CN105958519B - A kind of power distribution network energy-storage system configuration method based on active management and cost effectiveness analysis - Google Patents
A kind of power distribution network energy-storage system configuration method based on active management and cost effectiveness analysis Download PDFInfo
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- CN105958519B CN105958519B CN201610272874.1A CN201610272874A CN105958519B CN 105958519 B CN105958519 B CN 105958519B CN 201610272874 A CN201610272874 A CN 201610272874A CN 105958519 B CN105958519 B CN 105958519B
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- 238000004146 energy storage Methods 0.000 title claims abstract description 180
- 238000009826 distribution Methods 0.000 title claims abstract description 42
- 238000007726 management method Methods 0.000 title claims abstract description 33
- 238000012043 cost effectiveness analysis Methods 0.000 title claims abstract description 24
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- 238000005457 optimization Methods 0.000 claims description 8
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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Abstract
The power distribution network energy-storage system configuration method based on active management and cost effectiveness analysis that the present invention relates to a kind of, specifically includes following steps：Step S1：The active management system of automotive to active management power distribution network is established, while establishing the cost effectiveness analysis system including stored energy capacitance allocation models；Step S2：The distribution system module reads the time series data of year load and photovoltaic power output, records real-time SVR/OLTC operating status, and be passed to cost effectiveness analysis system and EMS control module；Step S3：By comparing the voltage indexes of current voltage level data and setting, the voltage level for sending charge-discharge electric power information to energy-storage system module to control at this time is located in normal range (NR) EMS module；Step S4：The cost-benefit that the cost effectiveness analysis system carries out energy-storage system calculates, and optimizes the capacity configuration of energy storage.The active management effect of power distribution network is played by establishing power distribution network active management system of automotive；Pass through energy storage cost effectiveness analysis system energy accurate description energy-storage system allocation models.
Description
Technical field
The present invention relates to energy-storage system planning field in active distribution network, more particularly to one kind based on active management at
The power distribution network energy-storage system configuration method of this performance analysis.
Background technique
Distributed generation resource (DG) generate electricity by way of merging two or more grid systems be considered as 21 century power industry one of important research direction.DG future
Power distribution network will be accessed on a large scale.However the increase of DG permeability also will bring one to distribution network voltage, power quality, management and running
The influence of series.Energy-storage system adjusts and has both the feature for accumulation of energy power by its fast power, in smooth intermittent energy
Power swing, peak load shifting improve quality of voltage and have all played huge effect in terms of providing backup power source, are actively
Power distribution network realizes the key point run to the distributed energy flexible modulation accessed extensively and the network optimization, and configuration will be straight
It connects and influences active distribution network for the ability of distributed energy active management and the economy of the network operation.
Currently, the configuration of energy storage is to realize a certain or multiple functions (such as based on energy storage：It reduces network loss, stabilize distribution
Power fluctuation, power-supply fluctuation, peak load shifting etc.) optimization energy storage capacity.Due to power distribution network, distributed generation resource, energy storage, bear
Lotus has collectively constituted active distribution system, and active distribution system is a unified entirety, so advising in active distribution network energy storage
The effect of energy storage itself is only considered in drawing, ignores the systematicness of active distribution network, ignores the active management function of active distribution network
The traditional planning method of energy, keeps the adaptedness of model poor, and calculated result inaccuracy, resulting systems organization allocation plan is not
Rationally.
Summary of the invention
In view of this, the object of the present invention is to provide a kind of power distribution network energy storage based on active management and cost effectiveness analysis
' In System Reconfiguration Method, the active management that power distribution network is played by establishing power distribution network active management system of automotive act on；Pass through energy storage cost
Performance analysis system energy accurate description energy-storage system allocation models provides the reasonable plan of energy-storage system configuration.
