CN104598687A - Optimized construction method for photovoltaic storage battery power supply system of small buoy power source for water quality monitoring - Google Patents
Optimized construction method for photovoltaic storage battery power supply system of small buoy power source for water quality monitoring Download PDFInfo
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Abstract
The invention discloses an optimized construction method for a photovoltaic storage battery power supply system of a small buoy power source for water quality monitoring. The optimum construction method comprises the following steps: calculating the power consumption of a buoy system; modeling an optimized objective function of the small buoy system; determining the maximum number of continuous rainy days of the small buoy system; establishing the constraint conditions of the small buoy system; configuring parameter optimization and sensitivity analysis. The optimized objective function is established by merging the environment and weather conditions of an applied place of the small buoy for water quality monitoring and mutual influences of the factors such as a buoy carrying instrument, instrument power consumption and running time and combining the restrictive conditions of the area, size, weight and the like of a buoy body. In a feasible solution area restricted by the restrictive conditions, low investment cost and small power-failure hours are sought, and in combination with the historical data information of the environment and weather of the applied place, the method obtains an optimized configuration scheme of a photovoltaic storage battery hybrid power supply system meeting the weather factor requirement of practical conditions of the applied place of the small buoy and also meeting the requirement of system reliability.
Description
Technical field
The present invention relates to a kind of optimization construction method of photovoltaic storage battery electric power system of water quality monitoring Miniature Buoy power source of bubbling through the water column.Be specially a kind of based on the constraint of buoy body and the photovoltaic of local meteorologic factor constraint, the optimum capacity collocation method of accumulator quantity optimization algorithm.
Background technology
Water resource, as a kind of basic natural resources, is the Source of life that the mankind depend on for existence.For realizing the sustainable use of water resource, supervision and analysis carries out to water quality very necessary.The water quality monitoring Miniature Buoy of bubbling through the water column can realize gathering the relevant data of real-time water-quality guideline, process, storage, each index of transmission to specifying receiver by carrying necessary chemical analysis instrument and various water quality sensor thereon, can realize in addition following the tracks of the position of buoy, have fault can the additional function such as automatic alarm in time.For offshore type water quality monitoring Miniature Buoy system, adopt photovoltaic storage battery mixed power supply system, absorb by solar energy photovoltaic panel the daylight projected above the unscreened water surface and be converted into instrument, the instrument power supply that electric energy can be lift-launch easily, on the other hand by unnecessary electric energy storage in accumulator, the night of penetrating for all the time illumination width and overcast and rainy equipment electricity consumption use.This power supply mode can not only solve the electrical problem of water quality monitoring Miniature Buoy effectively, can reduce the consumption of fossil resource simultaneously, achieve the green of water quality monitoring, economy and environmental protection object.
But existing water quality monitoring Miniature Buoy power source of bubbling through the water column---photovoltaic storage battery power supply region method comes with some shortcomings:
First, the design in current Miniature Buoy system medium power source adopts the mode of modular parallel combination, generally can be wanted the power consumption of carrying equipment by estimation, determine configuration of modular battery pack 1-2 cover.Although this parallel extended mode improves the power supply reliability of system, add the volume of power source part, weight and direct investment cost.
Secondly, in recent years based on the most attention to water quality monitoring, the different monitoring sensor of Multiple Type and signal transmission apparatus need to carry in Miniature Buoy.Because in application, the power consumption variation range of equipment is wide in range, for real needs, design water quality monitoring Miniature Buoy power source---the case of photovoltaic storage battery electric power system increases gradually.This mode needs the power consumption data first calculating the concrete equipment carried in detail, clearly to guarantee the number of days of system normal power supply under continuous condition without sunshine, then adopt the power of photovoltaic panel, the ampere-hour number of accumulator that the empirical method computing system of photovoltaic storage battery power supply region should configure.But, mainly can carry out for ground fixed in position photovoltaic storage battery electric power system for the photovoltaic storage battery electric power system Empirical Design used for reference at present.Owing to not considering that in application, photovoltaic storage battery settles the constraint condition such as volume, weight related to, the photovoltaic storage battery system designed often is caused to install less than realizing on selected Miniature Buoy body in practical application, need, again to ordering volume, area, Miniature Buoy body that counterweight is enough, to add indirect investment cost and the time cost of water quality monitoring Miniature Buoy system.
