluation index;
then obtaining an information entropy E according to the calculation, and further obtaining an objective weight omega;
wherein: y is ij For the processed standardized data value, n is the number of grid-connected stability evaluation indexes of photovoltaic power generation (n is 4), m is the number of evaluation objects, and p ij Is an index value of the index data.
(2) Subjective weight of the evaluation index can be obtained through an analytic hierarchy process.
Scoring each index by a nine-scale method, and constructing a judgment matrix A:
after the column normalization processing is carried out on the judgment matrix A, weighting is carried out by using an arithmetic average method, and a subjective weight vector theta is obtained:
θ＝[θ 1 θ 2 θ 3 θ 4 ]
and S4, obtaining a stability evaluation result of the large-scale distributed photovoltaic grid-connected system through a fuzzy comprehensive quantitative calculation method. And (3) fusing the objective weight and the subjective weight obtained in the step (S3), and effectively resisting weight deviation:
wherein, theta is the subjective weight value, omega is the objective weight value;
dividing the stability of the photovoltaic power generation grid-connected system into 5 different grades, and establishing a fuzzy comment set V: v= { V1 (good stability), V2 (better stability), V3 (general stability), V4 (poor stability), V5 (poor stability) };
constructing Gauss type membership functions, and calculating to obtain a fuzzy comprehensive judgment matrix, wherein the Gauss type membership functions f (y) specifically comprise:
wherein: y is an evaluation index of frequency stability of the large-scale photovoltaic power generation grid-connected system, and sigma and c are parameters;
the index Y in the index matrix Y is evaluated ij Respectively substituting the judgment matrix F into the membership functions to obtain the judgment matrix F as follows:
wherein f Vk (y ij ) (k=1, 2, … 5; j=1, 2, … n) is an index y ij For the judgment grade V k Is a membership degree of (2);
and combining the comprehensive weights to obtain the overall quantitative evaluation of the stability evaluation system of the large-scale photovoltaic power generation grid-connected system:
B j ＝[b i (V 1 ) b i (V 2 ) b i (V 3 ) b i (V 4 ) b i (V 5 )]
wherein: b i (V k )＝∑(λ i ·f V1 (y i1 ))，
b i (V k ) Is a relative comment V representing each stability index k Is a membership of (1).
The invention has the beneficial effects that:
according to the method, according to the characteristic analysis of the distributed photovoltaic grid-connected system, the stability of the large-scale photovoltaic grid-connected system is accurately and quantitatively evaluated, the influence of the large-scale photovoltaic grid-connected system on the stability of the power grid can be intuitively represented, and the method has a certain reference value for improving the stability of the large-scale distributed photovoltaic grid-connected system.
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FIG. 1 is a flow chart of a method for quantitatively evaluating stability of a distributed photovoltaic system, which takes into account communication delay;
FIG. 2 includes a frequency response model of a photovoltaic power generation power system
FIG. 3 is a schematic diagram of a system stability evaluation index.
Detailed Description
The present invention is further illustrated in the following drawings and detailed description, which are to be understood as being merely illustrative of the invention and not limiting the scope of the invention. It should be noted that the words "front", "rear", "left", "right", "upper" and "lower" used in the following description refer to directions in the drawings, and the words "inner" and "outer" refer to directions toward or away from, respectively, the geometric center of a particular component.
As shown in fig. 1, a method for quantitatively evaluating stability of a distributed photovoltaic system in consideration of communication delay in this embodiment includes the following steps:
s1, establishing a frequency response model of a power system containing photovoltaic power generation, taking the influence of communication delay into consideration, realizing time-lag linearization based on a Pade approximation method, and constructing a system linear state space model;
in order to explore the frequency response characteristic of large-scale distributed photovoltaic power generation, on the basis of a traditional power system load frequency modulation control model, the frequency control of a distributed photovoltaic power generation auxiliary system is considered, and a distributed photovoltaic frequency modulation control strategy of P-U external characteristics is combined,
as shown in fig. 2, a power system frequency response (LFC-PV) model including photovoltaic power generation is constructed;
the power balance equation of the traditional LFC power system is as follows:
ΔP T (s)-ΔP L (s)＝2H·s·Δf(s)+D·Δf(s)
wherein DeltaP T (s)-ΔP L (s) is delta power mismatch, ΔP L For system load disturbance, Δf is the system frequency deviation, and H, D is the equivalent inertia time constant and the system damping coefficient, respectively.
