CN104021502B - Electrical-network load loss risk estimation method suitable for windy and rainy weather - Google Patents

Abstract

The invention discloses an electrical-network load loss risk estimation method suitable for windy and rainy weather, belonging to the technical field of risk estimation of power system. The method comprises the steps that data in the aspects of windy and rainy weather and electrical-network failure tripping is collected, the line failure rate under the windy and rainy weather condition is obtained, and further a power system operation risk estimation model under the windy and rainy weather condition is established; the load-loss probability, the load-loss quantity, the line power and the node voltage under a load loss state are calculated; and different load loss states are combined to obtain the load reduction index, line overload risk value and low-voltage risk value of the power system under the windy and rainy weather condition. The method is especially used for risk estimation when the electrical network loses load under the windy and rainy weather condition, the risk during load loss of the electrical network to be estimated under the windy and rainy weather condition is mastered, risk estimation for the electrical network under the windy and rainy weather condition can be carried out, and safe operation of the electrical network can be ensured.

Description

Power grid load loss risk assessment method suitable for weather conditions

Technical Field

The invention relates to the technical field of risk assessment of power systems, in particular to a power grid load loss risk assessment method suitable for wind and rain weather conditions.

Background

Currently, power system evaluation methods have been widely studied. The method is mainly divided into three categories: a certainty assessment method, a probabilistic assessment method, a risk assessment method. Deterministic evaluation methods generally place only the most severe and trusted incidents in value; the probabilistic method does not quantize the consequences of the accident by specific indexes; the risk assessment method considers the possibility of accidents and the severity of consequences, carries out quantitative assessment on uncertainty factors in the operation of the power system, and comprehensively coordinates the safety and the economy of the power system.

However, the current risk assessment method in the aspect of the power system is mainly completed by the following four steps: the first step is to obtain the operation data and state of the power system; secondly, selecting an expected fault set and analyzing the faults; judging the consequences of the expected faults on the power system, entering the fourth step if the power supply risk occurs, and returning to the second step if the power supply risk does not occur; and fourthly, calculating a risk index, and carrying out risk prompt according to the index. The risk assessment method carries out quantitative risk assessment on uncertain factors in the power system and carries out risk grade division according to the size of risk indexes. However, the risk assessment method selects an expected fault set, has certain subjectivity and certainty, and is insufficient in random consideration of faults of the power system, so that risk assessment cannot be performed on power grid load loss under the weather conditions of wind and rain, the risk condition of the power grid load loss cannot be comprehensively mastered, and power grid disastrous accidents can be caused when the power grid load loss risk is serious.

Chinese patent publication No. CN103632310A, published as 3/12/2014, discloses a large power grid operation risk assessment method, which includes the following steps: 1) failure and risk factor statistics; 2) calculating risk probability; 3) risk quantitative assessment based on load loss; 4) grading the risk index and evaluating the result. The large power grid operation risk assessment method does not aim at risk assessment when the power grid is unloaded under the weather condition of wind and rain, and cannot master the risk condition when the power grid is unloaded under the weather condition of wind and rain, and power grid disastrous accidents can be caused when the power grid load loss risk is serious under the weather condition of wind and rain.

Disclosure of Invention

The invention provides a risk assessment method applicable to power grid load loss under the weather conditions, aiming at solving the defects that the existing risk assessment method in the aspect of power systems does not aim at risk assessment when a power grid is in load loss under the weather conditions, cannot master the risk condition when the power grid is in load loss under the weather conditions, and is easy to cause power grid disastrous accidents.

In order to achieve the purpose, the invention adopts the following technical scheme:

a power grid load loss risk assessment method suitable for weather conditions comprises the following steps:

(1-1) acquiring historical records of meteorological data, line data, generator data and load data monitored by an evaluated power grid in real time;

(1-2) establishing an element fault rate calculation model of the evaluated power grid under the weather condition, and calculating the element fault rate under the weather condition according to the element fault rate calculation model;

(1-3) extracting the fault state of the power system under the weather condition of wind and rain by adopting a Monte Carlo method, and calculating the accident probability of the power system according to the fault state of the power system and the element fault rate under the weather condition of wind and rain to obtain the accident probability of the power system of the power grid to be evaluated;

(1-4) carrying out optimal load loss calculation under the fault state of the power system to obtain optimal load loss amount;

(1-5) calculating a series of risk indexes of the power system under the weather condition, and performing risk evaluation on the power system under the weather condition according to the risk indexes to obtain a risk evaluation result of the power system under the weather condition;

and (1-6) analyzing a risk evaluation result of the power system under the weather condition to obtain a power system operation control strategy of the evaluated power grid after the power grid is unloaded under the weather condition.

According to the scheme, the risk assessment method and the system are specially used for risk assessment when the power grid is unloaded under the weather condition of wind and rain, and the risk condition when the assessed power grid is unloaded under the weather condition of wind and rain is mastered, so that the risk assessment is performed on the power grid under the weather condition of wind and rain, and the safe operation of the power grid is guaranteed. The scheme simulates uncertainty and randomness of operation of the evaluated power grid under the weather condition, and the optimal nonlinear programming model is utilized to comprehensively evaluate the power grid. Firstly, collecting data in the aspects of weather and power grid barrier trip, solving the element fault rate under the weather condition, and further establishing a power system operation risk evaluation model under the weather condition; then calculating the load loss probability, the load loss amount, the line power and the node voltage in the load loss state; and finally, integrating each load loss state to obtain a load reduction index, a line overload risk value and a low voltage risk value of the power system under the weather condition, and comprehensively evaluating the power supply reliability degree of each link of the power grid so as to find out weak links of the power system under the weather condition and take targeted protection measures.