The present invention is realized using following scheme：A kind of power distribution network energy-storage system based on active management and cost effectiveness analysis
Configuration method specifically includes following steps：
Step S1：An active management system of automotive to active management power distribution network is established, the active management system of automotive includes matching
Electric system module, energy-storage system module and EMS module, while establishing a cost-effectiveness point to configure energy-storage system model
Analysis system；
Step S2：The distribution system module reads the time series data of year load and photovoltaic power output under each scene,
Real-time SVR/OLTC operating status is recorded, and the operating status of SVR/OLTC, peak load shifting information are passed to cost-effectiveness
Real-time busbar voltage assessment data are also conveyed to EMS control module by analysis system；
Step S3：EMS module gives energy-storage system module by comparing the voltage indexes of current voltage level data and setting
The voltage level for sending charge-discharge electric power information to control at this time is located in normal range (NR), if busbar voltage is out-of-limit at this time, then leads to
SVR and OLTC control voltage is crossed to be located in normal range (NR)；It energy-storage system module estimation energy storage charge-discharge electric power at this time and fills
Depth of discharge, and dynamic adjusts energy storage charge-discharge electric power；
Step S4：The cost effectiveness analysis system obtain energy storage life cycle, SVR OLTC operating status, peak load shifting
After information, the cost-benefit for carrying out energy-storage system is calculated, and continues to optimize the capacity configuration of energy storage, until arriving allocation optimum capacity.
Further, the distribution system module includes distributed photovoltaic power, BESS, load, SVR/OLTC；
SOC and SOH index of aging of the energy-storage system module to assess BESS；Feedback arrives after SOC index evaluation
EMS module, EMS module send charge-discharge power demand to BESS according to SOC state and instruct；SOH index indicates energy-storage system module
The remaining life period；
The EMS module reaches peak load shifting and adjustment electricity to adjust the trend in energy storage, photovoltaic, load and network
Pressure；When the uncertainty of PV power output causes overtension, EMS module sends charge requirement instruction to energy-storage system module；Electricity
When pressing through low, EMS module sends electric discharge requirement command to energy-storage system module.
Further, the stored energy capacitance allocation models of the cost effectiveness analysis system is bilayer model：
The objective function of the stored energy capacitance allocation models is as follows：
Internal layer optimization：
In formula：ΩBESSNode set is installed for energy storage；NsFor scene sum；
Since energy-storage system overall cost of ownership includes Technics of Power Electronic Conversion PSC cost, energy storage installed capacity cost and energy storage
Device operation expense, energy-storage system overall cost of ownership are：
In formula：CBESSFor k-th of node energy storage conversion to annual energy storage overall cost of ownership；CPSCFor energy storage power electronics
Converter unit cost；PBESSFor single energy storage device rated power；CWFor energy storage unit capacity cost of investment；WBESSIt is single
Energy storage device rated capacity；CfinstallFor installation cost coefficient；R is discount rate；N is planning horizon, with year unit；η is energy storage
Device transfer efficiency；Y is planning year；For the annual operating and maintenance cost of k-th of node energy storage；For k-th of node energy storage
Life cycle cost；
If energy storage device belongs to grid company, not all for third party
In formula：M is year number of days.T is the planning period, is divided into 24 periods；
If energy storage device belongs to the third party energy storage investor, since distributed energy storage equipment efficiency for charge-discharge is different, and
Price is different with the flow direction of fund when charge and discharge, so：
In formula：The respectively electric discharge of energy storage and charging expense；Respectively discharge power and charging
Power；For energy storage device life cycle cost；
Via net loss cost is：
In formula：The Power loss and time scale that Δ P (t), Δ t are respectively；clossFor unit Web-based exercise；
Low-carbon annual earnings are that energy-storage system discharges in load peak, to reduce regulating units power output, are：
In formula：Power output when peak regulation is used for for energy storage；CLCThe homogenizing year cost of electricity-generating of peak regulation is used for for fired power generating unit；
Energy storage is used for the low high-incidence year income of storage：
In formula：Cpeak, CoffpeakFor the electricity price in load rush hour and non-peak moment；Load peak is used for for energy storage
The year discharge capacity at moment；
Reducing OLTC/SVR O&M income is：
In formula：The saving annual earnings of OLTC/SVR number of run are reduced for k-th of node；COLTC&SVRFor OLTC
With the operation and maintenance cost of SVR；cfomOLTC/SVR O&M cost factor；Tsaved, TcycleThe saving of respectively OLTC/SVR is transported
Row number and total cycle times, Tcycle=150,000；For the energy storage year number of run of k-th of node；
The constraint condition of the stored energy capacitance allocation models is as follows：
The constraint condition of power-balance is：
In formula：PisAnd QisThe respectively active injection of node i and idle injection；UiFor the voltage magnitude of node i；
J ∈ i indicates that node j is connected with node i；GijAnd BijThe respectively real and imaginary parts of node admittance matrix；θijFor section
Phase angle difference between point i, j.
