CN104795833A - Capacity optimization and configuration method of individual micro-grid storage battery energy storage system - Google Patents

Capacity optimization and configuration method of individual micro-grid storage battery energy storage system Download PDF

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Publication number
CN104795833A
CN104795833A CN201510232344.XA CN201510232344A CN104795833A CN 104795833 A CN104795833 A CN 104795833A CN 201510232344 A CN201510232344 A CN 201510232344A CN 104795833 A CN104795833 A CN 104795833A
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power
storage battery
micro
capacity
capacitance sensor
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CN104795833B (en
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邓长虹
潘华
吴之奎
易琪钧
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Wuhan University WHU
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    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06Electricity, gas or water supply
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00Energy generation through renewable energy sources
    • Y02E10/50Photovoltaic [PV] energy
    • Y02E10/56Power conversion systems, e.g. maximum power point trackers
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00Energy generation through renewable energy sources
    • Y02E10/70Wind energy
    • Y02E10/76Power conversion electric or electronic aspects
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/10Flexible AC transmission systems [FACTS]
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70Smart grids as climate change mitigation technology in the energy generation sector
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E70/00Other energy conversion or management systems reducing GHG emissions
    • Y02E70/30Systems combining energy storage with energy generation of non-fossil origin
    • YGENERAL 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
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

The invention discloses a capacity optimization and configuration method of an individual micro-grid storage battery energy storage system. The capacity optimization and configuration method comprises the following steps: firstly, determining the installed capacity of wind power generation and photovoltaic power generation in the micro-grid and the size of load connected to the micro-grid system, and inputting each reference data required for calculation; making sure whether a diesel engine serving as a backup power supply is available or not and how large the capacity of the diesel engine power generation is according to the actual situation of the micro-grid; determining the relevant constraint conditions and each datum of the selected energy storage battery as well as setting indexes of the power shortage rate of the load power supply for the micro-grid; calculating the total power of wind and light generation according to the detailed resource data and the load power requirement in the same period of time so as to obtain the power balance; calculating the required energy storage capacity according to power balance of each period of time to obtain the power shortage which is possibly generated in each period of time and cannot be compensated by the storage battery; and calculating the total power shortage rate in the period of time required by the system so as to obtain the total capacity of the storage battery to meet the requirement. According to the invention, the reasonable energy storage capacity meeting the system running requirement can be obtained.

