CN109742781A - A kind of optimization method of marine diesel energy mix system configuration - Google Patents
A kind of optimization method of marine diesel energy mix system configuration Download PDFInfo
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Abstract
The present invention discloses a kind of optimization method of marine diesel energy mix system configuration, is related to energy mix system regions.The sum that the present invention passes through the solar panel in the photovoltaic generating module to marine diesel energy mix system, system configuration parameter including the sum of blower in wind power generation module and the sum of the battery group in battery energy storage module is optimized using following step: initially setting up the Model for Multi-Objective Optimization of marine diesel energy mix system configuration, the Model for Multi-Objective Optimization is optimized using artificial bee colony algorithm, obtain the allocation optimum parameter for meeting cost and availability optimization aim, so that marine diesel energy mix system availability is high and meets requirement at low cost.
Description
Technical field
The present invention relates to energy mix system regions, in particular to a kind of marine diesel energy mix system configuration it is excellent
Change method.
Background technique
The generating mechanism of diesel engine is produced electricl energy by petroleum.In recent years, these greens of solar energy, wind energy, battery energy storage
Clean energy resource, they can be implemented as load supplying together with diesel engine, to achieve energy-saving and emission reduction purposes.
For energy mix system, many optimization methods are proposed in the prior art: modified particle swarm optiziation is used for
Revised genetic algorithum, is used to optimize the reliability of active distribution network system, will changed by the cost for optimizing energy storage type tramcar
Into particle swarm algorithm optimization home energy source management system use cost, genetic algorithm is used for energy mix system model
It optimizes and configures, global extremum finding algorithm is used to optimize the energy of fuel cell system, by improved ant group optimization
For optimizing the scale of independent hybrid power system, convex optimization method is used to optimize photovoltaic/battery/diesel hybrid system
Size, glowworm swarm algorithm is used to optimize free-standing energy mix system, crow searching algorithm is used to optimize photovoltaic/wind
Harmonious searching algorithm is used to optimize photovoltaic/diesel generating system scale, population is calculated by machine/tide/cell hybrid systems
Method is used for Optimization of Diesel Engine/photovoltaic system scale, is used to optimize solar hybrid system for differential evolution algorithm, realizes
Optimum voltage control, is used to optimize photovoltaic/blower/hybrid system availability for Revised genetic algorithum.
These methods mainly consider the fixed energy mix system of structure, and also with good grounds city in other technologies
Manage the solar panels size in position calculating photovoltaic generating system and inclination angle, energy output quantity.Above method is for land
On energy mix system.
Ship is the ship of mobile means of transport, especially oceangoing voyage, there is a longevity of service, the remote feature of voyage, because
This energy mix system for being applied to sea going ship needs to consider geographical location locating for ship and its solar radiation
Amount.In addition, ship is different from the equipment to work in land, in addition to equipment cost, the service life of equipment is also to distribute rationally
One of an important factor for.Therefore biobjective scheduling marine diesel will be carried out in terms of low cost and the long life two herein
The configuration of energy mix system, however be at present optimized with simple target.
Summary of the invention
In order to overcome technical problem as described above, the present invention proposes a kind of marine diesel energy mix system configuration
Optimization method optimizes the Model for Multi-Objective Optimization by using artificial bee colony algorithm, obtain meeting cost and
The allocation optimum parameter of availability optimization aim, so that marine diesel energy mix system availability is high and meets at low cost
It is required that.
Specific technical solution of the present invention is as follows:
The present invention proposes a kind of optimization method of marine diesel energy mix system configuration, comprising:
Marine diesel energy mix system include photovoltaic generating module, wind power generation module, battery energy storage module and
Diesel engine power supply module, to include the sum of solar panel in the photovoltaic generating module, in wind power generation module
System configuration parameter including the sum of battery group in the sum and battery energy storage module of blower is carried out using following step
Optimization:
S1 establishes the Model for Multi-Objective Optimization of marine diesel energy mix system configuration, comprising:
S11, according to the use cost situation and stable operation situation of marine diesel energy mix system configuration, respectively
Establish the cost objective function C of the marine diesel energy mix system configurationTWith availability objective function T；
S12 determines the cost objective function CTWith the constraint condition of the relevant configured parameter of availability objective function T；
S2 optimizes the Model for Multi-Objective Optimization using artificial bee colony algorithm, obtains meeting cost and can
With the allocation optimum parameter of property optimization aim.