Voltage constraint condition is：
Umin≤Ui≤Umax
In formula：UminAnd UmaxThe respectively voltage magnitude bound of node i；
Number constraint condition is installed in energy storage：
Energy storage charge-discharge electric power constraint condition is：
-Pkmax≤Pk(t)≤Pkmax
-Qkmax≤Qk(t)≤Qkmax
In formula：Pk(t) and QkIt (t) is respectively the active and idle of k-th of inverter output of t moment；SkmaxAnd QkmaxRespectively
For the rated capacity and the reactive power upper limit of k-th of inverter；
Energy storage charging and discharging state constraint condition is：
The charging and discharging state of energy storage has continuity in timing, and the energy storage energy of each time point should meet SOC
The upper limit requirement of state, while initial SOC and final SOC state should be made to be consistent within a fixed cycle, then：
In formula：K=1,2 ... .Nst；For the SOC value of k-th of energy storage of t moment；
Further, the step S4 solves bilayer model using genetic algorithm and sequential quadratic programming algorithm：
Determine that the stored energy capacitance of outer layer, internal layer optimize the charge-discharge electric power of energy storage by sequential quadratic programming algorithm by genetic algorithm,
Optimization aim is peak load shifting and voltage fluctuation.
Compared with prior art, the active management that the present invention plays power distribution network by establishing power distribution network active management system of automotive is made
With；Pass through energy storage cost effectiveness analysis system energy accurate description energy-storage system allocation models.
Detailed description of the invention
Fig. 1 is overall system architecture schematic diagram of the invention.
Fig. 2 is energy storage charge control policy map in the control section EMS in the present invention.
Fig. 3 is energy storage control of discharge policy map in the control section EMS in the present invention.
Fig. 4 is the algorithm flow chart of cost effectiveness analysis system of the invention.
Specific embodiment
The present invention will be further described with reference to the accompanying drawings and embodiments.
The power distribution network energy-storage system configuration method based on active management and cost effectiveness analysis that the present embodiment provides a kind of, such as
Shown in Fig. 1, following steps are specifically included：
Step S1：An active management system of automotive to active management power distribution network is established, the active management system of automotive includes matching
Electric system module, energy-storage system module and EMS module, while establishing a cost-effectiveness point to configure energy-storage system model
Analysis system；
Step S2：The distribution system module reads the time series data of year load and photovoltaic power output under each scene,
Real-time SVR/OLTC operating status is recorded, and the operating status of SVR/OLTC, peak load shifting information are passed to cost-effectiveness
Real-time busbar voltage assessment data are also conveyed to EMS control module by analysis system；
Step S3：EMS module gives energy-storage system module by comparing the voltage indexes of current voltage level data and setting
The voltage level for sending charge-discharge electric power information to control at this time is located in normal range (NR), if busbar voltage is out-of-limit at this time, then leads to
SVR and OLTC control voltage is crossed to be located in normal range (NR)；It energy-storage system module estimation energy storage charge-discharge electric power at this time and fills
Depth of discharge, and dynamic adjusts energy storage charge-discharge electric power；
Step S4：The cost effectiveness analysis system obtain energy storage life cycle, SVR OLTC operating status, peak load shifting
After information, the cost-benefit for carrying out energy-storage system is calculated, and continues to optimize the capacity configuration of energy storage, until arriving allocation optimum capacity.