Namely:
photovoltaic frequency modulation control strategy based on P-U external characteristics, and transfer functions of the frequency response model corresponding to the distributed photovoltaic are as follows:
where a is the fitting coefficient and k is the control coefficient.
The frequency deviation of the system adding the distributed photovoltaic power generation link to the traditional LFC model can be expressed as:
wherein DeltaP PV For power deviation, Δp of photovoltaic power generation control loop T (s)-ΔP L (s) is the incremental power mismatch, H, D is the equivalent inertial time constant, the system damping coefficient, respectively.
T g 、T t For the time constant of the power system of the speed regulator and turbine, R is the speed regulating coefficient of the power system, and DeltaP S And(s) is the power deviation generated by the main control loop, and Δf is the system frequency deviation.
Aiming at the communication delay problem existing in the frequency modulation control process of the system, a Pade approximation method is adopted for time-lag linearization, a linear model of the system is constructed, and linear state space representation of the distributed photovoltaic power generation system is further obtained through deduction.
When considering communication delay T d The model frequency deviation is:
wherein DeltaP PV For power deviation, Δp of photovoltaic power generation control loop T (s)-ΔP L (s) is increment power mismatch, H, D is equivalent inertia time constant, system damping coefficient and T respectively d Is communication delay; the Pade function is defined as:
wherein T is d For communication delay, N pq And D pq The polynomials of the orders p and q, respectively;
selecting a fifth-order function to linearize the time lag, wherein the corresponding fifth-order pad approximation function is as follows:
the state space of a single-area power system with PV is realized as follows:
wherein A is a system matrix, B is a control input matrix, Γ is an interference matrix, x-state vectors, u (t) input vectors, w (t) is an interference variable, C is an observation matrix, and y (t) is a system output.
S2, analyzing characteristics of the large-scale distributed photovoltaic power generation grid-connected system, and selecting a system frequency steady-state error, a sensitivity of a feedback system, a gain margin of a closed-loop system and a phase margin of the closed-loop system as evaluation indexes; calculating the relevant attribute of the stability of the characterization system in the large-scale distributed photovoltaic power generation grid-connected system to obtain the stability evaluation index of the distributed photovoltaic power generation system;
the system frequency deviation equation is:
wherein,
r is the speed regulation coefficient of the power system, H, D is the equivalent inertia time constant, the system damping coefficient and delta P respectively S (s) is the power deviation, ΔP, generated by the main control loop L G for system load disturbance 0 (s) five-order pad approximation function, ΔP PV T is the power deviation of a photovoltaic power generation control loop g 、 T t Time constant of the power system for the speed governor, turbine; according to the final value theorem, the steady state value of the system frequency deviation is:
wherein,
r is the speed regulation coefficient of the power system, D is the system damping coefficient, and delta P L ΔP for system load disturbance PV T is the power deviation of a photovoltaic power generation control loop g 、T t Time constant of the power system for the speed governor, turbine; disturbance of load ΔP L As an input, a system frequency deviation Δf as an output, a closed loop transfer function between the system frequency deviation and the load step change is:
wherein,
the sensitivity function is obtained according to the above equation:
wherein S is R 、S K 、S K1 、S α Corresponding sensitivity functions of R, K, K and alpha respectively.