Further, the S11 includes:
The cost objective function use by the marine diesel energy mix system configuration year Meteorological, Nian Wei
The sum of shield expense and year fuel consumption cost are indicated；The availability objective functionWherein DNM table
Show the demand not met.
Further:
DNM indicates the demand not met, and is expressed from the next:
In formula, u (t) is a jump function, when the general power of photovoltaic generating module and the generation of wind turbine power generation module is greater than
Or equal to load demand when, u (t)=1, otherwise u (t)=0, the sample number taken in 1 year is Ndata, battery energy storage module
In, minimum amount of power e that battery can storemin_batt, the current electricity E of batterybatt(t), the photovoltaic generating module of system
In the general power P that t moment generatespv(t), the general power P that the wind turbine power generation module of system is generated in t momentwt(t), load is to electricity
The demand of energy is denoted as El(t)。
Further, the general power P that the photovoltaic generating module of the system is generated in t momentpv(t) it is obtained by following step
It takes:
The influence irregularly waved that ship rides the sea, the calculating of solar incident angle i at this time are not considered
Simplify and indicated by formula:
Cosi=sinh (8)
Method phase intensity of solar radiation IDNIt can be obtained by formula (9-10),
IDN=I0Pm (9)
In formula (9), I0It is solar constant, P is atmosphere coefficient of transparency, and m is the air quality that light penetrates, and is obtained by formula (10)
It arrives,
Globalradiation intensity I on inclined surfaceθIt can be obtained by formula (11)-formula (12):
Iθ=IDθ+Idθ+IRθ (11)
In formula (11)-formula (12), inclination angle of inclined plane θ=0, IDθIt is the beam radia intensity on inclined surface, IdθIt is inclination
Solar scattered radiation intensity on face, IRθIt is ground return radiation intensity obtained on inclined surface, due to inclination angle of inclined plane θ=0,
Formula (12) can simplify an accepted way of doing sth (13):
Iθ=IDN·(cosi+cosh) (13)
According to formula (13), the solar radiation intensity of in ship's navigation different moments, different location can be calculated, so
ItIt can be obtained by formula (14):
Therefore, the power p that solar panel generates in the unit timepv(t) it can be obtained by formula (15):
ppv(t)=It(t)×A×jpv (15)
In formula (15), the square measure of solar panel is m2, the area of A expression solar panel, jpvIt indicates too
The electric energy conversion ratio of positive energy solar panel, the general power P that the photovoltaic generating module of system is generated in t momentpvIt (t) can be with by formula (16)
It obtains:
Ppv(t)=Npv×ppv(t) (16)
In formula (16), NpvIt is the sum of solar panel in system, shown in value range such as formula (17):
0≤Npv≤Nmax_pv (17)
Wherein Nmax_pvIndicate NpvMaximum value.
Further, the S2 includes:
Artificial bee colony algorithm is divided into four-stage, i.e. initial phase, EB optimizing phase, OB optimizing phase and SB optimizes rank
Section:
In initial phase, program needs random generation NPThe initial value of a solution to be optimized, NPIndicate the size of population, NP
The bigger food source that it can find is also more, and the number of food source is exactly the number of solution x (l, d) to be optimized, and the value of x (l, d) can
To be obtained by formula (38):
X (l, d)=xmin(d)+rand×[xmax(d)-xmin(d)] (38)
In formula (38), xmax(d) and xminIt (d) is its maximum value and minimum value respectively, rand indicates the random number in 0~1,
D is dimension, and l is the serial number of solution to be optimized,
In EB optimizing phase and OB optimizing phase, more new explanation z (l, d) can be obtained by formula (39):
Z (l, d)=x (l, d)+yld×[x(l,d)-x(r,d)] (39)
Y in formula (39)ldIndicate -1~1 random number, r is 1~NPBetween a random integers and be not equal to l, due to x
(l, d) has maximum value and minimum value, so z (l, d) calculates the value range that may exceed x (l, d), if hair
Raw such case, it is necessary to this more new explanation is abandoned, obtains a new explanation as substitute using formula (38),
Probability p used in the OB optimizing phaselIt is calculated such as formula (40):
In formula (40), F (l) is the functional value of the corresponding cost and availability optimization aim of optimization solution, the cost and
Availability optimization aim includes:
The cost and availability optimization aimWherein,
λ1And λ2Indicate CTIt is preset value, Max (C with importance of the T in system optimizationT) and Min (CT) respectively indicate the maximum of cost
Value and minimum value, Max (T) and Min (T) respectively indicate the maximum value and minimum value of availability,
The work of OB optimizing phase is assessed the optimization solution that the EB optimizing phase obtains, corresponding according to nectar quantity
Probability selects food source, in the SB optimizing phase, as the number k that it is not updatedcountGreater than threshold value klimitWhen, then, just utilize
Formula (38) is randomly derived a new explanation to be compared with optimal value before, if new explanation is more preferable, just instead of current optimal
Solution, if algorithm meets the condition of convergence, exports optimal solution, otherwise enters iterative calculation next time.
