CN106911139B - The energy-optimised management method of super capacitor RTG based on genetic algorithm - Google Patents
The energy-optimised management method of super capacitor RTG based on genetic 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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
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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
- H02J7/00—Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
- H02J7/34—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering
- H02J7/345—Parallel operation in networks using both storage and other dc sources, e.g. providing buffering using capacitors as storage or buffering devices
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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
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
Abstract
The present invention optimizes whole hybrid power RTG system capacity management, obtains the optimal output power of the diesel generating set and supercapacitor group under system entirety energy consumption minimum in the case where considering system energy consumption and non-renewable energy.Propose a kind of super capacitor RTG energy management method based on genetic algorithm.In the case where considering hybrid power system energy consumption and non-renewable capacity factor, the mathematical model of hybrid power system is established by the characterisitic parameter of diesel generating set, supercapacitor group and loading demand, provide objective function and constraint condition, last genetic Optimization Algorithm solves function, obtains the optimal output power of generating set and capacitor group.The present invention is based on the super capacitor RTG energy management methods of genetic algorithm, are applied to hybrid power RTG system, the hybrid power RTG system includes diesel generating set, supercapacitor group and load motor.
Description
Technical field
The present invention relates to crane hybrid power system energy managements, and in particular to a kind of super electricity based on genetic algorithm
Hold the energy-optimised management method of RTG.
Background technique
Currently, China's ports handling machine passes mainly with diesel generating set for main energy source in order to reduce
Fuel consumption and discharge caused by the large-sized diesel generating set of system, domestic and foreign scholars propose supercapacitor, flywheel and lithium
Battery reduces the scale of diesel generating set as power buffer.Wherein, the energy density of lithium battery is high, but
Low efficiency when high current charge-discharge, battery life are not grown, and price is more expensive.The energy density of supercapacitor is low, but power is close
Degree is high, and does not have any electrochemical reaction in charge and discharge process, can quickly absorb and release energy, high-efficient,
Service life is long.When motor Accelerating running, peak power requirements time are relatively short, supercapacitor can provide the peak work of short time
Rate.And flywheel is similar to super capacitor characteristics, but its self-discharge rate is high.
For the energy management strategies of RTG, totally it is divided into two kinds, one is rule-based strategy, another kind is to be based on
The strategy of optimization.
2006, South Korea Sang-Min Kim and Seung-Ki Sul had studied the energy of super capacitor hybrid electric RTG
Buret reason and control strategy problem, are controlled using traditional PI, and the discharge amount of rate of economizing gasoline 35%, diesel engine unit exhaust gas reduces
More than 40%.Between 2010-2012, a series of papers that French Petar J.Grbovic is delivered, to based on supercapacitor
Power-driven system control strategy and three-level DC converter have carried out system research, have reached crane system and have made in regeneration
The uninterrupted operation of dynamic process.The work of the two people is all based on the energy management control strategy of rule.
The hybrid power RTG power-supply system (Hybrid System) of SUMITOMO CHEMICAL heavy industry research and development is using lithium battery as energy storage
Device.The power output of battery is substantially at stable state in the application, and charge-discharge velocity is high, improves the circulation longevity of lithium battery
Life.The experimental data of Sumitomo Heavy Industries Ltd demonstrates, and the cycle life of the lithium battery can have 7 years or more, largely improves
The disadvantage that service life of lithium battery is not grown.RTG diesel generating set and lithium battery hybrid power supply technology multiple container terminals into
It has gone trial operation, and has achieved certain effect.In October, 2006, in August, 2007 was in Hong Kong world packaging at Japanese Guia Hill port
Box terminal (HIT), in Japanese big black container terminal, in May, 2008 is in Shenzhen Yantian trans-container harbour point within 2 months 2008
Performance test has not been carried out, wherein loading demand general power is 370kW, lithium by taking a hybrid power RTG of Hong Kong harbour as an example
The output power of battery pack and diesel generator sets distinguishes 270KW and 130KW, and relative to conventional crane system, diesel generator sets are matched
The power set reduces nearly 65%, and black smoke phenomenon significantly reduces.Research aspect, Zhenhua heavy industry have developed lithium battery RTG at home
Model machine, experiment show that its energy-saving effect is significant.These work are also based on rule.