And->The open loop transfer functions of the system are respectively:
wherein,
k is gain, R is speed regulation coefficient of the power system, H, D is equivalent inertia time constant and system damping coefficient, alpha is control share, K 1 Fitting coefficient a for photovoltaic control coefficient G 0 (s) a fifth order pad approximation function,and->Respectively open loop transfer functions of the system;
and drawing a Bode diagram based on the open loop transfer function to obtain a gain margin and a phase angle margin.
S3, respectively solving the objective weight and the objective weight by using an analytic hierarchy process and an entropy weight process, combining the objective weight and the objective weight into a comprehensive weight to determine the index weight, and calculating to obtain a fuzzy comprehensive judgment matrix.
(1) Objective weights of the evaluation indexes can be obtained through an entropy weight method.
Firstly, evaluating index data x of stability of a large-scale distributed photovoltaic power generation system ij Processing, calculating to obtain an evaluation index matrix Y, and calculating by adopting a formula 1 when the stability index is larger and better within a certain range; when the stability index is smaller and better within a certain range, calculating by adopting a formula 2;
formula 1:
formula 2:
x ij the measured value, y, of the grid-connected stability evaluation index of the jth photovoltaic power generation at the ith moment of the system ij The processed standardized data value is obtained; max (x) j )，min(x j ) Respectively obtaining maximum and minimum values of the j-th stability evaluation index;
then obtaining an information entropy E according to the calculation, and further obtaining an objective weight omega;
wherein: y is ij For the processed standardized data value, n is the number of grid-connected stability evaluation indexes of photovoltaic power generation (n is 4), m is the number of evaluation objects, and p ij Is an index value of the index data.
(2) Subjective weight of the evaluation index can be obtained through an analytic hierarchy process.
Scoring each index by a nine-scale method, and constructing a judgment matrix A:
after the column normalization processing is carried out on the judgment matrix A, weighting is carried out by using an arithmetic average method, and a subjective weight vector theta is obtained:
θ＝[θ 1 θ 2 θ 3 θ 4 ]
and S4, obtaining a stability evaluation result of the large-scale distributed photovoltaic grid-connected system through a fuzzy comprehensive quantitative calculation method. And (3) fusing the objective weight and the subjective weight obtained in the step (S3), and effectively resisting weight deviation:
wherein, theta is the subjective weight value, omega is the objective weight value;
dividing the stability of the photovoltaic power generation grid-connected system into 5 different grades, and establishing a fuzzy comment set V: v= { V1 (good stability), V2 (better stability), V3 (general stability), V4 (poor stability), V5 (poor stability) };
constructing Gauss type membership functions, and calculating to obtain a fuzzy comprehensive judgment matrix, wherein the Gauss type membership functions f (y) specifically comprise:
wherein: y is a stability evaluation index of the large-scale photovoltaic power generation grid-connected system, and sigma and c are parameters;
the index Y in the index matrix Y is evaluated ij Respectively substituting the judgment matrix F into the membership functions to obtain the judgment matrix F as follows:
wherein,is index y ij For the judgment grade V k Is a membership degree of (2);
and combining the comprehensive weights to obtain the overall quantitative evaluation of the stability evaluation system of the large-scale photovoltaic power generation grid-connected system:
B j ＝[b i (V 1 ) b i (V 2 ) b i (V 3 ) b i (V 4 ) b i (V 5 )]
wherein:
b i (V k ) Is a relative comment V representing each stability index k Is a membership of (1). The technical means disclosed by the scheme of the invention is not limited to the technical means disclosed by the embodiment, and also comprises the technical scheme formed by any combination of the technical features.
