Electric power system adequacy analysis method based on Monte Carlo simulation method

Technical Field

The present invention relates to the field of power system analysis abundant , in particular to a kind of the electric power system based on Monte carlo simulation method for analyzing sufficient degree.

Background Art

abundant power system is in the system to the electric power system, output, transformer equipment rated capacity and voltage fluctuation to the extent permitted, consider element plans and non-planned stop and operation conditions to continuously provide to the user the capacity of the electric power and the electric energy demand. Indicators abundant reflected in the study period under static conditions in the power system in the system capacity to meet load power and electric energy the extent of the demand.

Experience has shown that, under disaster weather conditions the possibility of the malfunction of the components is greatly increased, because the power system high-voltage transmission line especially in the long distance transmission and distribution lines for a long time in the environment are in a complicated weather, the occurrence of a failure by the impact of weather change is very large, therefore, element of the original parameters, such as the failure rate is the function of the weather conditions.

A probability of occurrence of bad weather, although not high, but in adverse weather conditions to lower element of the marked increase in the failure, generating great and the damage of the elements, the electrical power grid and distribution network has a plurality of associated and dramatically increased the possibility of the malfunction of the associated, the so-called phenomenon of "fault aggregation". Therefore, in the electric power system to assess abundantabundant take into account the impact of the changes in the weather is very necessary.

The results of the evaluation of the power system by abundant the impact of weather changes, a very large, abundant of the assessment model is the focus of all studies. Consider the weather state established herein the mathematical model of the assessment abundant , the disaster weather system component under the conditions of the method for calculating the failure rate, and based on the component state duration of the Monte carlo simulation method for the samples, calculated results of the evaluation of the electric wire netting, to provide the basis of the power network analysis abundance.

Content of the invention

The purpose of this invention is to overcome the problems in the prior art of the above-mentioned deficiency, based on Monte carlo simulation provides a sufficient degree of analysis method for the electric power system.

In order to realize the purpose of the above-mentioned invention, the present invention provides the following technical scheme:

Monte carlo simulation method based on a sufficient degree of analysis method for electric power system, comprising the following steps:

Step a, the data forming system information collecting element: through the collection element in different weather conditions the number of times of failure, in a calendar year is calculated in units of the average value of the failure rate ;

Step b, the component state duration sampling forming system state sequence: the running state and the duration of the fault state of sampling, timing of sampling of the Monte carlo simulation method, power system element and the running time of a fault, the repair time compliant index distribution, according to the element to determine the failure rate and the recovery of the element in a given time period the duration of the state and condition, and then according to the electric power system in the given time period the state of all the elements the duration and state, to obtain the system of a state sequence and duration;

Step c, the electric power system to assess the state of the system within the: taking the state of the system in accordance with the time sequence in a sequence of a system state, into the fault evaluation process, and store the result of the evaluation; if the system state have assessed, then the read-in the state of the result of the evaluation; and state sequence in the system after the assessment is completed, the results of statistical assessment, calculating the corresponding indicators abundant ; the cutting load probability indicators include abundant P_PLC, the load frequency the year cuts F_EFLC, the load sustained the year cuts T_EDLC, each time the cutting load sustained T_ADLC, load ectomy expected value C_ELC, expected value insufficient power E_EENS;

Step d, to obtain power system fault severity: abundant through the system the result of calculation of the indicators, the fault severity of electric system, the power system fault severity level indicators S_SI, power system electric quantity indicators reduction I_BPECI and system indicators power I_BPII expressed.

Preferably, in said step a, the Through the equation Expressed, through transformation, obtained when a normal weather λ component failure rate and a desired value of the disaster weather λ when the expected value of the component failure rate ', that is, λ=λ^N+SN(1-F)λ′=λ^N+SSF,N to the desired duration of a normal weather, through the equation Computing, n_i for the duration of a normal weather, the expectations of the disaster weather S duration, through the equation Computing, s_i for the duration of the disaster weather, for a survey cycle T; F said fault occurs in the percentage of the disaster weather, said j said statistical period the number of times a certain weather conditions, is the range of its value j∈N.

Preferably, in said step b, component state duration sampling method adopts (Monte-Carlo) sequence of the Monte carlo simulation method.

Preferably, in said step c, said load probability P_PLC by the equation, Computing, the cutting load S as a set of system state; t_i i for the duration of the state of the system; the load frequency states the year to cut F_EFLC through equation F_EFLC = (8760/T) · N_i calculation, wherein N_i to a state of load; when the sustained load states the year to cut T_EDLC through equation T_EDLC = P_PLC × 8760 calculation; the each time the cutting load sustained T_ADLC through the equation Calculation; the load ectomy expected value C_ELC through the equation Computing, wherein C_i i to the state of the system the cutting load; expected value insufficient power E_EENS through the equation Computing, the system state i is a positive integer.