Description

A kind of independent micro-capacitance sensor energy-storage system of accumulator capacity configuration optimizing method
Technical field
The invention belongs to micro-grid system technical field, especially a kind of independent micro-capacitance sensor energy-storage system of accumulator capacity configuration optimizing method.
Background technology
Heavy difficult point when applying energy storage device in micro-capacitance sensor is the determination of stored energy capacitance under different application scene.When micro-capacitance sensor application energy storage device, if can not for demand science determination stored energy capacitance, expection requirement may cannot be met on the one hand because stored energy capacitance is too small, a large amount of wastes that fund may be caused unnecessary because stored energy capacitance is excessive on the other hand, therefore the reasonable disposition tool of stored energy capacitance is of great significance.When configuring energy storage device in micro-capacitance sensor, if do not consider self constraint various of energy storage device, will the life-span of energy storage device be caused to be greatly affected, even and then affect the safe operation of whole system.
Energy accumulation capacity configuration conventional is at present important to be had: (1) is according to the maximum power vacancy configuration stored energy capacitance occurred in system operation, but the drawback of this method is, by making configured stored energy capacitance be greater than actual demand, to cause waste; (2) determine required stored energy capacitance according to various Stable Control Strategy, but this method can lose accuracy science in default of the overall consideration retrained for energy storage device itself.
In micro-capacitance sensor, the impact of new forms of energy power output climate is very large, easy appearance is fluctuated thus the stable operation of influential system, therefore need on the basis considering the various constraints of energy storage device, to determine a rational stored energy capacitance for power shortage, to meet the service requirement of microgrid.
Summary of the invention
The object of the invention is to overcome the deficiencies in the prior art, provide a kind of independent micro-capacitance sensor energy-storage system of accumulator capacity configuration optimizing method.
The technical solution adopted in the present invention is: a kind of independent micro-capacitance sensor energy-storage system of accumulator capacity configuration optimizing method, is characterized in that, comprise the following steps:
Step 1: determine the installed capacity of wind power generation and photovoltaic generation in micro-capacitance sensor and the payload of access micro-grid system, input calculates every resource data used;
Step 2: define without making the diesel engine generator of back-up source and the amount of capacity of diesel generation according to micro-capacitance sensor actual conditions;
Step 3: determine select the related constraint condition of storage battery and every data and the index of micro-capacitance sensor short of electricity rate is formulated;
Step 4: wind speed, intensity of illumination, temperature, the load power data of surveying according to prediction or former years, calculating wind power generation and the meritorious of photovoltaic generation are exerted oneself, and new forms of energy are gained merit and are exerted oneself and power shortage detailed resource data that load is gained merit between demand, calculate the gross power of wind power generation and photovoltaic generation and same period load power demand, obtain power difference;
Step 5: the stored energy capacitance needed for calculating according to the power difference of each period, and the power shortage obtaining that issuable storage battery of each period cannot compensate;
Step 6: calculate short of electricity rate total in the period required by micro-capacitance sensor, obtain the storage battery total capacity that can meet the demands.
As preferably, the related constraint condition of the storage battery described in step 3 comprises that state-of-charge SOC retrains, charging and discharging currents constraint, charging/discharging voltage constraint, system power supply reliability constraint.
As preferably, described state-of-charge SOC reflects the residual capacity of current storage battery, and its computing formula is:
SOC = 1 - Q 1 Q ;
Wherein Q 1represent the electricity of having released, Q represents reference capacity, also referred to as with the electricity under constant current fully charged state; And the electricity Q released 1represent with electric current and the integration of time:
Q 1=∫idt;
Easily know that discharging current is just, charging current is negative;
State-of-charge SOC can react the discharge and recharge degree of depth of storage battery, for ensureing the normal operation of storage battery and extending its useful life, need limit the scope of state-of-charge SOC:
SOC min≤SOC≤SOC max
Wherein, SOC minand SOC maxbe respectively minimum value and the maximum of storage battery charge state.
As preferably, the charging and discharging currents of storage battery can regulate within the specific limits, thus reaches the requirement of different discharge and recharge time, but charging and discharging currents is crossed senior general and damaged equipment itself, therefore does following restriction to charging and discharging currents I:
I≤I max
According to different types of storage battery, set corresponding maximum current I max.
As preferably, when storage battery is in certain voltage range, can discharge and recharge be carried out, but if port voltage exceedes charging/discharging voltage bound, then cannot carry out discharge and recharge, therefore following restriction is done to charging/discharging voltage U:
U STOP≤U≤U FULL
U in formula sTOPfor final discharging voltage, U fULLfor full charge pressure.
As preferably, because wind energy and solar energy have the feature of randomness and fluctuation, the micro-capacitance sensor being in islet operation the whole year there will be the situation that generator output is less than load, at this moment the deficiency needing uninterrupted power supply to supplement wind energy and solar energy to exert oneself, therefore described system power supply reliability constraint load short of electricity rate LPSP (lossof power supply probability) this index is weighed; The definition of LPSP is:
LPSP = Σ i = 1 N [ P L ( t i ) - ( P wt ( t i ) + P pv ( t i ) + P b ( t i ) ) ] Σ i = 1 N P L ( t i ) ;
In formula: P l(t i) be t ithe micro-grid load power in moment; P wt(t i) be t ithe active power of output of moment wind power system; P pv(t i) be t ithe active power of output of moment photovoltaic generating system; P b(t i) be t ithe storage battery active power power in moment; N is that the sampling interval chosen in computational process is counted, generally in units of year.
Advantage of the present invention and good effect are:
For the energy storage battery making back-up source in micro-capacitance sensor, consider various Index Constraints and the system requirements of equipment itself, carry out energy storage device discharge and recharge calculating by the period, thus obtain a scientific and reasonable capacity.
Accompanying drawing explanation
Fig. 1: the process chart being the embodiment of the present invention.