Technical solution provided by the invention has the benefit that
The present invention is total by the solar panel in the photovoltaic generating module to marine diesel energy mix system
System configuration ginseng including the sum of battery group in the sum and battery energy storage module of blower several, in wind power generation module
Number is optimized using following step: being initially set up the Model for Multi-Objective Optimization of marine diesel energy mix system configuration, is adopted
Manually ant colony algorithm optimizes the Model for Multi-Objective Optimization, obtains meeting cost and availability optimization aim
Allocation optimum parameter, so that marine diesel energy mix system availability is high and meets requirement at low cost.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, required use in being described below to embodiment
Attached drawing be briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for this
For the those of ordinary skill of field, without creative efforts, it can also be obtained according to these attached drawings others
Attached drawing.
Fig. 1 show a kind of optimization method schematic diagram of marine diesel energy mix system configuration of the present invention；
Fig. 2 show what the present invention optimized marine diesel energy mix system configuration using artificial bee colony algorithm
Block diagram；
Fig. 3 show a kind of variation diagram for the solar radiation amount that ship receives of the present invention；
Fig. 4 is the wind speed change curve in a kind of wind turbine power generation module of the present invention；
Fig. 5 is the change curve of bearing power in a kind of simulated voyage that single is round-trip of the present invention；
Fig. 6, which is that the present invention is a kind of, uses artificial bee colony algorithm, particle swarm algorithm and differential evolution algorithm respectively to mixing energy
Source system optimizes configuration simulated effect figure.
Specific embodiment
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with attached drawing to embodiment party of the present invention
Case is described in further detail.
Marine diesel energy mix system in the present invention includes photovoltaic generating module, wind power generation module, battery storage
Energy module and diesel engine power supply module, optimize system configuration parameter, so that system configuration parameter meets so that system
Availability it is high while cost is relatively low, system configuration parameter here includes: the solar panel in photovoltaic generating module
Sum, blower in wind power generation module sum and battery energy storage module in battery group sum.
It is as shown in Figure 1 a kind of optimization method schematic diagram of marine diesel energy mix system configuration of the present invention, comprising:
S1 establishes the Model for Multi-Objective Optimization of marine diesel energy mix system configuration, comprising:
S11, according to the use cost situation and stable operation situation of marine diesel energy mix system configuration, respectively
Establish the cost objective function C of the marine diesel energy mix system configurationTWith availability objective function T；
How this step specifically discloses according to the comprising modules and working principle of energy mix system, establishes energy mix system
The cost objective function C of systemTWith the specific implementation process of availability objective function T.
In photovoltaic generating module, it is necessary first to which what is obtained is illumination of the every piece of solar panel suffered by t moment
Intensity It, all the time on different location on earth, ItIt is all different, it can be derived by by following formula.
E=9.87sin2B-7.53cosB-1.5sinB (1)
Wherein,N=1,2 ..., 365.E represents the time difference, and unit is min.N indicates number of days (January 1
When, n=1).
True solar time H can be obtained by formula (2).
Ls=15 ° of tz (3)
In formula (2-3), when Hs is the standard of this area, unit h.L is local longitude, and unit is degree.LsIt is local
Longitude where local standard time, unit are degree.For the Eastern Hemisphere, ± take just, and for the Western Hemisphere, ± take it is negative.tzIt is local
Time zone.
Solar elevation h can be obtained by formula (4)-formula (6).
Sinh=sin φ sin δ+cos φ cos ω (4)
ω=15 ° (H-12) (5)
In formula (4)-formula (6),It is local latitude, δ is declination angle, and ω is solar hour angle, their unit all degree of being.
