CN107274085A - A kind of optimum management method of the energy storage device of double electric type ships - Google Patents
A kind of optimum management method of the energy storage device of double electric type ships Download PDFInfo
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Abstract
The present invention provides a kind of optimum management method of the energy storage device of double electric type ships, and the power and energy requirement for obtaining ship are circulated according to the exemplary operation of target ship；Collect each manufacturer's ferric phosphate lithium cell, ultracapacitor, the specifications parameter of propulsion electric machine；Using ship energy efficiency index and energy storage device price as target, the electric propulsion system model of target ship whole ship is built；Multiple-objection optimization calculating is carried out using genetic algorithm, optimal energy storage device selecting type scheme is obtained；Energy requirement forecast model is set up to the energy storage device after type selecting, the Rolling optimal strategy on limited period of time is set up；Fuzzy controller is set up, the control rule base of energy management system for ship population fuzzy controller is set up, theoretical using intelligent group, i.e., particle group optimizing method is optimized to fuzzy controller.The present invention improves the economic performance of ship and extends the service life of battery by reasonably selecting the capacity of each energy storage device and the flow direction for controlling energy of intelligence.
Description
Technical field
The present invention relates to pure electric ship energy storage device field, and in particular to a kind of energy storage device of double electric type ships it is excellent
Change management method.
Background technology
In recent years, such as super capacitor, the battery development of all kinds of energy storage devices is swift and violent, and performance, which has, to be substantially improved.It is applied
The existing CROSS REFERENCE of ship.All kinds of energy storage devices from the difference of principle make its energy storage characteristic different because of its structure, such as super capacitor
Electric discharge is fast, but power density is low；Ferric phosphate lithium cell power density is high, but it is limited in one's ability to bear discharge current, special according to them
Property learn from other's strong points to offset one's weaknesses, constitute energy composite energy storage device, i.e., double electricity types can preferably tackle the power demand of ship,
The life-span of energy storage device can be extended.But need to the two preferable energy management of progress and optimization, how reasonably using storage
Energy device, this safeguards and all played an important role at utmost playing energy storage device characteristic and extending its service life, reduction.
The content of the invention
The technical problem to be solved in the present invention is：A kind of optimum management method of the energy storage device of double electric type ships is provided,
Energy storage device can be reasonably used, extends energy storage device service life.
The present invention is that the technical scheme that solution above-mentioned technical problem is taken is：A kind of energy storage device of double electric type ships
Optimum management method, it is characterised in that：It includes：
Step one：Energy storage device type selecting：
Data acquisition：The power and energy requirement for obtaining ship are circulated according to the exemplary operation of target ship；Collect each factory
Business's ferric phosphate lithium cell, ultracapacitor, the specifications parameter of propulsion electric machine, are made traction table, and mesh is obtained from the traction table
Mark the power-equipment type selecting of ship；
Model is set up：Using ship energy efficiency index and energy storage device price as target, the electric power for building target ship whole ship is pushed away
Enter system model；The whole ship electric propulsion model includes conversion oil consumption model, motor model and battery energy management model；
Lectotype and calculation：Described power and energy requirement are imported in electric propulsion system model, entered using genetic algorithm
Row multiple-objection optimization is calculated, and is obtained the actual specific equipment in one group of Pareto optimal solution, correspondence traction table, is obtained optimal storage
Can lectotype selection scheme；
Step 2: energy management：
To the energy storage device after type selecting, set up energy requirement forecast model, according to the aeronautical data of ship history and
The real time information that intelligent transportation system is provided, predicts the power demand of ship subsequent period；Set up the rolling on limited period of time
Optimisation strategy, to next sampling instant, according to the actual power demand of ship, the prediction to the model of ship is modified, so
Carry out new Optimization Prediction again afterwards；
Fuzzy controller is set up, the state-of-charge of energy storage device, power demand, prediction power demand are carried out at obfuscation
Reason, forms input fuzzy variable, and each input fuzzy variable then is sent into fuzzy controller；Set up ship energy management system
The control rule base of system population fuzzy controller, theoretical using intelligent group, i.e., particle group optimizing method is to fuzzy controller
Optimize.
As stated above, described power and energy requirement are long according to the work ship at present with target ship same type
Time service counts the data of one group drawn and time correlation.
As stated above, described ferric phosphate lithium cell, the specifications parameter of ultracapacitor include battery capacity, battery list
Body weight, battery cell price and charging and discharging curve；It is special that the specifications parameter of described propulsion electric machine includes total erection weight, efficiency
Linearity curve.
