阅读说明：本技术 基于不确定性风险计算的电网新能源接入方法 (Power grid new energy access method based on uncertainty risk calculation ) 是由 吴军 黄文鑫 吴志军 郭子辉 韩锐 邱睿 于 2021-08-11 设计创作，主要内容包括：本发明涉及电力系统能源转型技术,具体涉及基于不确定性风险计算的电网新能源接入方法,首先构建电网不确定性因素模型,基于概率潮流计算得到电网实际运行情况的概率分布,基于风险理论计算电网不确定性风险大小；以电网运行风险水平最小为目标函数进行新能源接入点寻优的电网规划,基于盲数理论改进不确定性因素下的模型约束条件,最终得到不同可信度下的最优接入方案。该方法在新能源并网点选择的电网规划中充分考虑系统风险要素,有利于平抑新能源随机出力对系统的影响,改善电压、功率越限等不利运行情况。实现了提高新能源接入渗透率、完成电力系统能源转型的目的,具有重要实际意义。(The invention relates to an energy transformation technology of a power system, in particular to a power grid new energy access method based on uncertainty risk calculation, which comprises the steps of firstly constructing a power grid uncertainty factor model, obtaining probability distribution of actual operation conditions of a power grid based on probability load flow calculation, and calculating the uncertainty risk of the power grid based on a risk theory; and (3) planning the power grid by optimizing the new energy access point by taking the minimum power grid operation risk level as a target function, and improving model constraint conditions under uncertainty factors based on a blind number theory to finally obtain the optimal access scheme under different credibility. According to the method, system risk factors are fully considered in power grid planning of new energy grid-connected point selection, the influence of new energy random output on a system is favorably stabilized, and adverse running conditions such as voltage and power out-of-limit are improved. The purposes of improving the new energy access permeability and completing the energy transformation of the electric power system are achieved, and the method has important practical significance.)

1. The power grid new energy access method based on uncertainty risk calculation is characterized by comprising the following steps: the method comprises the following steps:

step 1, constructing a random model of an electric power system element based on probability load flow calculation;

step 2, completing probability load flow calculation and counting calculation results;

step 3, completing risk assessment according to the probability load flow calculation result;

step 4, constructing a planning optimization model of the new energy grid-connected point by taking the system operation risk and the minimum economic loss caused by the occurrence of the risk accident as an objective function;

step 5, improving the constraint condition based on a blind number theory;

and 6, solving the model by improving a genetic algorithm to obtain optimal access schemes under different credibility, and obtaining a planning scheme with optimal comprehensive benefit indexes by indiscriminate selection.

2. The uncertainty risk calculation-based power grid new energy access method according to claim 1, characterized in that: constructing a stochastic model of a power system element comprises: the system comprises a load random fluctuation model, a wind driven generator random output model and a photovoltaic generator random output model;

step 1.1, establishing a load random fluctuation model;

the random fluctuation condition of the load is described by a normal distribution function, and the calculation formula is as follows:

in the formula: f (P) and f (Q) are probability distribution functions of load active power and load reactive power respectively; mu.s_P、μ_QRespectively the average values of the normal distribution of the active power and the reactive power; sigma_P、σ_QRespectively the variance of the normal distribution of the active power and the reactive power;

step 1.2, establishing a random output model of wind power generation;

step 1.2.1, fitting probability distribution of wind speed through Weibull distribution, and calculating a formula as follows:

in the formula: v is the wind speed; k. c are two parameters of Weibull distribution respectively;

step 1.2.2, combining a typical relation between wind speed and a wind turbine generator set to obtain a random output model of wind power generation; the calculation formula is as follows:

in the formula: upsilon is_ci、v_N、υ_coRespectively comprises cut-in wind speed, rated wind speed and cut-off wind speed; p_NRated active power;

step 1.3, establishing a random output model of photovoltaic power generation;

establishing a random model of illumination intensity, introducing a power coefficient to obtain an output model of the wind generating set, wherein a calculation formula is as follows:

in the formula: gamma is a Gamma function; alpha and beta are two parameters of beta distribution respectively; p, P_MThe power and the maximum output power of the photovoltaic generator set are respectively.

3. The uncertainty risk calculation-based power grid new energy access method according to claim 1, characterized in that: the steps of completing the probability power flow calculation and counting the result comprise:

step 2.1, obtaining N groups of load data and generator output data with enough quantity through Monte Carlo simulation;

step 2.2, bringing each group of data into deterministic load flow calculation to obtain N groups of power system load flow calculation results;

and 2.3, carrying out digital characteristic analysis on the load flow calculation result, and calculating a mean value and a variance.

