CN109742799B - D-U space mixed multi-attribute wind power plant installed capacity interval decision method - Google Patents

Abstract

The invention relates to a decision-making method for a wind farm installed capacity interval based on D-U space hybrid multi-attribute, which uses the social benefit of wind farm power generation, wind abandonment rate, power grid line transmission safety margin and power shortage risk as attribute indicators to establish a wind farm. For the attribute matrix of the interval to be decided, a hybrid multi-attribute evaluation based on the set pair analysis D-U space is introduced to determine the optimal installed capacity interval of the wind farm.

Description

A decision-making method for wind farm installed capacity interval based on D-U space mixed multi-attribute

technical field

The invention relates to the technical field of electric power systems, in particular to a decision-making method for the installed capacity interval of a wind farm based on D-U space mixed multi-attribute.

Background technique

As countries around the world attach importance to environmental protection and demand for sustainable energy development, the focus of energy development has shifted to renewable energy. As the main utilization method of renewable energy, wind power has an unstoppable rapid and large-scale development. It is accompanied by the frequent occurrence of wind curtailment, the uncertainty of power grid operation and the decline of power quality. Therefore, a large number of studies have been conducted to evaluate the ability of the grid to accept wind power from the perspective of security, economy and resource utilization. Due to the changes in the operation mode of the power grid, the expansion of the grid planning and the change of the dispatching mode, the power grid's ability to accept wind power is constantly changing. This change directly affects the evaluation of the installed capacity of wind farms and is the premise for determining the installed capacity of wind farms. In addition, wind resource is another crucial factor affecting the installed capacity. Whether it is the uncertain wind power acceptance level or the wind resource with strong randomness, the optimization of the installed capacity of the wind farm becomes a complex and difficult to determine optimization problem. Therefore, in the process of installed capacity evaluation, there may be several installed capacity intervals to be optimized for decision makers to choose. How to determine which installed capacity interval is optimal is a problem to be solved by the present invention. At present, there is little research on how to optimize the installed capacity range of wind farms.

SUMMARY OF THE INVENTION

In view of this, the purpose of the present invention is to provide an interval decision-making method for wind farm installed capacity based on D-U space hybrid multi-attribute, using the social benefit of wind farm power generation, wind abandonment rate, power grid line transmission safety margin and power shortage risk as indicators. , a hybrid multi-attribute evaluation based on set pair analysis D-U space is introduced to determine the optimal installed capacity range of wind farms.

To achieve the above object, the present invention adopts the following technical solutions:

An interval decision-making method for wind farm installed capacity based on D-U space hybrid multi-attribute, comprising the following steps:

Step S1: obtaining the installed capacity interval of the wind farm to be optimized and the operating parameters and unit parameters of the wind farm to be connected to the power grid;

Step S2: Set the multi-attribute decision-making index:

Step S3: establishing the interval number attribute matrix of the installed capacity interval of the wind farm to be optimized;

Step S4: the obtained interval number attribute matrix is mapped to the D-U space;

Step S5: considering the different weights of each attribute in the decision-making process, calculate the comprehensive certainty measure and the comprehensive uncertainty measure of each to-be-decided installed capacity interval plan;

Step S6: According to the obtained comprehensive certainty measure and comprehensive uncertainty measure of each interval plan of installed capacity to be decided, calculate the connection number of each interval plan of the wind farm to be decided, and determine the pros and cons of each interval plan through the size of the connection number. put in order.

Further, the multi-attribute decision-making indicators include:

(1) Social benefit B of wind farm power generation:

B=B _s +B _e -C _c -C _m

Among them: B _s is the power generation income of the wind farm; _Be is the environmental benefit of the wind farm; C _c is the investment cost of the wind farm; C _m is the operation and maintenance cost of the wind farm.

(2) The curtailment rate D of the wind farm:

和

表示可发电量和实际发电量。in:

and

Indicates the amount of electricity that can be generated and the actual amount of electricity generated.

(3) Power shortage risk R of wind farms:

Among them: t _f is the total time period when the downward change rate of wind power output in a random simulation period T is greater than the reaction rate of the system rotating standby.

(4) Grid line transmission safety margin M

The line transmission safety margin M of the power system is defined as the minimum value of all line safety margins.

M=min{Ml _,t }(t=1,2,..., _Tt ; l=1,2,...,L).