As stated above, the calculation procedure of described genetic algorithm includes：
1) two variable Xs 1, X2 are defined, real coding is carried out to the two variables；
2) population scale is set, initial population is produced according to constraints；
3) calculating of quick non-dominated ranking and virtual crowding distance is carried out to contemporary population；Wherein, quick non-dominant
Sequence is carried out according to the ship Energy design index of each type selecting and energy storage device total price the two target function values, and
Virtual crowding distance is drawn according to range information of the individual vector in the variable space；
4) optimization aim for determining Energy design index E EDI, the energy storage device total price Price of ship to calculate, it is counted
Be expressed as follows：
Price=Mb*n1+Ms*n2
In formula：S is the conversion factor of carbon dioxide, and P is the power of power system, and f is correction factor, fiTo consider ship
The dimensionless correction factor limited by technology or regulation requirement design maximum Loading conditions, Capacity is that ship is total
Tonnage；VrefFor under design maximum Loading conditions, in the case that defined shaft power is promoted, in calmness with no wind, no waves
Ship speed under sea situation；fwTo consider the dimensionless factor of the influence of wave height, wave frequency and wind speed to ship speed；MbFor battery
The price of monomer, MsFor the price of electric capacity monomer, n1For the number of battery cell, n2For the number of electric capacity monomer；
5) genetic manipulation, including selection, intersection and variation are carried out；Select probability, recombination fraction and aberration rate are set, son is obtained
Population；
6) elite retention strategy is carried out, i.e., is merged parent population with sub- population, and carries out being based on quick non-dominant
Sequence and the selection of virtual crowding distance, then parameter parent population of future generation；Iterations adds 1, is back to 3), until repeatedly
Untill generation number reaches the maximum of setting.
As stated above, in described battery energy management model, mode of operation is divided as follows：
(1) when power demand is more than upper threshold values, and target vessel operation is in starting, anxious acceleration or high capacity, super electricity
Container group and ferric phosphate lithium cell group cooperation are electric machine with energy；
(2) when power demand is between threshold values up and down, when target vessel operation is in acceleration mode, ultracapacitor group is excellent
First high current repid discharge provides acceleration energy for propulsion electric machine；
(3) when power demand is less than lower threshold values, when target ship works in steady steaming state, ferric phosphate lithium cell group is excellent
First work and provide energy for propulsion electric machine.
As stated above, described battery energy management model is according to the charged of the power demand combination battery of target ship
State controls the discharge current of energy storage device.
Beneficial effects of the present invention are：Start with terms of the type selecting of energy storage device and energy management two, ensureing ship
On the premise of power performance, by reasonably selecting the flow direction of the capacity of each energy storage device and the control energy of intelligence, improve
The economic performance of ship and the service life for extending battery.
Brief description of the drawings
Fig. 1 is the method flow diagram of one embodiment of the invention.
Embodiment
With reference to instantiation and accompanying drawing, the present invention will be further described.
The present invention provides a kind of optimum management method of the energy storage device of double electric type ships, as shown in figure 1, it includes：
Step one：Energy storage device type selecting：
Data acquisition：The power and energy requirement for obtaining ship are circulated according to the exemplary operation of target ship；Collect each factory
Business's ferric phosphate lithium cell, ultracapacitor, the specifications parameter of propulsion electric machine, are made traction table, and mesh is obtained from the traction table
Mark the power-equipment type selecting of ship.Described power and energy requirement is according to work ship at present with target ship same type
Work long hours and count the data of one group drawn and time correlation.Described ferric phosphate lithium cell, the specification of ultracapacitor
Parameter includes battery capacity, battery cell weight, battery cell price and charging and discharging curve；The specification ginseng of described propulsion electric machine
Number includes total erection weight, efficiency characteristic.
Model is set up：Using ship energy efficiency index and energy storage device price as target, the electric power for building target ship whole ship is pushed away
Enter system model；The whole ship electric propulsion model includes conversion oil consumption model, motor model and battery energy management model.
Battery energy management model controls energy storage device according to the state-of-charge of the power demand combination battery of target ship
Discharge current.In described battery energy management model, mode of operation is divided as follows：
(1) when power demand is more than upper threshold values, and target vessel operation is in starting, anxious acceleration or high capacity, super electricity
Container group and ferric phosphate lithium cell group cooperation are electric machine with energy；
(2) when power demand is between threshold values up and down, when target vessel operation is in acceleration mode, ultracapacitor group is excellent
First high current repid discharge provides acceleration energy for propulsion electric machine；
(3) when power demand is less than lower threshold values, when target ship works in steady steaming state, ferric phosphate lithium cell group is excellent
First work and provide energy for propulsion electric machine.