4. The uncertainty risk calculation based power grid new energy access method according to claim 3, characterized in that: the step of completing risk assessment according to the load flow calculation result obtained in the step 2.2 comprises the following steps:

step 3.1, calculating according to the load flow calculation result obtained in the step 2.2 by using the ratio of the out-of-limit times to the total simulation times to obtain the out-of-limit probability, wherein the calculation formula is as follows:

in the formula: n is the Monte Carlo simulation times; m is the out-of-limit times;

step 3.2, the severity S is represented by the relative amount by which the voltage or current exceeds or falls below the limit;

step 3.2.1, out-of-limit severity of Voltage S_VThe calculation formula of (a) is as follows:

in the formula: s_VmaxSeverity of the upper voltage limit; v_maxIs the upper limit value of the voltage; s_VminSeverity of the lower limit of voltage; v_minIs the lower limit of the voltage;

step 3.2.2, tidal current out-of-limit severity S_PThe calculation formula of (a) is as follows:

in the formula: s_PmaxThe severity of the trend is the upper limit; p_maxThe upper limit value of the power flow; s_PminThe severity of the lower limit of the trend; p_minThe lower limit value of the power flow;

step 3.3, the uncertainty risk comprises the probability of occurrence of the risk accident and the severity of the risk accident, and the calculation mode is as follows:

R＝P×S

in the formula: r is the quantitative risk degree of the event; p is the probability of the accident; and S is the severity after the accident occurs.

5. The uncertainty risk calculation-based power grid new energy access method according to claim 1, characterized in that: the method for constructing the planning optimization model of the new energy grid-connected point comprises the following steps:

step 4.1, the planning target of the power grid planning optimization model is as follows: the risk of the power grid and the economic loss caused by the occurrence of the risk accident are minimum;

step 4.2, the economic loss comprises load shedding loss caused by the out-of-limit tidal current and capacity cost caused by reactive compensation adopted for voltage regulation, and the objective function is as follows:

in the formula: in the formula: k is a radical of₁、k₂The weight coefficient represents the importance degree of two parts of the objective function; r_Vmaxi、R_VminjThe risk that the voltage of the node i is higher than the upper limit and the risk that the voltage of the node j is lower than the lower limit are respectively set; r_SkThe risk of the branch k out-of-limit tidal current; n1, N2 and L1 are respectively a node set which can cause voltage exceeding and limiting and a branch set which can cause power flow exceeding; c_V、C_SThe economic losses caused by voltage out-of-limit and power flow out-of-limit respectively occur, and the calculation modes of the two are as follows:

C_V＝∑Q_CC’₀

in the formula: p_kIs the active power of line k; l is₁The branch set which is possible to have the power flow out-of-limit is selected;is the line active upper limit; c₀Is the electricity price; q_cThe reactive capacity required for regulating the voltage is obtained by load flow calculation; c'₀The cost required for a unit of reactive compensation capacity.

6. The uncertainty risk calculation-based power grid new energy access method according to claim 1, characterized in that: the improvement steps of the constraint condition based on the blind number theory are as follows:

step 5.1, establishing a blind number BM model;

step 5.1.1, the definition of the blindness number is as follows:

let G be a set of regular ash numbers, α_iE.g. G, real number T_i∈[0，1]Then, there are:

when alpha is_iAre not equal to each other, andwhen f (x) is a blind number; t is_iIs x falls within alpha_i(ii) a confidence level of; x falls within an interval, α_iIs a zonal ash number;

step 5.1.2, BM model of blind number;

let A, B be two blind numbers:

p (A-B & gtbeta) is called as a blind BM model; let β be 0, i.e., P (a-B > 0), representing the confidence that a > B, the calculation of the BM model is shown as follows:

the larger the value of P (A-B > 0), the higher the credibility of the blind information of A > B, the more credible; otherwise, the lower the credibility is, the more unreliable the credibility is;

step 5.2, based on a blind number theory, improving the constraint condition of the power grid planning model, wherein the formal first two formulas are power balance constraints and respectively represent active balance and reactive balance; the last three formulas are reliability constraint, and the reliability is higher when the reliability is higher;

in the formula:the power flow is a blind number power flow on a line connected with the node i, and the power flow is equivalent to the reactive power flow;representing the load at the node i and the output of the generator, wherein both are represented by blind numbers, and the reactive power is the same; l (i) denotes a set of branches connected to node i;respectively representing the blind number power flow and the power flow upper limit of the branch;the upper and lower voltage limits of the node, respectively;is the node voltage, expressed in blind numbers; t is the credibility; l is_o、N_oIs the set of all branches and nodes;

step 5.3, the construction method of the blind number model comprises the following steps: establishing a ten-order blind number model, dividing possible values of power into ten intervals, and corresponding to the ten gray scale intervals; the confidence level of each gray scale interval is represented by the probability that the power falls on that interval.