Preferably, the meteorological data comprise the wind speed v and the rainfall p of the climate zone where the evaluated power grid is located;

the line data comprises lines of the evaluated gridFailure times n of the circuit in one statistical period hour, MTTR of outage hour, per unit resistance value r, per unit reactance value x, per unit admittance b to ground, line length l, transmission capacity S_l；

The generator data comprises normal operation hour MTTF, shutdown hour MTTR, power plant to which the generator belongs, capacity P of each generator for supplying power to the evaluated power grid_GOutput reactive lower limit Q_GminAnd upper limit Q_Gmax；

The load data comprises the maximum value P of the active load of each transformer substation in the statistical period hour_dAnd maximum value of reactive load Q_d。

Preferably, the failure rate λ of the element under weather conditions_mThe calculation formula of (2) is as follows:

${\mathrm{\λ}}_m={\mathrm{\λ}}_m^{\′}\frac{N_m+S_m}{S_m}{F}_m={\mathrm{\λ}}_m^{\′}\frac{\underset{i}{\Σ}{n}_i+\underset{i}{\Σ}{s}_i}{\underset{i}{\Σ}{s}_i}{F}_m---\left(1\right),$

wherein λ is_mIs the element failure rate of element m under weather conditions; lambda [ alpha ]_m' is the mean failure rate for long term operation of element m under normal climatic conditions; n is a radical of_mIs the expected number of days of continuous operation of element m under normal climatic conditions; s_mIs the expected number of days of continuous operation of element m in windy and rainy weather conditions; f_mIs the percentage of the failure of the element m under the weather conditions, F is more than or equal to 0_mThe number of times or days of the fault under the weather condition of wind and rain is firstly calculated and then the ratio of the number of times or days of the fault is obtained; n is_iIs the number of days of continued operation of element m under the ith normal climate condition; s_iIs the number of days of continued operation of element m in the ith weather condition.

Preferably, different power system fault states resulting from failure of one or more components in a weather condition are extracted and the duration of each power system fault state is recorded;

assuming that the total number of elements of the evaluated grid power system is N_cAnd the power system accident caused by the shutdown of any element m is marked as E_mThen, the power system accident E_mProbability of power system accident occurring P (E)_m) The calculation formula of (2) is as follows:

$P\left(E_m\right)=\frac{{\mathrm{\λ}}_m}{{\mathrm{\λ}}_m+{\mathrm{\μ}}_m}\underset{n\≠m}{\Π}(1-\frac{{\mathrm{\λ}}_n}{{\mathrm{\λ}}_n+{\mathrm{\μ}}_n}),(m=1,2,...,N_c;n=1,2,...,N_c)---\left(2\right),$

wherein, mu_mIs the repair rate of one element m in the total number of elements under the weather condition; mu.s_nIs the repair rate of another element n in the total number of elements in the weather condition; lambda [ alpha ]_mIs the element failure rate of element m under weather conditions; lambda [ alpha ]_nIs the failure rate of one of the other n elements in the total number of elements in a weather climate.

Preferably, the node voltage and the line power of the power system are calculated by respectively adopting an optimal nonlinear programming model based on alternating current power flow for different power system fault states under the extracted weather conditions;

the optimal nonlinear programming model based on the alternating current power flow is as follows:

$C_i=\underset{i=1}{\overset{n}{\Σ}}(P_{di}-P_{li})---\left(3\right),$

$\begin{array}{cc}s.t.& \underset{j=1}{\overset{n}{\Σ}}{U}_i{U}_j(g_{ij}{\mathrm{cos\θ}}_{ij}+b_{ij}{\mathrm{sin\θ}}_{ij})+P_{li}-P_{gi}=0\end{array}---\left(4\right),$

$\underset{j=1}{\overset{n}{\Σ}}{U}_i{U}_j(g_{ij}{\mathrm{sin\θ}}_{ij}-b_{ij}{\mathrm{cos\θ}}_{ij})+Q_{li}-Q_{gi}=0---\left(5\right),$

0≤P_li≤P_di，0≤Q_li≤Q_di(6)，

U_imin≤U_i≤U_imax(7)，

P_gimin≤P_gi≤P_gimax，Q_gimin≤Q_gi≤Q_gimax(8)，

$P_{ij}^2+Q_{ij}^2\≤S_{ijmax}^2---\left(9\right),$

$\left\{\begin{array}{c}{P}_{ij}=U_i{U}_j(g_{ij}{\mathrm{cos\θ}}_{ij}+b_{ij}{\mathrm{sin\θ}}_{ij})-U_i^2{g}_{ij}\\ Q_{ij}=-U_i{U}_j(b_{ij}{\mathrm{cos\θ}}_{ij}-g_{ij}{\mathrm{sin\θ}}_{ij})+U_i^2{b}_{ij}\end{array}\right.---\left(10\right),$

wherein, C_iIs the minimum load loss, P_diIs the active power before load shedding of node i, P_liIs the active power, Q, of the node i after load shedding_diIs reactive power, Q, before load shedding at node i_liIs reactive power, U, after load reduction of node i_i、U_jIs the voltage of node i, j, θ_ijIs the phase angle difference between nodes i, j, P_gi、P_gimax、P_giminIs the active power of the generator at node i and its upper and lower limits, Q_gi、Q_gimax、Q_giminIs the reactive power of the generator at node i and its upper and lower limits, S_ijmaxIs the line transmission capacity, P_ijIs the active power of branch ij, Q_ijIs the reactive power of branch ij, U_imax、U_iminIs the upper and lower limits of the voltage at node i, b_ijIs the line susceptance, g, between nodes i and j_ijIs the line conductance between nodes i and j;

equation (3) is an optimally planned objective function, representing the minimum loss load; equation (4) is an alternating current power flow equation, representing the active power constraint of the power balance equation; equation (5) is an alternating current power flow equation, representing the reactive power constraint of the power balance equation; the upper and lower bounds of the active power and the reactive power of the load nodes are restrained after the load is lost in the formula (6); equation (7) is the voltage upper and lower bound of the node; the formula (8) is the upper and lower bound constraint of the active power and the reactive power of the generator; the formula (9) is that the active power and the reactive power of the line are not out-of-limit constrained; formula (10) is line active and reactive;

in order to improve the calculation efficiency of the optimal nonlinear programming model, the node voltage and the line power of the power system are calculated by the formulas (4) and (5); if the line is not overloaded and the power flow is converged, no load loss calculation is carried out; and if the line is overloaded and the power flow is not converged, performing optimal nonlinear programming model calculation to obtain the optimal load loss of the evaluated power grid.

