CN109217354A - A kind of micro-capacitance sensor economic load dispatching method based on particle swarm optimization algorithm - Google Patents
A kind of micro-capacitance sensor economic load dispatching method based on particle swarm optimization algorithm Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
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Abstract
The micro-capacitance sensor economic load dispatching method based on particle swarm optimization algorithm that the invention discloses a kind of.Particle swarm optimization algorithm makes full use of the state of experience and group's experience adjustments particle itself, can effectively optimize to system parameter.It is advantageous that solving the optimization problem of some continuous functions.For above situation, particle swarm optimization algorithm is applied in the economic load dispatching research of micro-capacitance sensor.The mathematical model of micro battery is initially set up, the Runing e conomy indicator and related constraint of micro-capacitance sensor are then considered according to dispatching criterion, establishes the economic load dispatching model of micro-capacitance sensor, proposes economic optimization scheduling strategy.According to every constraint condition, the micro-capacitance sensor economic dispatch program based on particle swarm optimization algorithm is write, numerical results show the power output situation that the algorithm is applied to distribution micro battery that can be effective and reasonable in the economic load dispatching of micro-capacitance sensor, realize economic load dispatching.
Description
Technical field
The present invention relates to the economic load dispatching fields of micro-capacitance sensor, more particularly to a kind of micro- electricity based on particle swarm optimization algorithm
Net economic load dispatching method.
Background technique
Strong supplement of the distributed generation system as central power supply system, the economy in power supply and the dirt to environment
There is certain advantage compared with bulk power grid in terms of dye degree.However, the cost of electricity-generating of distributed generation resource and to the pollution of environment still not
Hold and ignores.Distributed generation resource is linked into power grid in the form of micro-capacitance sensor, is the most effective mode for playing distributed generation resource efficiency.Cause
This, the economic load dispatching research of micro-capacitance sensor has received the concern of many scholars.
Up to the present, many algorithms are applied in the economic load dispatching optimizing research of micro-capacitance sensor by people, and such as heredity is calculated
Method, particle swarm optimization algorithm etc..Mainly there are two aspects for optimization problem: first is that requiring to find global minima point, second is that requiring to have
Higher convergence rate.There are three basic operators for genetic algorithm: selection intersects and makes a variation.The realization of these operators needs many
Parameter, and the selection of these parameters seriously affects the quality of solution, and the selection of these parameters is largely by experience.Population
Optimization algorithm does not have the intersection of genetic algorithm and variation, and system initialization is one group of RANDOM SOLUTION, most by iterated search
The figure of merit.It makes full use of the state of experience and group's experience adjustments particle itself, can effectively carry out to system parameter
Optimization.
Based on above-mentioned advantage, the present invention proposes to be applied to particle swarm optimization algorithm in the economic load dispatching of micro-capacitance sensor.For
Micro-capacitance sensor containing two class clean energy resource forms of electricity generation of wind-power electricity generation and photovoltaic power generation generates electricity, generally for effective use clean energy resource
The preferential whole generated energy for utilizing wind-power electricity generation and photovoltaic power generation.Dump power then considers the economy of micro-capacitance sensor according to dispatching criterion
Operating index and relevant constraint are distributed to each distributed generation resource.Journey is write using particle swarm optimization algorithm in Matlab
Sequence, program operation result show the algorithm equal energy under cost of electricity-generating minimum and most light two objective functions of environmental
The output power for effectively distributing each distributed generation resource realizes the economic load dispatching of micro-capacitance sensor.
Summary of the invention
It is an object of the present invention to particle swarm optimization algorithm is applied in the economic load dispatching of micro-capacitance sensor, this algorithm is utilized
The advantages such as easy to accomplish, precision is high and convergence is fast, the power output situation of each distributed generation resource, is realized micro- in reasonable distribution micro-capacitance sensor
The economic and environment-friendly operation of power grid.
To achieve the above object, the technical scheme adopted by the invention is as follows: a kind of micro- electricity based on particle swarm optimization algorithm
Net economic load dispatching method, comprising the following steps:
1) in micro-capacitance sensor established by the present invention, distributed generation resource includes uncontrollable type micro battery and controllable type micro battery.