Fig. 2: the resource data figure being micro-capacitance sensor in the embodiment of the present invention, wherein (a) represents load data, and (b) represents air speed data, and (c) represents photometric data, and (d) represents temperature data.
Embodiment
Understand for the ease of those of ordinary skill in the art and implement the present invention, below in conjunction with drawings and Examples, the present invention is described in further detail, should be appreciated that exemplifying embodiment described herein is only for instruction and explanation of the present invention, is not intended to limit the present invention.
Ask for an interview Fig. 1, one provided by the invention independent micro-capacitance sensor energy-storage system of accumulator capacity configuration optimizing method, comprises the following steps:
In the present embodiment, for certain island domestic, get the real data of its whole year, wind, light installation total capacity is respectively 14MW and 10MW.The incision of blower fan, specified and cut-out wind speed be respectively 2.5,9,19m/s, the maximum power output of photovoltaic cell under standard test condition is 83w.As shown in Figure 2, wherein (a) represents load data, and (b) represents air speed data, and (c) represents photometric data, and (d) represents temperature data for annual load data and wind, light resources data.
Step 2: define without making the diesel engine generator of back-up source and the amount of capacity of diesel engine generator according to micro-capacitance sensor actual conditions;
In the present embodiment, installed capacity sent out by bavin is 0, and namely in this wind, light, the lonely net system of storage micro-capacitance sensor, energy storage battery makes full back-up source.
Step 3: determine select the related constraint condition of storage battery and every data and the index of micro-capacitance sensor short of electricity rate is formulated; The related constraint condition of storage battery comprises state-of-charge SOC constraint, charging and discharging currents constraint, charging/discharging voltage constraint, system power supply reliability constraint.
(1) state-of-charge SOC retrains: SOC is used to the state parameter of nominal present battery capacity, carries out management and the control of battery, thus can use battery pack better, and increase the service life by state parameter accurately and reliably.It is defined as: SOC reflects the residual capacity of current storage battery, and its computing formula is:
SOC = 1 - Q 1 Q ;
Wherein Q 1represent the electricity of having released, Q represents reference capacity, also referred to as with the electricity under constant current fully charged state; And the electricity Q released 1represent with electric current and the integration of time:
Q 1=∫idt
Easily know that discharging current is just, charging current is negative;
State-of-charge SOC can react the discharge and recharge degree of depth of storage battery, for ensureing the normal operation of storage battery and extending its useful life, need limit the scope of state-of-charge SOC:
SOC min≤SOC≤SOC max
Wherein, SOC minand SOC maxbe respectively minimum value and the maximum of storage battery charge state.
(2) charging and discharging currents constraint: the charging and discharging currents of storage battery can regulate within the specific limits, thus reaches the requirement of different discharge and recharge time, but charging and discharging currents is crossed senior general and is damaged equipment itself, therefore following restriction is done to electric current I:
I≤I max
For dissimilar storage battery, set corresponding discharge and recharge Limited Current value I max.In formula, current value is order of magnitude.
(3) charging/discharging voltage constraint: can discharge and recharge be carried out when storage battery is in certain voltage range, but if port voltage exceedes charging/discharging voltage bound, then cannot carry out discharge and recharge, therefore following restriction is done to voltage U:
U STOP≤U≤U FULL
In formula, voltage bound is respectively full charge pressure and final discharging voltage.
(4) constraint of system power supply reliability: because wind energy and solar energy have the feature of randomness and fluctuation, the micro-capacitance sensor being in islet operation the whole year there will be the situation that generator output is less than load, the deficiency at this moment needing uninterrupted power supply to supplement wind energy and solar energy to exert oneself.
System power supply reliability constraint load short of electricity rate LPSP (loss of power supplyprobability) this index is weighed; The definition of LPSP is:
LPSP = Σ i = 1 N [ P L ( t i ) - ( P wt ( t i ) + P pv ( t i ) + P b ( t i ) ) ] Σ i = 1 N P L ( t i ) ;
In formula: P l(t i) be t ithe micro-grid load power in moment; P wt(t i) be t ithe active power of output of moment wind power system; P pv(t i) be t ithe active power of output of moment photovoltaic generating system; P b(t i) be t ithe storage battery active power power in moment; N is that the sampling interval chosen in computational process is counted, generally in units of year.
In the present embodiment, short of electricity rate index is decided to be 5%.It is as shown in table 1 that various types of storage battery calculates data used.
Table 1: various types of storage battery calculates data used
Step 4: wind speed, intensity of illumination, temperature, the load power data of surveying according to prediction or former years, calculating wind power generation and the meritorious of photovoltaic generation are exerted oneself, and new forms of energy are gained merit and are exerted oneself and power shortage detailed resource data that load is gained merit between demand, calculate the gross power of wind power generation and photovoltaic generation and same period load power demand, obtain power difference;
Step 5: the stored energy capacitance needed for calculating according to the power difference of each period, and the power shortage obtaining that issuable storage battery of each period cannot compensate;
Step 6: calculate short of electricity rate total in the period required by micro-capacitance sensor, obtain the storage battery total capacity that can meet the demands.
The desired volume that in following table 2 the present embodiment, various types of storage battery calculates and system add energy storage device after short of electricity rate, the short of electricity rate index after the present embodiment meets required storage battery total capacity size that this microgrid service requirement calculates and adds energy storage device.
Table 2: the desired volume that various types of storage battery calculates and the short of electricity rate after adding energy storage device
Battery types Required total capacity (kwh) Short of electricity rate
Lithium ion battery 2334 4.998%
Lead acid accumulator 2554 5%
Nickel-hydrogen accumulator 2498 4.997%
Cadmium-nickel storage cell 2521 4.999%
Should be understood that, the part that this specification does not elaborate all belongs to prior art.
Should be understood that; the above-mentioned description for preferred embodiment is comparatively detailed; therefore the restriction to scope of patent protection of the present invention can not be thought; those of ordinary skill in the art is under enlightenment of the present invention; do not departing under the ambit that the claims in the present invention protect; can also make and replacing or distortion, all fall within protection scope of the present invention, request protection range of the present invention should be as the criterion with claims.