Claims (3)
1. A distributed photovoltaic system stability quantitative evaluation method considering communication delay is characterized by comprising the following steps:
s1, establishing a frequency response model of a power system containing photovoltaic power generation, taking the influence of communication delay into consideration, realizing time-lag linearization based on a Pade approximation method, and constructing a system linear state space model; the step S1 specifically comprises the following steps:
s11, in order to explore the frequency response characteristics of large-scale distributed photovoltaic power generation, on the basis of a traditional power system load frequency modulation control model, the distributed photovoltaic power generation auxiliary system frequency control is considered, and a power system frequency response LFC-PV model containing photovoltaic power generation is constructed by combining a distributed photovoltaic frequency modulation control strategy with P-U external characteristics;
the power balance equation of the traditional LFC power system is as follows:
△P T (s)-△P L (s)＝2H·s·△f(s)+D·△f(s)
wherein DeltaP T (s)-△P L (s) is delta power mismatch, ΔP L For system load disturbance, Δf is system frequency deviation, H, D is equivalent inertia time constant and system damping coefficient respectively;
namely:
photovoltaic frequency modulation control strategy based on P-U external characteristics, and transfer functions of the frequency response model corresponding to the distributed photovoltaic are as follows:
wherein a is a fitting coefficient, and k is a control coefficient;
the frequency deviation of a system added to a traditional LFC model in a distributed photovoltaic power generation link is expressed as:
wherein DeltaP PV For the power deviation of the photovoltaic power generation control loop, deltaP T (s)-△P L (s) is increment power mismatch, H, D is equivalent inertia time constant and system damping coefficient respectively;
T g 、T t for the time constant of the power system of the speed regulator and turbine, R is the speed regulating coefficient of the power system, and DeltaP S (s) is the power deviation generated by the main control loop, and Δf is the system frequency deviation;
s12, aiming at the problem of communication delay in the frequency modulation control process of the system, adopting a Pade approximation method for time-lag linearization, constructing a linear model of the system, and further deriving to obtain a linear state space representation of the distributed photovoltaic power generation system;
when the communication delay is considered, the model frequency deviation is:
wherein DeltaP PV For the power deviation of the photovoltaic power generation control loop, deltaP T (s)-△P L (s) is increment power mismatch, H, D is equivalent inertia time constant, system damping coefficient and T respectively d Is communication delay;
the Pade function is defined as:
wherein T is d For communication delay, N pq And D pq Polynomial of the order p and q respectively
Selecting a fifth-order function to linearize the time lag, wherein the corresponding fifth-order pad approximation function is as follows:
the state space of a single-area power system with PV is realized as follows:
y(t)＝C·x(t)
wherein A is a system matrix, B is a control input matrix, Γ is an interference matrix, x-state vectors, u (t) input vectors, w (t) is an interference variable, C is an observation matrix, and y (t) is system output;
s2, analyzing characteristics of the large-scale distributed photovoltaic power generation grid-connected system, calculating relevant attributes representing system stability in the large-scale distributed photovoltaic power generation grid-connected system, and obtaining an evaluation index of the stability of the power system; the evaluation index in step S2 includes: the system frequency steady-state error, the sensitivity of a feedback system, the gain margin of a closed-loop system and the phase margin of the closed-loop system;
the system frequency deviation equation is:
wherein,
r is the speed regulation coefficient of the power system, H, D is the equivalent inertia time constant and the system damping coefficient respectively, and DeltaP S (s) is the power deviation, ΔP, generated by the main control loop L G for system load disturbance 0 (s) five-order pad approximation function, ΔP PV Power deviation of a photovoltaic power generation control loop; t (T) g 、T t Time constant of the power system for the speed governor, turbine; according to the final value theorem, the steady state value of the system frequency deviation is:
wherein,
r is the speed regulation of the power systemCoefficient D is the system damping coefficient, ΔP L For system load disturbance, ΔP PV T is the power deviation of a photovoltaic power generation control loop g 、T t Time constant of the power system for the speed governor, turbine;
disturbance of load DeltaP L As input, the system frequency deviation Δf is as output, and the closed loop transfer function between the system frequency deviation and the load step change is:
wherein,
the sensitivity function is obtained according to the above equation:
wherein S is R 、S K 、S α Sensitivity functions corresponding to R, K, K and alpha respectively;
and->The open loop transfer functions of the system are respectively:
wherein,
k is gain, R is speed regulation coefficient of the power system, H, D is equivalent inertia time constant and system damping coefficient, alpha is control share, K 1 Fitting coefficient a for photovoltaic control coefficient G 0 (s) a fifth order pad approximation function,and->Respectively open loop transfer functions of the system; drawing a Bode diagram based on an open loop transfer function to obtain a gain margin and a phase angle margin;
s3, respectively solving the subjective weight and the objective weight by using an analytic hierarchy process and an entropy weight process, combining the subjective weight and the objective weight into a comprehensive weight to determine an index weight, and calculating to obtain a fuzzy comprehensive judgment matrix;
and S4, obtaining a stability evaluation result of the large-scale distributed photovoltaic grid-connected system through a fuzzy comprehensive quantitative calculation method.