Solar incident angle i can be obtained by formula (7).
Cosi=cos θ sinh+sin θ coshcos (α-γ) (7)
In formula (7), θ is inclination angle of inclined plane, and α is solar azimuth, and γ is inclined-plane azimuth, their unit degree of being.
Assuming that not considering the influence irregularly waved that ship rides the sea, it is believed that the photovoltaic battery panel on ship is always
Be it is horizontal positioned, then inclination angle of inclined plane θ=0, the calculating of solar incident angle i at this time can simplify and be indicated by formula (8).
Cosi=sinh (8)
Method phase intensity of solar radiation IDNIt can be obtained by formula (9-10).
IDN=I0Pm (9)
In formula (9), I0It is solar constant, P is atmosphere coefficient of transparency.M is the air quality that light penetrates, and is obtained by formula (10)
It arrives.
Globalradiation intensity I on inclined surfaceθIt can be obtained by formula (11)-formula (12).
Iθ=IDθ+Idθ+IRθ (11)
In formula (11)-formula (12), IDθIt is the beam radia intensity on inclined surface, IdθIt is that the sun on inclined surface dissipates
Penetrate radiation intensity, IRθIt is ground return radiation intensity obtained on inclined surface.But due to inclination angle of inclined plane θ=0, formula (12) can be with
Simplify an accepted way of doing sth (13).
Iθ=IDN·(cosi+cosh) (13)
According to formula (13), the solar radiation intensity of in ship's navigation different moments, different location can be calculated, so
ItIt can be obtained by formula (14).
Therefore, the power p that solar panel generates in the unit timepv(t) it can be obtained by formula (15).
ppv(t)=It(t)×A×jpv (15)
In formula (15), the square measure of solar panel is m2, the area of A expression solar panel, jpvIt indicates too
The electric energy conversion ratio of positive energy solar panel.The general power P that the photovoltaic generating module of system is generated in t momentpvIt (t) can be with by formula (16)
It obtains.
Ppv(t)=Npv×ppv(t) (16)
In formula (16), NpvIt is the sum of solar panel in system, shown in value range such as formula (17).
0≤Npv≤Nmax_pv (17)
Wherein Nmax_pvIndicate NpvMaximum value.
In wind power generation module, the power p of unit time inner blower generationwt(t) it can be obtained by formula (18).
In formula (18), the wind speed of t moment is vt, the rated wind speed of blower is denoted as vr, corresponding to blower rated power
It is denoted as Pr_wt.When actual wind speed is greater than threshold wind velocity vminWhen, blower is started to work, when wind speed is too big, greater than early warning wind speed vmax
When, in order to protect blower, blower stops working at this time.
So general power P for being generated in t moment of the wind turbine power generation module of systemwt(t) available by formula (19).
Pwt(t)=Nwt×pwt(t) (19)
In formula (19), NwtIt is the sum of system blower, value range is by shown in such as (20).
0≤Nwt≤Nmax_wt (20)
Wherein Nmax_wtIndicate NwtMaximum value.
Battery energy storage module is due to the intermittence of the new energy such as solar energy, wind energy and the mutability of electrical load and wave
Dynamic property, energy mix system also should ensure that it has and fill other than can meet the needs of load is to the energy at any time
The energy storage of foot.
In battery energy storage module, maximum electricity e that one piece of battery can storemax_battWith minimum amount of power emin_batt
It can be obtained by formula (21).
emin_batt=(1-DoD) × emax_batt (21)
In formula (21), note battery maximum depth of discharge is DoD.For normal, battery can be provided when dispatching from the factory it is specified most
Large capacity.The maximum electricity E so stored in batteries all at this timemax_battWith minimum amount of power Emin_battIt can be by formula
(22)-formula (23) obtains.
Emax_batt=Nbatt×emax_batt (22)
Emin_batt=Nbatt×emin_batt (23)
In formula (22)-formula (23), NbattIt is the sum of battery group in system, shown in value range such as formula (24).
0≤Nbatt≤Nmax_batt (24)
Wherein Nmax_battIndicate NbattMaximum value.
In t moment, if the electric energy summation that photovoltaic generating module and wind turbine power generation module generate is higher than the demand of load, just
It charges to battery, at this time the electricity E of batterybatt(t) it can be obtained by formula (25).If photovoltaic generating module and wind
The electric energy summation that machine electricity generation module generates just discharges to battery, at this time the total electricity of battery lower than the demand of load
It can be obtained by formula (26).