Further, the step S3 is specifically:

分别表示待决策区间方案i关于属性j的属性值的下限和上限；建立方案集合P对属性集合A的属性矩阵C_m×n。Step S31: Denote that P={P ₁ , P ₂ ,..., P _m } is a set containing m plans to be decided, that is, m planned intervals for installed capacity; A={A ₁ , A ₂ ,... A _n } is a set of n attributes; the value of scheme P _i for attribute A _j is denoted as

respectively represent the lower limit and upper limit of the attribute value of the plan i in the to-be-decided interval with respect to the attribute j; establish the attribute matrix C _m×n of the plan set P to the attribute set A.

Step S32: Normalize the attribute matrix C _m×n :

When attribute j is a cost attribute:

When attribute j is a benefit attribute:

Step S33: Calculate the social benefit B, wind abandonment rate D, line transmission safety margin M and power shortage risk R corresponding to the installed capacity interval of the wind farm by using the stochastic simulation method, and obtain the attribute matrix through normalization processing:

表示一个区间数，其它依此类推。Among them, "1" represents the attribute parameter of the installed capacity value in the interval "1";"2" represents the attribute parameter of the installed capacity value in the interval "2"; m represents the attribute parameter of the installed capacity value in the interval m; "-" indicates the lower limit of the indicator interval; "+" indicates the upper limit of the indicator interval;

Represents an interval number, and so on for others.

通过以下式将其转换成联系数a_ij+b_iji，其中：Further, the step S4 is specifically: for the interval number

Convert it to the connection number a _ij +b _ij i by the following formula, where:

In the formula, a _ij and b _ij are the identity and difference of the scheme i with respect to the attribute j represented by the connection number, respectively.

Further, the step S5 is specifically: calculate the comprehensive certainty measure S _i,D and the comprehensive uncertainty measure S _i,U of each to-be-decided installed capacity interval scheme by the following formula:

Among them, ω _j is the weight of the index j to the measure.

Further, the step S6 is specifically: using the connection number to make a decision, the size between the two connection numbers must be clearly defined. For any two connection numbers (X ₁ =S _{1, D} +S _{1, U} i; X ₂ =S _2,D +S _2,U i), the comparison rules are:

1) If S _1,D =S _2,D , when S _1,U =S _2,U , X ₁ is said to be equal to X ₂ ;

2) If S _1,D =S _2,D , when S _1,U >S _2,U , X ₁ is said to be larger than X ₂ ;

3) When S _1,D > S _2,D , X ₁ is said to be greater than X ₂ ; if there are S _1,D +S _1,U >S _2,D +S _2,U , then X ₁ is said to be significantly greater than X2 _;

If X _f is significantly larger than X _i (i=1,2,...,m and i≠f), then the fth decision scheme is the best.

Compared with the prior art, the present invention has the following beneficial effects:

The present invention takes into account the social benefits of power generation, wind abandonment rate, power grid line transmission safety margin and power shortage risk indicators of wind farms, and introduces a hybrid multi-attribute evaluation based on set pair analysis D-U space to determine the optimal installed capacity interval of wind farms. Taking into account the economics of wind farm access and safety.

Description of drawings

Detailed ways

The present invention will be further described below in conjunction with the embodiments.

The present invention provides an interval decision-making method for installed capacity of wind farms based on D-U space hybrid multi-attribute, comprising the following steps

Step S1: obtaining the installed capacity interval of the wind farm to be optimized, and obtaining the operating parameters and unit parameters of the wind farm to be connected to the power grid;

Step S2: Select multi-attribute decision-making indexes, and take wind farm power generation social benefit B, wind curtailment rate D, power grid line transmission safety margin M and power shortage risk R as attribute indexes.

(1) One-year social benefit of wind farm power generation B:

B=B _s +B _e -C _c -C _m

Among them: B _s is the power generation income of the wind farm; _Be is the environmental benefit of the wind farm; C _c is the investment cost of the wind farm; C _m is the operation and maintenance cost of the wind farm.

(2) One-year curtailment rate D of wind farms:

和

表示可发电量和实际发电量。in:

and

Indicates the amount of electricity that can be generated and the actual amount of electricity generated.

(3) The one-year power shortage risk R of a wind farm is defined as follows:

Among them: t _f is the total duration of the downward change rate of wind power output in a random simulation period T (one year) that is greater than the response rate of the system spinning reserve.

(4) Grid line transmission safety margin M

In a power system, the safety margin of a line is the remaining active power transfer capacity on the line.

The line transmission safety margin M of the power system is defined as the minimum value of the safety margin of all lines within one year.