In addition, owing to being subject to the impact such as environment, weather in Practical Project, water quality monitoring Miniature Buoy power source---be subject to randomness and the impact of cyclical variation factor in photovoltaic storage battery electric power system operational process.At present to water quality monitoring Miniature Buoy power source---not consider when photovoltaic storage battery electric power system designs between designed performance parameter and with the reciprocal effect of other relation factors, then designed photovoltaic storage battery electric power system fails to realize under the prerequisite meeting system operation reliability, reduce system investments construction cost, the object that science builds.
Therefore, for overcoming the above problems, need the water quality monitoring Miniature Buoy power source that a kind of science is provided---the optimization construction method of photovoltaic storage battery electric power system.
Summary of the invention
The object of the invention is the inadequate science of construction method, the not accurate enough existing drawback of the photovoltaic storage battery electric power system in order to solve existing water quality monitoring Miniature Buoy power source.Carry the reciprocal effect of the factors such as instrument, instrument power consumption, working time by the answer environment of land used, meteorological condition and the buoy that merge water quality monitoring Miniature Buoy, the restrictive condition such as area, volume, weight in conjunction with buoy body sets up water quality monitoring Miniature Buoy power source---the optimization object function of photovoltaic storage battery electric power system.In the area of feasible solution that constraint condition limits, seek that cost of investment is low, no electricity hours is few, and the environment on connected applications ground and meteorological historical data information, both met the weather conditions requirement that Miniature Buoy answers land used actual conditions, met again the photovoltaic storage battery mixed power supply system configuration scheme that system reliability requires.
The invention provides a kind of optimization construction method of photovoltaic storage battery electric power system of water quality monitoring Miniature Buoy power source, mainly comprise following six steps:
Step one, Miniature Buoy system power dissipation calculate;
Calculate the operation power consumption and day operation hourage that need to carry the water quality monitoring equipment in buoy body, form the per day energy consumption of Miniature Buoy system, these water quality monitoring equipment can be regarded as the load of Miniature Buoy power source part, therefore be called load equipment, then then just can calculate the average power consumption value of load equipment.
The optimization object function modeling of step 2, Miniature Buoy system;
Determine related parameter values and the cost of the photovoltaic generation, batteries to store energy, buoy body etc. related in Miniature Buoy system.Be that target sets up Miniature Buoy power source with cost minimization---the optimization object function of photovoltaic storage battery electric power system.
Step 3, based on the maximum continuous overcast and rainy days of meteorologic factor determination Miniature Buoy system;
Output based on photovoltaic storage battery electric power system is subject to the impact of the meteorologic factors such as sunshine, and photovoltaic generation has obvious discontinuity and undulatory property with the change of environment in time.According to than the weather information being easier to obtain, as intensity of illumination, temperature and relative humidity, statistical study is carried out to the influence factor of photovoltaic storage battery electric power system generated energy.According to influence factor, the continuous wet weather that statistical separates out the most severe month in recent years causes the number of days do not generated electricity, for reasonably determining to answer land used buoy the longest operating overcast and rainy days to provide the decision-making foundation of science.
Step 4, Miniature Buoy system constraints are set up;
Based on the buoy body volume, area, the buoyancy that relate in application, and the condition such as the power of power section, energy sets up water quality monitoring Miniature Buoy power source---and photovoltaic storage battery electric power system runs the constraint condition that should meet.
Step 5, configuration parameter optimization;
Adopting linear integer programming algorithm, constantly search for, calculate and build water quality monitoring Miniature Buoy power source---the cost of photovoltaic storage battery electric power system, finally exports optimum solution, obtains Miniature Buoy system photovoltaic storage battery allocation optimum parameter x
j=[x
1, x
2], j=1,2 ... n, n are Miniature Buoy system selectable buoy body number, x
1for correspondence optimization select buoy body after the number of accumulator determined, x
2it is then the number of the corresponding appointment wattage photovoltaic panel determined.
Step 6, sensitivity analysis;
When utilizing sensitivity analysis to investigate the change of continuous rainy weather, water quality monitoring Miniature Buoy system can safeguards system power section not power-off, the continual and steady time span fluctuation range run.