In the present embodiment, according to the lasting progress of above step, the energy-storage system module will update SOC state and fortune
Row service life state (SOH), until the service life state of energy storage reaches operational limit.
In the present embodiment, the distribution system module includes distributed photovoltaic power, BESS, load, SVR/OLTC；Its
Middle distributed generation resource power output has uncertainty, is divided into multiple power output scenes.SVR/OLTC device is adjusted for voltage；
SOC and SOH index of aging of the energy-storage system module to assess BESS, passes through the active of SOC and SOH
Management can enable energy storage to operate in normally with the parameters such as the charge-discharge electric power of active accommodation energy storage device and charge and discharge number
Working condition；Feedback arrives EMS module after SOC index evaluation, and EMS module sends charge-discharge power demand to BESS according to SOC state and refers to
It enables；The remaining life period of SOH index instruction energy-storage system module.
The control centre of the entire active distribution system of EMS module, to adjust energy storage, photovoltaic, load and network
In trend reach peak load shifting and adjustment voltage, by the charge power of the voltage condition of distribution system and energy-storage system, fill
Discharge condition and the control parameter of input compare, and pass through the charge and discharge initial time of comparing result real time coordination energy-storage system
And charge-discharge electric power, energy storage is realized to the active management of voltage and peak load shifting；When the uncertainty of PV power output causes
When overtension, EMS module sends charge requirement instruction to energy-storage system module；When brownout, EMS module is to energy-storage system
Module sends electric discharge requirement command.
In the present embodiment, the stored energy capacitance allocation models of the cost effectiveness analysis system is bilayer model, in model
Involved in the investment operating cost of energy storage, life cycle cost, Web-based exercise, low-carbon income, peak load shifting arbitrage income, subtract
The operation income of other voltage adjusting devices in few power grid：
The objective function of the stored energy capacitance allocation models is as follows：
Internal layer optimization：
In formula：ΩBESSNode set is installed for energy storage；NsFor scene sum；
Since energy-storage system overall cost of ownership includes Technics of Power Electronic Conversion PSC cost, energy storage installed capacity cost and energy storage
Device operation expense, energy-storage system overall cost of ownership are：
In formula：CBESSFor k-th of node energy storage conversion to annual energy storage overall cost of ownership；CPSCFor energy storage power electronics
Converter unit cost；PBESSFor single energy storage device rated power；CWFor energy storage unit capacity cost of investment；WBESSIt is single
Energy storage device rated capacity；CfinstallFor installation cost coefficient；R is discount rate；N is planning horizon, with year unit；η is energy storage
Device transfer efficiency；Y is planning year；For the annual operating and maintenance cost of k-th of node energy storage；For k-th of node energy storage
Life cycle cost；
If energy storage device belongs to grid company, not all for third party
In formula：M is year number of days.T is the planning period, is divided into 24 periods；
If energy storage device belongs to the third party energy storage investor, since distributed energy storage equipment efficiency for charge-discharge is different, and
Price is different with the flow direction of fund when charge and discharge, so：
In formula：The respectively electric discharge of energy storage and charging expense；Respectively discharge power and charging
Power；For energy storage device life cycle cost；
Via net loss cost is：
In formula：The Power loss and time scale that Δ P (t), Δ t are respectively；clossFor unit Web-based exercise；
Low-carbon annual earnings are that energy-storage system discharges in load peak, to reduce regulating units power output, are：
In formula：Power output when peak regulation is used for for energy storage；CLCThe homogenizing year cost of electricity-generating of peak regulation is used for for fired power generating unit；
Energy storage is used for the low high-incidence year income of storage：
In formula：Cpeak, CoffpeakFor the electricity price in load rush hour and non-peak moment；Load peak is used for for energy storage
The year discharge capacity at moment；
Reducing OLTC/SVR O&M income is：
In formula：The saving annual earnings of OLTC/SVR number of run are reduced for k-th of node；COLTC&SVRFor OLTC
With the operation and maintenance cost of SVR；cfomOLTC/SVR O&M cost factor；Tsaved, TcycleThe saving of respectively OLTC/SVR is transported
Row number and total cycle times, Tcycle=150,000；For the energy storage year number of run of k-th of node；
The constraint condition of the stored energy capacitance allocation models is as follows：
The constraint condition of power-balance is：
In formula：PisAnd QisThe respectively active injection of node i and idle injection；UiFor the voltage magnitude of node i；
J ∈ i indicates that node j is connected with node i；GijAnd BijThe respectively real and imaginary parts of node admittance matrix；θijFor section
Phase angle difference between point i, j.