Preferably, the series of risk indicators for the power system in the rainy weather condition includes:

(6-1) load loss probability PLC index, the duration t of each power system fault state_iSubstituting the formula (11) for the power system load loss probability evaluation to obtain a load loss probability PLC index; the calculation formula of the load loss probability PLC index is as follows:

$PLC=\underset{i\∈S}{\Σ}\frac{t_i}{T}---\left(11\right),$

s in the formula (11) is a state set of the power system with load loss; t is the total simulated hours; adding the i load losing times to obtain the total load losing time, wherein the ratio of the total time to the simulated total time is the proportion of the load losing time to the total time, namely the load losing probability;

(6-2) loss load degree ELC index, which is the minimum loss load C of each power system in the failure loss load state under the weather condition_iSubstituting the formula (12) into the formula (12) to obtain the loss load degree ELC index of the power system under the total simulated hourly measured and estimated weather condition, wherein the calculation formula of the loss load degree ELC index is as follows:

$ELC=\frac{8760}{T}\underset{i\∈S}{\Σ}{C}_i---\left(12\right),$

the load loss degree ELC index is the total load loss number in the total simulation hours and is converted into the load loss value in the total simulation hours;

(6-3) Power supply adequacy EENS indicator relating duration t of each Power System Fault State_iAnd minimum unload amount C for each unload state_iSubstituting the formula (13) into the formula (13) to obtain the power supply adequacy EENS index of the power system under the condition of quantitative estimation of weather, wherein the calculation formula of the power supply adequacy EENS index is as follows:

$EENS=8760\underset{i\∈S}{\Σ}{C}_i\frac{t_i}{T}---\left(13\right),$

c in formula (13)_iThe load loss amount in the ith load loss state is multiplied by the duration hour of each load loss to obtain the power shortage generating amount;

(6-4) line overload risk R_OLmIndexes including accident probability P (Em) and line power P_ijSubstituting into equation (14) to obtain line overload risk R_OLmIndex, line overload risk R_OLmThe calculation formula of the index is as follows:

r in the formula (14)_OLmIs the overload risk of the line after the element m is out of service due to a fault under the weather condition; g₁Is a set of overload accident states of the power system under the weather conditions; k is the total number of lines; p_ijIs the tide in the line under weather conditions; p'_ijIs the line active power capacity;

(6-5) node Low Voltage Risk R_LVmIndexes including accident probability P (Em) and node voltage V_iSubstituting formula (15) to obtain node low voltage risk R_LVmIndex, node Low Voltage Risk R_LVmThe calculation formula of the index is as follows:

$R_{LVm}=\underset{E_m\∈G_2}{\Σ}P\left(E_m\right)\×\underset{i=1}{\overset{n}{\Σ}}(e^{V_0-V_i}-1),V_0-V_i>0---\left(15\right),$

in the formula (15), R_LVmIs the node low voltage risk after the element m has failed and stopped running under the weather conditions; g₂The method is characterized in that the method is a low-voltage accident state set of nodes of the power system under the weather conditions; n is the total number of nodes; v_iIs the actual node voltage at the time of line failure under the weather conditions; v₀Is the node voltage at which the line is operating normally.

The load loss probability PLC evaluates the possibility of load loss of the power system under the weather condition of wind and rain, and is more visual than the qualitative analysis of the probability of load loss based on the quantity standard. The power supply adequacy EENS index evaluates that the average annual shortage is caused when various faults occur in the power system under the weather conditionThe power supply capacity of the power system to be evaluated can be quantitatively obtained. Line overload risk R_OLmThe line overload risk caused by various faults of the power system under the weather condition is evaluated, so that the line overload risk value caused by each line fault is obtained, generally in the level of 10 < -5 > to 10 < -4 >, the line with the larger overload risk when the power system fails under the weather condition can be accurately positioned through the index, and a reference basis is provided for an operation department. Node low voltage risk R_LVmThe node low-voltage risk caused by various faults of the power system under the weather condition is evaluated, the node low-voltage risk value caused by each line fault is obtained through calculation and is generally in the grade of 10 < -5 > to 10 < -4 >, and when the power system fails, the node with high low-voltage risk under the weather condition can be conveniently located through the index. And performing risk evaluation on the power system under the weather condition according to various data obtained in the risk evaluation process to obtain a corresponding operation control strategy for power grid load loss risk evaluation under the weather condition.

Preferably, the optimal nonlinear programming model calculates the optimal load loss of the evaluated power grid by using a nonlinear solver (fmincon) based on a matlab optimization toolkit, and the calculation implementation process of the optimal load loss is as follows:

(7-1) selection of a form of fmincon to handle the nonlinear programming problem

X＝fmincon(FUN，X0，A，B，Aeq，Beq，LB，UB，NONLCON)；

(7-2) setting an unknown vector X, taking the unknown quantity in the optimal nonlinear programming model as a sub-vector of X, and assigning an initial value;

(7-3) setting upper and lower limits of the unknown vector X;

(7-4) writing a subfunction FUN with the minimum loss load amount as an objective function;

(7-5) writing an optimal nonlinear programming model processing sub-function NONLCON, and carrying out iterative solution on the value of the vector X obtained by each iteration;

and (7-6) calling the subfunctions FUN and NONLCON by fmincon to solve the minimum load loss amount, wherein the minimum load loss amount is the optimal load loss amount of the evaluated power grid under the weather condition.

The invention can achieve the following effects:

1. firstly, collecting data in the aspects of weather and power grid barrier trip, solving the element fault rate under the weather condition, and further establishing a power system operation risk evaluation model under the weather condition; then calculating the load loss probability, the load loss amount, the line power and the node voltage in the load loss state; and finally, integrating each load loss state to obtain a load reduction index, a line overload risk value and a low voltage risk value of the power system under the weather condition, and comprehensively evaluating the power supply reliability degree of each link of the power grid so as to find out weak links of the power system under the weather condition and take targeted protection measures.

2. Aiming at the risk evaluation of the power grid under the condition of wind and rain load loss, the risk condition of the evaluated power grid under the condition of wind and rain load loss is mastered, so that the risk evaluation of the power grid under the condition of wind and rain load loss is carried out, and the safe operation of the power grid is ensured.

3. The method simulates uncertainty and randomness of operation of the power grid to be evaluated under the weather conditions, and utilizes the optimal nonlinear programming model to comprehensively evaluate the power grid.