7. The uncertainty risk calculation-based power grid new energy access method according to claim 1, characterized in that: the improvement of the genetic algorithm and the comparison and selection of the comprehensive benefits comprise the following steps:

step 6.1, the improvement of the genetic algorithm comprises the calculation of fitness and the selection of variation rate;

step 6.1.1, calculating the fitness;

the calculation formula of the fitness is as follows:

fit(x)＝K-f(x)

in the formula: fit (x) is fitness; k is a given large number and is larger than the maximum value of the objective function, so that the fitness is ensured to be larger than 0;

6.1.2, selecting the variation rate;

when the inheritance frequency is lower, the mutation rate is increased; when the inheritance frequency is larger, the mutation rate is reduced; for the offspring with high fitness, mutation is not carried out; for individuals with low fitness, the individuals are mutated to find a better solution;

step 6.2, solving a ten-order blind number model of the new energy grid-connected point power grid planning through a genetic algorithm to obtain an optimal access scheme under different credibility;

6.3, comparing and selecting the optimal access schemes under different credibility by the comprehensive benefit indexes to obtain a new energy grid-connected access scheme;

the calculation mode of the comprehensive benefit index eta is as follows:

in the formula: f is an objective function value of the model; t is a reliability value and reflects the reliability degree of the system.

Technical Field

The invention belongs to the technical field of energy transformation of power systems, and particularly relates to a power grid new energy access method based on uncertainty risk calculation.

Background

The selection of the power supply position is an extremely important link in the planning of the power system, and the high-proportion access of environment-friendly new energy becomes a necessary route for the power system to complete energy transformation and achieve the 30-60 double-carbon target. The access of new energy represented by photovoltaic and wind power enables the randomness and uncertainty of a power system at two ends of a source and a load to be remarkably improved. If a new energy source is accessed to an improper position, the system is easy to have abnormal operation states in frequency, voltage and tide, so that the risk of system operation is increased, and a power failure accident of the power system is caused. Therefore, under the brand-new development situation of the power system, the system uncertainty factor is correctly calculated, and in the planning stage, the system uncertainty factor is processed in a scientific mode, so that the access position of new energy is reasonably determined, the system is kept at a low operation risk level, and the method has important practical significance for safe and stable operation of the power system and energy transformation completion.

Disclosure of Invention

Aiming at the problems in the background art, the invention provides a power grid new energy access method based on uncertainty risk calculation.

In order to solve the technical problems, the invention adopts the following technical scheme: the power grid new energy access method based on uncertainty risk calculation comprises the following steps:

step 1, constructing a random model of an electric power system element based on probability load flow calculation;

step 2, completing probability load flow calculation and counting calculation results;

step 3, completing risk assessment according to the probability load flow calculation result;

step 4, constructing a planning optimization model of the new energy grid-connected point by taking the system operation risk and the minimum economic loss caused by the occurrence of the risk accident as an objective function;

step 5, improving the constraint condition based on a blind number theory;

and 6, solving the model by improving a genetic algorithm to obtain optimal access schemes under different credibility, and obtaining a planning scheme with optimal comprehensive benefit indexes by indiscriminate selection.

In the method for accessing new energy to a power grid based on uncertainty risk calculation, constructing a stochastic model of power system elements includes: the system comprises a load random fluctuation model, a wind driven generator random output model and a photovoltaic generator random output model;

step 1.1, establishing a load random fluctuation model;

the random fluctuation condition of the load is described by a normal distribution function, and the calculation formula is as follows:

in the formula: f (P) and f (Q) are probability distribution functions of load active power and load reactive power respectively; mu.s_P、μ_QRespectively the average values of the normal distribution of the active power and the reactive power; sigma_P、σ_QRespectively the variance of the normal distribution of the active power and the reactive power;

step 1.2, establishing a random output model of wind power generation;

step 1.2.1, fitting probability distribution of wind speed through Weibull distribution, and calculating a formula as follows:

in the formula: v is the wind speed; k. v are two parameters of Weibull distribution respectively;

step 1.2.2, combining a typical relation between wind speed and a wind turbine generator set to obtain a random output model of wind power generation; the calculation formula is as follows:

in the formula: v. of_ci、v_N、v_coRespectively comprises cut-in wind speed, rated wind speed and cut-off wind speed; p_NRated active power;

step 1.3, establishing a random output model of photovoltaic power generation;

establishing a random model of illumination intensity, introducing a power coefficient to obtain an output model of the wind generating set, wherein a calculation formula is as follows:

in the formula: gamma is a Gamma function; alpha and beta are two parameters of beta distribution respectively; p, P_MThe power and the maximum output power of the photovoltaic generator set are respectively.