The invention has the advantages that:
1. the application demand of connected applications buoy carrying equipment power consumption, buoy body cost and restrictive condition design photovoltaic storage battery electric power system, aim at the object that global optimization reduces the overall cost of System's composition, rational objective function is proposed, to realize the optimization structure that photovoltaic storage battery electric power system is formed cost/generating capacity;
2. in conjunction with the on-site meteorological condition of buoy installation and operation, increase statistical regression algorithm, overcast and rainy continuously in the 3-5 come into operation to Miniature Buoy system carries out statistical study, science determines the continuous overcast and rainy days of local maximum possible, for the abundance of photovoltaic storage battery electric power system, reliable, economic power supply provide theory support;
3., in the parameter of selected buoy body, after specifying the constraint condition of Miniature Buoy system, adopt integer programming algorithm in area of feasible solution, seek the photovoltaic storage battery electric power system optimum solution meeting the constraint condition such as volume, buoyancy; Then by sensitivity analysis, affect fluctuation range on the operation stability of designed Miniature Buoy system when investigating meteorological condition change, during for follow-up weather conditions variation, system cloud gray model decision-making provides foundation.
Accompanying drawing explanation
Fig. 1 is the process flow diagram based on photovoltaic storage battery Optimal Capacity method under buoy body constraint condition provided by the invention;
Fig. 2 is the process flow diagram based on the maximum continuous overcast and rainy days of meteorologic factor determination Miniature Buoy system in the present invention;
Fig. 3 is A ground 1-2 month solar radiation value, temperature, relative humidity numerical value in embodiment;
Fig. 4 be in embodiment A ground 1-2 month per day photovoltaic power generation quantity and continuously without generated energy number of days;
Fig. 5 is iterative integer optimized algorithm process flow diagram.
Embodiment
Below in conjunction with drawings and Examples, the present invention is described in detail.
The invention provides a kind of optimization construction method of photovoltaic storage battery electric power system of water quality monitoring Miniature Buoy power source, flow process as shown in Figure 1, specifically comprises the steps:
Step one, Miniature Buoy system power dissipation calculate;
The present invention is mainly for the Miniature Buoy system for water quality monitoring in lake, river, its power supply adopts photovoltaic storage battery composition, consider that photovoltaic generation is subject to the inside even from weather such as sunshine larger, thus have employed the energy resource supply instability that accumulator supplements photovoltaic system, meet the real time power consumption demand that photovoltaic system runs.By photovoltaic system generating supply electric loading when sunlight is fine, charge in batteries; Night and overcast and rainy time by storage battery power supply to load, meet the sample and transform requirement of Monitoring Data.Therefore, the power consumption of Miniature Buoy system, energy requirements are the starting points of subsequent design.Should by calculating the operation power consumption and day operation hourage that need to carry the water quality monitoring equipment (load equipment) in buoy body, form the per day energy consumption of Miniature Buoy system, just obtain the per day power consumption of load equipment divided by 24 hours, thus determine load equipment power and energy situation.The optimization object function modeling of step 2, Miniature Buoy system;
The cost of the photovoltaic storage battery electric power system of water quality monitoring Miniature Buoy system relates generally to following components:
A. photovoltaic panel, by watt accounting price during purchase.
B. the accumulator within system serviceable life, presses watt-hour accounting price during purchase.
The series small buoy body cost of the producer different model of C. supplying, general cost increases gradually along with the increase of Miniature Buoy bulk volume, its surface area, buoyancy.
D. the expense such as other load voltages matched power transducer, photovoltaic charge controller and installation cost, compared with the cost of this part expense and Miniature Buoy body and photovoltaic storage battery power pack, portion is very little, can think substantially constant, consider by fixed investment.
First the optimum capacity configuration of the photovoltaic storage battery electric power system of water quality monitoring Miniature Buoy should will ensure that Miniature Buoy is in the 3-5 life cycle come into operation, and builds operating cost minimum.Therefore, by water quality monitoring Miniature Buoy power source---the construction cost function of photovoltaic storage battery electric power system regards the objective function of optimal design as.In order to reduce water quality monitoring Miniature Buoy power source---the cost of photovoltaic storage battery electric power system, needs to be optimized research to the composition of photovoltaic storage battery, and target function type (1) is the cost function f of Miniature Buoy photovoltaic storage battery electric power system.
min f＝V
j+C-ηC
-kT(1)
Wherein V
jrepresent the cost of j numbering Miniature Buoy body, price generally increases along with the increase of buoy bulk volume, and correspondingly the capacity of buoyage, buoyancy also increase; System dynamic source hardware initial investment cost C is constructed as follows, and supposes selected certain model accumulator single unit price P
b, solar cell (in 10 watts/sheet) unit price P
pas value coefficient, the accumulator quantity x of selected model
1with solar cell quantity x
2as decision variable, then C=P
bx
1+ P
px
2.Along with the increase of tenure of use, photovoltaic panel and service lifetime of accumulator constantly reduce, the cost value η C that photovoltaic storage battery system can be reused after removing
-kTrepresent, wherein 0 < η < 1, η is defined as arrangement detection loss factor during recycling, T is the Miniature Buoy system photovoltaic storage battery power source cycle of operation, generally count per year, k represents that power source part runs the length of service, and current k is taken as the integer of 3 to 5 usually.