Drawings

FIG. 1 is a schematic block diagram of a process of the present invention.

Fig. 2 is a schematic diagram comparing the results of calculating the load loss probability of the ac power flow and the dc power flow according to the present invention.

Fig. 3 is a schematic diagram comparing the annual load loss of the ac power flow and the dc power flow calculation according to the present invention.

Fig. 4 is a schematic diagram comparing the results of calculating the expected value of the power shortage by the ac power flow and the dc power flow according to the present invention.

Fig. 5 is a schematic diagram of the accident probability of an outage line and system according to the present invention.

Fig. 6 is a schematic diagram of the outage line and system overload risk according to the present invention.

FIG. 7 is a schematic diagram of the risk of low voltage at the shutdown circuit and node according to the present invention.

Detailed Description

The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings.

Example (b): a method for evaluating the risk of power grid load loss under the weather conditions is disclosed, and referring to fig. 1, the method comprises the following steps:

(1-1) acquiring historical records of meteorological data, line data, generator data and load data monitored by an evaluated power grid in real time; the meteorological data comprise wind speed v and rainfall p of a climate area where the evaluated power grid is located; the line data comprises the failure times n of each line of the evaluated power grid within one statistical period hour, MTTR (maximum transmission time) of outage hours, unit resistance per unit value r, unit reactance per unit value x, unit admittance to ground b per unit value, line length l and transmission capacity S_l(ii) a The generator data comprises normal operation hour MTTF, shutdown hour MTTR, power plant to which the generator belongs, capacity P of each generator for supplying power to the evaluated power grid_GOutput reactive lower limit Q_GminAnd upper limit Q_Gmax(ii) a The load data comprises the maximum value P of the active load of each transformer substation in the statistical period hour_dAnd maximum value of reactive load Q_d。

(1-2) component failure rate meter for establishing evaluated power grid under weather conditionsThe calculation model is used for calculating the element failure rate under the weather condition according to the element failure rate calculation model; component failure rate λ under weather conditions_mThe calculation formula of (2) is as follows:

${\mathrm{\&lambda;}}_m={\mathrm{\&lambda;}}_m^{\&prime;}\frac{N_m+S_m}{S_m}{F}_m={\mathrm{\&lambda;}}_m^{\&prime;}\frac{\underset{i}{\&Sigma;}{n}_i+\underset{i}{\&Sigma;}{s}_i}{\underset{i}{\&Sigma;}{s}_i}{F}_m---\left(1\right),$

wherein λ is_mIs the element failure rate of element m under weather conditions; lambda [ alpha ]_m' is the mean failure rate for long term operation of element m under normal climatic conditions; n is a radical of_mIs the expected number of days of continuous operation of element m under normal climatic conditions; s_mIs an element under the weather conditionsm desired number of days of continuous operation; f_mIs the percentage of the failure of the element m under the weather conditions, F is more than or equal to 0_mThe number of times or days of the fault under the weather condition of wind and rain is firstly calculated and then the ratio of the number of times or days of the fault is obtained; n is_iIs the number of days of continued operation of element m under the ith normal climate condition; s_iIs the number of days of continued operation of element m in the ith weather condition.

(1-3) extracting the fault state of the power system under the weather condition of wind and rain by adopting a Monte Carlo method, and calculating the accident probability of the power system according to the fault state of the power system and the element fault rate under the weather condition of wind and rain to obtain the accident probability of the power system of the power grid to be evaluated; extracting different power system fault states formed by one or more element faults under the weather condition, and recording the duration of each power system fault state;

assuming that the total number of elements of the evaluated grid power system is N_cAnd the power system accident caused by the shutdown of any element m is marked as E_mThen, the power system accident E_mProbability of power system accident occurring P (E)_m) The calculation formula of (2) is as follows:

$P\left(E_m\right)=\frac{{\mathrm{\&lambda;}}_m}{{\mathrm{\&lambda;}}_m+{\mathrm{\&mu;}}_m}\underset{n\&NotEqual;m}{\&Pi;}(1-\frac{{\mathrm{\&lambda;}}_n}{{\mathrm{\&lambda;}}_n+{\mathrm{\&mu;}}_n}),(m=1,2,...,N_c;n=1,2,...,N_c)---\left(2\right),$

wherein, mu_mIs the repair rate of one element m in the total number of elements under the weather condition; mu.s_nIs the repair rate of another element n in the total number of elements in the weather condition; lambda [ alpha ]_mIs the element failure rate of element m under weather conditions; lambda [ alpha ]_nIs the failure rate of one of the other n elements in the total number of elements in a weather climate.

(1-4) carrying out optimal load loss calculation under the fault state of the power system to obtain optimal load loss amount; calculating node voltage and line power of the power system by respectively adopting an optimal nonlinear programming model based on alternating current power flow for different power system fault states under the extracted weather conditions;

the optimal nonlinear programming model based on the alternating current power flow is as follows:

$C_i=\underset{i=1}{\overset{n}{\&Sigma;}}(P_{di}-P_{li})---\left(3\right),$

$\begin{array}{cc}s.t.& \underset{j=1}{\overset{n}{\&Sigma;}}{U}_i{U}_j(g_{ij}{\mathrm{cos\&theta;}}_{ij}+b_{ij}{\mathrm{sin\&theta;}}_{ij})+P_{li}-P_{gi}=0\end{array}---\left(4\right),$

$\underset{j=1}{\overset{n}{\&Sigma;}}{U}_i{U}_j(g_{ij}{\mathrm{sin\&theta;}}_{ij}-b_{ij}{\mathrm{cos\&theta;}}_{ij})+Q_{li}-Q_{gi}=0---\left(5\right),$