In formula (25)-formula (26), battery is E in the energy storage capacity summation of t momentbatt(t), the demand to electric energy is loaded
It is denoted as El(t), inverter conversion ratio and battery pack charge efficiency are respectively jinvAnd jbatt, the variable quantity of time is Δ t.
Certainly, no matter there is that situation, the total electricity of battery will be maintained at E alwaysmax_battAnd Emin_battBetween,
If being filled with cannot recharge, whereas if electricity out of power will not be reduced to 0, E is at most just dropped tomin_batt, then
The electric energy P that t moment battery can providebatt(t) it can be obtained by formula (27).
In diesel engine power supply module, in t moment, if the energy that the above three parts can be provided and the need less than load
It asks, the output power P of diesel engined(t) it can be obtained by formula (28).Otherwise, there is no need to be powered by diesel engine, i.e. Pd(t) it is equal to
0。
The fuel consumption F of diesel engineD(t) (unit l/h) can be obtained by formula (29).
FD(t)=BD×PN+AD×Pd(t) (29)
Wherein, the rated output power of diesel engine is PN, parameter AD=0.246 (l/kWh), BD=0.0845 (l/kW
h).At this point, according to the monovalent P of fuelF, so that it may fuel consumption cost C of the diesel engine in t moment is obtained by formula (30)f_d
(t)。
Cf_d(t)=PF×FD(t) (30)
By the above-mentioned model established to system modules about working principle, can be quantified by specific formula for calculation
Firstly, with save the cost as a purpose when, there are three parameters in need of consideration: year Meteorological Cc, year maintenance expense
Use CmWith year fuel consumption cost Cf。
Year Meteorological CcIt can be obtained by formula (31).
In formula (31), the allowance for depreciation of equipment is i, solar panel, blower, battery and diesel engine service life be respectively
npv、nwt、nbattAnd nd, initial input cost is respectively Cpv、Cwt、CbattAnd Cd。
Year maintenance cost CmIt can be obtained by formula (32).
Cm=Npv×Cmtn_pv+Nwt×Cwtn_wt+Cmtn_d (32)
In formula (32), the year maintenance cost of each unit of solar panel is denoted as Cmtn_pv, the year maintenance of single blower
Expense is denoted as Cmtn_wt, the year maintenance cost of diesel engine is denoted as Cmtn_d。
Diesel engine year maintenance cost Cmtn_dIt can be obtained by formula (33).
In formula (33), it is assumed that the sample number taken in 1 year is Ndata, for convenience of calculation, access according to when it is (small with h
When) it is unit, i.e. Ndata=8760, it is P that diesel engine, which consumes the maintenance cost that every degree electricity generates,mtn_d。
At this point, diesel engine year fuel consumption cost CfIt can be obtained by formula (34).
In conjunction with analysis above, the totle drilling cost C of energy mix optimization systemTIt can be obtained by formula (35).
CT=Cc+Cm+Cf (35)
Secondly, introducing the concept of availability to keep the working time of system elongated, it is that can decision continual and steady
One of key component of operation.Availability T can be obtained by formula (36).
In formula (36), DNM indicates the demand not met, it can be indicated by formula (37).
In formula (37), u (t) is a jump function, when the general power of photovoltaic generating module and the generation of wind turbine power generation module
More than or equal to load demand when, u (t)=1, otherwise u (t)=0.
If simple target makes to save cost to the maximum extent, service life may not be too long.On the contrary, if single
Target is to prolong the service life to the maximum extent, and cost is possible will be very high.Both systems are all less likely can be raw in reality
It is applied in work.Therefore, the system for selecting a low cost and long-life all to take into account is vital.So variable Npv、
NwtAnd NbattValue by C in objective functionTIt is determined when reaching minimum value and when T reaches maximum value.
Therefore, in conjunction with this step Chinese style (35) and (36), min (CT) and Max (T) constitute marine diesel mixing energy
The optimization object function of source system configuration.
S12 determines the cost objective function CTWith the constraint condition of the relevant configured parameter of availability objective function T；
Perhaps clean energy resource has very big advantage relative to petroleum fuel, it should which promotion is widely used.But after all to have
A degree, thing again it is handy can not excess given so needing reasonably to plan the quantity of three kinds of novel devices
Certain limitation, the maximum value of these three variables are to be manually set, therefore their value is needed in conjunction with each in practical application
The characteristics of region, accounts for.