Wherein, uncontrollable type micro battery includes wind-power electricity generation and photovoltaic power generation, mathematical model give output power, start-up cost with
And the calculation of operation expense, and regardless of fuel cost and environmental improvement cost.Controllable type micro battery includes bavin
Fry dried food ingredients motor, fuel cell and miniature gas turbine, the energy non-clean energy used in view of it, mathematical model are removed and are provided
The calculation of output power, start-up cost and operation expense also needs to provide fuel cost and environmental improvement cost.
2) micro-capacitance sensor economic load dispatching model is minimum using cost of electricity-generating and environmental improvement cost minimization is objective function, with function
Rate balance and power bound are constrained to constraint condition.Micro-grid connection operation, using preferentially utilize uncontrollable type micro battery
Whole generated energy and diesel-driven generator do the optimizing scheduling strategy of backup power source, only when micro-capacitance sensor itself is unable to satisfy load
Electric energy is carried out with bulk power grid when demand or micro-capacitance sensor own power surplus to interact.
3) particle swarm optimization algorithm makes full use of the state of experience and group's experience adjustments particle itself, can be effective
System parameter is optimized.It is advantageous that solving the optimization problem of some continuous functions.Particle is initial in population
Position is randomly generated in region of search, and the speed of each particle also gives at random.Particle swarm algorithm is applied in program, often
A particle all carries out once in the movement of solution space position, then optimizing completes an iteration.Iterative process repeats, until
Meet one of following condition: particle is opposing stationary in solution space, or reaches maximum number of iterations.It is updated using following two formula
Speed and position:
4) by above-mentioned formula, in the process for finding objective function optimal solution, program volume is largely reduced
The complexity write, and optimal solution can be acquired with faster speed.In view of people for particle swarm optimization algorithm parameter selection
It is relatively reasonable in the selection of the parameters such as Studying factors through there is more mature theoretical research result, therefore required optimal solution
Also there is certain accuracy.
Technical solution of the present invention has the advantages that
Technical solution of the present invention has initially set up the mathematical model of each distributed generation resource, has then examined according to dispatching criterion
Consider micro-capacitance sensor Runing e conomy indicator and relevant constraint, establish the economic load dispatching model of micro-capacitance sensor, propose power generation at
Sheet and two objective functions of environmental improvement cost and each constraint condition.Reasonable peace has been write based on particle swarm optimization algorithm again
The program of each distributed generation resource power output in micro-capacitance sensor is arranged, to achieve the purpose that carry out economic load dispatching to micro-capacitance sensor.
Below by drawings and examples, technical scheme of the present invention will be described in further detail.
Detailed description of the invention
Fig. 1 is particle swarm algorithm flow chart.
Fig. 2 is the daily load curve of a certain small-sized microgrid.
Fig. 3 is photovoltaic, blower day part goes out force data.
DE, FC, MT day part handle number when Fig. 4 a, b are respectively using cost of electricity-generating and environmental improvement cost as objective function
According to.
Micro-capacitance sensor day part and power grid are handed over when Fig. 5 a, b are respectively using cost of electricity-generating and environmental improvement cost as objective function
Mutual electricity.
The cost number of micro-capacitance sensor day part when Fig. 6 a, b are respectively using cost of electricity-generating and environmental improvement cost as objective function
According to.
Specific embodiment
Below in conjunction with the drawings and specific embodiments, the present invention will be described in further detail.
Fig. 1 is particle swarm algorithm flow chart.System parameter is initialized, number of particles generally takes 20-40, asks for most of
It inscribes 10 particles and can obtain and is preferable as a result, value 40 herein.The length of particle, i.e. space dimensionality are determined by optimization problem
It is fixed, the number of referred to herein as schedulable distributed generation resource.Maximum number of iterations can freely be set, herein value 1000.Particle
Speed and position initial value are randomly generated.
