CN101916999A - 500kV regional control center control domain optimization system - Google Patents

Abstract

The invention discloses a 500kV regional control center control domain optimization system which comprises a model module, a data module, a calculation module, an encoding module, an optimizing module and an execution module, wherein the model module is used for establishing and storing a mathematical model of a regional control center optimization control domain; the data module is used for inputting and storing basic parameters needed by the mathematical model in the model module; the calculation module is used for calculating and storing a result according to the mathematical model of the model module and the basic parameters of the data module; the encoding module is used for carrying out binary encoding on a 500kV substation in a region and storing a code; the optimizing module is used for searching and storing an optimal solution set of the regional control center optimization control domain according to the result of the calculation module and the code of the encoding module; the execution module is used for selectively accessing the 500kV substation to a regional control center and controlling the 500kV substation by the regional control center according to the optimal solution set of the optimizing module. The invention optimizes the 500kV regional control center control domain on the aspects of construction and operation cost, running monitor risks and control operation efficiency.

Description

500KV Regional Control Center control domain optimization system

Technical field

The present invention relates to a kind of Substation Optimization system, especially a kind of 500KV Regional Control Center control domain optimization system.

Background technology

Chinese patent " 500KV transformer station the area control system " (patent No. 200620099105; December 26 2007 day for announcing) a kind of 500KV transformer station area control system of being made up of system of Regional Control Center automation main website, frequency image monitoring system, relay protection fault information management system is disclosed; this system has realized the management mode of 500KV transformer station remote centralized control, unattended, few man on duty by setting up the electrical network Regional Control Center, has reduced the operation management cost effectively, has improved Operation and Maintenance efficient.Thus, control pattern in district's is popularized in China's power grid construction rapidly and is come.Yet, quick increase along with 500kV website quantity, the also corresponding increase of district's control console for centralized control point, found the problem that some demand urgently researching and solving in the operation gradually, operating reliability and the district's control central task efficient brought as the increase of regulated station number of spots reduce, and the district inserts the outstanding problems such as economic and social benefit how many regulated stations could obtain maximum in the control center.Therefore, simply consider the enabling capabilities of software and hardware technology and ignore control domain and enlarge the influence of back, will seriously hinder the development of Regional Control Center management mode economy and reliability.

Summary of the invention

The invention provides and a kind ofly can better bring into play the Regional Control Center effect, optimize and combine resource distribution to realize raising the efficiency and increasing the 500KV Regional Control Center control domain optimization system of benefit target.

Adopt following technical scheme for solving the problems of the technologies described above the present invention, this system comprises:

Model module is used to set up the also Mathematical Modeling in storage area control centre optimal control territory;

Data module is used for importing and the required basic parameter of memory model module Mathematical Modeling;

Computing module is used for calculating and event memory according to the Mathematical Modeling of model module and the basic parameter of data module;

Coding module is used for 500KV transformer station in the zone is carried out binary coding and stores this coding;

The optimizing module is used for seeking the also optimal solution set in storage area control centre optimal control territory according to the result of computing module and the coding of coding module by genetic algorithm;

Executive Module is used for optionally 500KV transformer station in the zone being inserted Regional Control Center and controlled by it according to the optimal solution set of optimizing module.

Because Regional Control Center is its central task with operation monitoring and control operation, so during the performance of this way to manage of evaluation region control centre, should mainly weigh from three aspects:

1) integrated cost of building and runing;

2) risk of operation monitoring;

3) efficient of control operation.

Model module is weighed quality with the different control domains of examining Regional Control Center with the target of above-mentioned three aspects, has set up Model for Multi-Objective Optimization, and its target function is expressed as:

F(X)＝[TC(X)，R(X)，E(X)]→Optimal (1)

(1) in the formula:

TC (X)---the integrated cost of scheme;

The risk indicator value of R (X)---scheme;

E (X)---the operating efficiency of scheme;

X---control variables set.

Because possible regulated station is a limited number of discrete variables, therefore, X is defined as each 500kV power transformation in the zone/string and mends the set of the control right of attribution at station as control variables in the Optimization Model target function, and the various combination of each station control right of attribution obtains different Region control schemes and makes control variables:

X _i＝[x _i1x _i2......x _im] (2)

(2) in the formula:

x _Ij, j ∈ 1,2 ..., M---refer to that j power transformation/string benefit stood in the control domain scheme of control center, i kind district

The control right of attribution; Control by Regional Control Center as if transformer station, then x _Ij Put 1; Otherwise, x _IjPut 0; M is the sum that power transformation in the zone/string is mended the station.

Above-mentioned employing [0,1] control variables, the control domain problem at control center, district just changes into for the two-value combinatorial optimization problem.

For Regional Control Center, the constraints that influences its control range generally comprises:

1. there is the requirement of design capacity and certain capacity nargin in master supervisory system, can certain restriction be arranged to the monitoring station quantity that inserts control center, district;

2. because the restriction in central apparatus quantity and space is controlled in the district, operations staff on duty has the constraint of some upper limits when can hold;

3. the concurrent operations task may appear in control center, district, in order to finish these concurrent tasks, the operations staff on duty who distinguishes the control center is had a quantitative lower limit constraint; Along with the expansion of control center, district control range, the probability of concurrent a plurality of operation task quantity also can become greatly, so this constraint is the function about control variables.

Therefore, the Optimization Model bound for objective function comprises:

(1) technological constraint of supervisory control system: definition dependent variable q _i500kV power transformation/the string that is Regional Control Center control in the i kind candidate control domain scheme is mended station quantity, then

$q_i=\underset{j=1}{\overset{M}{\mathrm{\Σ}}}{x}_{\mathrm{ij}}$

The note constant parameter is as follows:

B1, b2, b3-1 supervisory control system analog quantity, quantity of state and the output remote control amount number that transformer station on average takies;

B4-1 transformer station is to the percentage fill of supervisory control system CPU disposal ability;

B5-1 the protection management information system front end processor number that transformer station takies;

The transmission bandwidth of the remote image monitoring system that b6-1 transformer station takies;

A1, A2, supervisory control system analog quantity, quantity of state and output remote control amount capacity that A3-1 district control center software and hardware support system allows;

The front end processor number that A5-1 district control center protection management information system allows;

The total transmission bandwidth of permission of A6-1 district control center remote image monitoring system;

Then technological constraint can be expressed as:

b1*q _i≤A1；

b2*q _i≤A2；

b3*q _i≤A3；

b4*q _i≤25％；

b5*q _i≤A5；

b6*q _i≤A6。

(2) district's control center operations staff's restricted number: definition dependent variable m is the operator on duty of the operation class quantity of district's value in control center, then should satisfy following inequality constraints:

F _max(X _i)/W _p≤m≤m ₀ (3)

(3) in the formula:

Constant W _p: in operations staff's unit interval the operation task quantity that can handle;

Constant m ₀: the operation personnel amount on duty that the multipotency in control center, 1 district holds simultaneously;

F _Max: the maximum quantity of concurrent operations task in the same period in a year;

Obviously, F _MaxBe key and the difficult point that model module is set up Optimization Model.

If it is certain that transformer station/circuit produces the probability of operation, the quantity of then distinguishing control center access regulated station is many more, and the probability that produces the multioperation task in the same time period generation is big more.Statistics shows, the number of operations at control center, district is relevant with the switchgear total amount of its operation and management, therefore is similar to think the quantity E linear correlation of distinguishing contingent operation total amount F in the control center 1 year and controlled switchgear.

The switchgear total amount of note candidate scheme i inferior segment control center control is E _i, with the function statement E of control variables X _iFor:

$E_i=\underset{\underset{x_{\mathrm{ij}}\≠0}{j=1}}{\overset{M}{\mathrm{\Σ}}}{E}_{\mathrm{ij}}$

The note district average annual operation task number in control center is Ni, then can obtain both relations by actual count data linear fit:

N _i＝α*E _i+β (4)

(4) in the formula:

α, β are fitting coefficient, according to district's control center history run statistics sample (E _0j, N _0j, ask for by following formula with least square method,

$\left\{\begin{array}{c}\mathrm{\α}=\frac{[\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{N}_{0i}{E}_{0i}-\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{N}_{0i}{E}_{0i}/k]}{[\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{E_{0i}}^2-{\left(\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{E}_{0i}\right)}^2/k]}\\ \mathrm{\β}=\left(\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{N}_{0i}\right)/k-\mathrm{\α}\left(\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{E}_{0i}\right)/k\end{array}\right.---\left(5\right)$

(5) in the formula:

The scheme of the subscript 0 expression district current control domain correspondence in control center;

K is for calculating total sample number;

To the total operation amount N that takes place among the scheme i 1 year _iCan be obtained by formula (4), be T hour the average time that the note operator on duty finishes an operation task, when calculating the probability of a concurrent k operation task in the T period, remembers that its each operation task getting on the probability statistics of generation in [t, t+T] period arbitrarily:

p＝T/8760

Then the probability-distribution function that S operation task occur in the period [t, t+T] is:

$F(S=k)=C_F^k{p}^k{(1-p)}^{N_i-k}---\left(6\right)$

(6) in the formula:

The S value is 0,1 ..., k ..., N _iThis probability distribution is a binomial distribution, and the longitudinal axis is a probability distribution density under the serialization curve that its function normal distribution approaches, and transverse axis is the number that the same time operation task occurs, and the maximum of then getting S among the corresponding confidential interval Φ is F _Max

Estimate the benefit and the performance at control center, district, can carry out from integrated cost, operation risk and three aspects of operating efficiency.Economy is generally weighed with construction and operation cost.Operation risk is weighed according to the actual employing risk assessment index of Regional Control Center, i.e. risk probability of happening and bring the product of loss thus.Operating efficiency then adopts the operating time to weigh.Set up the Mathematical Modeling of respective objects function in the model module at three evaluation indexes.

The computing formula of TC in the Optimization Model target function (X) is:

$\mathrm{TC}=\mathrm{IC}\·(F/P,i,T)+\mathrm{OC}\·(F/A,i,T)$

$=\mathrm{IC}\·{(1+i)}^T+({\mathrm{OC}}_d+{\mathrm{OC}}_s)\·\left[\frac{{(1+i)}^T-1}{i}\right]---\left(7\right)$

(7) in the formula:

IC is the investment construction cost of Regional Control Center;

OC is that total operating cost comprises district's control center operation cost OC _dWith the total operating cost OC of transformer station _s

T is service life;

I is the fund annual rate of profit;

Because the investment construction cost at control center, district is for building disposable input then, the operation cost of control center, district and transformer station is then for dropping into year by year by average annual OC in the T.Take into account the time benefit of fund, convert the depreciation end of term and add up and obtain end of term integrated cost TC both are unified.

The investment construction cost IC computing formula of Regional Control Center is:

$\mathrm{IC}=\underset{j}{\mathrm{\Σ}}{C}_j+C_{\mathrm{CE}}+C_I---\left(8\right)$

(8) in the formula:

C _jBe the constant term cost, j represents the construction investment of " image shows for monitoring, protection, data, power supply, training " system respectively, and these transformer station's quantity with the control of control center, district are irrelevant, are fixed cost;

C _CEBe the communication system cost;

C _IInfrastructure construction cost for control center, district;

Along with transformer station's quantity increase of control center, district control, the input of communications optical cable and switching equipment also can increase, and it also arrives the distance dependent of control centre with regulated station, so C _CEComputing formula be:

$C_{\mathrm{CE}}=c_{\mathrm{CE}}\×\underset{k=1}{\overset{q_i}{\mathrm{\Σ}}}{d}_k---\left(9\right)$

(9) in the formula:

c _CEAverage cost (ten thousand/km) for every km communications service through converting;

d _kDistance for regulated station k distance areas control centre;

The infrastructure construction cost at control center, district contains costs such as office building, civil engineering, and main part is a constant term, necessarily disposes relevant variable item with personnel Regional Control Center but contain, so C _IComputing formula be:

C _I＝C _I0+C _II*np (10)

(10) in the formula:

C _I0Be the constant term in the capital construction;

C _IIBe variable coefficient per capita;

Np is district's total personnel's number in control center;

The daily operating cost at control center, district mainly comprises the labour cost of the annual payment of control centre, and so the gathering of expenses such as plant maintenance expense and daily operation expenses is OC _dComputing formula be:

OC _d＝C _p+C _D+C _EM (11)

(11) in the formula:

C _pBe district's control center year labour cost;

C _DDaily operation spending for control center, district;

C _EMBe the plant maintenance expense, only relevant with the number of devices at control center, district, can regard constant as;

Labour cost is proportional to control center, district worker's number, so C _pComputing formula be:

C _p＝ac*np (12)

(12) in the formula:

Ac is labour cost per capita;

Np is district's total personnel's number in control center;

The computing formula of np is:

np＝p ₀+p ₁

＝p ₀+q _oc*m (13)

(13) in the formula:

p ₀For with the quantity q of transformer station of control center, district control _iIrrelevant administration and administrative staff's constant;

p _IFor with the controlled quantity q of transformer station _iRelevant operation number on duty;

q _OcOperation class quantity for the Regional Control Center arrangement;

M is operator on duty's quantity of the operation class in control center, district.

Daily operation spending is relevant with control center, district worker's number, can be considered the linear function of worker's number np, so C _DComputing formula be:

C _D＝np×c _D0(14)

(14) in the formula:

c _D0Be everyone the average daily operation spending of control center, district;

Under given Region control pattern, transformer station can be divided into collection prosecutor formula transformer station and control mode transformer station two classes on the spot according to controlled form, so the total operating cost OC of transformer station _sComputing formula be:

OC _s＝OC _c+OC _l＝q _i*C _Lc+(M-q _i)*C _Ll+M*C _OD (15)

(15) in the formula:

OC _cBe collection prosecutor formula transformer station operation cost;

OC _lFor controlling the operation cost of transformer station on the spot;

q _iPower transformation/the string that is control center, district control in the i kind controlling schemes is mended station quantity;

C _LcLabour cost C for controlled transformer station _Lc

C _LlFor controlling the labour cost recruitment of transformer station on the spot;

M is the sum of 500KV transformer station in the zone;

C _ODFor collection prosecutor formula or control other daily expenditures of transformer station on the spot;

OC _cComputing formula be:

OC _c＝q _i*(C _Lc+C _OD)

C _LcComputing formula be:

C _Lc＝ac _s*n _cp (16)

(16) in the formula:

Ac _sBe labour cost per capita;

n _CpNumber total on duty for each controlled transformer station;

OC _lComputing formula be:

OC _l＝(M-q _i)*(C _Ll+C _OD)

C _LlComputing formula be:

C _Ll＝ac _s*n _lp (17)

(17) in the formula:

Ac _sBe labour cost per capita;

n _LpNumber total on duty for each controlled transformer station.

As seen, the main difference of two kinds of form transformer station operation costs is that the operation cost that the minimizing of number on duty causes reduces.Because collection prosecutor formula transformer station is because the main operational mode that adopts " unattended, few man on duty " is controlled in the distant place of region of acceptance control centre; Control mode transformer station then directly accepts the traditional 500KV substation operation attended mode of order employing of higher level's scheduling on the spot.

Operation monitoring risk indicator R is defined as: for transformer station all monitor message amounts in the zone, leak because of the operations staff and to see or wrongly see the operation of power networks value-at-risk that important information is brought that then the computing formula of R (X) is in the Optimization Model target function:

R(q _i)＝R ₁(q _i)+R ₂(q _i)＝(M-q _i)*C*p ₂+q _i*C*p ₁ (18)

(18) in the formula:

R ₁(q _i) for distinguishing control center operation risk value;

R ₂(q _i) be independent operating substation operation value-at-risk;

M is the sum that power transformation in the zone/string is mended the station;

C is the amount of information constant of each required monitoring of transformer station;

p ₁The operator on duty misunderstands or omits the probability of every information for the operation of control center, district;

p ₂For upright operation substation operation operator on duty misunderstands or omits the probability of every information.

Obviously, for control center, district, independent operating transformer station amount of information will have been lacked a lot, alleviate the operations staff to tasks such as the screening of amount of information, classification, improved efficiency for monitoring, simultaneously, transmission course in the middle of information reduces takes place to leak and sees or the wrong Probability p of human error such as seeing ₂See or leak the Probability p of seeing than district's control pattern little amount of information mistake ₁Little a lot.

The computing formula of E in the Optimization Model target function (X) is:

E(q _i)＝1/(T _l+T _d) (19)

(19) in the formula:

T _lBe the time of grid switching operation;

T _dBe the operating time of solution of emergent event prolongation;

The circuit grid switching operation relates to two ends transformer station, whether inserts control center, district according to circuit two ends transformer station, and the transmission line in the zone is divided into following three classes:

The category-A circuit: the transformer station that the circuit two ends connect inserts control center, district, and establishing such circuit, to finish the needed time of grid switching operation be t1;

The category-B circuit: the transformer station of circuit one end inserts control center, district, and the transformer station of the other end does not insert control center, district, and establishing the required time of such circuit grid switching operation is t2;

C class circuit: the transformer station that the circuit two ends connect does not all insert control center, district, and establishing the required time of such circuit grid switching operation is t3.

In general t2 and t3 difference are little, can get identical value, then T _lComputing formula be:

T _l＝2A(N _A*t ₁+(N _L-N _A)*t ₂)(20)

(20) in the formula:

A is the grid switching operation number of times desired value that single switch took place at interval in a year;

N _ABe category-A circuit sum;

N _LBe 500KV circuit sum in the zone;

t ₁For the category-A circuit is finished the needed time of grid switching operation;

t ₂For the category-B circuit is finished the needed time of grid switching operation

Taking place in transformer station need be more than 2 people on the spot during the burst accident of emergency processing, and control pattern in district's influence the efficient of emergency processing because the duty personnel is less, causes certain delay with respect to independent operation mode, totally incurs loss through delay total time T in 1 year _dWith access district's control center quantity q of transformer station _iSo positive correlation is T _dComputing formula be:

T _d＝q _i*P _d*t _d (21)

(21) in the formula:

P _dBe in 1 year transformer station take place need be more than the 2 people probability of the burst accident of emergency processing on the spot;

t _dTake place need be more than 2 people " unattended, few man on duty " pattern operating time of the prolongation that brings of " have people on duty " pattern relatively during the burst accident of emergency processing on the spot for each transformer station.

Binary coding is taked following mode in the coding module:

(1) the 500KV transformer station that does not insert Regional Control Center in the zone is numbered, as transformer station 1, transformer station 2 ... the M of transformer station;

(2) each the transformer station's object in the zone all has one group of corresponding property parameters, comprising: transformer station's coordinate, and main transformer platform number, number etc. is returned in outlet;

(3) numbering of each the loop line Lu Junyong two ends transformer station in the zone is to describing;

(4) get 1 for the binary code of the transformer station's correspondence that inserts Regional Control Center, otherwise get 0, the coded sequence that this group is represented by the binary code of M position is just represented a control domain scheme;

(5) t are shown for each and every one body surface of i of population

Wherein, j gene

(j ∈ 1,2 M) has reflected the controlled situation of the j of transformer station, value 1 or 0.

Genetic algorithm is taked following mode in the optimizing module:

(1) fitness function

If t is for i the chromosome of population

The preface value be

Definition

Fitness function be:

$S_i^t=\frac{1}{1+p_i^t}$

(2) two stage of multiple target genetic algorithm

Algorithm 1

1) initial population: given crossover probability p _c, the variation Probability p _m, population scale N, the maximum individual number M in maximum evolutionary generation T and the temporary storage; Produce the initial individual x of population scale at random _i=(x _I1x _I2, x _Im) (i=1,2 ..., N) constitute initial population p ₁, with p ₁In all individualities carry out quick non-domination ordering, be that all individualities of 1 are put into temporary storage A with preface value wherein ₁In, make t=1;

2) intersect: from p _tIn with crossover probability p _cThe picked at random several body forms the mating pond, is N from scale _c=N*p _cThe mating pond in select the parent individuality of a pair of participation interlace operation at random Carry out interlace operation, generate the offspring and be designated as The individuality of not participating in interlace operation is designated as the offspring of oneself, and the set that generates the offspring is designated as q _t

3) variation: from q _tIn with the variation Probability p _mSelect to participate in the parent individuality of mutation operation

Carry out mutation operation, generate the offspring

The individuality of not participating in mutation operation is designated as the offspring of oneself, and the set that generates the offspring is designated as

4) protect excellent file: use

Middle preface value is 1 individuality replacement A _tIn individuality, and generate new interim holder A _T+1

5) select: right

In individuality, determine that fitness function is Individuality is pressed the descending ordering of fitness, choose top n and form population p of future generation _T+1, make t=t+1;

6) end condition: as temporary storage A _T+1In individual number when reaching M, change algorithm 2; When satisfying default algebraically T, stop output A _T+1In individuality, otherwise, change the step (2);

Algorithm 2

1) initial population: be used for the identical crossover probability p of algorithm 1 _c, the variation Probability p _m, population scale N, and the maximum individual number M in the temporary storage are with p _tIn individuality be initial population, to p _tIn individuality, carry out following algorithm operating;

2) intersect: from p _tIn with crossover probability p _cThe picked at random several body forms the mating pond, is N from scale _c=N*p _cThe mating pond in select the parent individuality of a pair of participation interlace operation at random

Carry out interlace operation, generate the offspring and be designated as

The individuality of not participating in interlace operation is designated as the offspring of oneself, and the set that generates the offspring is designated as q _t

3) variation: from q _tIn with the variation Probability p _mSelect to participate in the parent individuality of mutation operation

Carry out mutation operation, generate the offspring

The individuality of not participating in interlace operation is designated as the offspring of oneself, and the set that generates the offspring is designated as

4) protect excellent file: use

Middle preface value is 1 individuality replacement A _tIn individual and generate new interim holder A _T+1, when | A _T+1|＞during M, reduce A by the method for determining crowding _T+1In individual number to M;

5) select: right

In individuality, determine that fitness function is Individuality is pressed the descending ordering of fitness, choose top n and form population p of future generation _T+1, make t=t+1;

6) end condition: when satisfying default algebraically T, or individual number reaches M in the temporary storage, and makes ρ _t, s _tAll be tending towards at 0 o'clock, stop, output A _T+1In individuality, otherwise, change the step (2).

Executive Module optionally inserts 500KV transformer station in the zone Regional Control Center and controlled by it by 2M bridge and front server.

Performance Regional Control Center effect that the present invention is abundant, optimize and combine power network resources configuration, realized raising the efficiency and increasing the target of benefit.

Description of drawings

Fig. 1 is the structural representation of 500KV Regional Control Center control domain optimization system of the present invention.

Fig. 2 is two stage of the multiple target genetic algorithm flow chart that the optimizing module adopts in the 500KV Regional Control Center control domain optimization system of the present invention.

Fig. 3 is a structural representation of optimizing 500KV transformer station electrical network in the Regional Control Center zone, preceding Nanning.

Fig. 4 is a structural representation of optimizing 500KV transformer station electrical network in the Regional Control Center zone, Nanning, back.

Among the figure: 1 transformer station or string are mended station, 22M bridge, 3 front servers, the server of 4 Regional Control Centers, 5 Regional Control Center control domain optimization system.

Embodiment

As shown in Figure 1,500KV Regional Control Center control domain optimization system of the present invention comprises six modules, is respectively model module, data module, computing module, coding module, optimizing module and Executive Module.Wherein, the prior also Mathematical Modeling in storage area control centre optimal control territory of setting up is also stored wherein from the outside through data module input data in the model module; At this moment, computing module calculates also event memory in conjunction with model and data that both provide; Then, this result is transferred to the optimizing module in the lump with the binary coding that is preset at the interior 500KV transformer station in zone in the coding module, seeks the also optimal solution set in storage area control centre optimal control territory at this by genetic algorithm; At last, 500KV transformer station in the optimal solution set selection area that is provided according to a last module by Executive Module inserts them Regional Control Center and includes its extent of actual control in.

Wherein, model module is from three aspects 1) build and the integrated cost of operation; 2) risk of operation monitoring; 3) efficient of control operation is weighed the quality with the different control domains of examining Regional Control Center, has set up Model for Multi-Objective Optimization thus, and its target function is expressed as:

F(X)＝[TC(X)，R(X)，E(X)]→Optimal (1)

(1) in the formula:

TC (X)---the integrated cost of scheme;

The risk indicator value of R (X)---scheme;

E (X)---the operating efficiency of scheme;

X---control variables set.

Because possible regulated station is a limited number of discrete variables, therefore, X is defined as each 500kV power transformation in the zone/string and mends the set of the control right of attribution at station as control variables in the Optimization Model target function, and the various combination of each station control right of attribution obtains different Region control schemes and makes control variables:

X _i＝[x _i1x _i2......x _im] (2)

(2) in the formula:

x _Ij, j ∈ 1,2 ..., M---refer to that j power transformation/string mended the control right of attribution of standing in the control domain scheme of control center, i kind district; Control by Regional Control Center as if transformer station, then x _Ij Put 1; Otherwise, x _IjPut 0; M is the sum that power transformation in the zone/string is mended the station.

Above-mentioned employing [0,1] control variables, the control domain problem at control center, district just changes into for the two-value combinatorial optimization problem.

For Regional Control Center, the constraints that influences its control range generally comprises:

1. there is the requirement of design capacity and certain capacity nargin in master supervisory system, can certain restriction be arranged to the monitoring station quantity that inserts control center, district;

2. because the restriction in central apparatus quantity and space is controlled in the district, operations staff on duty has the constraint of some upper limits when can hold;

3. the concurrent operations task may appear in control center, district, in order to finish these concurrent tasks, the operations staff on duty who distinguishes the control center is had a quantitative lower limit constraint; Along with the expansion of control center, district control range, the probability of concurrent a plurality of operation task quantity also can become greatly, so this constraint is the function about control variables.

Therefore, the Optimization Model bound for objective function comprises:

(1) technological constraint of supervisory control system: definition dependent variable q _i500kV power transformation/the string that is Regional Control Center control in the i kind candidate control domain scheme is mended station quantity, then

$q_i=\underset{j=1}{\overset{M}{\mathrm{\Σ}}}{x}_{\mathrm{ij}}$

The note constant parameter is as follows:

B1, b2, b3-1 supervisory control system analog quantity, quantity of state and the output remote control amount number that transformer station on average takies;

B4-1 transformer station is to the percentage fill of supervisory control system CPU disposal ability;

B5-1 the protection management information system front end processor number that transformer station takies;

The transmission bandwidth of the remote image monitoring system that b6-1 transformer station takies;

A1, A2, supervisory control system analog quantity, quantity of state and output remote control amount capacity that A3-1 district control center software and hardware support system allows;

The front end processor number that A5-1 district control center protection management information system allows;

The total transmission bandwidth of permission of A6-1 district control center remote image monitoring system;

Then technological constraint can be expressed as:

b1*q _i≤A1；

b2*q _i≤A2；

b3*q _i≤A3；

b4*q _i≤25％；

b5*q _i≤A5；

b6*q _i≤A6。

(2) district's control center operations staff's restricted number: definition dependent variable m is the operator on duty of the operation class quantity of district's value in control center, then should satisfy following inequality constraints:

F _max(X _i)/W _p≤m≤m ₀(3)

(3) in the formula:

Constant W _p: in operations staff's unit interval the operation task quantity that can handle;

Constant m ₀: the operation personnel amount on duty that the multipotency in control center, 1 district holds simultaneously;

F _MaxThe maximum quantity of concurrent operations task in the same period in 1 year;

Obviously, F _MaxBe key and the difficult point that model module is set up Optimization Model.

If it is certain that transformer station/circuit produces the probability of operation, the quantity of then distinguishing control center access regulated station is many more, and the probability that produces the multioperation task in the same time period generation is big more.Statistics shows, the number of operations at control center, district is relevant with the switchgear total amount of its operation and management, therefore is similar to think the quantity E linear correlation of distinguishing contingent operation total amount F in the control center 1 year and controlled switchgear.

The switchgear total amount of note candidate scheme i inferior segment control center control is E _i, with the function statement E of control variables X _iFor:

$E_i=\underset{\underset{x_{\mathrm{ij}}\≠0}{j=1}}{\overset{M}{\mathrm{\Σ}}}{E}_{\mathrm{ij}}$

The note district average annual operation task number in control center is Ni, then can obtain both relations by actual count data linear fit:

N _i＝α*E _i+β (4)

(4) in the formula:

α, β are fitting coefficient, according to district's control center history run statistics sample (E _0j, N _0j), ask for by following formula with least square method,

$\left\{\begin{array}{c}\mathrm{\α}=\frac{[\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{N}_{0i}{E}_{0i}-\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{N}_{0i}{E}_{0i}/k]}{[\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{E_{0i}}^2-{\left(\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{E}_{0i}\right)}^2/k]}\\ \mathrm{\β}=\left(\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{N}_{0i}\right)/k-\mathrm{\α}\left(\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{E}_{0i}\right)/k\end{array}\right.---\left(5\right)$

(5) in the formula:

The scheme of the subscript 0 expression district current control domain correspondence in control center;

K is for calculating total sample number;

To the total operation amount N that takes place among the scheme i 1 year _iCan be obtained by formula (4), be T hour the average time that the note operator on duty finishes an operation task, when calculating the probability of a concurrent k operation task in the T period, remembers that its each operation task getting on the probability statistics of generation in [t, t+T] period arbitrarily:

p＝T/8760

Then the probability-distribution function that S operation task occur in the period [t, t+T] is:

$F(S=k)=C_F^k{p}^k{(1-p)}^{N_i-k}---\left(6\right)$

(6) in the formula:

The S value is 0,1 ..., k ..., N _iThis probability distribution is a binomial distribution, its function normal distribution

The longitudinal axis is a probability distribution density under the serialization curve that approaches, and transverse axis is the number that the same time operation task occurs, and the maximum of then getting S among the corresponding confidential interval Φ is F _Max

Estimate the benefit and the performance at control center, district, can carry out from integrated cost, operation risk and three aspects of operating efficiency.Economy is generally weighed with construction and operation cost.Operation risk is weighed according to the actual employing risk assessment index of Regional Control Center, i.e. risk probability of happening and bring the product of loss thus.Operating efficiency then adopts the operating time to weigh.Set up the Mathematical Modeling of respective objects function in the model module at three evaluation indexes.

The computing formula of TC in the Optimization Model target function (X) is:

$\mathrm{TC}=\mathrm{IC}\·(F/P,i,T)+\mathrm{OC}\·(F/A,i,T)$

$=\mathrm{IC}\·{(1+i)}^T+({\mathrm{OC}}_d+{\mathrm{OC}}_s)\·\left[\frac{{(1+i)}^T-1}{i}\right]---\left(7\right)$

(7) in the formula:

IC is the investment construction cost of Regional Control Center;

OC is that total operating cost comprises district's control center operation cost OC _dWith the total operating cost OC of transformer station _s

T is service life;

I is the fund annual rate of profit;

Because the investment construction cost at control center, district is for building disposable input then, the operation cost of control center, district and transformer station is then for dropping into year by year by average annual OC in the T.Take into account the time benefit of fund, convert the depreciation end of term and add up and obtain end of term integrated cost TC both are unified.

The investment construction cost IC computing formula of Regional Control Center is:

$\mathrm{IC}=\underset{j}{\mathrm{\Σ}}{C}_j+C_{\mathrm{CE}}+C_I---\left(8\right)$

(8) in the formula:

C _jBe the constant term cost, j represents the construction investment of " image shows for monitoring, protection, data, power supply, training " system respectively, and these transformer station's quantity with the control of control center, district are irrelevant, are fixed cost;

C _CEBe the communication system cost;

C _IInfrastructure construction cost for control center, district;

Along with transformer station's quantity increase of control center, district control, the input of communications optical cable and switching equipment also can increase, and it also arrives the distance dependent of control centre with regulated station, so C _CEComputing formula be:

$C_{\mathrm{CE}}=c_{\mathrm{CE}}\×\underset{k=1}{\overset{q_i}{\mathrm{\Σ}}}{d}_k---\left(9\right)$

(9) in the formula:

c _CEAverage cost (ten thousand/km) for every km communications service through converting;

d _kDistance for regulated station k distance areas control centre;

The infrastructure construction cost at control center, district contains costs such as office building, civil engineering, and main part is a constant term, necessarily disposes relevant variable item with personnel Regional Control Center but contain, so C _IComputing formula be:

C _I＝C _I0+C _II*np (10)

(10) in the formula:

C _I0Be the constant term in the capital construction;

C _IIBe variable coefficient per capita;

Np is district's total personnel's number in control center;

The daily operating cost at control center, district mainly comprises the labour cost of the annual payment of control centre, and so the gathering of expenses such as plant maintenance expense and daily operation expenses is OC _dComputing formula be:

OC _d＝C _p+C _D+C _EM (11)

(11) in the formula:

C _pBe district's control center year labour cost;

C _DDaily operation spending for control center, district;

C _EMBe the plant maintenance expense, only relevant with the number of devices at control center, district, can regard constant as;

Labour cost is proportional to control center, district worker's number, so C _pComputing formula be:

C _p＝ac*np (12)

(12) in the formula:

Ac is labour cost per capita;

Np is district's total personnel's number in control center;

The computing formula of np is:

np＝p ₀+p ₁

＝p ₀+q _oc*m (13)

(13) in the formula:

p ₀For with the quantity q of transformer station of control center, district control _iIrrelevant administration and administrative staff's constant;

p _IFor with the controlled quantity q of transformer station _iRelevant operation number on duty;

q _OcOperation class quantity for the Regional Control Center arrangement;

M is operator on duty's quantity of the operation class in control center, district.

Daily operation spending is relevant with control center, district worker's number, can be considered the linear function of worker's number np, so C _DComputing formula be:

C _D＝np×c _D0(14)

(14) in the formula:

c _D0Be everyone the average daily operation spending of control center, district;

Under given Region control pattern, transformer station can be divided into collection prosecutor formula transformer station and control mode transformer station two classes on the spot according to controlled form, so the total operating cost OC of transformer station _sComputing formula be:

OC _s＝OC _c+OC _l＝q _i*C _Lc+(M-q _i)*C _Ll+M*C _OD (15)

(15) in the formula:

OC _cBe collection prosecutor formula transformer station operation cost;

OC _lFor controlling the operation cost of transformer station on the spot;

q _iPower transformation/the string that is control center, district control in the i kind controlling schemes is mended station quantity;

C _LcLabour cost C for controlled transformer station _Lc

C _LlFor controlling the labour cost recruitment of transformer station on the spot;

M is the sum of 500KV transformer station in the zone;

C _ODFor collection prosecutor formula or control other daily expenditures of transformer station on the spot;

OC _cComputing formula be:

OC _c＝q _i*(C _Lc+C _OD)

C _LcComputing formula be:

C _Lc＝ac _s*n _cp (16)

(16) in the formula:

Ac _sBe labour cost per capita;

n _CpNumber total on duty for each controlled transformer station;

OC _lComputing formula be:

OC _l＝(M-q _i)*(C _Ll+C _OD)

C _LlComputing formula be:

C _Ll＝ac _s*n _lp (17)

(17) in the formula:

Ac _sBe labour cost per capita;

n _LpNumber total on duty for each controlled transformer station.

As seen, the main difference of two kinds of form transformer station operation costs is that the operation cost that the minimizing of number on duty causes reduces.Because collection prosecutor formula transformer station is because the main operational mode that adopts " unattended, few man on duty " is controlled in the distant place of region of acceptance control centre; Control mode transformer station then directly accepts the traditional 500KV substation operation attended mode of order employing of higher level's scheduling on the spot.

Operation monitoring risk indicator R is defined as: for transformer station all monitor message amounts in the zone, leak because of the operations staff and to see or wrongly see the operation of power networks value-at-risk that important information is brought that then the computing formula of R (X) is in the Optimization Model target function:

R(q _i)＝R ₁(q _i)+R ₂(q _i)＝(M-q _i)*C*p ₂+q _i*C*p ₁ (18)

(18) in the formula:

R ₁(q _i) for distinguishing control center operation risk value;

R ₂(q _i) be independent operating substation operation value-at-risk;

M is the sum that power transformation in the zone/string is mended the station;

C is the amount of information constant of each required monitoring of transformer station;

p ₁The operator on duty misunderstands or omits the probability of every information for the operation of control center, district;

p ₂For upright operation substation operation operator on duty misunderstands or omits the probability of every information.

Obviously, for control center, district, independent operating transformer station amount of information will have been lacked a lot, alleviate the operations staff to tasks such as the screening of amount of information, classification, improved efficiency for monitoring, simultaneously, transmission course in the middle of information reduces takes place to leak and sees or the wrong Probability p of human error such as seeing ₂See or leak the Probability p of seeing than district's control pattern little amount of information mistake ₁Little a lot.

The computing formula of E in the Optimization Model target function (X) is:

E(q _i)＝1/(T _l+T _d) (19)

(19) in the formula:

T _lBe the time of grid switching operation;

T _dBe the operating time of solution of emergent event prolongation;

The circuit grid switching operation relates to two ends transformer station, whether inserts control center, district according to circuit two ends transformer station, and the transmission line in the zone is divided into following three classes:

The category-A circuit: the transformer station that the circuit two ends connect inserts control center, district, and establishing such circuit, to finish the needed time of grid switching operation be t1;

The category-B circuit: the transformer station of circuit one end inserts control center, district, and the transformer station of the other end does not insert control center, district, and establishing the required time of such circuit grid switching operation is t2;

C class circuit: the transformer station that the circuit two ends connect does not all insert control center, district, and establishing the required time of such circuit grid switching operation is t3.

In general t2 and t3 difference are little, can get identical value, then T _lComputing formula be:

T _l＝2A(N _A*t ₁+(N _L-N _A)*t ₂) (20)

(20) in the formula:

A is the grid switching operation number of times desired value that single switch took place at interval in a year;

N _ABe category-A circuit sum;

N _LBe 500KV circuit sum in the zone;

t ₁For the category-A circuit is finished the needed time of grid switching operation;

t ₂For the category-B circuit is finished the needed time of grid switching operation

Taking place in transformer station need be more than 2 people on the spot during the burst accident of emergency processing, and control pattern in district's influence the efficient of emergency processing because the duty personnel is less, causes certain delay with respect to independent operation mode, totally incurs loss through delay total time T in 1 year _dWith access district's control center quantity q of transformer station _iSo positive correlation is T _dComputing formula be:

T _d＝q _i*P _d*t _d (21)

(21) in the formula:

P _dBe in 1 year transformer station take place need be more than the 2 people probability of the burst accident of emergency processing on the spot;

t _dTake place need be more than 2 people " unattended, few man on duty " pattern operating time of the prolongation that brings of " have people on duty " pattern relatively during the burst accident of emergency processing on the spot for each transformer station.Binary coding is taked following mode in the coding module:

(1) the 500KV transformer station that does not insert Regional Control Center in the zone is numbered, as transformer station 1, transformer station 2 ... the M of transformer station;

(2) each the transformer station's object in the zone all has one group of corresponding property parameters, comprising: transformer station's coordinate, and main transformer platform number, number etc. is returned in outlet;

(3) numbering of each the loop line Lu Junyong two ends transformer station in the zone is to describing;

(4) get 1 for the binary code of the transformer station's correspondence that inserts Regional Control Center, otherwise get 0, the coded sequence that this group is represented by the binary code of M position is just represented a control domain scheme;

(5) t are shown for each and every one body surface of i of population

Wherein, j gene

(j ∈ 1,2 M) has reflected the controlled situation of the j of transformer station, value 1 or 0.

Genetic algorithm is taked following mode in the optimizing module:

(1) fitness function

If t is for i the chromosome of population

The preface value be

Definition

Fitness function be:

$S_i^t=\frac{1}{1+p_i^t}$

(2) two stage of multiple target genetic algorithm (see figure 2)

Algorithm 1

1) initial population: given crossover probability p _c, the variation Probability p _m, population scale N, the maximum individual number M in maximum evolutionary generation T and the temporary storage; Produce the initial individual x of population scale at random _i=(x _I1, x _I2..., x _Im) (i=1,2 ..., N) constitute initial population p ₁, with p ₁In all individualities carry out quick non-domination ordering, be that all individualities of 1 are put into temporary storage A with preface value wherein ₁In, make t=1;

2) intersect: from p _tIn with crossover probability p _cThe picked at random several body forms the mating pond, is N from scale _c=N*p _cThe mating pond in select the parent individuality of a pair of participation interlace operation at random

Carry out interlace operation, generate the offspring and be designated as

The individuality of not participating in interlace operation is designated as the offspring of oneself, and the set that generates the offspring is designated as q _t

3) variation: from q _tIn with the variation Probability p _mSelect to participate in the parent individuality of mutation operation

Carry out mutation operation, generate the offspring

The individuality of not participating in mutation operation is designated as the offspring of oneself, and the set that generates the offspring is designated as

4) protect excellent file: use Middle preface value is 1 individuality replacement A _tIn individuality, and generate new interim holder A _T+1

5) select: right In individuality, determine that fitness function is

Individuality is pressed the descending ordering of fitness, choose top n and form population p of future generation _T+1' make t=t+1;

6) end condition: as temporary storage A _T+1In individual number when reaching M, change algorithm 2; When satisfying default algebraically T, stop output A _T+1In individuality, otherwise, change the step (2);

Algorithm 2

1) initial population: be used for the identical crossover probability p of algorithm 1 _c, the variation Probability p _m, population scale N, and the maximum individual number M in the temporary storage are with p _tIn individuality be initial population, to p _tIn individuality, carry out following algorithm operating;

2) intersect: from p _tIn with crossover probability p _cThe picked at random several body forms the mating pond, is N from scale _c=N*p _cThe mating pond in select the parent individuality of a pair of participation interlace operation at random

Carry out interlace operation, generate the offspring and be designated as

The individuality of not participating in interlace operation is designated as the offspring of oneself, and the set that generates the offspring is designated as q _t

3) variation: from q _tIn with the variation Probability p _mSelect to participate in the parent individuality of mutation operation

Carry out mutation operation, generate the offspring

The individuality of not participating in interlace operation is designated as the offspring of oneself, and the set that generates the offspring is designated as

4) protect excellent file: use Middle preface value is 1 individuality replacement A _tIn individual and generate new interim holder A _T+1, when | A _T+1|＞during M, reduce A by the method for determining crowding _T+1In individual number to M;

5) select: right

In individuality, determine that fitness function is

Individuality is pressed the descending ordering of fitness, choose top n and form population p of future generation _T+1, make t=t+1;

6) end condition: when satisfying default algebraically T, or individual number reaches M in the temporary storage, and makes ρ _t, s _tAll be tending towards at 0 o'clock, stop, output A _T+1In individuality, otherwise, change the step (2).

Executive Module optionally inserts Regional Control Center with 500KV transformer station in the zone by 2M bridge and front server, grasps its de facto control to realize Regional Control Center.

The structure of 500KV transformer station electrical network in the Regional Control Center zone, the preceding Nanning of Fig. 3 display optimization, as seen from the figure, 500KV transformer station or string are mended station 1 in the zone totally 13 of A-M, the server 4 of Regional Control Center is mended the station by 2M bridge 2 and front server 3 with 500KV transformer station or string and is got in touch, wherein, solid line connects the actual directly actuated power transformation that inserts and distinguished the control center of expression/string benefit station 6: station, A Nanning, station, B Chongzuo, station, C Baise, D Baise string are mended station, station, E Pingguo and string benefit station, F Pingguo; Dotted line connection expression has pilot signal to write to each other with control center, district but reality is not controlled by it, by each station independent operation operation.Therefore, the control at 6 stations of A-F is not participated in coding as the fact of determining.The essence of the control domain allocation problem of Nanning district control is the control selection problem of remaining power transformation/string being mended the station, and it is respectively that station, G rivers and ponds, H rivers and ponds string are mended station, I guest station, J willow eastern station, station, K Wuzhou, station, L Guilin and station, M He Prefecture that these 7 power transformations/string is mended the station.According to the data of model module needs, the actual parameter or the historical data at above 13 stations of input in data module are as A1, A2, A3 ... C _j, C _DDeng, module, coding module, optimizing resume module obtain Regional Control Center optimal control territory, Nanning suggested design as calculated, that is: station, Nanning, station, Chongzuo, station, Baise, Baise are gone here and there and are mended station, station, Pingguo, string benefit station, Pingguo, station, rivers and ponds, string benefit station, rivers and ponds, guest station, Liu Dongzhan, the control station number is 10, district's every value in control center disposes 6 people at least, can realize total optimization under every constraints before satisfying district's control centrales like this.At last by Executive Module according to the optimizing result, station, G rivers and ponds, string benefit station, H rivers and ponds, I guest station, J willow eastern station are inserted Regional Control Center and controlled by it by 2M bridge and front server, grasp its de facto control (see figure 4) to realize Regional Control Center.

Claims (10)

1. 500KV Regional Control Center control domain optimization system is characterized in that this system comprises:

Model module is used to set up the also Mathematical Modeling in storage area control centre optimal control territory;

Data module is used for importing and the required basic parameter of memory model module Mathematical Modeling;

Computing module is used for calculating and event memory according to the Mathematical Modeling of model module and the basic parameter of data module;

Coding module is used for 500KV transformer station in the zone is carried out binary coding and stores this coding;

The optimizing module is used for seeking the also optimal solution set in storage area control centre optimal control territory according to the result of computing module and the coding of coding module by genetic algorithm;

Executive Module is used for optionally 500KV transformer station in the zone being inserted Regional Control Center and controlled by it according to the optimal solution set of optimizing module.

2. 500KV Regional Control Center control domain optimization system according to claim 1 is characterized in that described Mathematical Modeling is a Model for Multi-Objective Optimization, and its target function is expressed as:

F(X)＝[TC(X)，R(X)，E(X)]→Optimal (1)

(1) in the formula:

TC (X)---the integrated cost of scheme;

The risk indicator value of R (X)---scheme;

E (X)---the operating efficiency of scheme;

X---control variables set.

3. 500KV Regional Control Center control domain optimization system according to claim 2, it is characterized in that described X is defined as each 500kV power transformation in the zone/string and mends the set of the control right of attribution at station as control variables, the various combination of each station control right of attribution obtains different Region control schemes and makes control variables:

X _i＝[x _i1x _i2......x _im] (2)

(2) in the formula:

x _Ij, j ∈ 1,2 ..., M---refer to that j power transformation/string mended the control right of attribution of standing in the control domain scheme of control center, i kind district; Control by Regional Control Center as if transformer station, then x _IjPut 1; Otherwise, x _IjPut 0; M is the sum that power transformation in the zone/string is mended the station.

4. 500KV Regional Control Center control domain optimization system according to claim 2 is characterized in that described bound for objective function comprises:

(1) technological constraint of supervisory control system: definition dependent variable q _i500kV power transformation/the string that is Regional Control Center control in the i kind candidate control domain scheme is mended station quantity, then

$q_i=\underset{j=1}{\overset{M}{\mathrm{\Σ}}}{x}_{\mathrm{ij}}$

The note constant parameter is as follows:

B1, b2, b3-1 supervisory control system analog quantity, quantity of state and the output remote control amount number that transformer station on average takies;

B4-1 transformer station is to the percentage fill of supervisory control system CPU disposal ability;

B5-1 the protection management information system front end processor number that transformer station takies;

The transmission bandwidth of the remote image monitoring system that b6-1 transformer station takies;

A1, A2, supervisory control system analog quantity, quantity of state and output remote control amount capacity that A3-1 district control center software and hardware support system allows;

The front end processor number that A5-1 district control center protection management information system allows;

The total transmission bandwidth of permission of A6-1 district control center remote image monitoring system;

Then technological constraint can be expressed as:

b1*q _i≤A1；

b2*q _i≤A2；

b3*q _i≤A3；

b4*q _i≤25％；

b5*q _i≤A5；

b6*q _i≤A6。

(2) district's control center operations staff's restricted number: definition dependent variable m is the operator on duty of the operation class quantity of district's value in control center, then should satisfy following inequality constraints:

F _max(X _i)/W _p≤m≤m ₀ (3)

(3) in the formula:

Constant W _p: in operations staff's unit interval the operation task quantity that can handle;

Constant m ₀: the operation personnel amount on duty that the multipotency in control center, 1 district holds simultaneously;

F _Max: the maximum quantity of concurrent operations task in the same period in a year;

The switchgear total amount of note candidate scheme i inferior segment control center control is Ei, explains Ei with the function of control variables X and is:

$E_i=\underset{\underset{x_{\mathrm{ij}}\≠0}{j=1}}{\overset{M}{\mathrm{\Σ}}}{E}_{\mathrm{ij}}$

The note district average annual operation task number in control center is Ni, then:

N _i＝α*E _i+β (4)

(4) in the formula:

α, β are fitting coefficient, according to district's control center history run statistics sample (E0j N0j), asks for by following formula,

$\left\{\begin{array}{c}\mathrm{\α}=\frac{[\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{N}_{0i}{E}_{0i}-\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{N}_{0i}{E}_{0i}/k]}{[\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{E_{0i}}^2-{\left(\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{E}_{0i}\right)}^2/k]}\\ \mathrm{\β}=\left(\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{N}_{0i}\right)/k-\mathrm{\α}\left(\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{E}_{0i}\right)/k\end{array}\right.---\left(5\right)$

(5) in the formula:

The scheme of the subscript 0 expression district current control domain correspondence in control center;

K is for calculating total sample number;

Be T hour the average time that the note operator on duty finishes an operation task, when calculating the probability of a concurrent k operation task in the T period, remembers that the probability that its each operation task takes place is in any [t, t+T] period:

p＝T/8760

Then the probability-distribution function that S operation task occur in the period [t, t+T] is:

$F(S=k)=C_F^k{p}^k{(1-p)}^{N_i-k}---\left(6\right)$

(6) in the formula:

The S value is 0,1 ..., k ..., N _iUnder the serialization curve that this probability-distribution function normal distribution approaches among the corresponding confidential interval Φ maximum of S be F _Max

5. 500KV Regional Control Center control domain optimization system according to claim 2 is characterized in that the computing formula of described TC (X) is:

$\mathrm{TC}=\mathrm{IC}\·(F/P,i,T)+\mathrm{OC}\·(F/A,i,T)$

$=\mathrm{IC}\·{(1+i)}^T+({\mathrm{OC}}_d+{\mathrm{OC}}_s)\·\left[\frac{{(1+i)}^T-1}{i}\right]---\left(7\right)$

(7) in the formula:

IC is the investment construction cost of Regional Control Center;

OC is that total operating cost comprises district's control center operation cost OC _dWith the total operating cost OC of transformer station _s

T is service life;

I is the fund annual rate of profit;

The investment construction cost IC computing formula of Regional Control Center is:

$\mathrm{IC}=\underset{j}{\mathrm{\Σ}}{C}_j+C_{\mathrm{CE}}+C_I---\left(8\right)$

(8) in the formula:

C _jBe the constant term cost, j represents " image shows for monitoring, protection, data, power supply, training " respectively

The construction investment of system;

C _CEBe the communication system cost;

C _IInfrastructure construction cost for control center, district;

C _CEComputing formula be:

$C_{\mathrm{CE}}=c_{\mathrm{CE}}\×\underset{k=1}{\overset{q_i}{\mathrm{\Σ}}}{d}_k---\left(9\right)$

(9) in the formula:

c _CEAverage cost (ten thousand/km) for every km communications service through converting;

d _kDistance for regulated station k distance areas control centre;

C _IComputing formula be:

C _I＝C _I0+C _II*np (10)

(10) in the formula:

C _I0Be the constant term in the capital construction;

C _IIBe variable coefficient per capita;

Np is district's total personnel's number in control center;

OC _dComputing formula be:

OC _d＝C _p+C _D+C _EM (11)

(11) in the formula:

C _pBe district's control center year labour cost;

C _DDaily operation spending for control center, district;

C _EMBe plant maintenance expense constant;

C _pComputing formula be:

C _p＝ac*np (12)

(12) in the formula:

Ac is labour cost per capita;

Np is district's total personnel's number in control center;

The computing formula of np is:

np＝p ₀+p ₁

＝p ₀+q _oc*m (13)

(13) in the formula:

p ₀For with the quantity q of transformer station of control center, district control _iIrrelevant administration and administrative staff's constant;

p ₁For with the controlled quantity q of transformer station _iRelevant operation number on duty;

q _OcOperation class quantity for the Regional Control Center arrangement;

M is operator on duty's quantity of the operation class in control center, district.

C _DComputing formula be:

C _D＝np×c _D0 (14)

(14) in the formula:

c _D0Be everyone the average daily operation spending of control center, district;

OC _sComputing formula be:

OC _s＝OC _c+OC _l＝q _i*C _Lc+(M-q _i)*C _Ll+M*C _OD (15)

(15) in the formula:

OC _cBe collection prosecutor formula transformer station operation cost;

OC _lFor controlling the operation cost of transformer station on the spot;

q _iPower transformation/the string that is control center, district control in the i kind controlling schemes is mended station quantity;

C _LcLabour cost C for controlled transformer station _Lc

C _LlFor controlling the labour cost recruitment of transformer station on the spot;

M is the sum of 500KV transformer station in the zone;

C _ODFor collection prosecutor formula or control other daily expenditures of transformer station on the spot;

OC _cComputing formula be:

OC _c＝q _i*(C _Lc+C _OD)

C _LcComputing formula be:

C _Lc＝ac _s*n _cp (16)

(16) in the formula:

Ac _sBe labour cost per capita;

n _CpNumber total on duty for each controlled transformer station;

OC _lComputing formula be:

OC _l＝(M-q _i)*(C _Ll+C _OD)

C _LlComputing formula be:

C _Ll＝ac _s*n _lp (17)

(17) in the formula:

Ac _sBe labour cost per capita;

n _LpNumber total on duty for each controlled transformer station.

6. 500KV Regional Control Center control domain optimization system according to claim 2 is characterized in that the computing formula of described R (X) is:

R(q _i)＝R ₁(q _i)+R ₂(q _i)＝(M-q _i)*C*p ₂+q _i*C*p ₁ (18)

(18) in the formula:

R ₁(q _i) for distinguishing control center operation risk value;

R ₂(q _i) be independent operating substation operation value-at-risk;

M is the sum that power transformation in the zone/string is mended the station;

C is the amount of information constant of each required monitoring of transformer station;

p ₁The operator on duty misunderstands or omits the probability of every information for the operation of control center, district;

p ₂For upright operation substation operation operator on duty misunderstands or omits the probability of every information.

7. 500KV Regional Control Center control domain optimization system according to claim 2 is characterized in that the computing formula of described E (X) is:

E(q _i)＝1/(T ₁+T _d) (19)

(19) in the formula:

T ₁Be the time of grid switching operation;

T _dBe the operating time of solution of emergent event prolongation;

T ₁Computing formula be:

T _l＝2A(N _A*t ₁+(N _L-N _A)*t ₂) (20)

(20) in the formula:

A is the grid switching operation number of times desired value that single switch took place at interval in a year;

N _ABe category-A circuit sum;

N _LBe 500KV circuit sum in the zone;

t ₁For the category-A circuit is finished the needed time of grid switching operation;

t ₂For the category-B circuit is finished the needed time of grid switching operation;

T _dComputing formula be:

T _d＝q _i*P _d*t _d (21)

(21) in the formula:

P _dBe in 1 year transformer station take place need be more than the 2 people probability of the burst accident of emergency processing on the spot;

t _dTake place need be more than 2 people " unattended, few man on duty " pattern operating time of the prolongation that brings of " have people on duty " pattern relatively during the burst accident of emergency processing on the spot for each transformer station.

8. 500KV Regional Control Center control domain optimization system according to claim 1 is characterized in that described binary coding takes following mode:

(1) the 500KV transformer station that does not insert Regional Control Center in the zone is numbered, as transformer station 1, transformer station 2 ... the M of transformer station;

(2) each the transformer station's object in the zone all has one group of corresponding property parameters, comprising: transformer station's coordinate, and main transformer platform number, number etc. is returned in outlet;

(3) numbering of each the loop line Lu Junyong two ends transformer station in the zone is to describing;

(4) get 1 for the binary code of the transformer station's correspondence that inserts Regional Control Center, otherwise get 0, the coded sequence that this group is represented by the binary code of M position is just represented a control domain scheme;

(5) t are shown for each and every one body surface of i of population

Wherein, j gene

(j ∈ 1,2, M) anti-

Reflected the controlled situation of the j of transformer station, value 1 or 0.

9. 500KV Regional Control Center control domain optimization system according to claim 8 is characterized in that described genetic algorithm takes following mode:

(1) fitness function

If t is for i the chromosome of population

The preface value be

Definition Fitness function be:

$S_i^t=\frac{1}{1+p_i^t}$

(2) two stage of multiple target genetic algorithm

Algorithm 1

1) initial population: given crossover probability p _c, the variation Probability p _m, population scale N, the maximum individual number M in maximum evolutionary generation T and the temporary storage; Produce the initial individual x of population scale at random _i=(x _I1x _I2, x _Im) (i=1,2 ..., N) constitute initial population p ₁, with p ₁In all individualities carry out quick non-domination ordering, be that all individualities of 1 are put into temporary storage A with preface value wherein ₁In, make t=1;

2) intersect: from p _tIn with crossover probability p _cThe picked at random several body forms the mating pond, is N from scale _c=N*p _cThe mating pond in select the parent individuality of a pair of participation interlace operation at random

Carry out interlace operation, generate the offspring and be designated as

The individuality of not participating in interlace operation is designated as the offspring of oneself, and the set that generates the offspring is designated as q _t

3) variation: from q _tIn with the variation Probability p _mSelect to participate in the parent individuality of mutation operation

Carry out mutation operation, generate the offspring

The individuality of not participating in mutation operation is designated as the offspring of oneself, and the set that generates the offspring is designated as

4) protect excellent file: use

Middle preface value is 1 individuality replacement A _tIn individuality, and generate new interim holder A _T+1

5) select: right

In individuality, determine that fitness function is

Individuality is pressed the descending ordering of fitness, choose top n and form population p of future generation _T+1' make t=t+1;

6) end condition: as temporary storage A _T+1In individual number when reaching M, change algorithm 2; When satisfying default algebraically T, stop output A _T+1In individuality, otherwise, change the step (2);

Algorithm 2

1) initial population: be used for the identical crossover probability p of algorithm 1 _c, the variation Probability p _m, population scale N, and the maximum individual number M in the temporary storage are with p _tIn individuality be initial population, to p _tIn individuality, carry out following algorithm operating;

2) intersect: from p _tIn with crossover probability p _cThe picked at random several body forms the mating pond, is N from scale _c=N*p _cThe mating pond in select the parent individuality of a pair of participation interlace operation at random

Carry out interlace operation, generate the offspring and be designated as

The individuality of not participating in interlace operation is designated as the offspring of oneself, and the set that generates the offspring is designated as q _t

3) variation: from q _tIn with the variation Probability p _mSelect to participate in the parent individuality of mutation operation Carry out mutation operation, generate the offspring

The individuality of not participating in interlace operation is designated as the offspring of oneself, and the set that generates the offspring is designated as

4) protect excellent file: use

Middle preface value is 1 individuality replacement A _tIn individual and generate new interim holder A _T+1, when | A _T+1|＞during M, reduce A by the method for determining crowding _T+1In individual number to M;

5) select: right

In individuality, determine that fitness function is It is descending that individuality is pressed fitness

Ordering is chosen top n and is formed population p of future generation _T+1, make t=t+1;

6) end condition: when satisfying default algebraically T, or individual number reaches M in the temporary storage, and makes ρ _t, s _tAll be tending towards at 0 o'clock, stop, output A _T+1In individuality, otherwise, change the step (2).

10. according to the described arbitrary 500KV Regional Control Center control domain optimization system of claim 1 to 9, it is characterized in that described Executive Module optionally inserts 500KV transformer station in the zone Regional Control Center and controlled by it by 2M bridge and front server.

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