Claims (6)

1. an independent micro-capacitance sensor energy-storage system of accumulator capacity configuration optimizing method, is characterized in that, comprise the following steps:
Step 1: determine the installed capacity of wind power generation and photovoltaic generation in micro-capacitance sensor and the payload of access micro-grid system, input calculates every resource data used;
Step 2: define without making the diesel engine generator of back-up source and the amount of capacity of diesel generation according to micro-capacitance sensor actual conditions;
Step 3: determine select the related constraint condition of storage battery and every data and the index of micro-capacitance sensor short of electricity rate is formulated;
Step 4: wind speed, intensity of illumination, temperature, the load power data of surveying according to prediction or former years, calculating wind power generation and the meritorious of photovoltaic generation are exerted oneself, and new forms of energy are gained merit and are exerted oneself and power shortage detailed resource data that load is gained merit between demand, calculate the gross power of wind power generation and photovoltaic generation and same period load power demand, obtain power difference;
Step 5: the stored energy capacitance needed for calculating according to the power difference of each period, and the power shortage obtaining that issuable storage battery of each period cannot compensate;
Step 6: calculate short of electricity rate total in the period required by micro-capacitance sensor, obtain the storage battery total capacity that can meet the demands.
2. independent micro-capacitance sensor energy-storage system of accumulator capacity configuration optimizing method according to claim 1, is characterized in that: the related constraint condition of the storage battery described in step 3 comprises state-of-charge SOC constraint, charging and discharging currents constraint, charging/discharging voltage constraint, system power supply reliability constraint.
3. independent micro-capacitance sensor energy-storage system of accumulator capacity configuration optimizing method according to claim 2, is characterized in that: described state-of-charge SOC reflects the residual capacity of current storage battery, and its computing formula is:
SOC = 1 - Q 1 Q ;
Wherein Q 1represent the electricity of having released, Q represents reference capacity, also referred to as with the electricity under constant current fully charged state; And the electricity Q released 1represent with electric current and the integration of time:
Q 1=∫idt ;
Easily know that discharging current is just, charging current is negative;
State-of-charge SOC can react the discharge and recharge degree of depth of storage battery, for ensureing the normal operation of storage battery and extending its useful life, need limit the scope of state-of-charge SOC:
SOC min≤SOC≤SOC max
Wherein, SOC minand SOC maxbe respectively minimum value and the maximum of storage battery charge state.
4. independent micro-capacitance sensor energy-storage system of accumulator capacity configuration optimizing method according to claim 2, is characterized in that: described charging and discharging currents I constraints is:
I≤I max
According to different types of storage battery, set corresponding maximum current I max.
5. independent micro-capacitance sensor energy-storage system of accumulator capacity configuration optimizing method according to claim 2, is characterized in that: described charging/discharging voltage U constraints is:
U STOP≤U≤U FULL
U in formula sTOPfor final discharging voltage, U fULLfor full charge pressure.
6. independent micro-capacitance sensor energy-storage system of accumulator capacity configuration optimizing method according to claim 2, is characterized in that: described system power supply reliability constraint load short of electricity rate LPSP (loss of powersupply probability) this index is weighed; The definition of LPSP is:
LPSP = Σ i = 1 N [ P L ( t i ) - ( P wt ( t i ) + P pv ( t i ) + P b ( t i ) ) ] Σ i = 1 N P L ( t i ) ;
In formula: P l(t i) be t ithe micro-grid load power in moment; P wt(t i) be t ithe active power of output of moment wind power system; P pv(t i) be t ithe active power of output of moment photovoltaic generating system; P b(t i) be t ithe storage battery active power power in moment; N is that the sampling interval chosen in computational process is counted, generally in units of year.
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CN106230012A (en) * 2016-09-19 2016-12-14 华北电力大学(保定) Ultracapacitor and the Optimal Configuration Method of accumulator capacity in grid-connected photovoltaic system
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CN106779250A (en) * 2017-01-16 2017-05-31 浙江大学城市学院 A kind of isolated distributed power grid collocation method based on new Optimized model
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CN110247431A (en) * 2019-07-02 2019-09-17 中安瑞材(北京)科技有限公司 A kind of production capacity building system and its capacity collocation method
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