CN109711644A - Based on the fired power generating unit load optimal distribution method for improving pollen algorithm - Google Patents
Based on the fired power generating unit load optimal distribution method for improving pollen algorithm Download PDFInfo
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Abstract
The invention discloses a kind of based on the fired power generating unit load optimal distribution method for improving pollen algorithm, it include: that coal consuming character is fitted according to the coal consumption characterisitic parameter of generating set and establishes load optimal distribution model, unconstrained problem is converted by penalty function method, total generated output is distributed into each unit in conjunction with pollen algorithm is improved, finally obtains the optimal sharing of load result of each unit.The present invention can be in the case where having given electric power general power, the optimal value of every generating set of scientific and reasonable distribution, to reduce net coal consumption rate consumed by unit.
Description
Technical field
The invention belongs to swarm intelligence algorithm application technologies, are related to thermal power plant load optimal technology, more particularly, to one
Kind is based on the fired power generating unit load optimal distribution method for improving pollen algorithm.
Background technique
Typical optimization problem of the fired power generating unit load optimal distribution as electric system, load optimal distribution are considering always to need
Under the premise of various constraint conditions of summing, the active power of output of each generator is distributed rationally, to reduce cost of electricity-generating, drop
Low grid loss improves the utilization rate to fuel, and then improves the security reliability of electric system.It is non-thread due to the problem
The attributes such as property, various dimensions, multiple constraint, inquiring into and formulating reasonable operation plan is also key points and difficulties.
Compared to traditional dispatching method, emerging swarm intelligence algorithm is more flexible, and with its development derived it is various
Optimization algorithm based on biocenose intelligence has simultaneously been applied to various fields.
Pollen algorithm is to be based on pollen pollination in nature by one kind that British scholar YANG X.S. was proposed in 2012
The novel heuritic approach of process has the advantages that parameter is few, structure is simple, is easily achieved, there is good optimizing ability.
The pollen algorithm proposed in this paper that improves is the innovatory algorithm for pollen algorithm.
Summary of the invention
The object of the present invention is to provide it is a kind of based on improve pollen algorithm fired power generating unit load optimal distribution method,
Alleviate existing dispatching method and electric system economic benefits are difficult to the problem of adjusting.
The technical scheme adopted by the invention is that: it is a kind of based on the fired power generating unit load optimal distribution for improving pollen algorithm
Method follows the steps below to implement:
With the concrete form of the minimum objective function of fired power generating unit consumption of coal amount are as follows:
In formula, n is generator sum；PiFor the active power of unit i；ai、bi、ciFor the energy consumption characteristics coefficient of unit i.
In addition it is also contemplated that influence of the valve point effect to cost of electricity-generating, therefore above-mentioned formula should be changed to:
In formula, ei、fiFor the coal consumption characteristic coefficient of unit i；PiminIt is then the output power lower limit of unit i.
Its inequality constraints being related to is unit operation constraint, and correlation formula is as follows:
Pimin≤Pi≤Pimax (3)
In formula, Pimin、PimaxThe minimum and maximum active power of respectively unit i exports.
The practical problem that each unit load balances is included in the objective function of unit coal consumption characteristic by penalty function method,
Objective function after introducing penalty function are as follows:
In formula, n is generator sum, and σ is penalty factor, is generally taken between 100 to 150, F (Pi) be unit i standard coal
Consumption；PiFor the active power of unit i；D is total activation load.
The coal consumption characteristic equation that the optimizing distribution method is established according to the load and its coal consumption of each unit is as target letter
Given general power is passed through a part that penalty function method is included in objective function to optimize by number, the specific steps are as follows:
1) actual parameter of generating set is determined, and at the beginning of each unit load limits and generates one group of load at random in range
Initial value；
2) the corresponding coal consumption value of more each load determines initial optimum load dispatch scheme；
3) self-pollination or cross-pollination are determined according to the transition probabilities for improving pollen algorithm, thus to each machine
The load of group is updated；
4) cross-pollination optimization process is carried out to Optimal Load；
5) the corresponding coal consumption value of more each load determines the optimum load dispatch scheme of the secondary iteration；
6) until meeting iterated conditional, the Optimal Load value of each unit is exported.
Compared with prior art, the present invention can be in the case where having given electric power general power, every hair of scientific and reasonable distribution
The optimal value of motor group, to reduce net coal consumption rate consumed by unit.