Due to photovoltaic panel and the constantly progress of accumulator manufacturing technology, cost declines, then Miniature Buoy application expire after photovoltaic panel and accumulator little by the value again recycled, to simplify the analysis with design, objective function can be reduced to:
min f＝V
j+C (2)
Step 3, based on the maximum continuous overcast and rainy days of meteorologic factor determination Miniature Buoy system;
Consider that the output based on photovoltaic system is subject to the impact of sunshine and weather conditions, photovoltaic generation has obvious discontinuity and undulatory property with the change of environment in time.Selecting to be suitable for the RBF neural monitoring occasion in real time, according to than being easier to the weather information of acquisition as intensity of solar radiation, temperature and relative humidity, statistical study being carried out to the influence factor of photovoltaic system generated energy.
Utilize RBF neural to analyze the generated energy of following photovoltaic system, as shown in Figure 2, first need to confirm that Miniature Buoy answers the longitude and latitude of land used, collect the photovoltaic power generation quantity data that Miniature Buoy answers the meteorological number of the history of land used and correspondence, as the training sample of neural network, then by determining after training to build RBF neural, input weather data, export photovoltaic power generation quantity, just the nonlinear regression model (NLRM) of the mathematical relation represented between generated energy and weather information can be obtained, and then, maximum continuous overcast and rainy days in month is determined according to this condition of photovoltaic power generation quantity <0.By in the weather data input regression function in month minimum for the application ground photovoltaic power generation quantity by analyzing acquisition in application, the photovoltaic generation discharge curve in corresponding month can be obtained and determine corresponding maximum continuous overcast and rainy days.
The input x of RBF neural model can be chosen
pbe a tri-vector be made up of solar radiation value, temperature and relative humidity, namely
wherein x
1 pfor solar radiation value sequence, x
2 pfor temperature value sequence, x
3 pfor relative humidity value sequence; Exporting y is photovoltaic power generation quantity sequence.By calculating the generated energy in the most severe month of installing and answering land used, the number of days of prediction generating <0 is considered as because bad weather causes the maximum continuous overcast and rainy days that do not generate electricity.Like this, for reasonably determining, the decision-making foundation that buoy operating maximum continuous overcast and rainy days in ground provides science is installed.
Step 4, Miniature Buoy system constraints are set up;
Consider in the present invention that photovoltaic storage battery electric power system assembly is arranged on buoy body, corresponding volume, area, buoyancy restriction must be met.Thus, the cost of Miniature Buoy power source---photovoltaic storage battery electric power system is not only relevant with the factor such as power consumption, volume of monitoring instrument, and closely related with the parameter such as cost, volume, area, buoyancy of Miniature Buoy body.Set up Miniature Buoy power source---the constraint condition that the optimization of photovoltaic storage battery electric power system builds, the constraint condition of described photovoltaic storage battery electric power system mainly comprises following content:
1. volume constraint: getting single accumulator volume is V
b, battery pack is arranged in the Miniature Buoy shell of appointment model, if its volume upper limit is V
m.Then
V
b·x
1≤V
m(3)
2. area-constrained: in 10 watts/sheet, solar-electricity pool area is S
p, solar energy photovoltaic system is arranged in the Miniature Buoy system platform of appointment model, if its area upper limit is S
m.Then
S
p·x
2≤S
m(4)
3. qualitative restrain: getting single accumulator quality is m
b, in 10 watts/sheet, solar cell quality is m
pif the gross mass upper limit that carrying platform can support is m
m.Then
m
b·x
1+m
p·x
2≤m
m(5)
4. price constraints: getting every, accumulator unit price is P
b, solar cell is in 10 watts/sheet, and every sheet unit price is P
pif total initial investment upper limit of Miniature Buoy power section planning is P
m.Then
P
b·x
1+P
p·x
2≤P
m(6)
5. capacity-constrained: when not having light radiation continuously, the load supplying carried in Miniature Buoy comes from the electric energy stored by accumulator completely, supposes that single batteries to store energy value is E
b, the power consumption of load every day is E
f, do not have the number of days of light radiation to be d (traditional design method directly sets d as a certain numerical value in [7-15] scope) continuously, consider the short of electricity hourage LOLH of actual permission, can obtain:
For independently photovoltaic storage battery electric power system, load supplying is traced sth. to its source and is come from the electric energy that solar cell produces completely.Suppose operably every day solar irradiation, the effective directly power-on time of solar cell is made to be n hour, in this n hour, solar cell should provide all electricity consumptions of load, also to charge to accumulator, to ensure that accumulator stores in (24-n) hour of remainder electricity can meet the normal work of load, a certain amount of storage of electrical energy can also be remained in case of need, if this part energy for accumulator deposit is E simultaneously
0.If single solar cell generated energy hourly is E
p, the charge efficiency of solar cell to load and accumulator is η
1, accumulator is η to the power supplying efficiency of load
2, can obtain:
nE
p·p≥E
f·n/24·η
1+E
f·(24-n)/24·η
1·η
2+E
0/η
1(8)
6. nonnegativity Integer constrained characteristic
X
1>=0; x
2>=0 and be integer (9)
Step 5, configuration parameter optimization;
Because alternative Miniature Buoy body number is limited, by volume capacity of numbering sorts from small to large, the Miniature Buoy body that selected lowest number is corresponding in advance, determine corresponding constraint condition, then adopt linear integer programming algorithm, under calculation constraint condition, Miniature Buoy photovoltaic storage battery electric power system is formed, namely to clearly obtain under meeting Miniature Buoy system load equipment need for electricity condition, when construction cost represented by objective function is minimum, the accumulator quantity that should comprise in photovoltaic storage battery electric power system and photovoltaic panel quantity.If there is no feasible optimum solution, then show that buoy body capacity is too little, cause the accumulator of the necessity needed for the need for electricity for meeting load equipment and photovoltaic panel in buoy body owing to can not be placed on buoy body, namely without feasible optimum solution by the restriction of the condition such as volume, area.Therefore need again sequentially to select bigger Miniature Buoy body by number, correspondingly buoy body capacity increases, then available volume, area-constrained border increase, buoyancy increases, qualitative restrain border also increases, finally reach and relax constraint condition, progressively expand Search Range, to realize the object finding feasible optimum solution; If obtain feasible optimum solution, then export obtain water quality monitoring Miniature Buoy power source---photovoltaic storage battery electric power system distribute parameter x rationally
j=[x
1, x
2].
Described linear integer programming algorithm flow as shown in Figure 5, is specially: initialization, the objective function that input preceding step is set up and constraint condition; Determine that buoy body is numbered (from the most small size, searching for each numbering successively), determine that mathematical model parameter is optimized to solve; If find optimum solution just to export; Otherwise redefine buoy body numbering and mathematical model parameter is optimized and solves, until output optimum solution.
Step 6, sensitivity analysis;
Investigate the influence degree of fluctuation meeting to Miniature Buoy system run all right that continuous overcast and rainy days is possible, to continuous overcast and rainy employing sensitivity analysis, specify the interval range of Miniature Buoy system stable operation number of days and the interval range of continuous overcast and rainy days, for follow-up with party in request further collaborative suggestion theoretical foundation is provided.
Technical scheme of the present invention is further illustrated below by embodiment.
Embodiment one:
The optimum capacity collocation method of water quality monitoring Miniature Buoy photovoltaic storage battery is implemented as follows:
Step one, Miniature Buoy system power dissipation calculate
According to demand, the buoy designed by calculating should carry monitoring equipment power consumption and day energy consumption data.Concrete load electricity consumption situation is as shown in table 1:
Table 1 water quality monitoring Miniature Buoy carrying equipment electricity consumption information slip
In upper table " " represent corresponding device and be continuous collecting, do not relate to stand-by power consumption.
The photovoltaic cell adopted in the design's middle-size and small-size buoy medium power source and the correlation parameter of accumulator are as shown in table 2, table 3.Wherein photovoltaic cell needs the upper face being placed in circular buoy, and accumulator is placed in the inner cylindrical space of buoy body.Table 2 photovoltaic cell parameter list
Table 3 accumulator parameter table
The design selects the parameter of Miniature Buoy body as shown in table 4.