S2 optimizes the Model for Multi-Objective Optimization using artificial bee colony algorithm, obtains meeting cost and can
With the allocation optimum parameter of property optimization aim.
By step S11 it is found that because and can also interact between them there are two the targets to be optimized, so
Function u (the C of system performance quality is describedT, T) and it can be obtained by formula (40), it can unitize the two variables.
In formula (41), λ1And λ2It is the parameter of self-defining, they can indicate CTWith the importance of T in systems.One
In the possible realization of kind, λ1=λ2, it means that cost and availability are of equal importance.
The present invention is illustrated in figure 2 to optimize marine diesel energy mix system configuration using artificial bee colony algorithm
The step of scheme, artificial bee colony algorithm is divided into four-stage, i.e. initial phase 201, EB optimizing phase 202, OB optimizing phase 203
With the SB optimizing phase 204:
In initial phase, program needs random generation NPThe initial value of a solution to be optimized, NPIndicate the size of population, NP
The bigger food source that it can find is also more, and the number of food source is exactly the number of solution x (l, d) to be optimized, and the value of x (l, d) can
To be obtained by formula (39):
X (l, d)=xmin(d)+rand×[xmax(d)-xmin(d)] (39)
In formula (39), xmax(d) and xminIt (d) is its maximum value and minimum value respectively, rand indicates the random number in 0~1,
D is dimension, and l is the serial number of solution to be optimized,
In EB optimizing phase and OB optimizing phase, more new explanation z (l, d) can be obtained by formula (40):
Z (l, d)=x (l, d)+yld×[x(l,d)-x(r,d)] (40)
Y in formula (40)ldIndicate -1~1 random number, r is 1~NPBetween a random integers and be not equal to l, due to x
(l, d) has maximum value and minimum value, so z (l, d) calculates the value range that may exceed x (l, d), if hair
Raw such case, it is necessary to this more new explanation is abandoned, obtains a new explanation as substitute using formula (39),
Probability p used in the OB optimizing phaselIt is calculated such as formula (41):
In formula (41), F (l) is the functional value of the corresponding cost and availability optimization aim of optimization solution, the cost and
Availability optimization aim includes:
The cost and availability optimization aimWherein,
λ1And λ2Indicate CTIt is preset value, Max (C with importance of the T in system optimizationT) and Min (CT) respectively indicate the maximum of cost
Value and minimum value, Max (T) and Min (T) respectively indicate the maximum value and minimum value of availability,
The work of OB optimizing phase is assessed the optimization solution that the EB optimizing phase obtains, corresponding according to nectar quantity
Probability selects food source, in the SB optimizing phase, as the number k that it is not updatedcountGreater than threshold value klimitWhen, then, just utilize
Formula (38) is randomly derived a new explanation to be compared with optimal value before, if new explanation is more preferable, just instead of current optimal
Solution, if algorithm meets the condition of convergence, exports optimal solution, otherwise enters iterative calculation next time.
The present embodiment passes through the solar panel in the photovoltaic generating module to marine diesel energy mix system
System configuration including the sum of battery group in the sum and battery energy storage module of blower total, in wind power generation module
Parameter is optimized using following step: the Model for Multi-Objective Optimization of marine diesel energy mix system configuration is initially set up,
The Model for Multi-Objective Optimization is optimized using artificial bee colony algorithm, obtains meeting cost and availability optimization aim
Allocation optimum parameter so that marine diesel energy mix system availability is high and meets requirement at low cost.
Further, in order to verify the validity and reasonability that energy mix is distributed rationally, ship's navigation will be carried out herein
Measured test, for flight course planning from DaLian, China to the route of Aden, Yemen, the ship single round-trip time is about 38 days, is amounted to
912 hours.Geographical location as where ship under sail is different, and solar radiation amount can also change correspondingly.By formula
(1) calculating of-formula (14), in the round-trip simulated voyage of single, the solar radiation amount It that ship receives is as shown in Figure 3.
In wind turbine power generation module, each hour data of wind speed vt are as shown in figure 4, the randomness due to wind-force is big, institute
It is to be simulated to obtain by average climate regional on navigation route with data.