And Stefano Pietrosanti, William Holderbaum and Victor M.Becerra propose band and fly
The optimal management strategy of energy stores in the case where wheel, this optimization solved under container hoisting time random case are asked
Topic.The work of Yoash Levron and Doron Shmilovitz are also based on optimisation strategy, but object be fuel cell and
Mobile phone does not account for the transmission system with regeneration energy.
Still further aspect, most of scientific research scholar is for hybrid power RTG energy management just for diesel-driven generator
The progress of group and supercapacitor group or lithium battery group individually controls, rather than integrally accounts for from system.
Summary of the invention
Above-mentioned status and the relevant technologies there are aiming at the problem that, the present invention is considering system energy consumption and non-renewable energy
In the case of, whole hybrid power system energy management is optimized, the diesel generation under system entirety energy consumption minimum is obtained
The optimal output power of unit and supercapacitor group.A kind of super capacitor RTG energy based on genetic algorithm is proposed to this
Management method.According to designed mixed power system structure block diagram, proposes and consider hybrid power system energy consumption and non-renewable
Under capacity factor, hybrid power system is established by the characterisitic parameter of diesel generating set, supercapacitor group and loading demand
Mathematical model, provide objective function and constraint condition, last genetic Optimization Algorithm solves function, obtains generating set
With the optimal output power of capacitor group.
Technical scheme is as follows:
A kind of super capacitor RTG energy management method based on genetic algorithm is applied to hybrid power RTG system, described
Hybrid power RTG system includes diesel generating set, supercapacitor group and load motor.Load motor is hybrid power RTG
Lifting mechanism.Diesel generating set is connect with rectifier to be energized by DC (direct current) busbar to load motor, supercapacitor
Group is connect with two-way DC/DC converter is parallel to DC busbar again, and when lifting mechanism drives load to rise, supercapacitor group is used
Peak power is provided, when lifting mechanism decline, supercapacitor group absorption and regeneration power energy storage.
The super capacitor RTG energy management method based on genetic algorithm the following steps are included:
Step 1: initially setting up the mathematical model about diesel generating set.Disappeared according to typical diesel-driven generator fuel
The fuel consumption that consumption curve graph can obtain diesel-driven generator is normally approximately quadratic function relevant to generator power.
Wi f=ai(Pi E)2+biPi E+ci (1)
Wherein, Pi EFor the output power of generator, it is equal to Pi E(t), Pi E(t) it is produced for i-th of generator in t moment
Raw power, and meetai、biAnd ciIt is constant, value is determined by other parameters such as types.Therefore, it mixes
Close the form of the diesel generating set fuel consumption that motor generates in [0, T Δ t] time range in power RTG system are as follows:
Wherein, EICEFor the energy of generating set fuel consumption, Pi EratedFor the rated output power of engine, T is mixing
One complete cycle of operation of power RTG system, H are diesel oil calorific value.
Step 2: establishing the mathematical model about supercapacitor group.It is in and is fed, again according to hybrid power RTG system
When raw braking and these three standby states, corresponding supercapacitor group be respectively necessary in hybrid power RTG operating process to
Load provides energy, absorption and regeneration energy stores and cluster engine and energizes to the charging of capacitor group, obtains
Wherein, ESCFor the energy that capacitor group generates, PC(t) in the t power provided while being also for supercapacitor group
The power that the power or supercapacitor group of system back to supercapacitor group are provided to load, can just bear.Ought be
When system is in feed condition, i.e., capacitor group is energized to system, at this time PC(t) 0 <；When system be in regenerative braking state or to
When machine state, i.e., system charges to capacitor group, at this time PC(t) 0 >.
Step 3: needing after the mathematical model for establishing diesel generating set and supercapacitor group according to hybrid power
The relationship of system capacity establishes the mathematical model of non-renewable energy.According to the energy that in actual mechanical process, capacitor group absorbs
It is limited, because of total system energy consumption, non-renewable energy can still be generated.In order to reduce the generation of non-renewable energy, consider
Difference between generating set and the energy supply and loading demand of supercapacitor group entirety, the non-renewable cost of energy letter obtained
Number is as follows:
Wherein, ENon-reFor non-renewable energy, PLIt (t) is the demand power loaded in t moment, load point in the present invention
Cloth is known.
Step 4: listing objective function according to goal of the invention:
J=EICE+λ×ESC+γ×ENon-re (5)
Wherein, λ and γ is constant-weight, indicates overall energy consumption in capacitor group and the ratio of non-renewable energy point
Match.