Table 4 Miniature Buoy body number parameter
| Numbering | Diameter (m) | Highly (m) | Buoyancy (kg) | Cost (ten thousand yuan) |
| 1 | 0.8 | 0.4 | 60 | 0.8 |
| 2 | 1.2 | 0.6 | 90 | 1.5 |
| 3 | 1.6 | 0.8 | 120 | 2.1 |
The optimization object function of step 2, Miniature Buoy system is built;
min f＝V
j+C
Wherein the numbering of j can according to table 4 from 1 to 3 traversal, and C function is according to the unit price value determination parameter of table 2, table 3, and obtaining concrete system goal function is
min C＝V
j+500x
1+80x
2
Step 3, determine maximum continuous overcast and rainy days analysis based on meteorological effect factor;
The source of the photovoltaic generating system energy as an alternative is promptly accepted.But sunshine is unstable, the output of photovoltaic generating system is subject to the impact of sunshine and weather conditions.Although consider that weather condition has in a short time comparatively significantly to fluctuate, but for areal, its Changes in weather in a long time can tend towards stability.First, determine that A is that Miniature Buoy answers land used, its longitude and latitude is: north latitude 27.58 degree; East longitude 120.67 degree; Then, the meteorological number of history on Miniature Buoy application A ground and the photovoltaic power generation quantity of correspondence is collected, as the training sample of neural network RBF; Train complete, the RBF neural of structure, just there is input weather data, export the function of photovoltaic power generation quantity; Finally, maximum continuous overcast and rainy days in month is determined according to this condition of photovoltaic power generation quantity <0.
Statistics A ground weather information for many years, show the annual 1-2 month temperature in A ground compared with low, rainy weather is many, photovoltaic power generation quantity state at a low ebb.Wherein, A ground 1-2 month in solar radiation value, temperature, relative humidity data see Fig. 3, bring into RBF neural model obtain 1, every day in February generated energy prediction curve see Fig. 4.By scheming easily to know that date that generated energy is less than 0 is considered as because bad weather causes date of not generating electricity.Be 10 days by adding up the longest number of days that can not generate electricity of solar cell in known photovoltaic power generation quantity minimum month, therefore can set buoy the installation of specifying to run maximum continuous overcast and rainy days be d=10 days.
Step 4, Miniature Buoy system constraints are set up;
(1) volume constraint (accumulator):
Wherein d
j, h
jfor diameter and the height of selected numbering Miniature Buoy body, j represents the numbering of Miniature Buoy body, is j=1 in the present embodiment, and 2,3.
(2) area-constrained (photovoltaic):
(3) qualitative restrain:
15x
1+ 1.3x
2≤ m
jwherein m
jfor the demarcation safetybuoyance of selected numbering Miniature Buoy body.
(4) price constraints: the total cost budget of photovoltaic cell and accumulator is 16000 yuan.Then
500·x
1+80·x
2≤16000
(5) capacity-constrained: do not have the number of days of light radiation (i.e. maximum continuous overcast and rainy days) to be 10 continuously, consider that the short of electricity hourage of actual permission is 6 hours,
2×200x
1≥146×9.75/0.8(Wh)
According to the photovoltaic cell on A ground, in the date of light radiation abundance, the duration of charging is in sun-drenched 4 hours noons effectively every day, and the charge efficiency of solar cell to load and accumulator is 0.9, and accumulator is 0.8 to the power supplying efficiency of load, can obtain:
-29.6x
1+40x
2≥196(Wh)
(6) nonnegativity Integer constrained characteristic, x
1>=0; x
2>=0 and be integer.
Step 5, configuration parameter optimization;
After determining each component parameters such as Miniature Buoy body, photovoltaic panel, accumulator.According to Fig. 5 flow process, adopt linear integer programming algorithm to be optimized design to photovoltaic storage battery electric power system, working procedure under MATLAB environment, can obtain Miniature Buoy photovoltaic storage battery mixing structure parameter such as Optimum Design Results is j=2; x
1=5; x
2=6, namely select the buoy body being numbered 2; 5, accumulator, total rated capacity is 2000Ah; 6, solar cell, photovoltaic capacity is 60W; It is 17980 yuan containing the initial investment of buoy body.
Step 6, sensitivity analysis;
Because the numerical value of maximum continuous overcast and rainy days adds up weather information statistical computation out according to history, therefore they are not fixed value, there will be the fluctuation of certain limit in reality.Therefore calculated the optimum solution that can not affect model when what maximum continuous overcast and rainy days change within the scope of by sensitivity analysis, i.e. the ability of not influential system normal table work has certain practical significance.
For the situation that maximum continuous overcast and rainy days changes, the restrained boundary that can be equivalent in capacity-constrained changes, then former problem is just converted into the variation range asked and guarantee the capacity-constrained border that feasible optimum solution is constant.