In the method for accessing new energy to a power grid based on uncertainty risk calculation, the steps of completing probability load flow calculation and counting results comprise:

step 2.1, obtaining N groups of load data and generator output data with enough quantity through Monte Carlo simulation;

step 2.2, bringing each group of data into deterministic load flow calculation to obtain N groups of power system load flow calculation results;

and 2.3, carrying out digital characteristic analysis on the load flow calculation result, and calculating a mean value and a variance.

In the method for accessing the new energy of the power grid based on the uncertainty risk calculation, the step of completing risk assessment according to the probability load flow calculation result comprises the following steps:

step 3.1, calculating according to the probability load flow calculation result and the ratio of the out-of-limit times to the total simulation times to obtain the out-of-limit probability, wherein the calculation formula is as follows:

in the formula: n is the Monte Carlo simulation times; m is the out-of-limit times;

step 3.2, the severity S is represented by the relative amount by which the voltage or current exceeds or falls below the limit;

step 3.2.1, out-of-limit severity of Voltage S_VThe calculation formula of (a) is as follows:

in the formula: s_VmaxSeverity of the upper voltage limit; v_maxIs the upper limit value of the voltage; s_VminSeverity of the lower limit of voltage; v_minIs the lower limit of the voltage;

step 3.2.2, tidal current out-of-limit severity S_PThe calculation formula of (a) is as follows:

in the formula: s_PmaxThe severity of the trend is the upper limit; p_maxThe upper limit value of the power flow; s_PminThe severity of the lower limit of the trend; p_minThe lower limit value of the power flow;

step 3.3, the uncertainty risk comprises the probability of occurrence of the risk accident and the severity of the risk accident, and the calculation mode is as follows:

R＝P×S

in the formula: r is the quantitative risk degree of the event; p is the probability of the accident; and S is the severity after the accident occurs.

In the power grid new energy access method based on uncertainty risk calculation, the construction of a planning optimization model of a new energy grid-connected point comprises the following steps:

step 4.1, the planning target of the power grid planning optimization model is as follows: the risk of the power grid and the economic loss caused by the occurrence of the risk accident are minimum;

step 4.2, the economic loss comprises load shedding loss caused by the out-of-limit tidal current and capacity cost caused by reactive compensation adopted for voltage regulation, and the objective function is as follows:

in the formula: in the formula: k is a radical of₁、k₂The weight coefficient represents the importance degree of two parts of the objective function; r_Vmaxi、R_VminjThe risk that the voltage of the node i is higher than the upper limit and the risk that the voltage of the node j is lower than the lower limit are respectively set; r_SkThe risk of the branch k out-of-limit tidal current; n1, N2 and L1 are respectively a node set which can cause voltage exceeding and limiting and a branch set which can cause power flow exceeding; c_V、C_SThe economic losses caused by voltage out-of-limit and power flow out-of-limit respectively occur, and the calculation modes of the two are as follows:

C_V＝ΣQ_CC’₀

in the formula: p_kIs the active power of line k; l is₁The branch set which is possible to have the power flow out-of-limit is selected;is the line active upper limit; c₀Is the electricity price; q_cThe reactive capacity required for regulating the voltage is obtained by load flow calculation; c'₀Is unit of reactive powerThe cost required to compensate for capacity.

In the method for accessing the new energy of the power grid based on the uncertainty risk calculation, the improvement on the constraint condition based on the blind number theory comprises the following steps:

step 5.1, establishing a blind number BM model;

step 5.1.1, the definition of the blindness number is as follows:

let G be a set of regular ash numbers, α_iE.g. G, real number T_i∈[0，1]Then, there are:

when alpha is_iAre not equal to each other, andwhen f (x) is a blind number; t is_iIs x falls within alpha_i(ii) a confidence level of; x falls within an interval, α_iIs a zonal ash number;

step 5.1.2, BM model of blind number;

let A, B be two blind numbers:

p (A-B & gtbeta) is called as a blind BM model; let β be 0, i.e., P (a-B > 0), representing the confidence that a > B, the calculation of the BM model is shown as follows:

the larger the value of P (A-B > 0), the higher the credibility of the blind information of A > B, the more credible; otherwise, the lower the credibility is, the more unreliable the credibility is;

step 5.2, based on a blind number theory, improving the constraint condition of the power grid planning model, wherein the formal first two formulas are power balance constraints and respectively represent active balance and reactive balance; the last three formulas are reliability constraint, and the reliability is higher when the reliability is higher;

in the formula:the power flow is a blind number power flow on a line connected with the node i, and the power flow is equivalent to the reactive power flow;representing the load at the node i and the output of the generator, wherein both are represented by blind numbers, and the reactive power is the same; l (i) denotes a set of branches connected to node i;respectively representing the blind number power flow and the power flow upper limit of the branch;the upper and lower voltage limits of the node, respectively;is the node voltage, expressed in blind numbers; t is the credibility; l is_o、N_oIs the set of all branches and nodes;

step 5.3, the construction method of the blind number model comprises the following steps: establishing a ten-order blind number model, dividing possible values of power into ten intervals, and corresponding to the ten gray scale intervals; the confidence level of each gray scale interval is represented by the probability that the power falls on that interval.

In the method for accessing the new energy of the power grid based on the uncertainty risk calculation, the improvement of the genetic algorithm and the comparison and selection of the comprehensive benefits comprise the following steps:

step 6.1, the improvement of the genetic algorithm comprises the calculation of fitness and the selection of variation rate;

step 6.1.1, calculating the fitness;

the calculation formula of the fitness is as follows:

fit(x)＝K-f(x)

in the formula: fit (x) is fitness; k is a given large number and is larger than the maximum value of the objective function, so that the fitness is ensured to be larger than 0;

6.1.2, selecting the variation rate;

when the inheritance frequency is lower, the mutation rate is increased; when the inheritance frequency is larger, the mutation rate is reduced; for the offspring with high fitness, mutation is not carried out; for individuals with low fitness, the individuals are mutated to find a better solution;

step 6.2, solving a ten-order blind number model of the new energy grid-connected point power grid planning through a genetic algorithm to obtain an optimal access scheme under different credibility;

6.3, comparing and selecting the optimal access schemes under different credibility by the comprehensive benefit indexes to obtain a new energy grid-connected access scheme;

the calculation mode of the comprehensive benefit index eta is as follows:

in the formula: f is an objective function value of the model; t is a reliability value and reflects the reliability degree of the system.

Compared with the prior art, the invention has the beneficial effects that:

1. according to the method, the development direction of the power grid is fully considered, and the system risk elements are fully considered in the power grid planning selected by the new energy grid-connected point under the background of large-amplitude access of new energy, so that the influence of random output of the new energy on the system is favorably stabilized, and the adverse running conditions such as voltage and power out-of-limit are improved. The purposes of improving the new energy access permeability and completing the energy transformation of the electric power system are achieved, and the method has important practical significance.

2. The blind number constraint condition provided by the invention can well process uncertainty information in planning. Meanwhile, a blind number model is generated by probability distribution, and the relation between uncertainty risk calculation and optimization planning is further strengthened. Compared with the constraint conditions in the existing planning model, the method is more suitable for practical situations.

3. The optimal scheme comprehensive benefit comparison and selection method for ten-order blind digital model solution introduced by the invention can compare optimal schemes under different credibility levels, improves the flexibility and reliability of the planning scheme, and provides a brand new thought for power system planning.

Drawings

Fig. 1 is a flowchart of a method for determining new energy access to a power grid by uncertainty risk calculation according to an embodiment of the present invention;

FIG. 2 is a Monte Carlo simulation probabilistic power flow calculation graph provided by an embodiment of the present invention;

fig. 3 is a flowchart of solving a blind number constraint programming model by a genetic algorithm according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the following 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.

It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.

The present invention is further illustrated by the following examples, which are not to be construed as limiting the invention.

Wind power, photoelectricity and other large-scale distributed renewable energy sources are connected to the grid, and fluctuation of power load brings more uncertain factors to the power grid. The traditional power grid planning method cannot meet the requirements of power grid planning containing a plurality of uncertain factors. The embodiment provides a corresponding mathematical model for the uncertainty factors in the system; calculating a random operation state of the characterization system based on the probability load flow; calculating system risk based on a risk theory; the method comprises the following steps of taking the minimum economic loss caused by the risk of a power grid and the occurrence of a risk accident as a target function; and improving the model constraint condition based on a blind number theory, and carrying out necessary selection through a plurality of planning schemes to finally obtain the optimal scheme of the new energy grid-connected planning. The method provides reference for a power grid planning department to formulate a new energy grid-connected scheme, is beneficial to realizing high-proportion access of new energy, and drives the power system to complete energy transformation.