Voltage constraint condition is：
Umin≤Ui≤Umax
In formula：UminAnd UmaxThe respectively voltage magnitude bound of node i；
Number constraint condition is installed in energy storage：
Energy storage charge-discharge electric power constraint condition is：
-Pkmax≤Pk(t)≤Pkmax
-Qkmax≤Qk(t)≤Qkmax
In formula：Pk(t) and QkIt (t) is respectively the active and idle of k-th of inverter output of t moment；SkmaxAnd QkmaxRespectively
For the rated capacity and the reactive power upper limit of k-th of inverter；
Energy storage charging and discharging state constraint condition is：
The charging and discharging state of energy storage has continuity in timing, and the energy storage energy of each time point should meet SOC
The upper limit requirement of state, while initial SOC and final SOC state should be made to be consistent within a fixed cycle, then：
In formula：K=1,2 ... .Nst；For the SOC value of k-th of energy storage of t moment.
In the present embodiment, as shown in Fig. 2, the energy storage charge control strategy of the EMS module is specially：When voltage more on
In limited time, charging signals are passed to energy-storage system by EMS module, if charge power is less than or equal to maximum charge power at this time,
It is charged with power at this time；Voltage is then adjusted by OLTC/SVR if more than maximum charge power, and records OLTC/SVR's
Number of run.
In the present embodiment, as shown in figure 3, the energy storage control of discharge strategy of the EMS module is specially：When voltage more under
When limit or peak load (peak load) reach preset value, discharge signal is passed to energy-storage system by EMS, if discharging at this time
Power is less than or equal to maximum discharge power, then is discharged with power at this time；If more than maximum discharge power then by OLTC/
SVR adjusts voltage, and records the number of run of OLTC/SVR.
In the present embodiment, as shown in figure 4, the step S4 uses genetic algorithm and sequential quadratic programming algorithm to bilayer
Model is solved：The stored energy capacitance of outer layer is determined by genetic algorithm, generates the initial population of energy storage installed capacity, fitness
Function is that cost effectiveness analysis result is optimal；Internal layer optimizes the charge-discharge electric power of energy storage, optimization by sequential quadratic programming algorithm
Target is peak load shifting and voltage fluctuation.Wherein, the function of active management system of automotive is optimized by internal layer and is realized.
The foregoing is merely presently preferred embodiments of the present invention, all equivalent changes done according to scope of the present invention patent with
Modification, is all covered by the present invention.