0≤P_li≤P_di，0≤Q_li≤Q_di(6)，

U_imin≤U_i≤U_imax(7)，

P_gimin≤P_gi≤P_gimax，Q_gimin≤Q_gi≤Q_gimax(8)，

$P_{ij}^2+Q_{ij}^2\&le;S_{ijmax}^2---\left(9\right),$

$\left\{\begin{array}{c}{P}_{ij}=U_i{U}_j(g_{ij}{\mathrm{cos\&theta;}}_{ij}+b_{ij}{\mathrm{sin\&theta;}}_{ij})-U_i^2{g}_{ij}\\ Q_{ij}=-U_i{U}_j(b_{ij}{\mathrm{cos\&theta;}}_{ij}-g_{ij}{\mathrm{sin\&theta;}}_{ij})+U_i^2{b}_{ij}\end{array}\right.---\left(10\right),$

wherein, C_iIs the minimum load loss, P_diIs the active power before load shedding of node i, P_liIs the active power, Q, of the node i after load shedding_diIs reactive power, Q, before load shedding at node i_liIs reactive power, U, after load reduction of node i_i、U_jIs the voltage of node i, j, θ_ijIs the phase angle difference between nodes i, j, P_gi、P_gimax、P_giminIs the active power of the generator at node i and its upper and lower limits, Q_gi、Q_gimax、Q_giminIs the reactive power of the generator at node i and its upper and lower limits, S_ijmaxIs the line transmission capacity, P_ijIs the active power of branch ij, Q_ijIs the reactive power of branch ij, U_imax、U_iminIs the upper and lower limits of the voltage at node i, b_ijIs the line susceptance, g, between nodes i and j_ijIs the line conductance between nodes i and j;

equation (3) is an optimally planned objective function, representing the minimum loss load; equation (4) is an alternating current power flow equation, representing the active power constraint of the power balance equation; equation (5) is an alternating current power flow equation, representing the reactive power constraint of the power balance equation; the upper and lower bounds of the active power and the reactive power of the load nodes are restrained after the load is lost in the formula (6); equation (7) is the voltage upper and lower bound of the node; the formula (8) is the upper and lower bound constraint of the active power and the reactive power of the generator; the formula (9) is that the active power and the reactive power of the line are not out-of-limit constrained; formula (10) is line active and reactive;

in order to improve the calculation efficiency of the optimal nonlinear programming model, the node voltage and the line power of the power system are calculated by the formulas (4) and (5); if the line is not overloaded and the power flow is converged, no load loss calculation is carried out; and if the line is overloaded and the power flow is not converged, performing optimal nonlinear programming model calculation to obtain the optimal load loss of the evaluated power grid.

The optimal nonlinear programming model adopts a nonlinear solver (fmincon) based on a matlab optimization toolkit to calculate the optimal load loss of the evaluated power grid, and the calculation implementation process of the optimal load loss is as follows:

(7-1) selection of a form of fmincon to handle the nonlinear programming problem

X＝fmincon(FUN，X0，A，B，Aeq，Beq，LB，UB，NONLCON)；

(7-2) setting an unknown vector X, taking the unknown quantity in the optimal nonlinear programming model as a sub-vector of X, and assigning an initial value;

(7-3) setting upper and lower limits of the unknown vector X;

(7-4) writing a subfunction FUN with the minimum loss load amount as an objective function;

(7-5) writing an optimal nonlinear programming model processing sub-function NONLCON, and carrying out iterative solution on the value of the vector X obtained by each iteration;

and (7-6) calling the subfunctions FUN and NONLCON by fmincon to solve the minimum load loss amount, wherein the minimum load loss amount is the optimal load loss amount of the evaluated power grid under the weather condition.

(1-5) calculating a series of risk indexes of the power system under the weather condition, and performing risk evaluation on the power system under the weather condition according to the risk indexes to obtain a risk evaluation result of the power system under the weather condition; a set of risk indicators for an electrical power system in windy and rainy weather conditions includes:

(6-1) load loss probability PLC index, the duration t of each power system fault state_iSubstituting the formula (11) for the power system load loss probability evaluation to obtain a load loss probability PLC index; the calculation formula of the load loss probability PLC index is as follows:

$PLC=\underset{i\&Element;S}{\&Sigma;}\frac{t_i}{T}---\left(11\right),$

s in the formula (11) is a state set of the power system with load loss; t is the total simulated hours; adding the i load losing times to obtain the total load losing time, wherein the ratio of the total time to the simulated total time is the proportion of the load losing time to the total time, namely the load losing probability;

(6-2) loss load degree ELC index, which is the minimum loss load C of each power system in the failure loss load state under the weather condition_iSubstituting the formula (12) into the formula (12) to obtain the loss load degree ELC index of the power system under the total simulated hourly measured and estimated weather condition, wherein the calculation formula of the loss load degree ELC index is as follows:

$ELC=\frac{8760}{T}\underset{i\&Element;S}{\&Sigma;}{C}_i---\left(12\right),$

the load loss degree ELC index is the total load loss number in the total simulation hours and is converted into the load loss value in the total simulation hours;

(6-3) Power supply adequacy EENS indicator relating duration t of each Power System Fault State_iAnd minimum unload amount C for each unload state_iSubstituting the formula (13) into the formula (13) to obtain the power supply adequacy EENS index of the power system under the condition of quantitative estimation of weather, wherein the calculation formula of the power supply adequacy EENS index is as follows:

$EENS=8760\underset{i\&Element;S}{\&Sigma;}{C}_i\frac{t_i}{T}---\left(13\right),$

c in formula (13)_iThe load loss amount in the ith load loss state is multiplied by the duration hour of each load loss to obtain the power shortage generating amount;

(6-4) line overload risk R_OLmIndexes including accident probability P (Em) and line power P_ijSubstituting into equation (14) to obtain the line overload windDanger R_OLmIndex, line overload risk R_OLmThe calculation formula of the index is as follows:

r in the formula (14)_OLmIs the overload risk of the line after the element m is out of service due to a fault under the weather condition; g₁Is a set of overload accident states of the power system under the weather conditions; k is the total number of lines; p_ijIs the tide in the line under weather conditions; p'_ijIs the line active power capacity;

(6-5) node Low Voltage Risk R_LVmIndexes including accident probability P (Em) and node voltage V_iSubstituting formula (15) to obtain node low voltage risk R_LVmIndex, node Low Voltage Risk R_LVmThe calculation formula of the index is as follows:

$R_{LVm}=\underset{E_m\&Element;G_2}{\&Sigma;}P\left(E_m\right)\&times;\underset{i=1}{\overset{n}{\&Sigma;}}(e^{V_0-V_i}-1),V_0-V_i>0---\left(15\right),$

in the formula (15), R_LVmIs the node low voltage risk after the element m has failed and stopped running under the weather conditions; g₂The method is characterized in that the method is a low-voltage accident state set of nodes of the power system under the weather conditions; n is the total number of nodes; v_iIs the actual node voltage at the time of line failure under the weather conditions; v₀Is the node voltage at which the line is operating normally.