Step 5: the constraint condition of each variable is limited according to the objective function listed, constraint, electricity including generating set
The constraint of container group and load power demand constraint:
1) constraint of generating set: in order to make diesel-driven generator keep a lower specific fuel consumption, by operation model
Enclose is to have a certain range of, power limit Pi Emin≤Pi E(k)≤Pi Emax, wherein Pi EminAnd Pi EmaxRespectively i-th hair
The minimum and maximum power of motivation output.
2) constraint of capacitor group: the supercapacitor operation manual provided according to factory, in order to maintain supercapacitor
Service life, therefore admissible charge and discharge rate range be-PChmax≤PC(k)≤PDChmax, wherein PChmaxAnd PDChmaxIt is fair respectively
Perhaps maximum charge and discharge power.
3) load power demand constrains: ensuring that hybrid power RTG system is able to satisfy the power demand of load, therefore PE
(k)+PC(k)≥Pd(k)。
Step 6: solving the target about cost with genetic algorithm after giving objective function and constraint condition
Function, to obtain the diesel generating set of super capacitance hybrid power RTG and the optimal output power of supercapacitor group；Tool
Steps are as follows for body:
1): individual UVR exposure generates initial population；Super capacitance hybrid power RTG system a complete cycle it is negative
Load demand up-sampling, sampling number n obey being uniformly distributed for loading demand curve as far as possible, and the corresponding load of n sampled point is needed
Evaluation brings the objective function of step 4 into, obtains the target letter of the n variable about generating set power and capacitor group power
Number, while gene coding, coding reconciliation are carried out to this n variable using unsigned binary number according to the constraint condition of step 5
Coded program is mutually converted, and the size value of population size is m, and m value between 40-100, i.e. group are made of m individual, often
Individual is generated by random device；
2): calculating fitness；It is non-negative about hybrid power RTG energy consumption objective function value according to step 4, and
It is in the hope of functional minimum value is optimization aim, therefore the directly fitness individual as population m using target function value；
3): judging whether to meet Optimality Criteria；It is non-when bringing the fitness that hybrid power RTG objective function calculates into
Negative is considered as optimized individual, and the result obtained is the optimal output power of generating set and capacitor group of hybrid power system
Optimal output power, and it is considered the result wanted after optimization；
4): being selected, intersected and mutation operator；If being unsatisfactory for the Optimality Criteria in step 3), using with fitness at
The probability of direct ratio determines each individual replicate to the quantity in next-generation group, then using the method for single point crossing and basic
Position variation method carry out operation；
5): group brings into calculate in the objective function of hybrid power RTG Energy Management System again after a generation is evolved and fit
Angle value is answered, then return step 3) continue.
The present invention has the following effects that and advantage:
1. hybrid power RTG system of the invention is directed in the case where considering system energy consumption and non-renewable energy situation, surpass
When grade capacitor RTG system entirety energy consumption minimum, the optimal output power of generating set and capacitor at corresponding each moment can be obtained
The optimal output power of group；
It is genetic algorithm 2. super capacitor RTG system of the invention is because primary condition is unknown.System at
This function parameter can also be adjusted according to practical engineering project, if while known primary condition can also apply other optimization algorithm
To solve.
3. the system condition that the present invention considers is more sufficient, the energy consumption of system generation has both been considered it is contemplated that non-renewable energy
The factor of amount, is more conform with and practices production application.
Detailed description of the invention
Fig. 1 is hybrid power RTG system construction drawing of the present invention；
Fig. 2 is hybrid power RTG system power composition distribution map of the present invention；
Fig. 3 is genetic algorithm flow chart of the present invention
Specific embodiment
The present invention is in the case where considering system energy consumption and non-renewable energy, to whole hybrid power system energy pipe
Reason optimizes, and obtains the optimal output power of the diesel generating set and supercapacitor group under system entirety energy consumption minimum.
A kind of super capacitor RTG energy management method based on genetic algorithm is proposed to this.According to designed hybrid power system
Structural block diagram proposes and considers to pass through diesel generating set, super electricity under hybrid power system energy consumption and non-renewable capacity factor
The characterisitic parameter of container group and loading demand establishes the mathematical model of hybrid power RTG system, provides objective function and constraint item
Part, last genetic Optimization Algorithm solve function, obtain the optimal output power of generating set and capacitor group.