Claims (3)
1. a kind of power distribution network energy-storage system configuration method based on active management and cost effectiveness analysis, it is characterised in that：Specifically
Include the following steps：
Step S1：An active management system of automotive to active management power distribution network is established, the active management system of automotive includes power distribution system
System module, energy-storage system module and EMS module, while establishing a cost effectiveness analysis system including stored energy capacitance allocation models
System；
Step S2：The distribution system module reads the time series data of year load and photovoltaic power output under each scene, record
Real-time SVR/OLTC operating status, and the operating status of SVR/OLTC, peak load shifting information are passed to cost effectiveness analysis
Real-time busbar voltage assessment data are also conveyed to EMS control module by system；
Step S3：EMS module is sent by comparing the voltage indexes of current voltage level data and setting to energy-storage system module
Charge-discharge electric power information is located in normal range (NR) come the voltage level for controlling at this time, if busbar voltage is out-of-limit at this time, then passes through SVR
And OLTC control voltage is located in normal range (NR)；Energy-storage system module estimation energy storage charge-discharge electric power at this time and charge and discharge are deep
Degree, and dynamic adjusts energy storage charge-discharge electric power；
Step S4：The cost effectiveness analysis system obtain energy storage life cycle, SVR OLTC operating status, peak load shifting information
Afterwards, the cost-benefit for carrying out energy-storage system calculates, and continues to optimize the capacity configuration of energy storage, until arriving allocation optimum capacity；
The stored energy capacitance allocation models of the cost effectiveness analysis system is bilayer model：
The objective function of the stored energy capacitance allocation models is as follows：
Internal layer optimization：
In formula：ΩBESSNode set is installed for energy storage；NsFor scene sum；
Since energy-storage system overall cost of ownership includes Technics of Power Electronic Conversion PSC cost, energy storage installed capacity cost and energy storage device
Operation expense, energy-storage system overall cost of ownership are：
In formula：CBESSFor k-th of node energy storage conversion to annual energy storage overall cost of ownership；CPSCFor energy storage converters
Unit cost；PBESSFor single energy storage device rated power；CWFor energy storage unit capacity cost of investment；WBESSFor single energy storage dress
Set rated capacity；CfinstallFor installation cost coefficient；R is discount rate；N is planning horizon, with year unit；η turns for energy storage device
Change efficiency；Y is planning year；For the annual operating and maintenance cost of k-th of node energy storage；For the week in service life of k-th of node energy storage
Period cost；
If energy storage device belongs to grid company, not all for third party
In formula：M is year number of days, and T is the planning period, is divided into 24 periods；
If energy storage device belongs to the third party energy storage investor, since distributed energy storage equipment efficiency for charge-discharge is different, and charge and discharge
Price is different with the flow direction of fund when electric, so：
In formula：The respectively electric discharge of energy storage and charging expense；Respectively discharge power and charge power；For energy storage device life cycle cost；
Via net loss cost is：
In formula：The Power loss and time scale that Δ P (t), Δ t are respectively；clossFor unit Web-based exercise；
Low-carbon annual earnings are that energy-storage system discharges in load peak, to reduce regulating units power output, are：
In formula：Power output when peak regulation is used for for energy storage；CLCThe homogenizing year cost of electricity-generating of peak regulation is used for for fired power generating unit；
Energy storage is used for the low high-incidence year income of storage：
In formula：Cpeak, CoffpeakFor the electricity price in load rush hour and non-peak moment；The load peak moment is used for for energy storage
Year discharge capacity；
Reducing OLTC/SVR O&M income is：
In formula：The saving annual earnings of OLTC/SVR number of run are reduced for k-th of node；COLTC&SVRFor OLTC with
The operation and maintenance cost of SVR；cfomFor OLTC/SVR O&M cost factor；Tsaved, TcycleThe saving of respectively OLTC/SVR is transported
Row number and total cycle times, Tcycle=150,000；For the energy storage year number of run of k-th of node；
The constraint condition of the stored energy capacitance allocation models is as follows：
The constraint condition of power-balance is：
In formula：PisAnd QisThe respectively active injection of node i and idle injection；UiFor the voltage magnitude of node i；
J ∈ i indicates that node j is connected with node i；GijAnd BijThe respectively real and imaginary parts of node admittance matrix；θijFor node i,
Phase angle difference between j；
Voltage constraint condition is：
Umin≤Ui≤Umax
In formula：UminAnd UmaxThe respectively voltage magnitude bound of node i；
Number constraint condition is installed in energy storage：
Energy storage charge-discharge electric power constraint condition is：
-Pkmax≤Pk(t)≤Pkmax
-Qkmax≤Qk(t)≤Qkmax
In formula：Pk(t) and QkIt (t) is respectively the active and idle of k-th of inverter output of t moment；SkmaxAnd QkmaxRespectively kth
The rated capacity and the reactive power upper limit of a inverter；
Energy storage charging and discharging state constraint condition is：
The charging and discharging state of energy storage has continuity in timing, and the energy storage energy of each time point should meet SOC state
Upper limit requirement, while initial SOC and final SOC state should be made to be consistent within a fixed cycle, then：
In formula：K=1,2 ... .Nst；For the SOC value of k-th of energy storage of t moment.