And (1-6) analyzing a risk evaluation result of the power system under the weather condition to obtain a power system operation control strategy of the evaluated power grid after the power grid is unloaded under the weather condition.

The risk assessment method is specially used for risk assessment when the power grid is under the condition of wind and rain, and the risk condition when the assessed power grid is under the condition of wind and rain is mastered, so that the risk assessment is performed on the power grid under the condition of wind and rain, and the safe operation of the power grid is guaranteed. The embodiment simulates uncertainty and randomness of operation of the power grid to be evaluated under the weather condition of wind and rain, and the optimal nonlinear programming model is utilized to comprehensively evaluate the power grid. Firstly, collecting data in the aspects of weather and power grid barrier trip, solving the element fault rate under the weather condition, and further establishing a power system operation risk evaluation model under the weather condition; then calculating the load loss probability, the load loss amount, the line power and the node voltage in the load loss state; and finally, integrating each load loss state to obtain a load reduction index, a line overload risk value and a low voltage risk value of the power system under the weather condition, and comprehensively evaluating the power supply reliability degree of each link of the power grid so as to find out weak links of the power system under the weather condition and take targeted protection measures. Loss of load profileThe rate PLC evaluates the possibility of load loss of the power system under the weather condition of wind and rain, and is more intuitive than qualitative analysis of the probability of load loss based on the quantity standard. The power supply adequacy EENS indexes evaluate the average annual power shortage when various faults occur in the power system under the weather condition, and the power supply capacity of the evaluated power system can be quantitatively obtained. Line overload risk R_OLmThe line overload risk caused by various faults of the power system under the weather condition is evaluated, so that the line overload risk value caused by each line fault is obtained, generally in the level of 10 < -5 > to 10 < -4 >, the line with the larger overload risk when the power system fails under the weather condition can be accurately positioned through the index, and a reference basis is provided for an operation department. Node low voltage risk R_LVmThe node low-voltage risk caused by various faults of the power system under the weather condition is evaluated, the node low-voltage risk value caused by each line fault is obtained through calculation and is generally in the grade of 10 < -5 > to 10 < -4 >, and when the power system fails, the node with high low-voltage risk under the weather condition can be conveniently located through the index. And performing risk evaluation on the power system under the weather condition according to various data obtained in the risk evaluation process to obtain a corresponding operation control strategy for power grid load loss risk evaluation under the weather condition.

Step 1 is implemented: and acquiring measured data. And collecting climate data, line data, generator data and load data of the evaluated power grid, wherein the specific measured data is shown in table 1. The number of days that the ith wind speed v is more than 14m/S or the rainfall p is more than 25mm is S_iElement m is S within 5 years_iSumming to obtain S_m. According to the statistical n and n_sDetermine a ratio F_m. The invention takes an IEEE-RTS79 reliability test system as an implementation example.

Table 1 measured data for risk assessment under weather conditions

Step 2 is implemented: and calculating the failure rate of the elements under the weather conditions. And (3) establishing a calculation formula of the element fault rate under the weather condition as shown in the formula (1) to calculate the element fault rate under the weather condition.

Step 3 is implemented: and calculating the accident probability of the power system of the evaluated power grid. And (3) extracting the fault states of the power system under a large number of weather conditions by combining the fault rate of the elements, and calculating the accident probability of the power system according to the formula (2).

And (4) implementing the step: and calculating the optimal load loss amount. In this example, 10 fault lines with the largest accident probability of the power system in the weather are selected, as shown in table 2:

table 2 probability of power system accident under weather conditions (10)^-3)

Accident	2	2	9	2	3	3	4
								Accident	2	1	1	1	1	1	1
Accident	5	3	1
								Accident	0	0	0

And (3) sequentially judging whether the fault state of each power system has the risk of power flow unconvergence or line power out-of-limit on the basis of the implementation of the step (3), and if so, calculating the optimal load loss by using the alternating current power flow and the optimal nonlinear programming model.

And 5, implementation step: a series of risk assessment indicators are calculated. The load loss risk, line overload risk and low voltage risk values were calculated on the basis of the implementation of steps 3, 4, and the results are shown in tables 3, 4 and 5.

TABLE 3 calculation results of loss of load risk indicators in windy and rainy weather conditions

Table 4 lines with greater risk of overloading the power system lines in windy and rainy weather conditions (10)^-5)

Accident	3	1	1	3	1
						Overload	4	7	0	3	2

Table 5 line (10) with large low voltage risk value of power system under weather conditions^-5)

Accident line	3	2	1	3	2	3	4
								Low voltage	1	9	5	3	2	2	1
Accident line	6	8	1
								Low voltage	1	0	0

Table 3 is a loss of load risk indicator for operation on an IEEE-RTS79 system, which shows that the ac method used in the present invention is superior to the dc method. As can be seen from the table, the calculation results of the dc method and the ac method are different, which is theoretically true, and the index obtained by the dc method has a deviation of about 5% from the dc standard, and is within an acceptable allowable range.

It can be seen from fig. 2 that the results of the loss load PLC index calculated by the direct current method and the alternating current method are both slightly smaller than the standard result, the deviation between the alternating current method and the standard is larger when the simulation time is relatively short, and the convergence trend is that the alternating current method is better than the direct current method and the deviation of the alternating current method is smaller than the deviation of the direct current method along with the increase of the simulation time, which indicates that the calculation result of the PLC index of the present invention is more ideal.

It can be seen from fig. 3 that the average annual loss ELC index is slightly larger than the dc standard calculation result, and the deviation tends to increase slightly as the simulation time increases. The deviation of the calculation result of the alternating current method and the standard of the alternating current method is smaller than that of the direct current method, and the convergence trend is consistent with the standard of the alternating current method along with the increase of the simulation time, so that the calculation result of the ELC index is more ideal.