Initially set up the mathematical model of hybrid power RTG system.The mathematical modulo of diesel generating set and supercapacitor group
Type can be derived from by physical equation.The mathematical model combination hybrid power RTG system power of non-renewable energy forms distribution
Figure, can be derived from.Loading demand is distributed in RTG mono- complete handling of heavy goods process feelings of known super capacitance hybrid power
RTG binding characteristic parameter can calculate separately the loading demand for obtaining each operation time period under condition.
The setting of objective function is to make the hybrid power energy system of super capacitor RTG primary complete operation cycle
Energy consumption minimumization.These costs mainly include diesel generating set energy, supercapacitor group energy and non-renewable energy consumption
Cost.
Since the primary condition of objective function is unknown, genetic algorithm can be used to be solved.This method is by the U.S.
The Holland professor of Michigan university proposed in 1969, later again through De Jong, Goldberg et al. induction and conclusion institute
A kind of simulated evolutionary algorithm of formation, essence are a kind of efficient, parallel, global search methods, it can be in search process
Automatically obtain and accumulate the knowledge in relation to search space, and adaptively command deployment process in the hope of optimal solution.
Hybrid power RTG system structure diagram of the present invention, as shown in Figure 1.Hybrid power RTG system of the invention includes bavin
Oily generating set, supercapacitor group and load motor.Wherein, the lifting mechanism of hybrid power RTG is reduced to load motor M,
Diesel generating set connect with rectifier by DC (direct current) busbar give load motor energy supply, supercapacitor group with it is two-way
The connection of DC/DC converter is parallel to DC busbar again, and when lifting mechanism drives load to rise, supercapacitor group is used to provide peak
It is worth power, when lifting mechanism decline, supercapacitor group absorption and regeneration power energy storage.In conjunction with hybrid power RTG system power
Distribution map is formed, as shown in Fig. 2, non-renewable energy and generating set power, capacitor group power and load can be derived
The relationship of power.Power distribution composition includes diesel generating set output power, the output power of supercapacitor group and load
Demand power, circle indicate that hybrid power RTG system capacity relationship node, arrow indicate the flow direction of energy, generating set output
The input energy of both power and capacitor group output power as system entirety, bearing power are then output energy.Because non-
Regenerated energy volume production is born in the energy difference that system is integrally output and input, i.e. generating set output power and capacitor group output power
The whole difference with bearing power of the two, so obtaining non-renewable energy and generating set power, capacitor group power and bearing
Carry (3) formula of the relationship such as step 3 of power.
The present invention is based on the super capacitor RTG energy management methods of genetic algorithm, comprising the following steps:
Step 1: initially setting up the mathematical model about diesel generating set.Disappeared according to typical diesel-driven generator fuel
The fuel consumption that consumption curve graph can obtain diesel-driven generator is normally approximately quadratic function relevant to generator power.
Wi f=ai(Pi E)2+biPi E+ci (1)
Wherein, Pi EFor the output power of generator, it is equal to Pi E(t), Pi E(t) it is produced for i-th of generator in t moment
Raw power, and meetai、biAnd ciIt is constant, value is determined by other parameters such as types.Therefore, it mixes
Close the form of the diesel generating set fuel consumption that motor generates in [0, T Δ t] time range in dynamical system are as follows:
Wherein, EICEFor the energy of generating set fuel consumption, Pi EratedFor the rated output power of engine, T is mixing
One complete cycle of operation of power RTG system, H are diesel oil calorific value.
Step 2: establishing the mathematical model about supercapacitor group.It is in and is fed, again according to hybrid power RTG system
When raw braking and these three standby states, corresponding supercapacitor group be respectively necessary in hybrid power RTG operating process to
Load provides energy, absorption and regeneration energy stores and cluster engine and energizes to the charging of capacitor group, obtains
Wherein, ESCFor the energy that capacitor group generates, PC(t) in the t power provided while being also for supercapacitor group
The power that the power or supercapacitor group of system back to supercapacitor group are provided to load, can just bear.Ought be
When system is in feed condition, i.e., capacitor group is energized to system, at this time PC(t) 0 <；When system be in regenerative braking state or to
When machine state, i.e., system charges to capacitor group, at this time PC(t) 0 >.