2. a kind of power distribution network energy-storage system configuration side based on active management and cost effectiveness analysis according to claim 1
Method, it is characterised in that：The distribution system module includes distributed photovoltaic power, BESS, load, SVR/OLTC；
SOC and SOH index of aging of the energy-storage system module to assess BESS；Feedback arrives EMS mould after SOC index evaluation
Block, EMS module send charge-discharge power demand to BESS according to SOC state and instruct；The remaining longevity of SOH index instruction energy-storage system module
Order the period；
The EMS module reaches peak load shifting and adjustment voltage to adjust the trend in energy storage, photovoltaic, load and network；
When the uncertainty of PV power output causes overtension, EMS module sends charge requirement instruction to energy-storage system module；Voltage mistake
When low, EMS module sends electric discharge requirement command to energy-storage system module.
3. a kind of power distribution network energy-storage system configuration side based on active management and cost effectiveness analysis according to claim 1
Method, it is characterised in that：The step S4 solves bilayer model using genetic algorithm and sequential quadratic programming algorithm：Pass through
Genetic algorithm determines that the stored energy capacitance of outer layer, internal layer optimize the charge-discharge electric power of energy storage, optimization by sequential quadratic programming algorithm
Target is peak load shifting and voltage fluctuation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
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| CN106600459B (en) * | 2016-12-09 | 2020-10-23 | 国网安徽省电力有限公司经济技术研究院 | Optimization method for solving voltage deviation of photovoltaic access point |
| CN107742223B (en) * | 2017-05-04 | 2020-05-15 | 国家电网公司 | Provincial power grid power transmission and distribution pricing method considering power grid characteristics |
| TW201918980A (en) * | 2017-11-03 | 2019-05-16 | 仰融 | Energy storage network and method for storing and capitalizing off-peak electricity |
| CN109103914A (en) * | 2018-10-17 | 2018-12-28 | 上海电力设计院有限公司 | The micro-capacitance sensor energy storage Optimal Configuration Method of consideration source lotus storage synthetic operation |
| CN109948849B (en) * | 2019-03-19 | 2022-12-06 | 国网福建省电力有限公司 | Power distribution network frame planning method considering energy storage access |
| CN110061492B (en) * | 2019-03-21 | 2021-02-26 | 国网浙江省电力有限公司经济技术研究院 | Energy storage system capacity optimal configuration method considering power supply reliability of power distribution network |
| CN111913110B (en) * | 2019-05-10 | 2023-03-14 | 维谛技术有限公司 | Commercial power battery configuration evaluation method and system |
| CN110224397B (en) * | 2019-06-12 | 2022-04-12 | 南通大学 | User-side battery energy storage cost benefit analysis method under wind and light access background |
| CN111047119B (en) * | 2020-01-08 | 2022-05-03 | 浙江大学 | Electric vehicle charging station dynamic pricing method for regulating and controlling power quality |
| CN111614087B (en) * | 2020-06-09 | 2022-12-09 | 国网吉林省电力有限公司电力科学研究院 | Energy storage double-layer optimization configuration method participating in power grid peak shaving |
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