Into iterative cycles, by first time iteration to maximum number of iterations, each iteration is completed all in accordance with comparing adaptive value
It obtains individual extreme value and global extremum and updates.In each iterative process, particle updates certainly according to individual extreme value and optimal extreme value
Oneself speed and position on each dimension space, and calculate itself adaptive value, so as to next iteration seek new individual extreme value and
Global extremum.
Obtain the condition that optimal solution stops iteration are as follows: it is opposing stationary in solution space to reach maximum number of iterations or particle.
The validity of the micro-capacitance sensor economic load dispatching method based on particle swarm optimization algorithm and advanced is proposed for the verifying present invention
Property, the economic dispatch program based on particle group optimizing has been write in Matlab operation window and has carried out sample calculation analysis.
Parameter related with above-mentioned particle swarm optimization algorithm is as shown in table 1 in this programming.
1 particle swarm optimization algorithm parameter of table
DE, FC, MT day part handle number when Fig. 4 a, b are respectively using cost of electricity-generating and environmental improvement cost as objective function
According to.As shown in figure 4, no matter miniature gas turbine is prior to combustion using cost of electricity-generating or environmental improvement cost as objective function
Expect battery power output.When the gross output of photovoltaic, blower, fuel cell, miniature gas turbine is able to satisfy burden requirement, fuel
The load that battery and miniature gas turbine distribution photovoltaic and blower are not enough to supply, diesel-driven generator are not contributed.When photovoltaic, wind
When machine, fuel cell, miniature gas turbine are insufficient for load, diesel-driven generator provides power as backup power source.
Micro-capacitance sensor day part and power grid are handed over when Fig. 5 a, b are respectively using cost of electricity-generating and environmental improvement cost as objective function
Mutual electricity.As shown in figure 5, when using cost of electricity-generating and environmental improvement cost as objective function, the friendship of micro-capacitance sensor day part and power grid
Mutual electricity is consistent.This is determined by scheduling strategy.It is negative that it is not able to satisfy itself and if only if distributed generation resource in micro-capacitance sensor
When lotus demand, micro-capacitance sensor just need to be to bulk power grid power purchase；Generating electricity the extra load of energy and if only if distributed generation resource in micro-capacitance sensor need to
When asking, micro-capacitance sensor is to bulk power grid sale of electricity.
The cost number of micro-capacitance sensor day part when Fig. 6 a, b are respectively using cost of electricity-generating and environmental improvement cost as objective function
According to.As shown in fig. 6, cost of electricity-generating and environmental improvement cost are generally lower in the daytime, this is because photovoltaic power generation output power in the daytime,
Counteracting should the power that provides of the biggish distributed generation resource of and environmental improvement cost larger by cost of electricity-generatings such as fuel cells.Night
Between cost of electricity-generating and environmental improvement cost it is significantly raised, this is because night is peak times of power consumption, and without solar irradiation, photovoltaic hair
Electricity do not contribute, though the cost of wind-power electricity generation is low, be unable to satisfy whole loads, at this time fuel cell, miniature gas turbine and
This kind of cost of electricity-generating of diesel-driven generator bears main loads with the high distributed generation resource of environmental improvement cost.
Program operation result shows the micro-capacitance sensor economic load dispatching method proposed by the invention based on particle swarm optimization algorithm
The output power that each distributed generation resource can effectively be distributed realizes the economic and environment-friendly operation of micro-capacitance sensor.
The foregoing is only a preferred embodiment of the present invention, is not intended to restrict the invention, although referring to aforementioned reality
Applying example, invention is explained in detail, for those skilled in the art, still can be to aforementioned each implementation
Technical solution documented by example is modified or equivalent replacement of some of the technical features.It is all in essence of the invention
Within mind and principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (5)
1. a kind of micro-capacitance sensor economic load dispatching method based on particle swarm optimization algorithm, comprising the following steps:
1) in micro-capacitance sensor established by the present invention, distributed generation resource includes uncontrollable type micro battery and controllable type micro battery.Wherein,
Uncontrollable type micro battery includes wind-power electricity generation and photovoltaic power generation, and mathematical model gives output power, start-up cost and fortune
The calculation of row maintenance cost, and regardless of fuel cost and environmental improvement cost.Controllable type micro battery includes diesel oil hair
Motor, fuel cell and miniature gas turbine, the energy non-clean energy used in view of it, mathematical model are removed and provide output
The calculation of power, start-up cost and operation expense also needs to provide fuel cost and environmental improvement cost.