Lectotype and calculation：Described power and energy requirement are imported in electric propulsion system model, entered using genetic algorithm
Row multiple-objection optimization is calculated, and is obtained the actual specific equipment in one group of Pareto optimal solution, correspondence traction table, is obtained optimal storage
Can lectotype selection scheme.
The calculation procedure of described genetic algorithm includes：
1) two variable Xs 1, X2 are defined, real coding is carried out to the two variables.
2) population scale is set, initial population is produced according to constraints.
3) calculating of quick non-dominated ranking and virtual crowding distance is carried out to contemporary population；Wherein, quick non-dominant
Sequence is carried out according to the ship Energy design index of each type selecting and energy storage device total price the two target function values, and
Virtual crowding distance is drawn according to range information of the individual vector in the variable space.
4) optimization aim for determining Energy design index E EDI, the energy storage device total price Price of ship to calculate, it is counted
Be expressed as follows：
Price=Mb*n1+Ms*n2
In formula：S is the conversion factor of carbon dioxide, and P is the power of power system, and f is correction factor, fiTo consider ship
The dimensionless correction factor limited by technology or regulation requirement design maximum Loading conditions, Capacity is that ship is total
Tonnage；VrefFor under design maximum Loading conditions, in the case that defined shaft power is promoted, in calmness with no wind, no waves
Ship speed under sea situation；fwTo consider the dimensionless factor of the influence of wave height, wave frequency and wind speed to ship speed；MbFor battery
The price of monomer, MsFor the price of electric capacity monomer, n1For the number of battery cell, n2For the number of electric capacity monomer.
5) genetic manipulation, including selection, intersection and variation are carried out；Select probability, recombination fraction and aberration rate are set, son is obtained
Population；Genetic manipulation is the core link that NSGA-II carries out optimizing iteration, and selection operation therein is based on 3).
6) elite retention strategy is carried out, i.e., is merged parent population with sub- population, and carries out being based on quick non-dominant
Sequence and the selection of virtual crowding distance, then parameter parent population of future generation；Iterations adds 1, is back to 3), until repeatedly
Untill generation number reaches the maximum of setting.
Step 2: energy management：
To the energy storage device after type selecting, set up energy requirement forecast model, according to the aeronautical data of ship history and
The real time information that intelligent transportation system is provided, predicts the power demand of ship subsequent period；Set up the rolling on limited period of time
Optimisation strategy, it is to avoid model mismatch during because of complex working condition, time-varying, interference and the uncertainty produced, to next sampling instant, root
According to the actual power demand of ship, the prediction to the model of ship is modified, and new Optimization Prediction is then carried out again.
Fuzzy controller is set up, the state-of-charge of energy storage device, power demand, prediction power demand are carried out at obfuscation
Reason, forms input fuzzy variable, and each input fuzzy variable then is sent into fuzzy controller；Set up ship energy management system
The control rule base of system population fuzzy controller, theoretical using intelligent group, i.e., particle group optimizing method is to fuzzy controller
Optimize.
The present invention relates to the energy storage device of " double electric types " the pure electric ship of a kind of " ferric phosphate lithium cell+super capacitor "
Optimum management method, on the premise of the purpose of optimization is the power performance to ensure ship, by reasonably selecting each energy storage
The flow direction of the capacity of device and the control energy of intelligence, improves the economic performance of ship and extends the service life of battery.
Energy storage device type selecting comprises the following steps：According to the typical working cycles of target ship, obtain ship power and
Energy requirement；Build the electric propulsion system model of target ship；Led according to the power requirement data of the reference ship collected
Enter in model, using based on the algorithm control strategies of NSGA- II in multi-objective genetic algorithm, with EEDI (the ship efficiencies of ship
Design index) and price be optimization aim, carry out genetic algorithm calculating, obtain one group of Pareto optimal solution, correspondence reality is specific
Equipment, obtains suitable selecting type scheme.
Using the energy management fuzzy control strategy based on model prediction, composite power source is divided into 3 kinds of mode of operations, respectively
For：Ultracapacitor group works independently pattern, ultracapacitor group and ferric phosphate lithium cell group cooperation pattern, LiFePO4
Battery works independently pattern.According to the power demand under different operating modes, the state-of-charge of energy storage device and real-time operation conditions,
The real time information provided according to history aeronautical data, mathematical modeling and intelligent transportation system, predicts the power of ship subsequent period
Demand, on this basis using a kind of fuzzy controller based on particle swarm optimization algorithm, the rationally work of control composite power source
Pattern, realizes the energy distribution of energy storage device and reclaims, each energy storage device is played its advantage, improve the economy of ship
Performance, extends the service life of battery.