This section has carried out five kinds of different operating mode ship's navigations experiments, corresponding to bearing power provided by table 1,
When ship is when common sea area is navigated by water, it will be in Full-Speed mode, it, will be in cruise mould when ship is when the Strait of Malacca is navigated by water
Formula.In addition, ship rests in Dalian, Shanghai, Hong Kong, Singapore, Sri Lanka, this 6 cities of Aden are traded and safeguarded,
Its time consumed is provided by table 2.Therefore, in the round-trip simulated voyage of single, data such as Fig. 5 institute of each hour of load
Show.Simulation calculation is carried out to the disparate modules of energy mix system, required design parameter is calculated and is provided by table 3- table 6.
The bearing power of the different sail modes of table 1
The working time at the different harbours of table 2
The numerical value of 3 photovoltaic generating module parameter of table
The numerical value of 4 wind turbine power generation module parameter of table
The numerical value of 5 battery energy storage module parameter of table
The numerical value of 6 diesel engine power supply module parameter of table
7 algorithms of different of table distributes energy mix system rationally
System configuration result of the table 8 for the purpose of Different Optimization target
In order to preferably verify the optimization performance of method of the present invention, we are also by artificial bee colony algorithm, particle swarm algorithm and difference
Evolution algorithm is divided to optimize configuration emulation to energy mix system respectively, the optimizing curve being drawn in is as shown in Figure 6.
Data after being optimized with algorithms of different are as shown in table 7.Three kinds of algorithms are compared, although particle swarm algorithm is preceding
Outline is better than artificial bee colony algorithm in phase convergence rate, but it eventually falls into local optimum, and the final result of optimization is obvious
Not as good as artificial bee colony algorithm.And differential evolution algorithm is all not so good as artificial bee colony algorithm in convergence rate and final optimization pass result
It is good.Therefore, using artificial bee colony algorithm in this problem, there is fast convergence rate, stability is high, is not easy to fall into local optimum
Feature has more outstanding performance compared to other algorithms.
Biobjective scheduling system of the invention is compared with single object optimization system, the results are shown in Table 8.It can by table 8
See, biobjective scheduling system has apparent advantage.When reaching least cost, the availability of system can be very low；Instead
It, when availability reaches highest, needed for cost will be very high.But the optimum results of Bi-objective system configuration
Show by increasing certain expense on the basis of least cost, so that it may greatly improve the availability of system.
The foregoing is merely presently preferred embodiments of the present invention, is not used to limit invention, it is all in spirit of the invention and
Within 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 optimization method of marine diesel energy mix system configuration characterized by comprising
Marine diesel energy mix system includes photovoltaic generating module, wind power generation module, battery energy storage module and diesel oil
Machine power supply module, to including the sum of solar panel in the photovoltaic generating module, the blower in wind power generation module
Sum and battery energy storage module in battery group sum including system configuration parameter optimized using following step:
S1 establishes the Model for Multi-Objective Optimization of marine diesel energy mix system configuration, comprising:
S11 is established respectively according to the use cost situation and stable operation situation of marine diesel energy mix system configuration
The cost objective function C of the marine diesel energy mix system configurationTWith availability objective function T；
S12 determines the cost objective function CTWith the constraint condition of the relevant configured parameter of availability objective function T；
S2 optimizes the Model for Multi-Objective Optimization using artificial bee colony algorithm, obtains meeting cost and availability
The allocation optimum parameter of optimization aim.
2. the optimization method of marine diesel energy mix system configuration according to claim 1, which is characterized in that described
S11 includes:
The cost objective function use by the marine diesel energy mix system configuration year Meteorological, year maintenance expense
It is indicated with the sum of year fuel consumption cost；The availability objective functionWherein DNM expression does not have
There is the demand of satisfaction.