It can be seen from fig. 4 that the average annual power shortage expected value EENS index calculated by the alternating current method is obviously superior to the direct current method, the alternating current method has smaller standard deviation and the convergence trend is consistent with the standard no matter the simulation time is long, and the calculation result of the EENS index is relatively ideal.

The invention uses an exchange method to obtain the risk index, and the tables 4 and 5 respectively list the fault line with larger risk value.

And 6, implementation step: and analyzing the risk evaluation result to obtain an operation control strategy. Tables 2, 4 and 5 reflect the complexity of the risk of the power system after different line faults under the influence of weather conditions: 1) when the accident probability of the system is high after the line is tripped, the risk of the system is not necessarily high, such as No. 21, No. 23, No. 27 and No. 35 lines; 2) the overload risk is large when the accident probability of the system after the line is tripped is small, such as No. 12, No. 18 and No. 38 lines; 3) the low voltage risk is not large when the overload risk is large after the line is tripped, such as No. 12, No. 31 and No. 38 lines; 4) the overload risk is large when the accident probability of the system is large after the line is tripped, such as a No. 31 line; 5) when the accident probability of the system is high after the line is tripped, the low voltage risk is high, such as No. 4, No. 10 and No. 36 lines.

In order to more clearly analyze the calculation result of the risk assessment of the power system under the weather conditions, the accident probability, the overload risk and the low voltage risk of the power system are specifically analyzed below.

Fig. 5 lists the 10 lines with the highest probability of system accident after line trip, and the line sequence is: 27>21>9>23 ═ 36>35>4>5>31>10, and the system accident probability value after the line fault tripping is between 0.0005 and 0.0025; fig. 6 lists 5 lines with relatively large system overload risk due to outage, and the line sequence is: 31>18>12>38>11, and the overload risk value after the line fault tripping is between 0.000002 and 0.00045; fig. 7 lists the 10 lines with the greatest risk of low voltage due to outage, with the line ordering: 36>25>10>32>29 ═ 37>4>6>8>

18, the low voltage risk value after the line faults trip is between 0.00002 and 0.0012.

From the above analysis, it is found that the overload risk value of the system after the failure shutdown of the No. 31 line is relatively large, the system accident probability is relatively large, and the risk of the power transmission overload of the line is relatively large; the system accident probability is relatively high after the No. 4, 10 and 36 line faults are shut down, and the low voltage risk is relatively high. Line No. 31 connects node 17 and node 22, and node 22 has generator access, and node 17 is a connected node. The line fault rate of line number 31 obtained from the IEEE-RTS79 system was 0.54 times/year (see table 6).

TABLE 6 line Fault Rate List

As can be seen from table 6, line No. 31 is the line with the largest fault rate, and when it is tripped and shut down, power is transferred to other lines, which easily causes line overload; after the lines 4, 10 and 36 are tripped, the system has a high risk of low voltage, and a large amount of load is lost to recover the system voltage to an acceptable range. The 5 transmission lines are weak links of the power transmission network and need to pay attention.

No. 18, 12 and 38 lines which cause relatively large overload risks after outage; the lines 25, 32, 29, 37, 4 and 6, which cause relatively great risk of low voltage after shutdown, are monitored and managed in a reinforced way. For line trip faults, strong measures must be taken to strengthen the precautions: 1) the overhaul of the dangerous branch is enhanced, the relay protection of the power transmission line is enhanced, and the probability of the broken line of the dangerous branch is reduced; 2) and reducing a proper amount of load near the dangerous branch with a fault so as to restore the low-voltage risk value of the system to a normal range without generating great influence on the normal operation of the system.

The embodiments of the present invention have been described above with reference to the accompanying drawings, but the implementation is not limited to the above-described embodiments, and those skilled in the art can make various changes or modifications within the scope of the appended claims.

Claims (5)

1. A power grid load loss risk assessment method suitable for weather conditions is characterized by comprising the following steps:

(1-1) acquiring historical records of meteorological data, line data, generator data and load data monitored by an evaluated power grid in real time;

(1-2) establishing an element fault rate calculation model of the evaluated power grid under the weather condition, and calculating the element fault rate under the weather condition according to the element fault rate calculation model;

(1-3) extracting the fault state of the power system under the weather condition of wind and rain by adopting a Monte Carlo method, and calculating the accident probability of the power system according to the fault state of the power system and the element fault rate under the weather condition of wind and rain to obtain the accident probability of the power system of the power grid to be evaluated;

(1-4) carrying out optimal load loss calculation under the fault state of the power system to obtain optimal load loss amount;

(1-5) calculating a series of risk indexes of the power system under the weather condition, and performing risk evaluation on the power system under the weather condition according to the risk indexes to obtain a risk evaluation result of the power system under the weather condition;

(1-6) analyzing a risk evaluation result of the power system under the weather condition to obtain a power system operation control strategy of the evaluated power grid after the power grid is unloaded under the weather condition;

the meteorological data comprises wind speed of a climate zone in which the power grid to be evaluated is locatedRainfall and rainfall；

The line data comprises the failure times of each line of the evaluated power grid within one statistical period hourHours of outagePer unit resistance per unit valuerUnit reactance per unit valueAdmittance to ground unitPer unit value, line lengthTransmission capacity；

Generator data includes the hours of normal operation of each generator supplying power to the grid under evaluationHours of outagePower plant and capacity of generatorLower limit of output reactive powerAnd upper limit of；

The load data comprises the maximum active load of each transformer substation within the hour statistical periodAnd maximum reactive load；

Component failure rate under weather conditionsThe calculation formula of (2) is as follows:

（1），

wherein,is an elementComponent failure rate under weather conditions;is an elementAverage failure rate for long term operation under normal climatic conditions;is a component under normal climatic conditionsExpected number of continuous operation days;is an element under the weather conditionsExpected number of continuous operation days;is an elementThe percentage of the fault occurring under the weather condition is more than or equal to 0The number of times or days of the fault under the weather condition of wind and rain is firstly calculated and then the ratio of the number of times or days of the fault is obtained;is the firstElements in sub-normal climatic conditionsNumber of days of continuous operation;is the firstElements in sub-weathered weather conditionsThe number of continuous operation days.