Above example is merely to illustrate the design philosophy and feature of the present invention, and its object is to make technology in the art
Personnel can understand present disclosure and implement according to this, and protection scope of the present invention is not limited to above-described embodiment.So, it is all according to
The equivalent variations made according to disclosed principle, mentality of designing or modification, within protection scope of the present invention.
Claims (6)
1. a kind of optimum management method of the energy storage device of double electric type ships, it is characterised in that：It includes：
Step one：Energy storage device type selecting：
Data acquisition：The power and energy requirement for obtaining ship are circulated according to the exemplary operation of target ship；Collect each manufacturer's phosphorus
Sour lithium iron battery, ultracapacitor, the specifications parameter of propulsion electric machine, are made traction table, and object ship is obtained from the traction table
The power-equipment type selecting of oceangoing ship；
Model is set up：Using ship energy efficiency index and energy storage device price as target, the electric propulsion system of target ship whole ship is built
System model；The whole ship electric propulsion model includes conversion oil consumption model, motor model and battery energy management model；
Lectotype and calculation：Described power and energy requirement are imported in electric propulsion system model, carried out using genetic algorithm many
Objective optimization is calculated, and is obtained the actual specific equipment in one group of Pareto optimal solution, correspondence traction table, is obtained optimal energy storage and set
Standby selecting type scheme；
Step 2: energy management：
To the energy storage device after type selecting, energy requirement forecast model is set up, according to the aeronautical data and intelligence of ship history
The real time information that traffic system is provided, predicts the power demand of ship subsequent period；Set up the rolling optimization on limited period of time
Strategy, to next sampling instant, according to the actual power demand of ship, the prediction to the model of ship is modified, Ran Houzai
Carry out new Optimization Prediction；
Fuzzy controller is set up, the state-of-charge of energy storage device, power demand, prediction power demand are subjected to Fuzzy processing,
Input fuzzy variable is formed, each input fuzzy variable is then sent to fuzzy controller；Set up energy management system for ship
The control rule base of population fuzzy controller, theoretical using intelligent group, i.e., particle group optimizing method enters to fuzzy controller
Row optimization.
2. the optimum management method of the energy storage device of double electric type ships according to claim 1, it is characterised in that：Described
Power and energy requirement be drawn according to the statistics that works long hours at present with the work ship of target ship same type one group and
The data of time correlation.
3. the optimum management method of the energy storage device of double electric type ships according to claim 1, it is characterised in that：Described
Ferric phosphate lithium cell, the specifications parameter of ultracapacitor include battery capacity, battery cell weight, battery cell price and charge and discharge
Electric curve；The specifications parameter of described propulsion electric machine includes total erection weight, efficiency characteristic.
4. the optimum management method of the energy storage device of double electric type ships according to claim 1, it is characterised in that：Described
The calculation procedure of genetic algorithm includes：
1) two variable Xs 1, X2 are defined, real coding is carried out to the two variables；
2) population scale is set, initial population is produced according to constraints；
3) calculating of quick non-dominated ranking and virtual crowding distance is carried out to contemporary population；Wherein, quick non-dominated ranking
It is to be carried out according to the ship Energy design index of each type selecting and energy storage device total price the two target function values, and it is virtual
Crowding distance is drawn according to range information of the individual vector in the variable space；
4) it is the optimization aim calculated, its mathematical table to determine Energy design index E EDI, the energy storage device total price Price of ship
Up to as follows：
<mrow>
<mi>E</mi>
<mi>E</mi>
<mi>D</mi>
<mi>I</mi>
<mo>=</mo>
<mfrac>
<mrow>
<mi>S</mi>
<mi>P</mi>
<mi>f</mi>
</mrow>
<mrow>
<msub>
<mi>f</mi>
<mi>i</mi>
</msub>
<msub>
<mi>CapacityV</mi>
<mrow>
<mi>r</mi>
<mi>e</mi>
<mi>f</mi>
</mrow>
</msub>
<msub>
<mi>f</mi>
<mi>w</mi>
</msub>
</mrow>
</mfrac>
<mo>,</mo>
</mrow>
Price=Mb*n1+Ms*n2
In formula：S is the conversion factor of carbon dioxide, and P is the power of power system, and f is correction factor, fiTo consider ship because of skill
The dimensionless correction factor that art or regulation are required and limited design maximum Loading conditions, Capacity is ship gross ton
Number；VrefFor under design maximum Loading conditions, in the case that defined shaft power is promoted, in calmness sea with no wind, no waves
Ship speed under condition；fwTo consider the dimensionless factor of the influence of wave height, wave frequency and wind speed to ship speed；MbFor battery list
The price of body, MsFor the price of electric capacity monomer, n1For the number of battery cell, n2For the number of electric capacity monomer；
5) genetic manipulation, including selection, intersection and variation are carried out；Select probability, recombination fraction and aberration rate are set, sub- kind is obtained
Group；
6) elite retention strategy is carried out, i.e., is merged parent population with sub- population, and carries out being based on quick non-dominated ranking
With the selection of virtual crowding distance, then parameter parent population of future generation；Iterations adds 1, is back to 3), until iteration time
Untill number reaches the maximum of setting.
