CN109271678A - A kind of accumulator cell charging and discharging method for optimizing scheduling based on photovoltaic microgrid operating cost - Google Patents
A kind of accumulator cell charging and discharging method for optimizing scheduling based on photovoltaic microgrid operating cost Download PDFInfo
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Abstract
The present invention relates to a kind of accumulator cell charging and discharging method for optimizing scheduling based on photovoltaic microgrid operating cost.The present invention is based on 24 hours prediction data of photovoltaic microgrid power load and photovoltaic power generation, a kind of optimization traffic control strategy of photovoltaic microgrid battery at following 24 hours is proposed.Patent gives the photovoltaic microgrid operating cost model being made of four subitems: (1) the battery aging cost portrayed based on depth of discharge；(2) the electricity needs expense based on Critical Peak Pricing；(2) based on the energy expenditure of tou power price；(4) gene-ration revenue based on photovoltaic online electricity price.The constraint condition of accumulator cell charging and discharging in binding model, realizes the optimization of operating cost model, will significantly reduce the operating cost of photovoltaic microgrid, facilitates the popularization and application of photovoltaic microgrid system.
Description
Technical field
The invention belongs to Photovoltaic new energy fields, are related to a kind of accumulator cell charging and discharging tune based on photovoltaic microgrid operating cost
Spend optimization method.
Background technique
Using the method for optimizing scheduling of accumulator cell charging and discharging, the operating cost of photovoltaic microgrid will be significantly reduced.Electric power storage
The optimizing scheduling process of pond charge and discharge needs to consider: (1) dynamic effects of each depth of discharge of battery to service life；(2)
Influence of the Critical Peak Pricing for electricity needs expense；(3) influence of the tou power price for energy expenditure；(4) photovoltaic online electricity price
Influence for photovoltaic microgrid income.However in practical applications, on the one hand people focus on photovoltaic microgrid construction period electric power storage
Tankage configuration and cost of investment, on the other hand then focus on how to improve photovoltaic power supply quality using accumulator cell charging and discharging.
Current accumulator cell charging and discharging scheduling optimization model seldom considers above-mentioned four factors simultaneously, usually avoids or simplify photovoltaic microgrid
Operating cost problem, will be unfavorable under mounting hardware configuration condition, utmostly improve photovoltaic microgrid operation income.
Summary of the invention
The present invention considers: (1) based on the photovoltaic microgrid power load and power generation history number in the case of weather-similar days
According to, it is contemplated that power load considers light in seasonal whole fluctuation and the localised waving characteristic in one week
Volt power generation follows the fluctuation of season and Changes in weather, can effectively realize that the 24 of photovoltaic microgrid power load and photovoltaic power generation are small
When predict；(2) accumulator cell charging and discharging is usually only focused in improvement photovoltaic power supply quality in photovoltaic microgrid at present, or is only focused on
Electricity needs expense and energy expenditure, and avoided in the operation of photovoltaic microgrid since unreasonable accumulator cell charging and discharging dispatches plan
Slightly generated service lifetime of accumulator variation, and this will become part very important in photovoltaic microgrid operating cost.Therefore
The present invention is based on predictions in 24 hours of photovoltaic microgrid power load and photovoltaic power generation, comprehensively consider accumulator cell charging and discharging dynamic cost
And compound electricity price expense, propose a kind of accumulator cell charging and discharging method for optimizing scheduling based on photovoltaic microgrid operating cost.
The present invention proposes a kind of accumulator cell charging and discharging method for optimizing scheduling based on photovoltaic microgrid operating cost, including following
Step:
Step (1) is real based on the photovoltaic microgrid power load and photovoltaic power generation historical data in the case of similar type day
Predictions in future 24 hours of existing photovoltaic microgrid power load and photovoltaic power generation.
State-of-charge of step (2) calculating accumulator in each charging-discharging cycle.
Depth of discharge of step (3) calculating accumulator in each charging-discharging cycle.In each charging-discharging cycle, battery is put
Electric depth is defined as the mean value of storage battery charge state decline and rising amplitude.
Depth of discharge of the step (4) according to battery, aging cost of the calculating accumulator in each charging-discharging cycle.
Step (5) sets photovoltaic microgrid operating cost objective function.The microgrid being made of for one photovoltaic and battery
System, the mesh that setting is made of electricity needs expense, energy expenditure, photovoltaic power generation online income and battery aging cost
Scalar functions J.
Step (6) sets photovoltaic microgrid operating cost bound for objective function: under electric power storage tank discharge and charge mode
Balanced supply and demand of energy condition, from external electrical network buy electric power need to meet stationarity condition, electric power storage tank discharge and charging
Maximum allowable power restrictive condition need to be met.
Step (7) is under the constraint condition of step (6), for photovoltaic microgrid operating cost target set by step (5)
Function, using PSO Algorithm battery each optimizing cycle charge-discharge electric power.