2) micro-capacitance sensor economic load dispatching model is minimum using cost of electricity-generating and environmental improvement cost minimization is objective function, flat with power
Weighing apparatus and power bound are constrained to constraint condition.Micro-grid connection operation, using preferentially utilize uncontrollable type micro battery it is complete
Portion's generated energy and diesel-driven generator do the optimizing scheduling strategy of backup power source, only when micro-capacitance sensor itself is unable to satisfy the demand of load
Or electric energy is carried out with bulk power grid when micro-capacitance sensor own power surplus and is interacted.
3) particle swarm optimization algorithm makes full use of the state of experience and group's experience adjustments particle itself, can be effective right
System parameter optimizes.It is advantageous that solving the optimization problem of some continuous functions.The initial position of particle in population
It is randomly generated in region of search, the speed of each particle also gives at random.Particle swarm algorithm is applied in program, each grain
Son all carries out once in the movement of solution space position, then optimizing completes an iteration.Iterative process repeats, until meeting
One of following condition: particle is opposing stationary in solution space, or reaches maximum number of iterations.Using following two formula renewal speed
The position and:
4) programming is largely reduced in the process for finding objective function optimal solution by above-mentioned formula
Complexity, and optimal solution can be acquired with faster speed.Have in view of parameter selection of the people for particle swarm optimization algorithm
More mature theoretical research result, it is relatively reasonable in the selection of the parameters such as Studying factors, therefore required optimal solution also has
There is certain accuracy.
2. a kind of micro-capacitance sensor economic load dispatching method based on particle swarm optimization algorithm according to claim 1, feature exist
Distributed generation resource includes uncontrollable type micro battery and controllable type micro battery in micro-capacitance sensor proposed in step 1), and is given
The mathematical model of the output power of each micro battery and each cost.
3. a kind of micro-capacitance sensor economic load dispatching method based on particle swarm optimization algorithm according to claim 1, feature exist
Micro-capacitance sensor economic load dispatching model proposed in step 2), using cost of electricity-generating and environmental improvement cost as objective function, with
Power constraint is constraint condition and the scheduling strategy that the uncontrollable micro battery of proposition is preferentially contributed.
4. a kind of micro-capacitance sensor economic load dispatching method based on particle swarm optimization algorithm according to claim 1, feature exist
Using particle swarm optimization algorithm as the committed step for guaranteeing micro-capacitance sensor economic load dispatching rapidity in step 3).Using following two
Formula renewal speed and position:
5. a kind of micro-capacitance sensor economic load dispatching method based on particle swarm optimization algorithm according to claim 1, feature exist
The accuracy of calculated result of the particle swarm optimization algorithm in micro-capacitance sensor economic load dispatching research is demonstrated in step 4).
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110601177A (en) * | 2019-08-06 | 2019-12-20 | 广东工业大学 | Economic optimization method for micro-grid containing wind power and photovoltaic power generation |
| CN111342462A (en) * | 2020-03-31 | 2020-06-26 | 安阳师范学院 | Microgrid optimization scheduling system, method, storage medium and computer program |
| CN112434974A (en) * | 2020-12-14 | 2021-03-02 | 上海玳鸽信息技术有限公司 | Block chain-based power scheduling method and device, electronic equipment and storage medium |
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- 2017-07-07 CN CN201710548993.XA patent/CN109217354A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110601177A (en) * | 2019-08-06 | 2019-12-20 | 广东工业大学 | Economic optimization method for micro-grid containing wind power and photovoltaic power generation |
| CN111342462A (en) * | 2020-03-31 | 2020-06-26 | 安阳师范学院 | Microgrid optimization scheduling system, method, storage medium and computer program |
| CN112434974A (en) * | 2020-12-14 | 2021-03-02 | 上海玳鸽信息技术有限公司 | Block chain-based power scheduling method and device, electronic equipment and storage medium |
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