5. the optimum management method of the energy storage device of double electric type ships according to claim 1, it is characterised in that：Described
In battery energy management model, mode of operation is divided as follows：
(1) when power demand is more than upper threshold values, and target vessel operation is in starting, anxious acceleration or high capacity, ultracapacitor
Group and ferric phosphate lithium cell group cooperation are electric machine with energy；
(2) when power demand is between threshold values up and down, when target vessel operation is in acceleration mode, ultracapacitor group is preferentially big
Electric current repid discharge provides acceleration energy for propulsion electric machine；
(3) when power demand is less than lower threshold values, when target ship works in steady steaming state, the preferential work of ferric phosphate lithium cell group
Energy is provided as propulsion electric machine.
6. the optimum management method of the energy storage device of double electric type ships according to claim 1, it is characterised in that：Described
Battery energy management model controls the electric discharge electricity of energy storage device according to the state-of-charge of the power demand combination battery of target ship
Stream.
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Cited By (9)
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| CN108382556A (en) * | 2018-02-23 | 2018-08-10 | 上海海事大学 | A kind of hybrid power ship battery pack equilibrium management method based on fuzzy control theory |
| CN110147583A (en) * | 2019-04-23 | 2019-08-20 | 常伟 | It is a kind of that the integrated application analysis method of energy-storage system is carried out by chemical energy storage battery |
| CN111559485A (en) * | 2019-02-13 | 2020-08-21 | 通用汽车环球科技运作有限责任公司 | Overshoot method for fast planing of ship |
| CN111859535A (en) * | 2020-06-20 | 2020-10-30 | 武汉理工大学 | Polar cruise ship fin stabilizer selection method and device based on AHP-entropy weight method |
| CN112217190A (en) * | 2019-07-10 | 2021-01-12 | 株洲中车时代电气股份有限公司 | Hybrid power system for ship and control method thereof |
| CN112909977A (en) * | 2021-03-25 | 2021-06-04 | 湖北省电力勘测设计院有限公司 | Real-time economic dispatching method for port power distribution network with participation of electric ship |
| CN113255250A (en) * | 2021-07-02 | 2021-08-13 | 湖北东湖实验室 | Accurate design method for battery capacity of battery-powered ship |
| CN116362296A (en) * | 2022-10-31 | 2023-06-30 | 无锡赛思亿电气科技有限公司 | Ship energy efficiency information collection management system and energy consumption state analysis method based on same |
| CN117879128A (en) * | 2024-03-13 | 2024-04-12 | 西北工业大学宁波研究院 | Energy management system and management strategy of large container ship composite energy system |
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| CN110147583A (en) * | 2019-04-23 | 2019-08-20 | 常伟 | It is a kind of that the integrated application analysis method of energy-storage system is carried out by chemical energy storage battery |
| CN112217190A (en) * | 2019-07-10 | 2021-01-12 | 株洲中车时代电气股份有限公司 | Hybrid power system for ship and control method thereof |
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| CN113255250B (en) * | 2021-07-02 | 2021-09-17 | 湖北东湖实验室 | Accurate design method for battery capacity of battery-powered ship |
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| CN116362296B (en) * | 2022-10-31 | 2024-03-01 | 无锡赛思亿电气科技有限公司 | Ship energy efficiency information collection management system and energy consumption state analysis method based on same |
| CN117879128A (en) * | 2024-03-13 | 2024-04-12 | 西北工业大学宁波研究院 | Energy management system and management strategy of large container ship composite energy system |
| CN117879128B (en) * | 2024-03-13 | 2024-05-10 | 西北工业大学宁波研究院 | Energy management system and management strategy of large container ship composite energy system |
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