The embodiment is realized by the following technical scheme, and the power grid new energy access method based on uncertainty risk calculation comprises the following steps:

s1, constructing a random model of the power system element based on the probability load flow calculation;

s2, completing probability load flow calculation and counting the calculation result;

s3, completing risk assessment through the probability load flow calculation result;

s4, constructing a planning optimization model of the new energy grid-connected point by taking the system operation risk and the minimum economic loss caused by the occurrence of risk accidents as objective functions;

and S5, improving the constraint condition based on the blind number theory.

And S6, solving the model by improving the genetic algorithm to obtain the optimal access scheme under different credibility, and obtaining the optimal planning scheme of the comprehensive benefit index by indiscriminate selection.

And S1, the random models of the power system elements comprise a load fluctuation random model, a wind turbine generator output random model and a photovoltaic generator output random model.

S2, the steps of completing the probability power flow calculation and counting the calculation result include:

s2.1, obtaining N groups of load data and generator output data with enough quantity through Monte Carlo simulation; bringing each group of data into deterministic load flow calculation;

s2.2, obtaining load flow results of the N groups of power systems;

and S2.3, carrying out digital characteristic analysis on the load flow result, calculating the mean value, the variance and the like, and preparing for risk calculation.

The risk level calculation in S3 is based on the probabilistic power flow calculation result. The severity of the risk accident is multiplied by the probability of the risk accident to obtain the size of the risk; and integrating to obtain a comprehensive risk value of the power system, and finishing quantitative evaluation work on the risk of the power system.

The objective function of the power grid planning in the S4 includes two parts, namely system operation risk and economic loss caused by a risk accident.

As shown in fig. 3, the specific steps of improving the constraint conditions of the planning model by the blind number theory in S5 are as follows:

s5.1, establishing a blind number BM model;

the basic definition of the blind number is as follows:

let G be a set of regular ash numbers, α_iE.g. G, real number T_i∈[0，1]Then, there are:

when alpha is_iAre not equal to each other, andwhen f (x) is a blind number; t is_iIs x falls within alpha_iThe confidence level of (3). In practical engineering, x often cannot fall precisely on α_iAbove, but falls within α_iSo that x falls on an interval, α_iIs a compartment type gray number.

In the process of optimizing and planning the power grid, various complex operations are required, and the comparison of the blind numbers is involved. Therefore, the present invention establishes a blind number BM model.

Let A, B be two blind numbers:

p (A-B > beta) is called BM model of blind number. The invention only needs to use the condition that beta is 0, namely P (A-B > 0), and the reliability of A > B is represented, and the calculation of the BM model is shown as the following formula:

in practical application, the larger the value of P (A-B > 0), the higher the credibility of the blind information of A > B, the more credible; otherwise, the lower the confidence level, the less confidence.

S5.2, improving the constraint condition of the power grid planning model based on a blind number theory;

the improved constraint conditions are as follows, wherein the first two formulas are power balance constraints and respectively represent active balance and reactive balance. The last three formulas are reliability constraints, and the higher the reliability is, the higher the reliability is.

In the formula:is a blind number load flow on a line connected with the node i (the same reactive principle is not described again);the load at the node i and the output of the generator are represented by blind numbers (the same reactive theory is not repeated); l (i) denotes a set of branches connected to node i;respectively representing the blind number power flow and the power flow upper limit of the branch;the upper and lower voltage limits of the node, respectively;is the node voltage, expressed in blind numbers; t is the credibility; l is_o、N_oIs the set of all branches and nodes.

S5.3, the construction method of the blind number model comprises the following steps:

and establishing a ten-order blind number model, and dividing possible values of power into ten intervals corresponding to ten gray scale intervals. The confidence level of each gray scale interval is represented by the probability that the power falls on that interval.

And solving the model by improving the genetic algorithm to obtain the optimal access scheme under different credibility, and obtaining the optimal planning scheme of the comprehensive benefit index by indiscriminate selection.

In specific implementation, as shown in fig. 1, a power grid new energy access method based on uncertainty risk calculation includes the steps of firstly, constructing a power grid uncertainty factor model, obtaining probability distribution of actual operation conditions of a power grid based on probability load flow calculation, and calculating uncertainty risk of the power grid based on a risk theory; and (3) planning the power grid by optimizing the new energy access point by taking the minimum power grid operation risk level as a target function, and improving model constraint conditions under uncertainty factors based on a blind number theory to finally obtain the optimal access scheme under different credibility. The method comprises the following specific steps:

1) and constructing a stochastic model of the power system element based on the probability load flow calculation.