The restrained boundary that can be obtained in capacity-constrained by Mathematical does not affect the feasibility of solution in [-4.44,1.02] this interval during change.Substitute in constraint condition and verify, can find that the restrained boundary in capacity-constrained only just can guarantee that feasible optimum solution is constant during change in [-4.44,0.6].This means that the error amount that maximum continuous overcast and rainy days allows is 1.3 days, as long as namely maximum continuous overcast and rainy days is no more than 11.3 days, the Miniature Buoy photovoltaic storage battery electricity generation system before built up just can guarantee that the normal table of water quality monitoring work carries out.Through this sensitivity analysis, show that the Miniature Buoy photovoltaic storage battery electricity generation system set up by optimized algorithm is under the prerequisite meeting system requirements, also there is certain stable and safe in operation allowance.
Claims (4)
1. the water quality monitoring optimization construction method of the photovoltaic storage battery electric power system of Miniature Buoy power source, is characterized in that:
Step one, Miniature Buoy system power dissipation calculate;
Calculate the operation power consumption and day operation hourage that need to carry the load equipment in buoy body, form the per day energy consumption of Miniature Buoy system, calculate the average power consumption value of load equipment;
The optimization object function modeling of step 2, Miniature Buoy system;
Be that target sets up optimization object function f with cost minimization:
minf＝V
j+C-ηC
-kT
Wherein V
jrepresent the cost of j numbering Miniature Buoy body, C is system dynamic source hardware initial investment cost, and T is the Miniature Buoy system photovoltaic storage battery power source cycle of operation, and k represents that power source part runs the length of service;
Ignore Miniature Buoy application expire after photovoltaic panel and accumulator by the value again recycled, objective function is reduced to:
minf＝V
j+C；
Step 3, based on the maximum continuous overcast and rainy days of meteorologic factor determination Miniature Buoy system;
Determine to answer land used buoy the longest operating overcast and rainy days according to influence factor; Described influence factor comprises intensity of illumination, temperature and relative humidity;
Step 4, Miniature Buoy system constraints are set up;
Step 5, configuration parameter optimization;
Adopting linear integer programming algorithm, calculate and build water quality monitoring Miniature Buoy power source---the cost of photovoltaic storage battery electric power system, obtains Miniature Buoy system photovoltaic storage battery allocation optimum parameter x
j=[x
1, x
2], j=1,2 ... n, n are Miniature Buoy system selectable buoy body number, x
1for correspondence optimization select buoy body after the number of accumulator determined, x
2it is then the number of the corresponding appointment wattage photovoltaic panel determined;
Step 6, sensitivity analysis;
When utilizing sensitivity analysis to investigate the change of continuous rainy weather, water quality monitoring Miniature Buoy system can safeguards system power section not power-off, the continual and steady time span fluctuation range run.
2. optimization construction method according to claim 1, is characterized in that: system dynamic source hardware initial investment cost C is constructed as follows, and supposes selected certain model accumulator single unit price P
b, solar cell unit price P
pas value coefficient, the accumulator quantity x of selected model
1with solar cell quantity x
2as decision variable, then C=P
bx
1+p
px
2, along with the increase of tenure of use, photovoltaic panel and service lifetime of accumulator constantly reduce, the cost value η C that photovoltaic storage battery system can be reused after removing
-kTrepresent, arrangement when wherein 0 < η < 1, η is defined as recycling detects loss factor.
3. optimization construction method according to claim 1, it is characterized in that: step 3 is specially, first need to confirm that Miniature Buoy answers the longitude and latitude of land used, collect the photovoltaic power generation quantity data that Miniature Buoy answers the meteorological number of the history of land used and correspondence, as the training sample of neural network, then by determining after training to build RBF neural, input weather data, export photovoltaic power generation quantity, obtain the nonlinear regression model (NLRM) of the mathematical relation represented between generated energy and weather information, maximum continuous overcast and rainy days in month is determined according to this condition of photovoltaic power generation quantity <0.
