CN105160149A - Method for constructing demand response scheduling evaluation system of simulated peak-shaving unit - Google Patents

Abstract

The invention discloses a method for constructing a demand response scheduling evaluation system of a simulated peak-shaving unit. The method comprises: determining demand response scheduling evaluation time; taking the simulated peak-shaving unit as a target, and constructing the three-layer demand response scheduling evaluation system of the simulated peak-shaving unit from time dimension, capacity dimension and object dimension, wherein a first layer is a totality index, a second layer is a generality index, and a third layer is a specificity index; taking an ideal peak-shaving curve as an evaluation target, and constructing the demand response scheduling evaluation system of the simulated peak-shaving unit; and performing analysis on an index system with an evaluation method of an attribute interval recognition theory, and performing scheduling evaluation calculation. The demand response scheduling evaluation system of the simulated peak-shaving unit, constructed with the method, has comprehensiveness, independence, easy measurement property, flexibility and practicality, is helpful for more visually understanding a demand response scheduling result and a user response state in power grid scheduling, and provides a scientific and accurate basis for implementing demand response and settlement.

Description

A kind of demand response scheduling evaluation system construction method simulating regulating units

Technical field

The present invention relates to a kind of demand response scheduling evaluation system construction method simulating regulating units, belong to technical field of power systems.

Background technology

Under the double influence of the cost of imbalance between power supply and demand, traditional regulating units, environment and resource restriction, load scheduling is becoming the new element of dispatching of power netwoks.Compare with conventional power generation usage resource, demand response resource participates in operation of power networks and controls there is some superiority, and such as when conditions permit, demand response resource can response scheduling and steering order rapidly, and demand response resource capacity adjustable elastic is larger afterwards in polymerization; Meanwhile, because demand response resource distribution comparatively disperses, polymerization can be optimized from network and geographical aspect, thus be conducive in emergency circumstances formulating accurate control program.In a broad sense, the interactive resource of Demand-side is a lot, as loads such as all kinds of illumination, air-conditioning, motor, and the energy storage devices such as all kinds of cold-storage, accumulation of heat, electric power storage, and distributed power source, electric automobile equal energy source replacement equipment etc.Demand response scheduling main target is peak load shifting, Demand-side resource is impelled to coordinate operation of power networks, therefore demand response user resources can be integrated into Yi Taitai " simulation regulating units " by us, by advanced ICT (information and communication technology) and software systems, realize polymerization and the coordination optimization of the demand response resources such as controllable burden, electric automobile, distributed power source, to participate in the power supply coordinated management system of electricity market and operation of power networks as a special unit.

Demand response resource has the features such as uncertain strong, resource dispersion, the virtual generating capacity of monomer are little, regulating power is more weak again, after polymerization, within scheduling time, user may be there is and exit demand response suddenly, or have neither part nor lot in demand response, or degree of participation does not reach requirement in advance etc., these all may cause scheduling capacity to occur fluctuation, impact simulation regulating units confidence level, brings certain pressure to peak regulation scheduling.Therefore, in ideal scheduling, demand response resource cannot be estimated more, also cannot estimate less, estimates more and will more traditional standby unit be caused to participate in scheduling, thus increase scheduling cost; Estimate less, fail to make full use of demand response resource, be difficult to the original intention realizing demand response resource.

Summary of the invention

The object of the invention is to overcome deficiency of the prior art, a kind of demand response scheduling evaluation system construction method simulating regulating units is provided, contribute to dispatching of power netwoks and understand demand response scheduling and user's responsive state more intuitively, for enforcement demand response and clearing provide science foundation accurately.

For achieving the above object, the technical solution adopted in the present invention is: a kind of demand response scheduling evaluation system construction method simulating regulating units, comprises the steps:

Step one: determine the demand response scheduling evaluation time, i.e. desirable peak regulation T.T.;

Step 2: to simulate regulating units for target, the demand response scheduling evaluation system of the simulation regulating units of three levels is built: ground floor is bulking property index, for demand response scheduling level is directly described from time dimension, capacity dimension and Object Dimension; The second layer is generality index, for comprehensive from different perspectives and systemic evaluation requirements response scheduling level; Third layer is concrete index, for weighing the degree of honouring an agreement of demand response scheduling in a certain specific indexes;

Step 3: with desirable peak regulation curve for assessment objective, sets up the demand response scheduling evaluation system of simulation regulating units;

Step 4: adopt the appraisal procedure of Attribute Interval Recognition Theory to analyze index system, carry out scheduling evaluation calculating.

Determine described in step one that the concrete steps of demand response scheduling evaluation time are as follows:

If the response time is 2 hours, 5min is made to be 1 period, if 1 Δ t=5min, response initial time T _s, response finish time T _f, i.e. response scheduling evaluation time T _f-T _s=24 Δ t;

If then the 1st response period is 2nd response period is the like, the 24th response period is

The index of generality described in step 2 comprises: start index, time index, capacity performance index and user's index;

Described concrete index comprises: start in index: simulation regulating units climbing rate and simulation regulating units start deviation ratio; In time index: simulation regulating units duration deviation ratio; In capacity performance index: simulation regulating units max cap., simulation regulating units minimum capacity and simulation regulating units capacity tolerance rate; In user's index: averaging analog peak load regulate starting-up time completion rate, averaging analog peak regulation duration completion rate and averaging analog peak completion rate.

The concrete steps of step 3 are as follows:

A. simulation regulating units climbing rate computation model is set up

Simulation regulating units climbing rate characterizes in the demand response resource units time exerting oneself of increasing or reduce, then:

In formula, p is simulation regulating units climbing rate, DR _cfor desirable peak, a is multiplying power and a ∈ (0,1], DR _ca is that grid company allows scheduling lower range limit, T _sfor simulation regulating units start-up time, namely reach the duration of scheduling range lower limit first;

B. set up simulation regulating units and start deviation ratio computation model

Simulation regulating units starts deviation ratio R _firstfor weighing comparatively in desirable peak regulation, simulate the speed of regulating units start-up time, then:

In formula, DR _tfor the desirability response scheduling duration;

C. simulation regulating units duration deviation ratio computation model is set up

Simulation regulating units duration deviation ratio R _totalfor weighing comparatively in desirable peak regulation, the range scale of simulation regulating units duration, then:

D. simulation regulating units max cap. computation model is set up

Simulation regulating units max cap. R _{max, cap}refer in demand response scheduling events, the maximal value of realistic simulation peak, then

In formula, DR _jfor the simulation peak of jth period, hop count when N is total, if DR _t=2h, N=8;

E. simulation regulating units minimum capacity computation model is set up

Simulation regulating units minimum capacity R _{min, cap}refer in demand response scheduling events, the minimum value of realistic simulation peak:

In formula, DR _jfor the simulation peak of jth period, if DR _t=1h, N=4;

F. simulation regulating units capacity tolerance rate computation model is set up

Simulation regulating units capacity tolerance rate R _{gap, cap}refer to simulation regulating units max cap. R _{max, cap}with simulation regulating units minimum capacity R _{min, cap}difference and desirable peak DR _cratio:

Simulation regulating units capacity tolerance rate R _{gap, cap}the smaller the better;

G. averaging analog peak load regulate starting-up time completion rate computation model is set up

Averaging analog peak load regulate starting-up time completion rate R' _firstuser's ratio that specific simulation regulating units starts deviation ratio requirement is met under referring to demand response event:

In formula, N (R _{i, first}) for judging whether i-th user meets specific simulation regulating units and start deviation ratio, if meet, N (R _{i, first}) be 1, otherwise N (R _{i, first}) be 0; N is the total number of users participating in demand response scheduling;

H. averaging analog peak regulation duration completion rate computation model is set up

Averaging analog peak regulation duration completion rate R ' _totaluser's ratio of specific simulation regulating units duration deviation ratio requirement is met under referring to demand response event:

In formula, N (R _{i, total}) for judging whether i-th user meets specific simulation regulating units duration deviation ratio, if meet, N (R _{i, total}) be 1, otherwise N (R _{i, total}) be 0;

I. averaging analog peak completion rate computation model is set up

Averaging analog peak completion rate R ' _{gap, cap}user's ratio that specific simulation regulating units capacity tolerance rate requires is met under referring to demand response event:

In formula, N (R _{i, gap, cap}) for judging whether i-th user meets specific simulation regulating units capacity tolerance rate, if meet, N (R _{i, gap, cap}) be 1, otherwise N (R _{i, gap, cap}) be 0.

Scheduling evaluation described in step 4 kind calculates and comprises the steps:

A) standardization of evaluation index

If [x _min, x _max] be the constant interval of a kth evaluation index value, i.e. x _minfor this index can getable minimum value, x _maxfor this index can getable maximal value, adopt following various dimensionless number evaluation index value be standardized as between [0,1],

When evaluation index is direct index, when namely " being the bigger the better ", adopt following formula:

When evaluation index is negative index, namely time " the smaller the better ", adopt following formula:

When evaluation index is osculant, namely time " moderate be advisable ", if [U ₁, U ₂] between optimal zone for this desired value, adopt following formula:

B) the criteria for classification battle array of evaluation index is set up

C _kbe an ordered partition class of attribute measure space, corresponding each evaluation index also can according to C _ksplit, form the criteria for classification battle array describing the good and bad degree of m evaluation index, as follows:

In formula, m is evaluation index number, and K is Comment gathers number; a _jkmeet a _j1≤ a _j2≤ ... ≤ a _mK; I ₁, I ₂..., I _mcertain area sample x after expression enforcement demand response _ithe value of m evaluation index;

C) single index Attribute Measure

Calculate i-th sample x _ia jth evaluation index x _ijthere is attribute C _kattribute Measure μ _ijk=μ (x _ij∈ C _k);

Work as x _ij≤ a _j1time, get μ _ij1=1, μ _ij2=... μ _ijK=0;

Work as x _ij>=a _jKtime, get μ _ijK=1, μ _ij1=... μ _ijK-1=0;

Work as a _jl≤ x _ij≤ a _jl+1time, get μ _ijk=0, k<l or k>l+1;

Wherein, a _jlthe value that jth row l arranges is in presentation class standard array;

D) weight is arranged

Adopt the relative importance of analytical hierarchy process to every evaluation index to assess, and respective weights is set according to the relative importance of every evaluation index;

E) comprehensive multi-index Attribute Measure

After calculating the Attribute Measure of i-th each indicator measurements of sample, then calculate i-th sample x _i(i=1,2 ..., n) there is attribute C _kattribute Measure μ _ik=μ (x _i∈ C _k),

Wherein, n is the total number of users participating in demand response scheduling, w _ja jth index I _jweight, w _j>=0, and that weight reflects is a jth index I _jrelative importance, the value of weight is by steps d) obtain;

F) Attribute Recognition

According to Reliability Code, to degree of confidence λ, if then think x _ibelong to C _kclass, the span of degree of confidence λ is 0.5 ~ 0.7;

According to scoring criterion, calculate synthesized attribute measure value according to size to x _icarry out classifying and sorting.

Compared with prior art, the beneficial effect that the present invention reaches is: to simulate regulating units for target, consider startability, the factor such as scheduling time and scheduling capacity, build the demand response scheduling evaluation system of simulation regulating units, with desirable peak regulation curve for assessment objective, consider peak nargin, carry out the dispatching effect assessment of simulating regulating units, the demand response scheduling evaluation system adopting the inventive method to build is assessed, possess comprehensive, independence, easy tolerance, dirigibility and practicality, contribute to dispatching of power netwoks and get more information about demand response scheduling and user's responsive state, for enforcement demand response and clearing provide science foundation accurately.

Accompanying drawing explanation

Fig. 1 is the structural representation of the demand response scheduling evaluation system of simulation regulating units.

Fig. 2 is the curve map of the demand response scheduling evaluation content of simulation regulating units.

Fig. 3 is certain simulation regulating units demand response dispatching load curve figure.

Embodiment

Below in conjunction with accompanying drawing, the invention will be further described.

Simulate a demand response scheduling evaluation system construction method for regulating units, comprise the steps:

Step one: determine the demand response scheduling evaluation time, i.e. desirable peak regulation T.T.;

If the response time is 2 hours, 5min is made to be 1 period, if 1 Δ t=5min, response initial time T _s, response finish time T _f, i.e. response scheduling evaluation time T _f-T _s=24 Δ t;

If then the 1st response period is 2nd response period is the like, the 24th response period is

Step 2: to simulate regulating units for target, the demand response scheduling evaluation system of the simulation regulating units of three levels is built: ground floor is bulking property index, for demand response scheduling level is directly described from time dimension, capacity dimension and Object Dimension; The second layer is generality index, for comprehensive from different perspectives and systemic evaluation requirements response scheduling level; Third layer is concrete index, for weighing the degree of honouring an agreement of demand response scheduling in a certain specific indexes.

Demand response scheduling evaluation to refer under certain demand response event of assessment the actual schedule that produces because of the effect of Demand-side aggregation of resources and desirable dispatch between gap, belong to later evaluation scope.Demand response scheduling evaluation target is from electrical network angle, to the reduction curve produced under the effect of Demand-side aggregation of resources carry out unified, comprehensively evaluate.The present invention is using the user's reduction plans in scheduling time as peak regulation resource, and to simulate regulating units for target structure scheduling evaluation system, starting characteristic, time response, the capacity characteristic of regulating units are simulated in emphasis assessment.Take into account the performance in starting characteristic, capacity characteristic etc. of the unique user virtual resource participating in scheduling simultaneously.

As shown in Figure 1, generality index comprises: start index, time index, capacity performance index and user's index.

Concrete index comprises:

Start in index: simulation regulating units climbing rate and simulation regulating units start deviation ratio;

In time index: simulation regulating units duration deviation ratio;

In capacity performance index: simulation regulating units max cap., simulation regulating units minimum capacity and simulation regulating units capacity tolerance rate;

In user's index: averaging analog peak load regulate starting-up time completion rate, averaging analog peak regulation duration completion rate and averaging analog peak completion rate.

Step 3: with desirable peak regulation curve for assessment objective, sets up the demand response scheduling evaluation system of simulation regulating units, and as shown in Figure 2, be the curve map of the demand response scheduling evaluation content of simulation regulating units, concrete steps are as follows:

A. simulation regulating units climbing rate computation model is set up

Be analogous to fired power generating unit, simulation regulating units climbing rate (namely simulating the ascending, descending load-bearing capacity of regulating units) characterizes in the demand response resource units time exerting oneself of increasing or reduce, then:

In formula, p is simulation regulating units climbing rate, DR _cfor desirable peak, a is multiplying power and a ∈ (0,1], DR _ca is that grid company allows scheduling lower range limit, T _sfor simulation regulating units start-up time, namely reach the duration of scheduling range lower limit first.

B. set up simulation regulating units and start deviation ratio computation model

Index A is absolute value assessment, but single numerical value does not have comparative, is difficult to find out simulation regulating units start-up time and desirable peak regulation lead time, therefore proposes simulation regulating units startup deviation ratio R _first, for weighing comparatively in desirable peak regulation, simulate the speed of regulating units start-up time, then:

In formula, DR _tfor the desirability response scheduling duration.In general, R _firstthe smaller the better, if R _firstwhen>=0.2, concerning dispatching of power netwoks department, now respond effect poor.

C. simulation regulating units duration deviation ratio computation model is set up

Actual peak regulation end time DR' _frefer in demand response scheduling events, actual peak last exceedes grid company and allows peak regulation lower range limit DR _cthe time point of a, exits the speed of dispatching of power netwoks for weighing demand response resource.Under desirable peak regulation, DR' _f=DR _f, DR _ffor the DR peak regulation end time, as 12:00,14:35 etc., but single numerical value does not have comparative, needs to consider the simulation peak load regulate starting-up time, therefore proposes simulation peak regulation duration T _l, for weighing comparatively in desirable peak regulation, actual peak regulation T.T., then:

T _l＝DR′ _f-DR′ _s

In formula: DR' _fpeak regulation lower range limit DR is allowed for actual peak exceedes grid company first _cthe time of a.

Formula (3) is absolute value assessment, is difficult to find out simulation peak regulation duration and peak regulation total time difference distance, therefore proposes the concept of simulation peak regulation duration deviation ratio, for weighing comparatively in desirable peak regulation, and the range scale of simulation peak regulation T.T., then:

In general, R _totalbe the bigger the better, if R _totalwhen≤0.8, concerning dispatching of power netwoks department, now respond effect poor.

D. simulation regulating units max cap. computation model is set up

Simulation regulating units max cap. R _{max, cap}refer in demand response scheduling events, the maximal value of realistic simulation peak, then

In formula, DR _jfor the peak of jth period, hop count when N is total, if DR _t=2h, N=8.When evaluating, R _{max, cap}not be the bigger the better, consider that demand response scheduling is actual, general desirable dispatch curve is definite value or piecewise function, comparatively fixing; If maximum peak to exceed desirable peak too much, then can cause actual peak regulation and desirable peak regulation gap excessive, affect dispatching of power netwoks department peak regulation effect.

E. simulation regulating units minimum capacity computation model is set up

Simulation regulating units minimum capacity R _{min, cap}refer in demand response scheduling events, the minimum value of realistic simulation peak:

In formula, DR _jfor the peak of jth period, if DR _t=1h, N=4.By that analogy, if minimum peak to be less than desirable peak too much, then can cause actual peak regulation and desirable peak regulation gap excessive, dispatching of power netwoks department peak regulation effect can be affected equally.

F. simulation regulating units capacity tolerance rate computation model is set up

Although allow demand response scheduling scope to have larger allowance, if in certain scheduling events, the adjustment of Demand-side scheduling of resource scope is excessive, will extreme influence demand response dispatching effect, also has certain negative effect to demand response scheduling prediction.

Simulation regulating units capacity tolerance rate R _{gap, cap}refer to simulation regulating units max cap. R _{max, cap}with simulation regulating units minimum capacity R _{min, cap}difference and desirable peak DR _cratio:

When actual schedule, if R _{gap, cap}excessive, namely peak is unstable, will cause the frequent switching of other peak regulation resource.Therefore, regulating units capacity tolerance rate is simulated the smaller the better.

G. averaging analog peak load regulate starting-up time completion rate computation model is set up

Averaging analog peak load regulate starting-up time completion rate R' _firstuser's ratio of specific simulation regulating units deviation ratio start-up time requirement is met under referring to demand response event:

In formula, N (R _{i, first}) for judging whether i-th user meets specific simulation regulating units deviation ratio start-up time, if meet, N (R _{i, first}) be 1, otherwise N (R _{i, first}) be 0; N is the total number of users participating in demand response scheduling.

H. averaging analog peak regulation duration completion rate computation model is set up

Averaging analog peak regulation duration completion rate R ' _totaluser's ratio of specific simulation regulating units duration deviation ratio requirement is met under referring to demand response event:

In formula, N (R _{i, total}) for judging whether i-th user meets specific simulation regulating units duration deviation ratio, if meet, N (R _{i, total}) be 1, otherwise N (R _{i, total}) be 0.

I. averaging analog peak completion rate computation model is set up

Averaging analog peak completion rate R ' _{gap, cap}user's ratio that specific simulation regulating units capacity tolerance rate requires is met under referring to demand response event:

In formula, N (R _{i, gap, cap}) for judging whether i-th user meets specific simulation regulating units capacity tolerance rate, if meet, N (R _{i, gap, cap}) be 1, otherwise N (R _{i, gap, cap}) be 0.

Amid all these factors, carry out importance judgement with demand response dispatching effect Four types evaluation index, by analysis, the importance ranking of four two-level index is followed successively by capacity performance index, starts index, time index and user's index, in follow-up index weights calculates, this point will be taken into full account.

Step 4: adopt the appraisal procedure of Attribute Interval Recognition Theory to analyze index system, carry out scheduling evaluation calculating.

In the comprehensive assessment of demand response implementation result, { low, lower, in, higher, high } 5 grades can be written as at an ordered partition class of attribute measure space F (demand response implementation result quality).The problem that attribute Recognition Model will solve is certain area sample x after enforcement demand response _ithe value I of m evaluation index ₁, I ₂..., I _mbelong to which kind of attribute C _k.Value evaluation problem being converted into evaluation index has certain generic attribute C _kthe computational problem of Attribute Measure value, specifically comprise the steps:

A) standardization of evaluation index

If [x _min, x _max] be the constant interval of a kth evaluation index value, i.e. x _minfor this index can getable minimum value, x _maxfor this index can getable maximal value, adopt following various dimensionless number evaluation index value be standardized as between [0,1],

When evaluation index is direct index, when namely " being the bigger the better ", adopt following formula:

When evaluation index is negative index, namely time " the smaller the better ", adopt following formula:

When evaluation index is osculant, namely time " moderate be advisable ", if [U ₁, U ₂] between optimal zone for this desired value, adopt following formula:

B) the criteria for classification battle array of evaluation index is set up

C _kbe an ordered partition class of attribute measure space, corresponding each evaluation index also can according to C _ksplit, form the criteria for classification battle array describing the good and bad degree of m evaluation index, as follows:

In formula, m is evaluation index number, and K is Comment gathers number; a _jkmeet a _j1≤ a _j2≤ ... ≤ a _mK; I ₁, I ₂..., I _mcertain area sample x after expression enforcement demand response _ithe value of m evaluation index;

C) single index Attribute Measure

Calculate i-th sample x _ia jth evaluation index x _ijthere is attribute C _kattribute Measure μ _ijk=μ (x _ij∈ C _k);

Work as x _ij≤ a _j1time, get μ _ij1=1, μ _ij2=... μ _ijK=0;

Work as x _ij>=a _jKtime, get μ _ijK=1, μ _ij1=... μ _ijK-1=0;

Work as a _jl≤ x _ij≤ a _jl+1time, get μ _ijk=0, k<l or k>l+1;

Wherein, a _jlthe value that jth row l arranges is in presentation class standard array;

D) weight is arranged

The relative importance of analytical hierarchy process to every evaluation index is adopted to assess, and respective weights is set according to the relative importance of every evaluation index, main process comprises: Maximum characteristic root and proper vector, the consistency desired result of the judgment matrix C that sets up recursive hierarchy structure, sets up judgment matrix C, calculates.Analytical hierarchy process agriculture products weight belongs to common methods, below the computation process of simple introduced layer fractional analysis.

Set up recursive hierarchy structure: the relation in analysis and evaluation system between each index, will determine that the index of weight is divided into several hierarchical structure by all;

Judgement Matricies C: in same level, the judgement of index relative importance is completed by some experts.The conclusion of " limit capacity that people distinguishes message level is 7 ± 2 " that draw according to psychological study, when passing judgment on the relative importance of index, introduces the proportion quotiety of nine points of positions.Each element c in judgment matrix C _ijfor i row index relative j row index carries out the value that importance compares between two;

Calculate Maximum characteristic root and the proper vector of judgment matrix C: each row vector of judgment matrix C is carried out geometric mean, then normalization, the row vector obtained is exactly weight vectors.If the Maximum characteristic root of C is λ _max, its corresponding proper vector is X, then CX=λ _maxx, the value of characteristic root and proper vector can be gained knowledge according to the dependency number of matrix computations and be obtained, and is not repeated herein;

Consistency desired result: coincident indicator n represents the index number in this level.Whether having satisfied consistance to measure different rank judgment matrix, need introduce the Aver-age Random Consistency Index RI value of judgment matrix, the value of RI is fixing.When n and exponent number are greater than 2, during the Consistency Ratio CR=CI/RI<0.10 of judgment matrix, namely think that judgment matrix has satisfied consistance, otherwise need to adjust judgment matrix, to make it that there is satisfied consistance.

According to above computation process, determine the weighted value W of different index ^t=[w ₁w ₂... w _j], j is whole index number in the index system set up.

E) comprehensive multi-index Attribute Measure

After calculating the Attribute Measure of i-th each indicator measurements of sample, then calculate i-th sample x _i(i=1,2 ..., n) there is attribute C _kattribute Measure μ _ik=μ (x _i∈ C _k),

Wherein, n is the total number of users participating in demand response scheduling, w _ja jth index I _jweight, w _j>=0, and that weight reflects is a jth index I _jrelative importance, the value of weight is by steps d) obtain;

F) Attribute Recognition

According to Reliability Code, to degree of confidence λ, if then think x _ibelong to C _kclass, the span of degree of confidence λ is 0.5 ~ 0.7;

According to scoring criterion, calculate synthesized attribute measure value according to size to x _icarry out classifying and sorting.

The demand response scheduling evaluation system of the simulation regulating units adopting the present invention to build below in conjunction with specific embodiment carries out evaluates calculation; following examples only for technical scheme of the present invention is clearly described, and can not limit the scope of the invention with this.

Suppose: before and after certain simulation regulating units type demand response scheduling, the load curve of user as shown in Figure 3, screens and calculates the load data required when carrying out the assessment of demand response dispatching effect:

Desirable scheduling capacity DR _c=80kW;

Float multiplying power a=0.85;

Desirable scheduling capacity upper limit 92kW;

Desirable scheduling capacity lower limit 68kW;

Desirable scheduling T.T. DR _t=2h

Actual schedule start time DR ' _s=12:15

Actual schedule finish time DR ' _f=13:55

Actual maximum scheduling capacity 100

Actual minimum scheduling capacity 50

Actual schedule T start-up time _s=15min

Participate in dispatched users sum n=20

Scheduling time completing user number n ₁=16

Scheduling completing user number n start-up time ₂=15

Scheduling capacity completing user number n ₃=14.

Calculation procedure:

(1) each index of evaluation system is calculated

---large index;

---minimal type index;

---large index;

A ₄=100---interval type index (the smaller the better);

A ₅=50---interval type index (being the bigger the better);

---minimal type index;

---minimal type index;

---minimal type index;

---minimal type index.

(2) standardization of evaluation index

The dimension of each index and the constant interval of desired value different, for ensureing assessment result objective, reasonable, before assessment, tackling evaluation index carry out standardization.

For index 1, the upper limit of standard index value is 1.3, and lower limit is 0.8, substitutes into large standardization formula:

As calculated, standardized index value is as shown in table 1:

Table 1 demand response dispatching effect evaluation index

(3) the criteria for classification battle array of evaluation index is set up

By the C of 5 indexs _kbe defined as 5 standards: (C ₁, C ₂, C ₃, C ₄, C ₅)=(is poor, poor, in, better, good)=(0.2,0.4,0.6,0.8,0.9).

(4) single index Attribute Measure

Calculate i-th sample x _ia jth evaluation index x _ijthere is attribute C _kattribute Measure μ _ijk=μ (x _ij∈ C _k), result is as shown in table 2.

Table 2 single index Attribute Measure Judgement Matrix

(5) weight is arranged

After assessment experts arranges judgement to certain demand response dispatching effect evaluation index relevant information, response scheduling estimation flow figure and scheduling actual information, can obtain correlation parameter according to demand.Under simulation regulating units environment: the importance ranking of four two-level index is followed successively by capacity performance index, starts index, time index and user's index, and obtaining the second level factor weight by analytical hierarchy process is:

A＝[0.30.10.40.2]

Principle according to the above analysis, weight calculation is carried out again in the basis of in many ways investigating, and obtains three grades of sub-factor weights and is respectively:

A ₁＝[0.60.4]

A ₂＝[1]

A ₃＝[0.30.30.4]

A ₄＝[0.30.40.3]

(6) comprehensive multi-index Attribute Measure

After calculating the Attribute Measure of each indicator measurements, then calculate multi objective there is attribute C _kattribute Measure μ _ik=μ (x _i∈ C _k) [10], result is as shown in table 3.

Wherein, 1≤i≤n, 1≤k≤K.W _ja jth index I _jweight, w _j>=0, and

(7) Attribute Recognition

According to Reliability Code, to degree of confidence λ, calculate then think x _ibelong to C _kclass, the usual value of degree of confidence λ is 0.5 ~ 0.7.

According to scoring criterion, calculate then can according to q _xisize to x _icarry out classifying and sorting.

Table 3 Attribute Recognition assessment result

According to result in table, according to maximum membership grade principle, the evaluation attribute recognition result of the dispatching effect of user time-sharing electricity price is " poor ", namely represents that the demand response scheduling result of appraisal are not yet qualified.But " in " Attribute Measure result be 0.4338, do not meet degree of confidence value, therefore this demand response scheduling evaluation result to be also greatly improved space for meeting dispatching of power netwoks requirement.

The above is only the preferred embodiment of the present invention; it should be pointed out that for those skilled in the art, under the prerequisite not departing from the technology of the present invention principle; can also make some improvement and distortion, these improve and distortion also should be considered as protection scope of the present invention.

Claims (5)

1. simulate a demand response scheduling evaluation system construction method for regulating units, it is characterized in that, comprise the steps:

Step one: determine the demand response scheduling evaluation time, i.e. desirable peak regulation T.T.;

Step 2: to simulate regulating units for target, the demand response scheduling evaluation system of the simulation regulating units of three levels is built: ground floor is bulking property index, for demand response scheduling level is directly described from time dimension, capacity dimension and Object Dimension; The second layer is generality index, for comprehensive from different perspectives and systemic evaluation requirements response scheduling level; Third layer is concrete index, for weighing the degree of honouring an agreement of demand response scheduling in a certain specific indexes;

Step 3: with desirable peak regulation curve for assessment objective, sets up the demand response scheduling evaluation system of simulation regulating units;

Step 4: adopt the appraisal procedure of Attribute Interval Recognition Theory to analyze index system, carry out scheduling evaluation calculating.

2. the demand response scheduling evaluation system construction method of simulation regulating units according to claim 1, is characterized in that, determine that the concrete steps of demand response scheduling evaluation time are as follows described in step one:

If the response time is 2 hours, 5min is made to be 1 period, if 1 Δ t=5min, response initial time T _s, response finish time T _f, i.e. response scheduling evaluation time T _f-T _s=24 Δ t;

If T _s=T ₁ ⁺ then the 1st response period is Δ T ₁=T ₂ ^--T ₁ ⁺(T _s) the 2nd response period be the like, the 24th response period is

3. the demand response scheduling evaluation system construction method of simulation regulating units according to claim 1, it is characterized in that, the index of generality described in step 2 comprises: start index, time index, capacity performance index and user's index;

Described concrete index comprises: start in index: simulation regulating units climbing rate and simulation regulating units start deviation ratio; In time index: simulation regulating units duration deviation ratio; In capacity performance index: simulation regulating units max cap., simulation regulating units minimum capacity and simulation regulating units capacity tolerance rate; In user's index: averaging analog peak load regulate starting-up time completion rate, averaging analog peak regulation duration completion rate and averaging analog peak completion rate.

4. the demand response scheduling evaluation system construction method of simulation regulating units according to claim 3, it is characterized in that, the concrete steps of step 3 are as follows:

A. simulation regulating units climbing rate computation model is set up

Simulation regulating units climbing rate characterizes in the demand response resource units time exerting oneself of increasing or reduce, then:

$p=\frac{{\mathrm{DR}}_c\&CenterDot;a}{T_s}---\left(1\right)$

In formula, p is simulation regulating units climbing rate, DR _cfor desirable peak, a is multiplying power and a ∈ (0,1], DR _ca is that grid company allows scheduling lower range limit, T _sfor simulation regulating units start-up time, namely reach the duration of scheduling range lower limit first;

B. set up simulation regulating units and start deviation ratio computation model

Simulation regulating units starts deviation ratio R _firstfor weighing comparatively in desirable peak regulation, simulate the speed of regulating units start-up time, then:

$R_{first}=\frac{T_s}{{\mathrm{DR}}_t},R_{first}\&Element;\&lsqb;0,1\&rsqb;---\left(2\right)$

In formula, DR _tfor the desirability response scheduling duration;

C. simulation regulating units duration deviation ratio computation model is set up

Simulation regulating units duration deviation ratio R _totalfor weighing comparatively in desirable peak regulation, the range scale of simulation regulating units duration, then:

$R_{total}=\frac{T_l}{{\mathrm{DR}}_t},R_{total}\&Element;\&lsqb;0,1\&rsqb;---\left(3\right);$

D. simulation regulating units max cap. computation model is set up

Simulation regulating units max cap. R _{max, cap}refer in demand response scheduling events, the maximal value of realistic simulation peak, then

$R_{max,cap}=max\left(\underset{j\&Element;N}{\&Sigma;}{\mathrm{DR}}_j\right)---\left(4\right)$

In formula, DR _jfor the simulation peak of jth period, hop count when N is total, if DR _t=2h, N=8;

E. simulation regulating units minimum capacity computation model is set up

Simulation regulating units minimum capacity R _{min, cap}refer in demand response scheduling events, the minimum value of realistic simulation peak:

$R_{min,cap}=min\left(\underset{j\&Element;N}{\&Sigma;}{\mathrm{DR}}_j\right)---\left(5\right)$

In formula, DR _jfor the simulation peak of jth period, if DR _t=1h, N=4;

F. simulation regulating units capacity tolerance rate computation model is set up

Simulation regulating units capacity tolerance rate R _{gap, cap}refer to simulation regulating units max cap. R _{max, cap}with simulation regulating units minimum capacity R _{min, cap}difference and desirable peak DR _cratio:

$R_{gap,cap}=\frac{max\left(\underset{j\&Element;N}{\&Sigma;}{\mathrm{DR}}_j\right)-min\left(\underset{j\&Element;N}{\&Sigma;}{\mathrm{DR}}_j\right)}{{\mathrm{DR}}_c}---\left(6\right)$

Simulation regulating units capacity tolerance rate R _{gap, cap}the smaller the better;

G. averaging analog peak load regulate starting-up time completion rate computation model is set up

Averaging analog peak load regulate starting-up time completion rate R' _firstuser's ratio that specific simulation regulating units starts deviation ratio requirement is met under referring to demand response event:

$R_{first}^{\&prime;}==\frac{\underset{i\&Element;n}{\&Sigma;}N\left(R_{i,first}\right)}{n}---\left(7\right)$

In formula, N (R _{i, first}) for judging whether i-th user meets specific simulation regulating units and start deviation ratio, if meet, N (R _{i, first}) be 1, otherwise N (R _{i, first}) be 0; N is the total number of users participating in demand response scheduling;

H. averaging analog peak regulation duration completion rate computation model is set up

Averaging analog peak regulation duration completion rate R ' _totaluser's ratio of specific simulation regulating units duration deviation ratio requirement is met under referring to demand response event:

$R_{total}^{\&prime;}=\frac{\underset{i\&Element;n}{\&Sigma;}N\left(R_{i,total}\right)}{n}---\left(8\right)$

In formula, N (R _{i, total}) for judging whether i-th user meets specific simulation regulating units duration deviation ratio, if meet, N (R _{i, total}) be 1, otherwise N (R _{i, total}) be 0;

I. averaging analog peak completion rate computation model is set up

Averaging analog peak completion rate R ' _{gap, cap}user's ratio that specific simulation regulating units capacity tolerance rate requires is met under referring to demand response event:

$R_{gap,cap}^{\&prime;}=\frac{\underset{i\&Element;n}{\&Sigma;}N\left(R_{i,gap,cap}\right)}{n}---\left(9\right)$

In formula, N (R _{i, gap, cap}) for judging whether i-th user meets specific simulation regulating units capacity tolerance rate, if meet, N (R _{i, gap, cap}) be 1, otherwise N (R _{i, gap, cap}) be 0.

5. the demand response scheduling evaluation system construction method of simulation regulating units according to claim 1, is characterized in that, scheduling evaluation described in step 4 kind calculates and comprises the steps:

A) standardization of evaluation index

If [x _min, x _max] be the constant interval of a kth evaluation index value, i.e. x _minfor this index can getable minimum value, x _maxfor this index can getable maximal value, adopt following various dimensionless number evaluation index value be standardized as between [0,1],

When evaluation index is direct index, when namely " being the bigger the better ", adopt following formula:

$z=\frac{x_{ij}-x_{min}}{x_{max}-x_{min}}---\left(10\right)$

When evaluation index is negative index, namely time " the smaller the better ", adopt following formula:

$z=\frac{x_{max}-x_{ij}}{x_{max}-x_{min}}---\left(11\right)$

When evaluation index is osculant, namely time " moderate be advisable ", if [U ₁, U ₂] between optimal zone for this desired value, adopt following formula:

$z=\left\{\begin{array}{cc}\frac{x_{ij}-x_{min}}{U_1-x_{\min }}& x_{min}<x_{ij}<U_1\\ 1& U_1\&le;x_{ij}\&le;U_2\\ \frac{x_{\max }-x_{ij}}{x_{max}-U_2}& U_2<x_{ij}<x_{\max }\end{array}\right.---\left(12\right)$

B) the criteria for classification battle array of evaluation index is set up

C _kbe an ordered partition class of attribute measure space, corresponding each evaluation index also can according to C _ksplit, form the criteria for classification battle array describing the good and bad degree of m evaluation index, as follows:

In formula, m is evaluation index number, and K is Comment gathers number; a _jkmeet a _j1≤ a _j2≤ ... ≤ a _mK; I ₁, I ₂..., I _mcertain area sample x after expression enforcement demand response _ithe value of m evaluation index;

C) single index Attribute Measure

Calculate i-th sample x _ia jth evaluation index x _ijthere is attribute C _kattribute Measure μ _ijk=μ (x _ij∈ C _k);

Work as x _ij≤ a _j1time, get μ _ij1=1, μ _ij2=... μ _ijK=0;

Work as x _ij>=a _jKtime, get μ _ijK=1, μ _ij1=... μ _ijK-1=0;

Work as a _jl≤ x _ij≤ a _jl+1time, get μ _ijk=0, k<l or k>l+1;

Wherein, a _jlthe value that jth row l arranges is in presentation class standard array;

D) weight is arranged

Adopt the relative importance of analytical hierarchy process to every evaluation index to assess, and respective weights is set according to the relative importance of every evaluation index;

E) comprehensive multi-index Attribute Measure

After calculating the Attribute Measure of i-th each indicator measurements of sample, then calculate i-th sample x _i(i=1,2 ..., n) there is attribute C _kattribute Measure μ _ik=μ (x _i∈ C _k),

${\mathrm{\&mu;}}_{ik}=\mathrm{\&mu;}(x_i\&Element;C_K)=\underset{j=1}{\overset{m}{\&Sigma;}}{w}_j{\mathrm{\&mu;}}_{ijk},1\&le;i\&le;n,1\&le;k\&le;K---\left(13\right)$

Wherein, n is the total number of users participating in demand response scheduling, w _ja jth index I _jweight, w _j>=0, and that weight reflects is a jth index I _jrelative importance, the value of weight is by steps d) obtain;

F) Attribute Recognition

According to Reliability Code, to degree of confidence λ, if then think x _ibelong to C _kclass, the span of degree of confidence λ is 0.5 ~ 0.7;

According to scoring criterion, calculate synthesized attribute measure value according to q _xisize to x _icarry out classifying and sorting.