The realization of the step 1) comprises that the random models of the elements of the power system comprise a load fluctuation random model, a wind turbine generator output random model and a photovoltaic generator output random model:

load random fluctuation model:

the random fluctuation condition of the load is described by a normal distribution function, and the calculation formula is as follows:

in the formula: f (P) and f (Q) are probability distribution functions of load active power and load reactive power respectively; mu.s_P、μ_QRespectively the average values of the normal distribution of the active power and the reactive power; sigma_P、σ_QThe variances of the active power and the reactive power are respectively normal distribution.

Random output model of wind power generation:

the output of the wind turbine generator changes along with the change of the wind speed, the probability distribution of the wind speed is fitted through Weibull distribution, and the calculation formula is as follows:

in the formula: v is the wind speed; k. c are two parameters of the Weibull distribution, respectively.

And then, combining the typical relation between the wind speed and the wind turbine generator set to obtain a random processing model of the wind power generation. The calculation formula is as follows:

in the formula: v. of_ci、v_N、v_coRespectively comprises cut-in wind speed, rated wind speed and cut-off wind speed; p_NIs rated active power.

Random output model of photovoltaic power generation:

the output of the photovoltaic generator is affected by the intensity of illumination. In the operation process of the distributed photovoltaic generator, the output power of the system is basically in direct proportion to the illumination intensity, firstly, a random model of the illumination intensity is established, and a power coefficient is introduced, so that an output model of the wind generating set can be obtained, wherein the calculation formula is as follows:

in the formula: gamma is a Gamma function; alpha and beta are two parameters of beta distribution respectively; p, P_MThe power and the maximum output power of the photovoltaic generator set are respectively.

And step 2), completing probability load flow calculation and counting a calculation result.

As shown in fig. 2, the step 2) of completing the probabilistic power flow calculation and counting the calculation result includes the specific steps of:

step 2.1), obtaining N groups of load and generator output data with enough quantity through Monte Carlo simulation:

step 2.2), each group of data is brought into deterministic load flow calculation:

step 2.3), obtaining load flow results of the N groups of power systems;

and 2.4) carrying out digital characteristic analysis on the load flow result, calculating the mean value, the variance and the like, and preparing for risk calculation.

And 3) completing risk assessment through a probability load flow calculation result.

And 3) completing risk assessment through a probability load flow calculation result, wherein the method specifically comprises the following steps:

step 3.1), calculating according to the calculation result of the step 2) by the ratio of the out-of-limit times to the total simulation times to obtain the out-of-limit probability, wherein the calculation formula is as follows:

in the formula: n is the Monte Carlo simulation times; m is the number of off-limits.

Step 3.2), severity S is expressed by the relative amount by which the voltage or current exceeds (or falls below) the limit. Voltage out-of-limit severity S_VThe calculation formula is as follows:

in the formula: s_VmaxSeverity of the upper voltage limit; v_maxIs the upper limit value of the voltage; s_VminSeverity of the lower limit of voltage; v_minIs the lower limit of the voltage.

Tidal current out-of-limit severity S_PThe calculation formula is as follows:

in the formula: s_PmaxThe severity of the trend is the upper limit; p_maxThe upper limit value of the power flow; s_PminThe severity of the lower limit of the trend; p_minIs the lower limit value of the power flow.

Step 3.3), the uncertainty risk is composed of the probability of the occurrence of the risk accident and the consequence of the occurrence of the risk accident, namely the severity of the accident. Thus, the risk is calculated as follows:

R＝P×S

in the formula: r is the quantitative risk degree of the event; p is the probability of the accident; and S is the severity after the accident occurs.

And 4) constructing a planning optimization model of the new energy grid-connected point by taking the system operation risk and the minimum economic loss caused by the occurrence of the risk accident as an objective function.