3. the optimization method of marine diesel energy mix system configuration according to claim 2, it is characterised in that:
DNM indicates the demand not met, and is expressed from the next:
In formula, u (t) is a jump function, when the general power of photovoltaic generating module and the generation of wind turbine power generation module is greater than or waits
When the demand of load, u (t)=1, otherwise u (t)=0, the sample number taken in 1 year are Ndata, in battery energy storage module, store
The minimum amount of power e that battery can storemin_batt, the current electricity E of batterybatt(t), the photovoltaic generating module of system is in t
Carve the general power P generatedpv(t), the general power P that the wind turbine power generation module of system is generated in t momentwt(t), load is to electric energy
Demand is denoted as El(t)。
4. the multiple-objection optimization configuration method of marine diesel energy mix system configuration according to claim 3, special
Sign is, the general power P that the photovoltaic generating module of the system is generated in t momentpv(t) it is obtained by following step:
Do not consider that the influence irregularly waved that ship rides the sea, the calculating of solar incident angle i at this time can simplify
And it is indicated by formula:
Cosi=sinh (8)
Method phase intensity of solar radiation IDNIt can be obtained by formula (9-10),
IDN=I0Pm (9)
In formula (9), I0It is solar constant, P is atmosphere coefficient of transparency, and m is the air quality that light penetrates, it is obtained by formula (10),
Globalradiation intensity I on inclined surfaceθIt can be obtained by formula (11)-formula (12):
Iθ=IDθ+Idθ+IRθ (11)
In formula (11)-formula (12), inclination angle of inclined plane θ=0, IDθIt is the beam radia intensity on inclined surface, IdθIt is on inclined surface
Solar scattered radiation intensity, IRθIt is ground return radiation intensity obtained on inclined surface, due to inclination angle of inclined plane θ=0, formula
(12) accepted way of doing sth (13) be can simplify:
Iθ=IDN·(cosi+cosh) (13)
According to formula (13), the solar radiation intensity of in ship's navigation different moments, different location can be calculated, so ItJust
It can be obtained by formula (14):
Therefore, the power p that solar panel generates in the unit timepv(t) it can be obtained by formula (15):
ppv(t)=It(t)×A×jpv (15)
In formula (15), the square measure of solar panel is m2, the area of A expression solar panel, jpvIndicate solar energy
The electric energy conversion ratio of solar panel, the general power P that the photovoltaic generating module of system is generated in t momentpv(t) it can be obtained by formula (16)
It arrives:
Ppv(t)=Npv×ppv(t) (16)
In formula (16), NpvIt is the sum of solar panel in system, shown in value range such as formula (17):
0≤Npv≤Nmax_pv (17)
Wherein Nmax_pvIndicate NpvMaximum value.
5. the multiple-objection optimization configuration method of marine diesel energy mix system configuration according to claim 1, special
Sign is that the S2 includes:
Artificial bee colony algorithm is divided into four-stage, i.e. initial phase, EB optimizing phase, OB optimizing phase and SB optimizing phase:
In initial phase, program needs random generation NPThe initial value of a solution to be optimized, NPIndicate the size of population, NPIt is bigger
The food source that it can find is also more, and the number of food source is exactly the number of solution x (l, d) to be optimized, and the value of x (l, d) can be by
Formula (39) obtains:
X (l, d)=xmin(d)+rand×[xmax(d)-xmin(d)] (39)
In formula (39), xmax(d) and xminIt (d) is its maximum value and minimum value respectively, rand indicates the random number in 0~1, and d is
Dimension, l are the serial numbers of solution to be optimized,
In EB optimizing phase and OB optimizing phase, more new explanation z (l, d) can be obtained by formula (40):
Z (l, d)=x (l, d)+yld×[x(l,d)-x(r,d)] (40)
Y in formula (40)ldIndicate -1~1 random number, r is 1~NPBetween a random integers and be not equal to l, due to x (l,
D) there are maximum value and minimum value, so z (l, d) calculates the value range that may exceed x (l, d), if it happens
Such case, it is necessary to this more new explanation is abandoned, obtains a new explanation as substitute using formula (39),
Probability p used in the OB optimizing phaselIt is calculated such as formula (41):
In formula (41), F (l) is the functional value of the corresponding cost and availability optimization aim of optimization solution, the cost and available
Property optimization aim includes:
The cost and availability optimization aimWherein, λ1And λ2
Indicate CTIt is preset value, Max (C with importance of the T in system optimizationT) and Min (CT) respectively indicate cost maximum value and
Minimum value, Max (T) and Min (T) respectively indicate the maximum value and minimum value of availability,
The work of OB optimizing phase is assessed the optimization solution that the EB optimizing phase obtains, according to the corresponding probability of nectar quantity
Food source is selected, in the SB optimizing phase, as the number k that it is not updatedcountGreater than threshold value klimitWhen, then, just utilize formula
(38) it is randomly derived a new explanation to be compared with optimal value before, if new explanation is more preferable, just instead of current optimal solution,
If algorithm meets the condition of convergence, optimal solution is exported, otherwise enters iterative calculation next time.
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