The device have the advantages that are as follows:
1, considered simultaneously according to power load in seasonal whole fluctuation and the localised waving characteristic in one week
The fluctuation of season and Changes in weather is followed to photovoltaic power generation, realizes photovoltaic microgrid power load and light based on similar type day
It predicts 24 hours of volt power generation；
2, comprehensively consider dynamic cost caused by accumulator cell charging and discharging depth and compound electricity price expense, give by four
The photovoltaic microgrid operating cost model that a subitem is constituted: (1) the battery aging cost portrayed based on depth of discharge；(2) it is based on
The electricity needs expense of Critical Peak Pricing；(2) based on the energy expenditure of tou power price；(4) power generation based on photovoltaic online electricity price is received
Benefit.
3,24 hours prediction data based on photovoltaic microgrid power load and power generation, propose a kind of photovoltaic microgrid battery
In following 24 hours optimization traffic control strategies.The constraint condition of accumulator cell charging and discharging in binding model, realize operation at
The optimization of this model will significantly reduce the operating cost of photovoltaic microgrid.
Detailed description of the invention
Fig. 1 is that load and photovoltaic export prediction curve.
Fig. 2 is accumulator charging/discharging process schematic diagram.
Fig. 3 is particle swarm optimization algorithm flow chart.
Specific embodiment
The present invention set optimization unit time Δ t as 15 minutes, therefore the optimizing cycle number T in 24 hours is 96.In conjunction with
Attached drawing 1,2,3, the specific implementation steps of the present invention are as follows:
Step (1) realizes light based on photovoltaic microgrid power load and power generation historical data in the case of similar type day
It predicts future 24 hours for lying prostrate microgrid power load and photovoltaic power generation.4 kinds of spring, summer, autumn, winter season types will be divided into season, it will
Weather is divided into fine, cloudy, 3 kinds of weather patterns of sleet, is divided into Monday, Tuesday, Wednesday, Thursday, Friday and festivals or holidays 6 for one week
Kind date type.It is prediction day corresponding to optimizing scheduling 24 hours determining first, micro- from photovoltaic according to the date type of prediction day
Candidate similar type day is found in net power load and photovoltaic power generation historical data；Then season and weather pattern are pressed respectively
Candidate is further screened similar type day；Finally according to the minimal difference of similar type day and prediction daily maximum temperature, really
Fixed optimal similar type day, using corresponding photovoltaic microgrid power load and photovoltaic power generation historical data as in 24 hours futures
Every 15 minutes prediction results, it is denoted as P respectivelyd(i) and PRE(i), i=1,2 ..., T.As shown in Fig. 1.
State-of-charge of step (2) calculating accumulator in each charging-discharging cycle.Assuming that battery is in i-th of optimizing cycle
State-of-charge SOC (i), shown in calculating process such as formula (1).
In formula, SOC (0) indicates the initial state-of-charge of battery；The self-discharge rate of σ expression battery；CBATIndicate electric power storage
The capacity in pond；ηCBAnd ηDBRespectively indicate the charging and discharging efficiency of battery；PBC(i) and PBD(i) battery is respectively indicated to exist
The charging and discharging power of i-th of optimizing cycle.
It is illustrated by taking attached accumulator charging/discharging process shown in Fig. 2 as an example, each charging-discharging cycle is by battery in figure
The local maximum and local minimum of state-of-charge (SOC) curve are constituted.Such as the A-B in figure corresponds to the half period, indicates
One discharge process；And B-C then indicates a charging process, so A-B-C constitutes a complete charging-discharging cycle.
Assuming that accumulator cell charging and discharging periodicity is M during 24 hours operation plans, corresponding number of semi-periods of oscillation is 2M,
Therefore the number summation of SOC curve local maximum and local minimum is 2M+1.It is engraved when the generation of 2M+1 local extremum
For ti, i=1,2 ... 2M+1, they correspond to ctkA optimizing cycle, as shown in formula (2).
In formula, Floor indicates downward bracket function.Therefore the state-of-charge of 2M+1 local extremum can be denoted as SOC respectively
(cti), i=1,2 ..., 2M+1.
Depth of discharge of step (3) calculating accumulator in each charging-discharging cycle.In each charging-discharging cycle, battery is put
Electric depth (DOD) is defined as the mean value of storage battery charge state decline and rising amplitude, as shown in formula (3).
In formula, DOD (k) is indicated during 24 hours operation plans, corresponding to k-th of charging-discharging cycle of battery
Depth of discharge.
Aging cost of step (4) calculating accumulator in each charging-discharging cycle.According to the depth of discharge DOD of battery
(k), the aging cost C of k-th of charging-discharging cycle of battery is determinedD(k), as shown in formula (4).