M=min{M _l,t }(t=1,2,...,T _t ; l=1,2,...,L)

Step S3: Establish the interval number attribute matrix of the installed capacity interval of the wind farm to be optimized

(

分别表示待决策区间方案i关于属性j的属性值的下限和上限)。建立方案集合P对属性集合A的属性矩阵C_m×n。(1) Interval attribute matrix. Note that P={P ₁ , P ₂ , ..., P _m } is a set containing m solutions to be decided, that is, m standby capacity planning intervals; A = {A ₁ , A ₂ , ... A _n } is n The set of attributes _{; the value of the scheme Pi for the attribute A j is} recorded as

(

respectively represent the lower limit and upper limit of the attribute value of the to-be-decided interval scheme i with respect to the attribute j). An attribute matrix C _m×n of the scheme set P to the attribute set A is established.

(2) Normalization of interval attribute matrix. In order to eliminate the influence of different dimensions on the results, the attribute matrix C _m×n is normalized.

When attribute j is a cost attribute:

When attribute j is a benefit attribute:

(3) Establish the attribute matrix of the decision-making interval of the wind farm. The stochastic simulation method is used to calculate the social benefit B, wind curtailment rate D, line transmission safety margin M and power shortage risk R corresponding to the installed capacity interval of the wind farm, and through normalization, the attribute matrix is obtained:

表示一个区间数，其它依此类推。Among them, "1" represents the attribute parameter of the installed capacity value in the interval "1";"2" represents the attribute parameter of the installed capacity value in the interval "2"; m represents the attribute parameter of the installed capacity value in the interval m; "-" indicates the lower limit of the indicator interval; "+" indicates the upper limit of the indicator interval;

Represents an interval number, and so on for others.

Step S4: map the interval number to the D-U space;

的不确定性体现在:虽然从区间的层面上其取值是确定的，但在具体的数值上是不确定的。对于区间数，通过以下两式将其转换成联系数a_ij+b_iji，其中：number of intervals

The uncertainty of is reflected in: although its value is determined from the interval level, it is uncertain in the specific value. For the interval number, it is converted into a connection number a _ij +b _ij i by the following two equations, where:

In the formula, a _ij and b _ij are the identity and difference of the scheme i with respect to the attribute j represented by the connection number, respectively.

Step S5: Considering the different weights of each attribute in the decision-making process, calculate the comprehensive certainty measure S _i,D and the comprehensive uncertainty measure S _i,U of each to-be-decided installed capacity interval scheme by the following two formulas.

Among them, ω _j is the weight of the index j to the measure.

Step S6: Calculate the connection number X _i =S _{i, D} + S _{i, U} i (X _i is the connection number of the ith decision-making plan) for each wind farm interval plan to be decided, and compare the value of the connection number X _i The merits and demerits of each interval scheme are sorted, and the one with the largest X _i is the final decision interval for the installed capacity of the wind farm.

Using the connection number to make a decision must clarify the size between the two connection numbers. For any two connection numbers (X ₁ =S _1,D +S _1,U i;X ₂ =S _2,D +S _2,U i) , the comparison rules are:

1) If S _1,D =S _2,D , when S _1,U =S _2,U , X ₁ is said to be equal to X ₂ ;

2) If S _1,D =S _2,D , when S _1,U >S _2,U , X ₁ is said to be larger than X ₂ ;

3) When S _1,D > S _2,D , X ₁ is said to be greater than X ₂ ; if there are S _1,D +S _1,U >S _2,D +S _2,U , then X ₁ is said to be significantly greater than X ₂ .

If X _f is significantly larger than X _i (i=1,2,...,m and i≠f), then the fth decision scheme is the best.

Example 1:

Taking the IEEE 30-node system as an example, the life span of the wind turbine is 20 years; the operating parameters of the dispatchable conventional generating units in the system are shown in Table 1; 0.5￥/(kW·h), the environmental benefit is equivalent to 0.0926￥/(kW·h), all confidence levels are taken as 0.9, and the optimization results are shown in Table 2. For the installed capacity intervals of wind farms [99,154]]MW (interval 1) and [85,99]MW (interval 2).

Table 1 Parameters of schedulable conventional units in IEEE30 node system

The stochastic simulation method is used to calculate the social benefit, wind curtailment rate, line transmission safety margin and power shortage risk corresponding to the installed capacity of the wind farm, and the attribute matrix is obtained:

Since wind curtailment rate and power shortage risk are cost attributes, while wind farm power generation social benefits and line transmission safety margins are benefit attributes, after normalization, the above attribute matrix is:

The importance of each decision attribute is considered, and weights are given, there is ω={0.6, 0.2, 0.1, 0.1}. Then there are X ₁ =0.469+0.125i corresponding to the installed capacity interval 1 of the wind farm, and X ₂ =0.94+0.552i corresponding to the installed capacity interval 2 of the wind farm.