Detailed description of the invention
Fig. 1 is the fired power generating unit load optimal distribution method flow diagram that the present invention improves pollen algorithm；
Fig. 2 is that the present invention implements general power when being 660MW, pollen algorithm and the comparative result figure for improving pollen algorithm；
Fig. 3 is that the present invention implements general power when being 770MW, pollen algorithm and the comparative result figure for improving pollen algorithm；
Fig. 4 is that the present invention implements general power when being 900MW, pollen algorithm and the comparative result figure for improving pollen algorithm.
Specific embodiment
Below with reference to specific drawings and embodiments, the present invention is described in detail, refering to fig. 1.
One, based on the mathematical modeling of penalty function
Coal consuming character is fitted according to the coal consumption characterisitic parameter of generating set and establishes load optimal point 1. determining first
With model, as with the concrete form of the minimum objective function of fired power generating unit consumption of coal amount:
In formula, n is generator sum；PiFor the active power of unit i；ai、bi、ciFor the energy consumption characteristics coefficient of unit i.
In addition it is also contemplated that influence of the valve point effect to cost of electricity-generating, therefore above-mentioned formula should be changed to:
In formula, ei、fiFor the coal consumption characteristic coefficient of unit i；PiminIt is then the output power lower limit of unit i.
Following two constraint condition is mainly considered in the objective function:
1) account load balancing constraints of system: i.e. the sum of active power of unit PiThe requirement of total load D should be met:
2) the bound constraint of unit output power:
Pimin≤Pi≤Pimax (4)
In formula, Pimin、PimaxThe minimum and maximum active power of respectively unit i exports.
2. being modeled with penalty function method to objective function
Due to needing to consider above-mentioned constraint condition in optimization process, thus introduce penalty function by the objective function be converted to it is non-about
Shu Wenti.
Account load balancing constraints condition is included in objective function using construction exterior point penalty function method herein.
Objective function after introducing penalty function is as follows:
In formula, n is generator sum, and σ is penalty factor, is generally taken between 100 to 150, F (Pi) be unit i standard coal
Consumption；PiFor the active power of unit i；D is total activation load.
Two, based on the fired power generating unit load optimal distribution for improving pollen algorithm
1. improving pollen algorithm (MFPA)
Pollen algorithm is to be based on pollen in nature by one kind that British scholar YANG X.S. was proposed in 2012 first
The novel heuritic approach of pollinating process has the advantages that parameter is few, structure is simple, is easily achieved, there is good optimizing energy
Power.
The characteristics of pollen algorithm, is to determine the optimization using self-pollination or cross-pollination according to transition probability p
Journey, correlation formula are as follows:
In formula,Position of the pollen i in t+1 circulation is represent,Represent jth corresponding to current optimal value
Group generator active power, L represent the degree of strength of pollination, and essence is the step factor for obeying column dimension distribution, related
Formula is as follows:
In formula, Г (λ) is standard gamma function, and in addition λ generally takes 1.5, and as s > 0, the distribution belongs to reasonable scope.
Big due to changing frequent and range, which belongs to global optimizing.
In formula,WithIt is same species different from pollenTwo pollen position, ε ∈ U (0,1).The mistake
Journey is substantially the random walk process in a limited adjacent domain, therefore belongs to local optimal searching.
The pollen algorithm proposed in this paper that improves is that added to be directed to the different flower of optimal flower individual and award on former algorithm
Powder process, and then its local optimal searching ability is improved, accelerate late convergence.
Cross-pollination process is carried out to optimum individual when individual values update finishes, correlation formula is as follows:
The step of improving pollen algorithm is as follows:
1) initial parameter of flower is set, generates the initial position of flower at random within the allowable range；
2) adaptive value of individual is assessed, chooses optimal flower individual；
3) determine that flower is to carry out self-pollination or cross-pollination according to transition probability, to update individual values；
4) cross-pollination process is carried out to optimum individual；
5) adaptive value of all related individuals is compared, updates optimal value；
If 6) meet iterated conditional, stops optimizing and exporting optimal solution, otherwise go to 2).