Preferably, in the step d, the reduction of the electric system the electric quantity indicators I_BPECI through equation I_BPECI = E_EENS/L calculation, wherein L is the maximum load in the electric system.

Preferably, in the step d, the serious degree indicators S_SI through equation S_SI = I_BPECI × 60 calculating preferred, in the step d, the system power-off indicators I_BPII through equation I_BPII = C_ELC/L calculation.

Compared with the prior art, the beneficial effect of the invention:

1, the invention is based on the electric power system of the Monte carlo simulation method to establish sufficient degree analysis that take into consideration the weather state of the mathematical model of the assessment abundant , the disaster weather system component under the conditions of the method for calculating the failure rate, and based on the component state duration of the Monte carlo simulation method for the samples, calculated results of the evaluation of the electric wire netting, to provide the basis of the power network analysis abundance.

2, this invention is based on the Monte carlo simulation method for analyzing power system adequate degrees ample degrees in the assessment process, obtained through the use of Monte carlo simulation sequence of the state of the system, and using storage technology, merging and state evaluation result of the state of the system, greatly reduces the state needs assessment, the efficiency is improved.

The Figure illustrates:

Figure 1 is a schematic diagram of the process of the invention is based on Monte carlo simulation method for analyzing power system adequate degrees.

Figure 2 is of random present Monte carlo simulation method of the invention is based on the electric power system adequate degrees in the analytical method of the T a statistical cycle of weather.

Figure 3 is graph of this invention is based on the Monte carlo simulation method for analyzing the power system cycle in sufficient degree within the T and a normal weather expected disaster weather.

Figure 4 is the electric power system in the analytical method of ample degrees state diagram of the power system elements based on Monte carlo simulation method of the present invention.

Mode of execution

Example binding assays below the specific embodiment of the invention for further detailed description. However, should not be interpreted that the scope of the present invention the above-mentioned subject embodiment of only limited to, the following, where the content of the invention-based technologies are realized by the scope of the invention.

Embodiment

A kind of the electric power system based on Monte carlo simulation method for analyzing sufficient degrees, as shown in Figure 1, comprises the following steps:

Step a, the data forming system information collecting element: through the collection element in different weather conditions the number of times of failure, in a calendar year is calculated in units of the average value of the failure rate ;

The Through the equation Expressed, through transformation, obtained when a normal weather λ component failure rate and a desired value of the disaster weather λ when the expected value of the component failure rate ', λ=λ^N+SN(1-F)λ′=λ^N+SSF,N the expected duration of a normal weather, through the equation Computing, n_i for the duration of a normal weather, the expectations of the disaster weather S duration, through the equation Computing, s_i for the duration of the disaster weather, for a survey cycle T; F said fault occurs in the percentage of the disaster weather;

A statistical cycle T of the random changes in the weather as shown in Figure 2, the period T and a normal weather expected value of relations disaster weather as shown in Figure 3.

Through the different values taking F λ and λ ' can know the result of calculation of the, element under the conditions of the failure rate of the disaster weather during normal weather conditions is far greater than the average failure rate the failure rate of, the disaster weather the system is more susceptible to malfunction.

Step b, the component state duration sampling forming system state sequence: component state duration sample time sequence of the Monte carlo simulation of the; power system element and the running time of a fault, the repair time compliant index distribution, according to the element to determine the failure rate and the recovery of the element in a given time period the duration of the state and condition, and then according to the electric power system in the given time period the state of all the elements the duration and state, to obtain the system of a state sequence and duration;

Sampling principle as shown in Figure 4, through the first A, B, of the three elements C running state and a fault state duration sample, obtaining system state and a state duration; Figure 4 the given time period in the simulation a total of 11 a system state, comprises 8 different system state, the same system state is that fault elements completely the same system state; as can be seen from the sampling principle, in the sequence of the state of the system the only difference between the two adjacent state of the state change is a single element, the state change means or element of the repair element failures; therefore can be changed into the multiple fault assessment on the basis of a state before carrying out the single fault assessment, such as state 4 is three heavy fault, can be in the state 3 on the basis of the fault assessment C single component, this can greatly simplifies assessment process multiple failure. Sample generated in the state of the system state of the system comprising a plurality of the same, and through the storage system to reduce state evaluation result of the state that requires the evaluation of the system, as shown in Figure 4 in state 10 can be directly read state 6 of the state assessment result, there is no need to re-computation.