It can be seen that the comprehensive evaluation result of installed capacity interval 2 is significantly larger than the comprehensive evaluation result of installed capacity in interval 1, so option 2 is selected as the optimal installed capacity interval.

The above descriptions are only preferred embodiments of the present invention, and all equivalent changes and modifications made according to the scope of the patent application of the present invention shall fall within the scope of the present invention.

Claims (1)

1. A wind power plant installed capacity interval decision method based on D-U space mixed multi-attribute is characterized by comprising the following steps:

step S1, acquiring an installed capacity interval of a wind power plant to be optimized, and operation parameters and unit parameters of the wind power plant to be accessed to a power grid;

step S2, setting a multi-attribute decision index:

step S3, establishing an interval number attribute matrix of the installed capacity interval of the wind power plant to be optimized;

step S4, mapping the obtained interval number attribute matrix to a D-U space;

step S5, calculating comprehensive certainty measure and comprehensive uncertainty measure of each installed capacity interval scheme to be decided in consideration of different weights of each attribute in the decision making process;

step S6: calculating a joint coefficient of each interval scheme of the wind power plant to be decided according to the obtained comprehensive certainty measure and comprehensive uncertainty measure of each installed capacity interval scheme to be decided, and sequencing the performance of each interval scheme according to the magnitude of the joint coefficient;

the multi-attribute decision index comprises:

(1) power generation social benefit B of wind farm:

B＝B_s+B_e-C_c-C_m

wherein: b is_sGenerating capacity gain for the wind power plant; b is_eEnvironmental benefits for wind farms; c_cInvestment cost for wind power plants; c_mOperating and maintaining costs for the wind farm;

(2) wind curtailment rate D of wind farm:

wherein:

and

representing the electricity generation amount and the actual electricity generation amount;

(3) risk of power shortage in wind farm R:

wherein: t is t_fThe downward change rate of the wind power output in a random simulation period T is greater than the total duration of the system rotation standby reaction rate;

(4) power grid line transmission safety margin M

The line transmission safety margin M of the power system is defined as the minimum value of all line safety margins

M＝min{M_l,t}，t＝1,2,…,T_t；l＝1,2,...,L；

The step S3 specifically includes:

step S31, remember P ═ P₁，P₂，…，P_mThe decision-making method comprises the steps that a set containing m schemes to be decided, namely m machine capacity planning intervals to be installed; a ═ A₁，A₂，…A_nIs a set of n attributes; scheme P_iFor attribute A_jIs given as

Respectively representing the lower limit and the upper limit of the attribute value of the attribute j of the interval scheme i to be decided; establishing an attribute matrix C of the scheme set P to the attribute set A_m×n；

Step S32, for attribute matrix C_m×nAnd (3) carrying out normalization:

when attribute j is a cost-type attribute:

when attribute j is a benefit type attribute:

step S33, calculating power generation social benefits B, wind abandon rate D, line transmission safety margin M and power shortage risk R corresponding to the installed capacity interval of the wind power plant by using a random simulation method, and obtaining an attribute matrix through standardized processing:

wherein, the '1' represents the attribute parameter of the installed capacity which is taken as the value of the interval '1'; "2" represents the attribute parameter of the installed capacity at the value of the interval "2"; m represents the attribute parameter of the installed capacity which is taken as a value in the interval m; "-" represents the index section lower limit; "+" indicates the upper limit of the indicator interval;

representing the number of intervals, and so on;

the step S4 specifically includes: for number of intervals

It is converted into a coefficient a by the following two formulas_ij+b_iji, wherein:

in the formula, a_ij、b_ijRespectively representing the identity and the difference of the scheme i represented by the joint coefficient with respect to the attribute j;

the step S5 specifically includes: calculating comprehensive certainty measure S of each installed capacity interval scheme to be decided according to the following formula_i,DAnd the comprehensive uncertainty measure S_i,U:

Wherein, ω is_jIs the weight of index j to the measure;

the step S6 specifically includes: the decision making by using the joint coefficients must make clear the size between two joint coefficients, and for any two joint coefficients X₁＝S_1,D+S_1,Ui；X₂＝S_2,D+S_2,Ui, the rules of comparison are:

1) if S_1,D＝S_2,DWhen S is_1,U＝S_2,UWhen it is called X₁Is equal to X₂；

2) If S_1,D＝S_2,DWhen S is_1,U＞S_2,UWhen it is called X₁To be greater than X₂；

3) When S is_1,D＞S_2,DWhen it is called X₁Greater than X₂(ii) a If there is S_1,D+S_1,U＞S_2,D+S_2,UThen call X₁Is significantly greater than X₂；

If X is_fIs significantly greater than X_iThen the f-th decision scheme is the best.