2. The method for quantitatively evaluating the stability of the distributed photovoltaic system according to claim 1, wherein in the step S3:
(1) Objective weights of the evaluation indexes can be obtained through an entropy weight method;
firstly, evaluating index data x of stability of a large-scale distributed photovoltaic power generation system ij Processing, calculating to obtain an evaluation index matrix Y, and calculating by adopting a formula 1 when the stability index is larger and better within a certain range; when the stability index is smaller and better within a certain range, calculating by adopting a formula 2;
formula 1:
formula 2:
x ij the measured value, y, of the grid-connected stability evaluation index of the jth photovoltaic power generation at the ith moment of the system ij The processed standardized data value is obtained; max (x) j )，min(x j ) Respectively obtaining maximum and minimum values of the j-th stability evaluation index;
then obtaining an information entropy E according to the calculation, and further obtaining an objective weight omega;
wherein: y is ij N is the grid-connected stability evaluation of the photovoltaic power generation for the processed standardized data valueThe number of the price indexes, n is 4, m is the number of the evaluation objects, and p ij An index value which is index data;
(2) Subjective weight of the evaluation index can be obtained through an analytic hierarchy process;
scoring each index by a nine-scale method, and constructing a judgment matrix A:
after the column normalization processing is carried out on the judgment matrix A, weighting is carried out by using an arithmetic average method, and a subjective weight vector theta is obtained:
θ＝[θ 1 θ 2 θ 3 θ 4 ]。
3. the method for quantitatively evaluating the stability of the distributed photovoltaic system according to claim 1, wherein in the step S4: obtaining a stability evaluation result of the large-scale distributed photovoltaic grid-connected system by a fuzzy comprehensive quantitative calculation method;
and (3) fusing the objective weight and the subjective weight obtained in the step (S3), and effectively resisting weight deviation:
wherein, theta is the subjective weight value, omega is the objective weight value;
dividing the stability of the photovoltaic power generation grid-connected system into 5 different grades, and establishing a fuzzy comment set V: v= { V1 (good stability), V2 (better stability), V3 (general stability), V4 (poor stability), V5 (poor stability) };
constructing Gauss type membership functions, and calculating to obtain a fuzzy comprehensive judgment matrix, wherein the Gauss type membership functions f (y) specifically comprise:
wherein: y is an evaluation index of frequency stability of the large-scale photovoltaic power generation grid-connected system, and sigma and c are parameters;
the index Y in the index matrix Y is evaluated ij Respectively substituting the judgment matrix F into the membership functions to obtain the judgment matrix F as follows:
wherein f Vk (y ij ) (k=1, 2, … 5; j=1, 2, … n) is an index y ij For the judgment grade V k Is a membership degree of (2);
and combining the comprehensive weights to obtain the overall quantitative evaluation of the stability evaluation system of the large-scale photovoltaic power generation grid-connected system:
B j ＝[b i (V 1 ) b i (V 2 ) b i (V 3 ) b i (V 4 ) b i (V 5 )]
wherein: b i (V k )＝∑(λ i ·f V1 (y i1 ))，b i (V k )
b i (V k ) Representing each stability index relative comment V k Is a membership of (1).
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