Step 3: needing after the mathematical model for establishing diesel generating set and supercapacitor group according to hybrid power
The relationship of system capacity establishes the mathematical model of non-renewable energy.According to the energy that in actual mechanical process, capacitor group absorbs
It is limited, because of total system energy consumption, non-renewable energy can still be generated.In order to reduce the generation of non-renewable energy, consider
Difference between generating set and the energy supply and loading demand of capacitor group entirety, the non-renewable cost of energy function obtained is such as
Under:
Wherein, ENon-reFor non-renewable energy, PLIt (t) is the demand power loaded in t moment, load point in the present invention
Cloth is known.
Step 4: listing objective function according to goal of the invention:
J=EICE+λ×ESC+γ×ENon-re (5)
Wherein, λ and γ is constant-weight, indicates overall energy consumption in the ratio of supercapacitor group and non-renewable energy
Distribution.
It is constraint including generating set, super Step 5: limit the constraint condition of each variable according to the objective function listed
The constraint and load power demand constraint of grade capacitor group:
1) constraint of generating set: in order to make diesel-driven generator keep a lower specific fuel consumption, by operation model
Enclose is to have a certain range of, power limit Pi Emin≤Pi E(k)≤Pi Emax, wherein Pi EminAnd Pi EmaxRespectively i-th hair
The minimum and maximum power of motivation output.
2) constraint of supercapacitor group: the supercapacitor operation manual provided according to factory, in order to maintain super electricity
The service life of container, therefore admissible charge and discharge rate range is-PChmax≤PC(k)≤PDChmax, wherein PChmaxAnd PDChmaxRespectively
It is allowed maximum charge and discharge power.
3) load power demand constrains: ensuring that hybrid power RTG system is able to satisfy the power demand of load, therefore PE
(k)+PC(k)≥Pd(k)。
Step 6: solving the target about cost with genetic algorithm after giving objective function and constraint condition
Function, to obtain the diesel generating set of super capacitance hybrid power RTG and the optimal output power of supercapacitor group；Tool
Body step is provided referring to Fig. 3, and as follows:
1): individual UVR exposure generates initial population；Super capacitance hybrid power RTG system a complete cycle it is negative
Load demand up-sampling, sampling number n obey being uniformly distributed for loading demand curve as far as possible, and the corresponding load of n sampled point is needed
Evaluation brings the objective function of step 4 into, obtains the target letter of the n variable about generating set power and capacitor group power
Number, while gene coding, coding reconciliation are carried out to this n variable using unsigned binary number according to the constraint condition of step 5
Coded program is mutually converted, and the size value of population size is m, and m value between 40-100, i.e. group are made of m individual, often
Individual is generated by random device；
2): calculating fitness；It is non-negative about hybrid power RTG energy consumption objective function value according to step 4, and
It is in the hope of functional minimum value is optimization aim, therefore the directly fitness individual as population m using target function value；
3): judging whether to meet Optimality Criteria；It is non-when bringing the fitness that hybrid power RTG objective function calculates into
Negative is considered as optimized individual, and the result obtained is the optimal output power of generating set and capacitor group of hybrid power system
Optimal output power, and it is considered the result wanted after optimization；
4): being selected, intersected and mutation operator；If being unsatisfactory for the Optimality Criteria in step 3), using with fitness at
The probability of direct ratio determines each individual replicate to the quantity in next-generation group, then using the method for single point crossing and basic
Position variation method carry out operation；
5): group brings into calculate in the objective function of hybrid power RTG Energy Management System again after a generation is evolved and fit
Angle value is answered, then return step 3) continue.