In formula, a, b, α, β correspond to the Fabrication parameter of battery, CIIndicate the cost of investment of battery cell's capacity.
Step (5) sets photovoltaic microgrid operating cost objective function.The microgrid being made of for one photovoltaic and battery
System is set by electricity needs expense CDemand, energy expenditure CEngergy, photovoltaic power generation surf the Internet income EETAnd battery aging
Cost CDThe objective function J constituted, as shown in formula (5).
J=min (CDemand+CEnergy-EET+CD) (5)
Wherein, min indicates minimalization function；Electricity needs expense CDemand, energy expenditure CEngergy, in photovoltaic power generation
Net income EETAnd battery aging cost CDIt calculates respectively such as formula (6), formula (7), shown in formula (8) and formula (9).
CDemand=Pmax×PRDC (6)
In formula, PmaxIndicate the electric load peak value occurred during 24 hours operation plans；PRDCIndicate that spike is negative
Lotus unit price of power；PEF(i) electric power bought in i-th of optimizing cycle from external electrical network is indicated；PREC(i) it indicates the
Tou power price in i optimizing cycle；PET(i) the online power of the photovoltaic power generation in i-th of optimizing cycle is indicated；PRET(i)
Indicate the photovoltaic online electricity price in i-th of optimizing cycle.
Step (6) sets photovoltaic microgrid operating cost bound for objective function.
Constraint condition (1): the balanced supply and demand of energy condition under electric power storage tank discharge and charge mode is respectively such as formula (10) and formula
(11) shown in.
Pd(i)=PEF(i)+PRE(i)-PET(i)+PBD(i) (10)
Pd(i)=PEF(i)+PRE(i)-PET(i)-PBC(i) (11)
In formula, Pd(i), PRE(i), PEF(i), PET(i), PBD(i) and PBC(i) meaning is as described above.
Constraint condition (2): the electric power P bought from external electrical networkEF(i) stationarity condition need to be met, such as formula (12) institute
Show.
ζ2P0≤PEF(i)≤ζ1P0 (12)
In formula, P0Indicate reference power；ζ1And ζ2Indicate PEF(i) bound coefficient of variation, can be respectively set to 0.8 He
0.2。
Constraint condition (3): electric power storage tank discharge and charging need to meet maximum allowable power restrictive condition, such as formula (13) and formula
(14) shown in.
0≤PBD(i)≤PMDB (13)
0≤PBC(i)≤PMCB (14)
In formula, PMDBAnd PMCBRespectively indicate the discharge power and the charge power upper limit of battery.
Step (7) is under the constraint condition of step (6), for photovoltaic microgrid operating cost target set by step (5)
Function, using PSO Algorithm battery each optimizing cycle discharge power PBD(i) and charge power PBC(i),
Implementation process is as shown in Fig. 3.
Claims (2)
1. a kind of accumulator cell charging and discharging method for optimizing scheduling based on photovoltaic microgrid operating cost, which is characterized in that this method tool
Body the following steps are included:
Step (1) realizes light based on the photovoltaic microgrid power load and photovoltaic power generation historical data in the case of similar type day
It predicts future 24 hours for lying prostrate microgrid power load and photovoltaic power generation；Optimization unit time Δ t is set as in 15 minutes, 24 hours
Optimizing cycle number T be 96；Optimal similar type day is determined, by corresponding photovoltaic microgrid power load and photovoltaic power generation history
Data are denoted as P as the prediction result in 24 hours futures every 15 minutes respectivelyd(i) and PRE(i), i=1,2 ..., T；
State-of-charge of step (2) calculating accumulator in each charging-discharging cycle；Assuming that lotus of the battery in i-th of optimizing cycle
Electricity condition SOC (i), shown in calculating process such as formula (1)；
In formula, SOC (0) indicates the initial state-of-charge of battery；The self-discharge rate of σ expression battery；CBATIndicate battery
Capacity；ηCBAnd ηDBRespectively indicate the charging and discharging efficiency of battery；PBC(i) and PBD(i) battery is respectively indicated at i-th
The charging and discharging power of optimizing cycle；
Depth of discharge of step (3) calculating accumulator in each charging-discharging cycle；In each charging-discharging cycle, electric power storage tank discharge is deep
Degree is defined as the mean value of storage battery charge state decline and rising amplitude；As shown in formula (3)；
In formula, DOD (k) indicates the electric discharge corresponding to k-th of charging-discharging cycle of battery during 24 hours operation plans
Depth；M is the accumulator cell charging and discharging periodicity during 24 hours operation plans；
Depth of discharge of the step (4) according to battery, aging cost C of the calculating accumulator in each charging-discharging cycleD(k), such as formula
(4) shown in；
In formula, a, b, α, β correspond to the Fabrication parameter of battery, CIIndicate the cost of investment of battery cell's capacity；