2. The method for evaluating the risk of power grid loss of load in the weather of the wind and rain according to claim 1, characterized in that different power system fault states caused by the fault of one or more elements in the weather of the wind and rain are extracted, and the duration of each power system fault state is recorded;

assuming the total number of elements of the evaluated grid power system isRandom elementPower system accidents caused by outages are recordedThen, power system accidentProbability of power system accidentThe calculation formula of (2) is as follows:

（2），

wherein,is one of the total number of elementsmRepair rate under weather conditions;is another element of the total number of elementsnRepair rate under weather conditions;is an elementComponent failure rate under weather conditions;is another element of the total number of elementsnComponent failure rate under weather conditions.

3. The method for evaluating the risk of power grid loss of load under the weather conditions of wind and rain according to claim 2, wherein node voltage and line power of the power system are calculated by respectively adopting an optimal nonlinear programming model based on alternating current power flow for different power system fault states under the extracted weather conditions of wind and rain;

the optimal nonlinear programming model based on the alternating current power flow is as follows:

=（3），

（4），

（5），

（6），

（7），

，（8），

(9)，

（10），

wherein,is the minimum amount of lost load,is a nodeThe active power before the load is cut off,is a nodeThe active power after the load reduction is carried out,is a nodeThe reactive power before the load is cut down,is a nodeThe reactive power after the load reduction is carried out,、is a node、The voltage of (a) is set to be,is a node、The phase angle difference between the two phases is small,、、is a nodeThe active power of the generator and the upper and lower limits thereof,、、is a nodeThe reactive power of the generator and the upper and lower limits thereof,is the transmission capacity of the line and,is a branch The active power of the power converter is set,is a branch The reactive power of (a) is,、is a nodeThe upper and lower limits of the voltage of (c),is a nodeAndthe electric susceptance of the line between the two,is a nodeAndthe line conductance between;

equation (3) is an optimally planned objective function, representing the minimum loss load; equation (4) is an alternating current power flow equation, representing the active power constraint of the power balance equation; equation (5) is an alternating current power flow equation, representing the reactive power constraint of the power balance equation; the upper and lower bounds of the active power and the reactive power of the load nodes are restrained after the load is lost in the formula (6); equation (7) is the voltage upper and lower bound of the node; the formula (8) is the upper and lower bound constraint of the active power and the reactive power of the generator; the formula (9) is that the active power and the reactive power of the line are not out-of-limit constrained; formula (10) is line active and reactive;

in order to improve the calculation efficiency of the optimal nonlinear programming model, the node voltage and the line power of the power system are calculated by the formulas (4) and (5); if the line is not overloaded and the power flow is converged, no load loss calculation is carried out; and if the line is overloaded and the power flow is not converged, performing optimal nonlinear programming model calculation to obtain the optimal load loss of the evaluated power grid.

4. The method as claimed in claim 3, wherein the risk of grid loss of load under windy and rainy weather conditions comprises:

(6-1) probability of loss of loadPLCIndex, duration of fault condition of each power systemSubstituting into formula (11) to evaluate the power system load loss probability and obtain the load loss probabilityPLCIndexes; probability of loss of loadPLCThe calculation formula of the index is as follows:

（11），

in the formula (11)SIs a set of states of the power system with lost load;Tis the total simulated hours; will be provided withAdding the load losing time to obtain the total load losing time, wherein the ratio of the total time to the simulated total time is the proportion of the load losing time to the total time, namely the load losing probability;

(6-2) loss load degree ELC index, which is the minimum loss load amount of each power system in the failure loss load state under the weather conditionSubstituting the formula (12) into the total simulation hour to obtain the loss load degree of the power system under the wind and rain climate condition of the quantitative estimationELCThe calculation formula of the index and the load loss degree ELC index is as follows:

（12），

the load loss degree ELC index is the total load loss number in the total simulation hours and is converted into the load loss value in the total simulation hours;

(6-3) Power supply adequacyEENSIndex, duration of fault condition of each power systemAnd minimum unload amount per unload stateSubstituting the formula (13) into the formula to obtain the power supply adequacy of the power system under the condition of quantitatively estimating the weatherEENSTarget, power supply adequacyEENSThe calculation formula of the index is as follows:

（13），

in the formula (13)Is the firstMultiplying the load loss amount of each load loss state by the duration of each load loss to obtain the power shortage generating amount;

(6-4) line overload riskIndex, probability of accident of power systemP (Em)And line powerSubstituting into equation (14) to obtain line overload riskIndex, line overload riskThe calculation formula of the index is as follows:

，（14），

in formula (14)Is an elementOverload risk of the line after failure outage under weather conditions;is a set of overload accident states of the power system under the weather conditions;is the total number of lines;is the tide in the line under weather conditions;is the line active power capacity;

(6-5) node Low Voltage RiskIndex, probability of accident of power systemP (Em)And node voltageSubstituting equation (15) to solve the node low voltage riskIndex, node low voltage riskThe calculation formula of the index is as follows:

，（15），

in the formula (15), the reaction mixture is,is an elementNode low voltage risk after failure outage under weather conditions;is a low voltage accident of a power system node under the weather conditionA set of states;is the total number of nodes;is the actual node voltage at the time of line failure under the weather conditions;is the node voltage at which the line is operating normally.

5. The method for evaluating the risk of power grid load loss under the weather conditions of the wind and rain according to claim 3 or 4, characterized in that the optimal nonlinear programming model calculates the optimal load loss of the evaluated power grid by using a nonlinear solver (fmincon) based on a matlab optimization toolkit, and the optimal load loss calculation is realized by:

(7-1) selecting form X = fmincon (FUN, X0, a, B, Aeq, Beq, LB, UB, nlcon) for fmincon to handle the nonlinear programming problem;

(7-2) setting an unknown vector X, taking the unknown quantity in the optimal nonlinear programming model as a sub-vector of X, and assigning an initial value;

(7-3) setting upper and lower limits of the unknown vector X;

(7-4) writing a subfunction FUN with the minimum loss load amount as an objective function;

(7-5) writing an optimal nonlinear programming model processing sub-function NONLCON, and carrying out iterative solution on the value of the vector X obtained by each iteration;

and (7-6) calling the subfunctions FUN and NONLCON by fmincon to solve the minimum load loss amount, wherein the minimum load loss amount is the optimal load loss amount of the evaluated power grid under the weather condition.