Step c, the electric power system to assess the state of the system: the electric power system in the state of the various components after the sampling, a Monte carlo simulation model, taking the state of the system in accordance with the time sequence in a sequence of a system state, into the fault evaluation process, and store the result of the evaluation; if the system state have assessed, then the read-in the state of the result of the evaluation; and state sequence in the system after the assessment is completed, the results of statistical assessment, calculating the corresponding indicators abundant , the cutting load probability indicators include abundant P_PLC, the load frequency the year cuts F_EFLC, the load sustained the year cuts T_EDLC, each time the cutting load sustained T_ADLC, load ectomy expected value C_ELC, expected value insufficient power E_EENS;

Can be obtained through the evaluation results in the evaluation state sequence under fault conditions of the system, to provide a basis for abundant index calculation;

Said load probability P_PLC by the equation, Computing, the cutting load S as a set of system state; t_i i for the duration of the state of the system; the load frequency states the year to cut F_EFLC through equation F_EFLC = (8760/T) · N_i calculation, wherein N_i to a state of load; when the sustained load states the year to cut T_EDLC through equation T_EDLC = P_PLC × 8760 calculation; the each time the cutting load sustained T_ADLC through the equation Calculation; the load ectomy expected value C_ELC through the equation Computing, wherein C_i i to the state of the system the cutting load; expected value insufficient power E_EENS through the equation Computing;

The state of the system in several consecutive sequence of the system state have the cutting load, the continuous several with a cutting load system state as a with a cutting load state;

Sufficient degrees of the assessment objective is to obtain various possible power system the probability of the state of the situation and load, then statistical abundant indicators. In order to a detailed assessment of the impact of multiple failure, solves the contradiction of calculation speed and precision, is to minimize the one hand, requires the evaluation of the state number, on the other hand, we must try to accelerate each state assessment speed. By adopting the Monte carlo simulation method system state sequence obtained, using storage technology and, merging and state evaluation result of the state of the system, greatly reduces the state number needs assessment. The multiple fault assessment into the single fault assessment in order to accelerate the evaluation speed, but the need to ensure orders in the arbitrary state of the system in terms of both heavy fault restraining item the trend of the in take appropriate generator power adjustment and cutting load measures the loads in the element.

In the power system k any of the element, the element is the failure rate of the disaster weather λ '_k, X_k is its operation state, the X_k the probability function P (X_k) to

M is a component the electric power system includes, X_i = (X_i1, X_i2, …, X_ik, …, X_im) power system operation state that a sample, X_i the joint probability distribution function P (X_i) according to the equation Calculation.

Wherein the system component includes the various system equipment and different load level, the system equipment or circuit or transformer for the generator.

Step d, to obtain power system fault severity: power system fault severity by serious degree indicators S_SI, power system electric quantity indicators reduction I_BPECI and system indicators power I_BPII expressed, serious degree indicators S_SI through equation S_SI = I_BPECI × 60 computing, wherein I_BPECI reduction of quantity indicators for electric power system, said system failure caused by the reduction of the power supply point of the sum of the quantity of the maximum load of the power system the ratio of the year;

The reduction of the electric system the electric quantity indicators I_BPECI through equation I_BPECI = E_EENS/L calculation, wherein L is the maximum load in the electric system.

System power failure indicators I_BPII through equation I_BPII = C_ELC/L computing, system power failure indicators I_BPII fault in the power supply point to the system caused by the load reduction of the sum of the system the ratio of the maximum load, in the year that the load of each MW of average power megawatt number.

S_SI the power transmission system in that the maximum load of the whole system year accumulation time (in min), is the extent of the system failure metric of a serious.

Monte carlo simulation method according to the present invention is based on the electric power system adequate IEEE-RTS79 analysis process, the degree of the power transmission system to assess the sufficiency of degrees, including the whole network system 32 generators, 33 line, 5 transformer. The result of calculation of the system indicators abundant table 1 is shown in:

Table 1 different analog time sufficient degrees of the assessment results

By table 1 can be known, along with the analog of the total time to calculate the increase of the number of the state of increased, and the ample degree evaluation indicators tend to be stable.

This invention selects analog total time is 40 million hours of abundance indicators as a research object, table 2 the total simulation time is 40 million hours under the condition of under different weather state sufficient degrees of the assessment results:

Table 2 ample degrees under different weather condition assessment results

The table 2 can be seen, relative to the normal weather, and the system of the disaster weather abundant evaluation indicators the result is obviously reduced. Large International network session in accordance with the indicators (CIGRE) dividing method, the disaster weather IEEE-RTS79 the extent of the system indicators S_SI belongs to a 3 stage, to the user has a very serious impact on the unreliable state, should be held in a timely manner repair and maintenance.