Step (5) sets photovoltaic microgrid operating cost objective function；The micro-grid system being made of for one photovoltaic and battery,
The target letter that setting is made of electricity needs expense, energy expenditure, photovoltaic power generation online income and battery aging cost
Number J, as shown in formula (5)；
J=min (CDemand+CEnergy-EET+CD) (5)
Wherein, min indicates minimalization function；Electricity needs expense CDemand, energy expenditure CEngergy, photovoltaic power generation surf the Internet income
EETAnd battery aging cost CDIt calculates respectively such as formula (6), formula (7), shown in formula (8) and formula (9)；
CDemand=Pmax×PRDC (6)
In formula, PmaxIndicate the electric load peak value occurred during 24 hours operation plans；PRDCIndicate peakload unit
Electricity price；PEF(i) electric power bought in i-th of optimizing cycle from external electrical network is indicated；PREC(i) indicate excellent at i-th
Change the tou power price in the period；PET(i) the online power of the photovoltaic power generation in i-th of optimizing cycle is indicated；PRET(i) it indicates
Photovoltaic online electricity price in i-th of optimizing cycle；
Step (6) sets photovoltaic microgrid operating cost bound for objective function: constraint condition (1): electric power storage tank discharge and filling
Balanced supply and demand of energy condition under power mode is respectively as shown in formula (10) and formula (11)；
Pd(i)=PEF(i)+PRE(i)-PET(i)+PBD(i) (10)
Pd(i)=PEF(i)+PRE(i)-PET(i)-PBC(i) (11)
In formula, Pd(i), PRE(i), PEF(i), PET(i), PBD(i) and PBC(i) meaning is as described above；
Constraint condition (2): the electric power P bought from external electrical networkEF(i) stationarity condition need to be met, as shown in formula (12)；
ζ2P0≤PEF(i)≤ζ1P0 (12)
In formula, P0Indicate reference power；ζ1And ζ2Indicate PEF(i) bound coefficient of variation, can be respectively set to 0.8 and 0.2；
Constraint condition (3): electric power storage tank discharge and charging need to meet maximum allowable power restrictive condition, such as formula (13) and formula (14) institute
Show；
0≤PBD(i)≤PMDB (13)
0≤PBC(i)≤PMCB (14)
In formula, PMDBAnd PMCBRespectively indicate the discharge power and the charge power upper limit of battery；
Step (7) is under the constraint condition of step (6), for photovoltaic microgrid operating cost objective function set by step (5),
Using PSO Algorithm battery each optimizing cycle discharge power PBD(i) and charge power PBC(i)。
2. a kind of accumulator cell charging and discharging method for optimizing scheduling based on photovoltaic microgrid operating cost according to claim 1,
It is characterized in that, step (1) is based on the photovoltaic microgrid power load and photovoltaic power generation historical data in the case of similar type day,
It predicts future 24 hours for realizing photovoltaic microgrid power load and photovoltaic power generation；Specifically: spring, summer, autumn, winter four will be divided into season
Kind season type, is divided into fine, cloudy, 3 kinds of weather patterns of sleet for weather, was divided into Monday, Tuesday, Wednesday, Thursday, week for one week
Five and six kinds of date types of festivals or holidays；Prediction day corresponding to optimizing scheduling 24 hours determining first, according to the day of prediction day
Phase type finds candidate similar type day from photovoltaic microgrid power load and photovoltaic power generation historical data；Then distinguish
Candidate is further screened similar type day by season and weather pattern；Finally according to similar type day and prediction day highest gas
The minimal difference of temperature, determines optimal similar type day, by corresponding photovoltaic microgrid power load and photovoltaic power generation historical data
As the prediction result in 24 hours futures every 15 minutes, it is denoted as P respectivelyd(i) and PRE(i), i=1,2 ..., T；Wherein T
Corresponding to the optimizing cycle number in 24 hours, it is equal to 96.
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| CN112467860A (en) * | 2021-01-28 | 2021-03-09 | 武汉美格科技股份有限公司 | Photovoltaic power generation monitoring device |
| CN112865235A (en) * | 2021-01-21 | 2021-05-28 | 清华-伯克利深圳学院筹备办公室 | Battery control method, electronic device, and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110441701A (en) * | 2019-07-16 | 2019-11-12 | 南方电网科学研究院有限责任公司 | Device for evaluating loss cost of energy storage battery |
| CN112865235A (en) * | 2021-01-21 | 2021-05-28 | 清华-伯克利深圳学院筹备办公室 | Battery control method, electronic device, and storage medium |
| CN112865235B (en) * | 2021-01-21 | 2024-05-10 | 清华-伯克利深圳学院筹备办公室 | Battery control method, electronic device and storage medium |
| CN112467860A (en) * | 2021-01-28 | 2021-03-09 | 武汉美格科技股份有限公司 | Photovoltaic power generation monitoring device |
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