4. optimization construction method according to claim 1, is characterized in that: the constraint condition described in step 4 comprises volume constraint, area-constrained, qualitative restrain, price constraints, capacity-constrained and nonnegative integer constraint, specific as follows:
(1) volume constraint: getting single accumulator volume is V
b, battery pack is arranged in the Miniature Buoy shell of appointment model, if its volume upper limit is V
m, then
V
b·x
1≤V
m
(2) area-constrained: in 10 watts/sheet, solar-electricity pool area is S
p, solar energy photovoltaic system is arranged in the Miniature Buoy system platform of appointment model, if its area upper limit is S
m, then
S
p·x
2≤S
m
(3) qualitative restrain: getting single accumulator quality is m
b, in 10 watts/sheet, solar cell quality is m
pif the gross mass upper limit that carrying platform can support is m
m, then
m
b·x
1+m
p·x
2≤m
m
(4) price constraints: getting every, accumulator unit price is P
b, solar cell is in 10 watts/sheet, and every sheet unit price is P
pif total initial investment upper limit of Miniature Buoy power section planning is P
m, then
P
b·x
1+P
p·x
2≤P
m
(5) capacity-constrained: suppose that single batteries to store energy value is E
b, the power consumption of load every day is E
f, do not have the number of days of light radiation to be d continuously, the actual short of electricity hourage LOLH allowed:
For independently photovoltaic storage battery electric power system, load supplying is traced sth. to its source and is come from the electric energy that solar cell produces completely, suppose operably every day solar irradiation, make the effective directly power-on time of solar cell be n hour, if be E for the energy of accumulator deposit
0, single solar cell generated energy hourly is E
p, the charge efficiency of solar cell to load and accumulator is η
1, accumulator is η to the power supplying efficiency of load
2:
nE
p·p≥E
f·n/24·η
1+E
f·(24-n)/24·η
1·η
2+E
0/η
1
(6) nonnegativity Integer constrained characteristic
X
1>=0; x
2>=0 and be integer.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105048934A (en) * | 2015-07-27 | 2015-11-11 | 宁波绿光能源科技有限公司 | Balanced load off-grid photovoltaic optimization method with smallest investment |
| CN108038256A (en) * | 2017-11-02 | 2018-05-15 | 浙江理工大学 | A kind of wet cloth heat-setting process real time temperature evaluation method |
| CN109684666A (en) * | 2018-11-23 | 2019-04-26 | 中国航空工业集团公司沈阳飞机设计研究所 | Aircraft index parameter susceptibility optimization method based on genetic algorithm |
| CN113298286A (en) * | 2021-03-31 | 2021-08-24 | 捷佳润科技集团股份有限公司 | Machine learning-based pitaya marketing time prediction method |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103077429A (en) * | 2013-01-10 | 2013-05-01 | 华北电力大学 | Capacity-optimizing method of isolated micro-electrical network containing wind-solar electricity-generating and electric-automobile electricity-transforming station |
| CN104242335A (en) * | 2014-06-30 | 2014-12-24 | 江苏华大天益电力科技有限公司 | Wind and light storage generating unit capacity optimal configuration method based on rated capacity |
-
2015
- 2015-01-26 CN CN201510037108.2A patent/CN104598687B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103077429A (en) * | 2013-01-10 | 2013-05-01 | 华北电力大学 | Capacity-optimizing method of isolated micro-electrical network containing wind-solar electricity-generating and electric-automobile electricity-transforming station |
| CN104242335A (en) * | 2014-06-30 | 2014-12-24 | 江苏华大天益电力科技有限公司 | Wind and light storage generating unit capacity optimal configuration method based on rated capacity |
Non-Patent Citations (3)
| Title |
|---|
| CODY A.HILL.ET AL.: ""Battery Energy Storage for Enabling Integration of Distributed Solar Power Generation"", 《IEEE TRANSACTIONS ON SAMRT GRID》 * |
| 张建华等: ""含风/光/柴/蓄及海水淡化负荷的微电网容量优化配置"", 《电工技术学报》 * |
| 马艺玮: ""孤岛型混合可再生能源发电系统的优化设计"", 《华南理工大学学报（自然科学版）》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105048934A (en) * | 2015-07-27 | 2015-11-11 | 宁波绿光能源科技有限公司 | Balanced load off-grid photovoltaic optimization method with smallest investment |
| CN105048934B (en) * | 2015-07-27 | 2017-06-16 | 宁波绿光能源科技有限公司 | A kind of equally loaded off-network photovoltaic optimization method of the smallest investment |
| CN108038256A (en) * | 2017-11-02 | 2018-05-15 | 浙江理工大学 | A kind of wet cloth heat-setting process real time temperature evaluation method |
| CN109684666A (en) * | 2018-11-23 | 2019-04-26 | 中国航空工业集团公司沈阳飞机设计研究所 | Aircraft index parameter susceptibility optimization method based on genetic algorithm |
| CN109684666B (en) * | 2018-11-23 | 2023-05-23 | 中国航空工业集团公司沈阳飞机设计研究所 | Aircraft index parameter sensitivity optimization method based on genetic algorithm |
| CN113298286A (en) * | 2021-03-31 | 2021-08-24 | 捷佳润科技集团股份有限公司 | Machine learning-based pitaya marketing time prediction method |
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