Claims (1)
1. a kind of super capacitor RTG energy management method based on genetic algorithm is applied to hybrid power RTG system, described mixed
Closing power RTG system includes diesel generating set, supercapacitor group and load motor；Load motor is hybrid power energy system
The lifting mechanism of system；Diesel generating set connect with rectifier by DC busbar give load motor energy supply, supercapacitor group with
Two-way DC/DC converter connection is parallel to DC busbar again, and when lifting mechanism drives load to rise, supercapacitor group is used to mention
For peak power, when lifting mechanism decline, supercapacitor group absorption and regeneration power energy storage；It is characterized in that described based on something lost
The super capacitor RTG energy management method of propagation algorithm the following steps are included:
Step 1: being approximately according to the fuel consumption that typical diesel-driven generator fuel consumption curve figure obtains diesel generating set
Quadratic function relevant to generator power:
Wi f=ai(Pi E)2+biPi E+ci (1)
Wherein, Pi EFor the output power of generator, it is equal to Pi E(t), Pi E(t) it is generated for i-th of generator in t moment
Power, and meetai、biAnd ciIt is constant；Diesel generating set is at [0, T Δ t] in hybrid power system
The form for the fuel consumption that load motor generates in time range are as follows:
Wherein, EICEFor the energy of generating set fuel consumption, Pi EratedFor the rated output power of engine, T is hybrid power
One complete cycle of operation of system, H are diesel oil calorific value；
Step 2: when being in feed, regenerative braking and these three standby states according to hybrid power RTG system, it is corresponding super
Capacitor group is respectively necessary for depositing to load motor offer energy, absorption and regeneration energy in hybrid power RTG system operation procedure
Storage and cluster engine charge to capacitor group to be energized, and is obtained
Wherein, ESCFor the energy that supercapacitor group generates, PC(t) power provided for supercapacitor group in t moment is simultaneously
It is also the power that the power or supercapacitor group of system back to supercapacitor group are provided to load, can just bears；I.e.
When system is in feed condition, i.e., when supercapacitor group is energized to system, PC(t) 0 <；When system is in regenerative braking state
Or standby mode, i.e., when system charges to supercapacitor group, PC(t) 0 >；
Step 3: non-renewable cost of energy function is as follows:
Wherein, ENon-reFor non-renewable energy, PLIt (t) is the demand power loaded in t moment, load distribution is known；
Step 4: listing objective function:
J=EICE+λ×ESC+γ×ENon-re (5)
Wherein, λ and γ is constant-weight, indicates overall energy consumption in supercapacitor group and the ratio of non-renewable energy point
Match；
Step 5: the constraint condition of each variable is limited according to the objective function listed, constraint, super electricity including generating set
The constraint of container group and load power demand constraint:
1) constraint of generating set: the power limit of diesel generating set is Pi Emin≤Pi E(k)≤Pi Emax, wherein Pi EminWith
Pi EmaxThe minimum and maximum power of respectively i-th of engine output；
2) constraint of supercapacitor group: admissible charge and discharge rate range is-PChmax≤PC(k)≤PDChmax, wherein PChmaxWith
PDChmaxIt is allowed maximum charge and discharge power respectively；
3) load power demand constrains: PE(k)+PC(k)≥Pd(k)；
Step 6: the objective function about cost is solved with genetic algorithm after giving objective function and constraint condition,
To obtain the diesel generating set of super capacitance hybrid power RTG and the optimal output power of supercapacitor group；Specific step
It is rapid as follows:
1): individual UVR exposure generates initial population；It is needed in the load of a complete cycle of super capacitance hybrid power RTG system
Up-sampling is sought, sampling number n obeys being uniformly distributed for loading demand curve as far as possible, by the corresponding loading demand value of n sampled point
The objective function for bringing step 4 into obtains the objective function of the n variable about generating set power and capacitor group power, together
When gene coding, coding and decoding journey carried out to this n variable using unsigned binary number according to the constraint condition of step 5
Sequence is mutually converted, and the size value of population size is m, and m value between 40-100, i.e. group are made of m individual, per each and every one
Body is generated by random device；
2): calculating fitness；It is non-negative about hybrid power RTG energy consumption objective function value according to step 4, and be with
The minimum value found a function is optimization aim, therefore directly using target function value as the fitness of m individual of population；
3): judging whether to meet Optimality Criteria；When bring into fitness that hybrid power RTG objective function calculates be it is non-negative i.e.
It is considered as optimized individual, the result obtained is optimal for the optimal output power of generating set and capacitor group of hybrid power system
Output power, and it is considered the result wanted after optimization；
4): being selected, intersected and mutation operator；If the Optimality Criteria in step 3) is unsatisfactory for, using directly proportional to fitness
Probability come determine each individual replicate to the quantity in next-generation group, then using single point crossing method and basic position
Variation method carries out operation；
5): group brings into the objective function of hybrid power RTG Energy Management System again after a generation is evolved and calculates fitness
It is worth, then return step 3) continue.
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| CN108988414A (en) * | 2018-06-28 | 2018-12-11 | 南京理工大学 | Bidirectional DC-DC converter control system and method based on hybrid power RTG |
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