Step 4), the planning target of the power grid planning optimization model is as follows: the goal of planning is to try to minimize the risk of the grid and the economic losses that occur when a risk accident occurs. The economic loss comprises load shedding loss caused by power flow out-of-limit, capacity cost brought by reactive compensation adopted for voltage regulation and the like. The objective function is as follows:

in the formula: k is a radical of₁、k₂The weight coefficient represents the importance degree of two parts of the objective function; r_Vmaxi、R_VminjThe risk that the voltage of the node i is higher than the upper limit and the risk that the voltage of the node j is lower than the lower limit are respectively set; r_SkThe risk of the branch k out-of-limit tidal current; n1, N2 and L1 are respectively a node set which can cause voltage exceeding and limiting and a branch set which can cause power flow exceeding; c_V、C_SThe economic losses caused by voltage out-of-limit and power flow out-of-limit respectively occur, and the calculation modes of the two are as follows:

C_V＝ΣQ_CC’₀

in the formula: p_kIs the active power of line k; l is₁The branch set which is possible to have the power flow out-of-limit is selected;is the line active upper limit; c₀Is the electricity price; q_cThe reactive capacity required for regulating the voltage is obtained by load flow calculation; c'₀The cost required for a unit of reactive compensation capacity.

And 5) improving the constraint condition based on a blind number theory.

Step 5) the improvement of the constraint condition based on the blind number theory is as follows:

step 5.1), establishing a blind number BM model.

The basic definition of the blind number is as follows:

let G be a set of regular ash numbers, α_iE.g. G, real number T_i∈[0，1]Then, there are:

when alpha is_iAre not equal to each other, andwhen f (x) is a blind number; t is_iIs x falls within alpha_iThe confidence level of (3). In practical engineering, x often cannot fall precisely on α_iAbove, but falls within α_iSo that x falls on an interval, α_iIs a compartment type gray number.

In the process of optimizing and planning the power grid, various complex operations are required, and the comparison of the blind numbers is involved. Therefore, a blind number BM model is established.

Let A, B be two blind numbers:

p (A-B > beta) is called BM model of blind number. In this embodiment, the case where β ═ 0, i.e., P (a-B > 0), is only used, and the confidence level of a > B is represented, and the calculation of the BM model is shown in the following formula:

in practical application, the larger the value of P (A-B > 0), the higher the credibility of the blind information of A > B, the more credible; otherwise, the lower the confidence level, the less confidence.

And 5.2) improving the constraint condition of the power grid planning model based on a blind number theory. The improved constraints are as follows. The first two formulas are power balance constraints and respectively represent active balance and reactive balance. The last three formulas are reliability constraints, and the higher the reliability is, the higher the reliability is.

In the formula:is a blind number load flow on a line connected with the node i (the same reactive principle is not described again);the load at the node i and the output of the generator are represented by blind numbers (the same reactive theory is not repeated); l (i) denotes a set of branches connected to node i;respectively representing the blind number power flow and the power flow upper limit of the branch;the upper and lower voltage limits of the node, respectively;is the node voltage, expressed in blind numbers; t is the credibility; l is_o、N_oIs the set of all branches and nodes.

Step 5.3), the construction method of the blind number model comprises the following steps: and establishing a ten-order blind number model, and dividing possible values of power into ten intervals corresponding to ten gray scale intervals. The confidence level of each gray scale interval is represented by the probability that the power falls on that interval.

And 6) solving the model by improving a genetic algorithm to obtain optimal access schemes under different credibility, and obtaining a planning scheme with optimal comprehensive benefit indexes by indiscriminate selection.

Step 6) the algorithm is improved, and the specific implementation process of comprehensive benefit comparison and selection is as follows:

step 6.1), improvement of genetic algorithm. The improvement comprises two aspects of calculation of fitness and selection of variation rate.

And calculating the fitness. In the power grid optimization planning of this embodiment, the objective function is risk and economic loss of the power grid, and in order to make the objective function larger, the fitness lower, a little improvement needs to be performed on the fitness. Fitness is calculated as follows:

fit(x)＝K-f(x)

in the formula: fit (x) is fitness; k is a given large number and is larger than the maximum value of the objective function, so that the fitness is ensured to be larger than 0.

And (4) selecting the variation rate. When the inheritance frequency is lower, the mutation rate is increased; when the inheritance frequency is larger, the mutation rate is reduced; for the offspring with high fitness, no mutation is carried out, so that excellent characters are maintained; for individuals with low fitness, the individual is mutated, and a better solution is conveniently found.

And 6.2) solving a ten-order blind number model of the new energy grid-connected point power grid planning through a genetic algorithm to obtain the optimal access scheme under different credibility.

And 6.3) completing comparison and selection work among the optimal access schemes under different credibility through comprehensive benefit indexes to obtain the optimal new energy grid-connected access scheme.

The calculation mode of the comprehensive benefit index is as follows:

in the formula: f is an objective function value of the model; t is a reliability value, and reflects the reliability degree of the system; the index can comprehensively compare the reliability and the target function of the scheme, and the larger the eta is, the better the scheme is.

While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention.