CN105740981B - Ac and dc systems off-load amount optimization method based on improved adaptive GA-IAGA - Google Patents
Ac and dc systems off-load amount optimization method based on improved adaptive GA-IAGA Download PDFInfo
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Abstract
The invention discloses the ac and dc systems off-load amount optimization methods based on improved adaptive GA-IAGA, including low-voltage load sheding amount optimization object function and constraint condition and the optimization of low-voltage load sheding amount；Low-voltage load sheding amount optimization object function and constraint condition include objective function, constraint condition, voltage indexes constraint and direct current system voltage control strategy, low-voltage load sheding amount is optimized for the optimization of the low-voltage load sheding amount based on improved adaptive GA-IAGA, including improved adaptive GA-IAGA and improved adaptive GA-IAGA optimize low-voltage load sheding amount process.Compared with prior art, the beneficial effects of the present invention are: obtaining optimization strategy as objective function to lose cost minimization simultaneously in conjunction with intelligent optimization method.In bulk power grid, by making the non-cutting load of important node can satisfy threshold values constraint to the node off-load for coupling extremely important load, to reduce system loss cost in the case where first time cut-out load guarantees system safety.The present invention compares conventional off-load strategy, improves flexibility and adaptability.
Description
Technical field
The present invention relates to power domains, and in particular to the ac and dc systems off-load amount optimization side based on improved adaptive GA-IAGA
Method.
Background technique
Power industry is the important foundation industry of national economy, plays essential branch to the development of other branchs of industry
Support effect.Go deep into thorough Electricity market analysis and have become Utilities Electric Co.'s adaptation requirement of the market economy, guarantee company invests back
Report and the element task for improving effectiveness of operation, only according to electricity needs characteristic, demand structure, the corresponding development rule for adjusting company
Draw and business plan, Cai Nengshi power grid enterprises establish oneself in an unassailable position in the market, acquire survival and development for a long time.
In recent years, due to advantages such as transmission capacity is big, power regulation rapid flexible, loss is small, asynchronous contact ability are strong,
D.C. high voltage transmission long-distance and large-capacity power transmission, the interconnection of big regional power grid and in terms of obtained it is very wide
General application.Simultaneously because the development support of novel power transistor, traditional pure AC network is gradually interconnected to alternating current-direct current
The transformation of power grid form.But hybrid AC/DC power transmission systems also give the operation of power grid and safety belt to carry out new problem, due to direct current
Inverter consumes the influence of a large amount of reactive powers, and the purer AC system of alternating current-direct current combined hybrid system voltage stability problem is more prominent
Out.
Revised genetic algorithum, which is introduced into ac and dc systems off-load amount optimisation strategy, important practical value.With quiet
State voltage stability index be constraint condition, using low-voltage load sheding loss cost minimization as objective function, thus solve it is optimal cut it is negative
Lotus configuration strategy realizes Optimal Control Strategy, and system is maintained to stablize, and reduces loss cost.
Summary of the invention
The purpose of the present invention is to provide the ac and dc systems off-load amount optimization methods based on improved adaptive GA-IAGA.
Above-mentioned purpose is achieved by the following technical solution:
A kind of ac and dc systems off-load amount optimization method based on improved adaptive GA-IAGA, including low-voltage load sheding amount optimization aim
Function and constraint condition and the optimization of low-voltage load sheding amount:
(1) low-voltage load sheding amount optimization object function and constraint condition include objective function, constraint condition, voltage indexes constraint
With direct current system voltage control strategy, in which:
The objective function is minF=C1S1+C2S2+C3S3, wherein S1、S2And S3Respectively business electrical, commercial power
With cities and towns rural household electricity utilization；C1、C2And C3For cost control coefficient；
The constraint condition includes equality constraint and inequality constraints；Wherein, the inequality constraints is one or more
Security constraint, including control variables constraint and state variable constraint；
The voltage indexes are constrained to voltage stability index constraint；
The direct current system voltage control strategy is to be added to hvdc control mode for the contribution of voltage stability margin
In alternating iteration Load flow calculation；
(2) low-voltage load sheding amount is optimized for the optimization of the low-voltage load sheding amount based on improved adaptive GA-IAGA, including improved adaptive GA-IAGA
Optimize low-voltage load sheding amount process with improved adaptive GA-IAGA, in which:
Intersection factor adaptive acquiring method in improved adaptive GA-IAGA are as follows:
Wherein, ffitIt (i) is the fitness that need to intersect individual, favgFor the individual average fitness of all intersections, fmaxTo intersect
Individual maximum adaptation degree, PcmaxFor maximum crossover probability, PcminFor minimum crossover probability；
The adaptive acquiring method of mutagenic factor in improved adaptive GA-IAGA are as follows:
Wherein, ffitIt (i) is the fitness for needing variation individual, favgFor all variation individual average fitness, fmaxFor variation
Individual maximum adaptation degree, PmmaxFor maximum mutation probability, PmminFor minimum mutation probability；
Further, the improved adaptive GA-IAGA optimization low-voltage load sheding amount process includes the following steps:
(1) initialize: input ac and dc systems low pressure overloads initial data, determines that genetic algorithm runs algebra, intersects general
Rate and mutation probability bound determine per generation number of samples, and group primary are randomly generated；
(2) Load flow calculation ranking fitness: is carried out to ac and dc systems and original overload data；To population data primary into
Row Load flow calculation；The control variable value of Load flow calculation under two kinds of data is asked poor, and result substitution objective function is suitable to get arriving
It answers angle value and sorts to it；
(3) it selects: after the fitness function value for calculating all previous generation individuals, selecting quantity using roulette method and be equal to
The parent group of per generation Population determines the parent group for generating filial generation from previous generation；
(4) intersect: crossover probability being sought according to adaptive algorithm and obtains crosspoint, by the adjacent body in parent group
Intersect two-by-two, including two individuals of head and the tail；
(5) it makes a variation: for the independent binary digit in 10 binary codings, after seeking self-adaptive mutation, according to
The arbitrarily selected binary digit of probability is inverted；
(6) preferably: after breeding variation, selecting the individual of per generation control cost minimization；It is less preferred suitable again after the completion of iteration
The maximum individual of response, as required ac and dc systems low-voltage load sheding amount.
Compared with prior art, the beneficial effects of the present invention are: in conjunction with intelligent optimization method simultaneously to lose cost minimization
Optimization strategy is obtained for objective function.In bulk power grid, by making important section to the node off-load for coupling extremely important load
The non-cutting load of point can satisfy threshold values constraint, to reduce in the case where first time cut-out load guarantees system safety
System loss cost.The present invention compares conventional off-load strategy, improves flexibility and adaptability.
Detailed description of the invention
Fig. 1: ac and dc systems schematic diagram.
Specific embodiment
The technical solution that the present invention will be described in detail combined with specific embodiments below.The effect of embodiment indicates that the present invention
Essentiality content, but do not limited the scope of protection of the present invention with this.Those skilled in the art should understand that can be with
Modification or equivalent replacement of the technical solution of the present invention are made, without departing from the essence and protection model of technical solution of the present invention
It encloses.
As extensive alternating current-direct current mixed connection electric system is increasingly becoming the citation form of China's grid power transmission, voltage stability
Problem is more prominent.For the deficiency of existing ac and dc systems Voltage Stability Analysis method, propose to be based on improved adaptive GA-IAGA
It take comprehensive practical voltage stability index as the ac and dc systems off-load amount optimization method of constraint.
Ac and dc systems off-load amount optimization method proposed by the present invention based on improved adaptive GA-IAGA, the specific steps are as follows:
One, hybrid AC/DC power transmission systems steady-state model
1, inverter mathematics model of stable state, ac and dc systems schematic diagram are shown in Fig. 1.
2, alternating current-direct current power flow algorithm: ac and dc systems trend is calculated using alternative iteration method, it is convenient that solution is realized, avoids weight
New column write exchange Jacobian matrix.
Two, voltage stability margin index
Voltage stability refer to electric system under given primary condition, the ability of maintenance voltage after being disturbed.
1, the voltage indexes principle equivalent based on Dai Weinan
According to the Dai Weinan principle of equal effects it is found that for any one electric system, any moment in terms of a certain load point into
It goes, it can be by its equivalent two node system powered through equivalent internal resistance to the node load at a potential source.If ZeqFor Dai Wei
Southern equivalent resistance, ZLFor load itself equivalent resistance, then the ac and dc systems node voltage stability margin equivalent based on Dai Weinan
Index are as follows:
As 0 < η < 1, system voltage is stablized；As η=0, system is in critical stable state；As η < 0, system
Voltage Instability.What thus index can have an elephant finds out the node operating status at a distance from stability boundaris, thus as index
Determine cutting load situation.
2, the Dai Weinan equivalent parameters based on alternating current-direct current flow solution calculates
There are four the amounts for needing to solve in thevenin equivalent circuit, is respectively as follows: Eeqr、Eeqi、Req、Xeq, need to arrange and write four sides
Cheng Jinhang is solved.According to available two equations of ground state Load flow calculation.One fractional increments are applied using load and application one is micro-
Small decrement is combined into equation group with ground state equation respectively and carries out Load flow calculation, as a result takes the two average value.
Three, ac and dc systems low-voltage load sheding amount optimizes
1, low-voltage load sheding amount optimization object function and constraint condition
(1) objective function
The final purpose of off-load amount optimization is to reach the condition of voltage stabilization with the smallest off-load loss cost.If S1、S2With
S3Respectively business electrical, commercial power and cities and towns rural household electricity utilization；C1、C2And C3For cost control coefficient, then optimization aim
Function are as follows: minF=C1S1+C2S2+C3S3；
(2) constraint condition
The constraint condition of optimization process is divided into two classes: equality constraint and inequality constraints.Wherein equality constraint is in trend
It is embodied in calculating.Inequality constraints is a series of security constraints, including control variable and state variable constraint.Carry out off-load amount
The premise of optimization is that each variable all must be in reasonable range.
(3) voltage indexes constrain
The key for controlling off-load amount is using voltage stability index as restrictive condition.On the basis of voltage steady margin index
Set up lower limit threshold values.When any node voltage stability margin is lower than threshold values in system, that is, enter low-voltage load sheding program.
(4) direct current system voltage control strategy
By hvdc control mode for the contribution of voltage stability margin be added in alternating iteration Load flow calculation to get go out
Voltage indexes have contemplated that the influence of hvdc control mode.
2, the low-voltage load sheding amount optimization based on improved adaptive GA-IAGA
The optimization of low-voltage load sheding amount is a multi-objective optimization question, needs to increase cost in generator and compensation device and bear
Reach balance between lotus off-load loss cost.It is to close with voltage stability index i.e. on the basis of variable feasible constraints condition
Key constraint carries out cost control.
(1) improved adaptive GA-IAGA
Genetic algorithm is that a kind of establish obtains optimal solution by iteration in natural selection principle and natural genetic mechanism
Searching method.Crossover probability P in the parameter of traditional genetic algorithmcWith mutation probability PmSelection be influence genetic algorithm behavior
With the key point of performance, convergence is directly affected.
In improved self-adapted genetic algorithm, in order to improve the relevance grade of algorithm, PcAnd PmIt is carried out certainly according to following formula
Adapt to adjustment:
Intersect factor adaptive acquiring method are as follows:
Wherein, ffitIt (i) is the fitness that need to intersect individual, favgFor the individual average fitness of all intersections, fmaxTo intersect
Individual maximum adaptation degree, PcmaxFor maximum crossover probability, PcminFor minimum crossover probability；
The adaptive acquiring method of mutagenic factor are as follows:
Wherein, ffitIt (i) is the fitness for needing variation individual, favgFor all variation individual average fitness, fmaxFor variation
Individual maximum adaptation degree, PmmaxFor maximum mutation probability, PmminFor minimum mutation probability；
(2) improved adaptive GA-IAGA optimization low-voltage load sheding amount process successively includes the following:
Initialization: input ac and dc systems low pressure overload initial data, determine genetic algorithm run algebra, crossover probability and
Mutation probability bound determines per generation number of samples, and group primary is randomly generated.
Ranking fitness: Load flow calculation is carried out to ac and dc systems and original overload data；Population data primary is carried out
Load flow calculation；The control variable value of Load flow calculation under two kinds of data is asked poor, and result is substituted into objective function to get adaptation is arrived
Angle value simultaneously sorts to it.
Selection: after the fitness function value for calculating all previous generation individuals, quantity is selected using roulette method and is equal to often
For the parent group of Population, the parent group for generating filial generation is determined from previous generation.
Intersect: crossover probability being sought according to adaptive algorithm and obtains crosspoint, by the adjacent body (packet in parent group
Include two individuals of head and the tail) intersect two-by-two.
Variation: for the independent binary digit in 10 binary codings, after seeking self-adaptive mutation, according to probability
Arbitrarily selected binary digit is inverted.
It is preferred that: after breeding variation, select the individual of per generation control cost minimization；Preferred fitness again after the completion of iteration
Maximum individual, as required ac and dc systems low-voltage load sheding amount.
It is below the improved adaptive GA-IAGA of certain IEEE30 node system, specific steps include:
(1) part of nodes Dai Weinan equivalent parameters and voltage stability margin index under original steady-state are calculated, knot is calculated
Fruit is as follows:
Thevenin's equivalence parameter and voltage indexes under 1 IEEE30 node system stable state of table
(2) on the basis of the calculating of stable state IEEE30 node, the random general exacerbation of each node is carried.It is calculated to verify optimization
Concern node is roughly divided into three classes by cutting load cost, is then searched for and cut automatically using improved adaptive GA-IAGA by the accuracy of method
Load strategy, optimum results are as follows:
2 IEEE30 node system low-voltage load sheding optimum results of table
| Node | Off-load amount | Index before optimizing | Index after optimization |
| 3 | 0.004+j0.020 | 0.004366 | 0.814776 |
| 6 | 0.005+j0.010 | 0.027507 | 0.666547 |
| 15 | 0.004+j0.010 | 0.050935 | 0.740450 |
| 18 | 0.002+j0.005 | 0.021534 | 0.577928 |
| 20 | 0 | 0.006270 | 0.099440 |
| 23 | 0.001+j0.001 | 0.009130 | 0.145214 |
| 24 | 0.001+j0.003 | 0.016427 | 0.166945 |
As it can be seen that node of the off-load strategy of improved adaptive GA-IAGA using voltage stability index lower than threshold values is as optimization algorithm
Optimized variable carries out least cost control on this basis, obtains optimal result.
The effect of above-described embodiment indicates that essentiality content of the invention, but protection of the invention is not limited with this
Range.Those skilled in the art should understand that can with modification or equivalent replacement of the technical solution of the present invention are made,
Without departing from the essence and protection scope of technical solution of the present invention.
Claims (1)
1. a kind of ac and dc systems off-load amount optimization method based on improved adaptive GA-IAGA, including low-voltage load sheding amount optimization aim letter
Several and constraint condition and low-voltage load sheding amount optimize, it is characterised in that:
(1) low-voltage load sheding amount optimization object function and constraint condition include objective function, constraint condition, voltage indexes constraint and straight
Streaming system voltage control strategy, in which:
The objective function is minF=C1S1+C2S2+C3S3, wherein S1、S2And S3Respectively business electrical, commercial power and city
Town rural household electricity utilization；C1、C2And C3For cost control coefficient；
The constraint condition includes equality constraint and inequality constraints；Wherein, the inequality constraints is one or more safety
Property constraint, including control variables constraint and state variable constraint；
The voltage indexes are constrained to voltage stability index constraint；
The direct current system voltage control strategy is that hvdc control mode is added to alternating for the contribution of voltage stability margin
In iteration Load flow calculation；
(2) low-voltage load sheding amount is optimized for the optimization of the low-voltage load sheding amount based on improved adaptive GA-IAGA, including improved adaptive GA-IAGA and changes
Into genetic algorithm optimization low-voltage load sheding amount process, in which:
Intersection factor adaptive acquiring method in improved adaptive GA-IAGA are as follows:
Wherein, ffitIt (i) is the fitness that need to intersect individual, favgFor the individual average fitness of all intersections, fmaxTo intersect individual
Maximum adaptation degree, PcmaxFor maximum crossover probability, PcminFor minimum crossover probability；
The adaptive acquiring method of mutagenic factor in improved adaptive GA-IAGA are as follows:
Wherein, ffitIt (i) is the fitness for needing variation individual, favgFor all variation individual average fitness, fmaxFor variation individual
Maximum adaptation degree, PmmaxFor maximum mutation probability, PmminFor minimum mutation probability；
Wherein, the improved adaptive GA-IAGA optimization low-voltage load sheding amount process includes the following steps:
(1) initialize: input ac and dc systems low pressure overload initial data, determine genetic algorithm run algebra, crossover probability and
Mutation probability bound determines per generation number of samples, and group primary is randomly generated；
(2) Load flow calculation ranking fitness: is carried out to ac and dc systems and original overload data；Tide is carried out to population data primary
Stream calculation；The control variable value of Load flow calculation under two kinds of data is asked poor, and result is substituted into objective function to get fitness is arrived
Value simultaneously sorts to it；
(3) it selects: after the fitness function value for calculating all previous generation individuals, selecting quantity equal to per generation using roulette method
The parent group of Population determines the parent group for generating filial generation from previous generation；
(4) intersect: crossover probability being sought according to adaptive algorithm and obtains crosspoint, two-by-two by the adjacent body in parent group
Intersect, including two individuals of head and the tail；
(5) it makes a variation: for the independent binary digit in 10 binary codings, after seeking self-adaptive mutation, according to probability
Arbitrarily selected binary digit is inverted；
(6) preferably: after breeding variation, selecting the individual of per generation control cost minimization；Preferred fitness again after the completion of iteration
Maximum individual, as required ac and dc systems low-voltage load sheding amount.
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| CN103701140A (en) * | 2014-01-06 | 2014-04-02 | 国家电网公司 | Dynamic reactive power reserve optimization method for improving transient voltage stability of alternating-current and direct-current power grid |
| CN104113056A (en) * | 2014-06-30 | 2014-10-22 | 南方电网科学研究院有限责任公司 | Method for optimizing low-voltage current-limiting control parameters |
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| CN103701140A (en) * | 2014-01-06 | 2014-04-02 | 国家电网公司 | Dynamic reactive power reserve optimization method for improving transient voltage stability of alternating-current and direct-current power grid |
| CN104113056A (en) * | 2014-06-30 | 2014-10-22 | 南方电网科学研究院有限责任公司 | Method for optimizing low-voltage current-limiting control parameters |
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