2. the fired power generating unit load optimal distribution based on MFPA
Specific allocation flow is as follows:
1) mathematical model of the fired power generating unit load optimal distribution based on penalty function is determined；
2) bound of the generated output of each unit is set；
3) load of each unit of random initializtion；
4) the optimum allocation load of each unit is obtained by improvement pollen algorithm；
The present invention is realized using MATLAB, using the historical data of three generating sets of certain power plant as foundation, is fitted each
The performance parameter and load bound, detailed data of platform generating set see the table below shown in 1；
Given three total loads are 660MW, 770MW, 900MW, are calculated respectively with improvement pollen algorithm, and with flower
Powder algorithm and mean allocation result calculated are compared.Algorithm population scale is set as 200, and evolution the number of iterations is
1000 generations, as a result as shown in table 2~4:
The performance parameter and load bound of each unit of table 1
Optimum results when 2 total load D=660MW of table
Optimum results when 3 total load D=770MW of table
Optimum results when 4 total load D=900MW of table
The data of sharing of load are by load value obtained from algorithm optimization；Coal consumption amount is then consumed by corresponding load
Net coal consumption rate；Deviation refers to the total consumption of coal deviation on the basis of improving pollen algorithm.
Observe the deviation in table, it is possible to find more excellent solution can be found than pollen algorithm by improving pollen algorithm, compare average mark
With becoming apparent, performance of the different units under different total load states can be more played.
Fig. 2~4 be respectively total load be 660MW, 770MW, 900MW when, the result of MFPA and FPA algorithm compares figure.By
This visible MFPA algorithm searches out optimal value before the 100th iteration, hence it is evident that be faster than FPA algorithm, therefore late convergence the former
Faster, optimal time is also shortened.
Claims (6)
1. a kind of based on the fired power generating unit load optimal distribution method for improving pollen algorithm characterized by comprising according to power generation
The coal consumption characterisitic parameter fitting coal consuming character of unit simultaneously establishes load optimal distribution model, will by penalty function method；Its turn
It is changed to unconstrained problem, total generated output is distributed into each unit in conjunction with pollen algorithm is improved, it is optimal to finally obtain each unit
Sharing of load result.
2. it is according to claim 1 a kind of based on the fired power generating unit load optimal distribution method for improving pollen algorithm, it is special
Sign is that the improvement pollen algorithm has weighed global optimizing ability and local optimal searching ability well.
3. it is according to claim 1 a kind of based on the fired power generating unit load optimal distribution method for improving pollen algorithm, it is special
Sign is, with the concrete form of the minimum objective function of fired power generating unit consumption of coal amount are as follows:
In formula, n is generator sum；PiFor the active power of unit i；ai、bi、ciFor the energy consumption characteristics coefficient of unit i.In addition also
It is considered as influence of the valve point effect to cost of electricity-generating, therefore above-mentioned formula should be changed to:
In formula, ei、fiFor the coal consumption characteristic coefficient of unit i；PiminIt is then the output power lower limit of unit i.
4. it is according to claim 1 a kind of based on the fired power generating unit load optimal distribution method for improving pollen algorithm, it is special
Sign is that the inequality constraints being related to is unit operation constraint, and correlation formula is as follows:
Pimin≤Pi≤Pimax (3)
In formula, Pimin、PimaxThe minimum and maximum active power of respectively unit i exports.
5. it is according to claim 1 a kind of based on the fired power generating unit load optimal distribution method for improving pollen algorithm, it is special
Sign is, the practical problem that each unit load balances is included in the objective function of unit coal consumption characteristic by penalty function method,
Objective function after introducing penalty function are as follows:
In formula, n is generator sum, and σ is penalty factor, is generally taken between 1 00 to 150, F (Pi) be unit i standard consumption of coal
Amount；PiFor the active power of unit i；D is total activation load.
6. it is according to claim 1 a kind of based on the fired power generating unit load optimal distribution method for improving pollen algorithm, it is special
Sign is that the coal consumption characteristic equation that the optimizing distribution method is established according to the load and its coal consumption of each unit is as objective function
To optimize, and given general power is passed through into a part that penalty function method is included in objective function, the specific steps are as follows:
1) it determines the actual parameter of generating set, and generates one group of load initial value at random in each unit load limitation range；
2) the corresponding coal consumption value of more each load determines initial optimum load dispatch scheme；
3) self-pollination or cross-pollination are determined according to the transition probabilities for improving pollen algorithm, to bear to each unit
Lotus is updated；
4) cross-pollination optimization process is carried out to Optimal Load；
5) the corresponding coal consumption value of more each load determines the optimum load dispatch scheme of the secondary iteration；
6) until meeting iterated conditional, the Optimal Load value of each unit is exported.
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| CN112856014A (en) * | 2020-12-30 | 2021-05-28 | 南京理工大学 | Method for constructing control system of intelligent valve electric actuator |
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