CN112583038B - Energy storage battery capacity configuration method based on distributed photovoltaic centralized absorption - Google Patents
Energy storage battery capacity configuration method based on distributed photovoltaic centralized absorption Download PDFInfo
- Publication number
- CN112583038B CN112583038B CN202011535546.9A CN202011535546A CN112583038B CN 112583038 B CN112583038 B CN 112583038B CN 202011535546 A CN202011535546 A CN 202011535546A CN 112583038 B CN112583038 B CN 112583038B
- Authority
- CN
- China
- Prior art keywords
- storage battery
- capacity
- battery
- distributed photovoltaic
- energy storage
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- 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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/04—Power grid distribution networks
-
- 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]
-
- 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
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/22—The renewable source being solar energy
-
- 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
-
- 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
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
Abstract
The invention relates to a capacity configuration method of an energy storage battery based on distributed photovoltaic centralized absorption, which comprises the following steps: 1) Establishing a preliminary storage battery capacity model considering external influence factors, and determining the preliminary storage battery capacity according to the preliminary storage battery capacity model; 2) Establishing a mathematical model of the relative capacity of the storage battery and the change of the environmental temperature taking into consideration the internal influence factors of the storage battery; 3) And determining the final capacity of the storage battery by combining the initial capacity of the storage battery and the relative capacity of the storage battery. Compared with the prior art, the method has the advantages that the capacity of the energy storage battery is determined by taking the distributed photovoltaic absorption as an aim, the concentrated load of the area is solved by utilizing the energy storage of the battery, the model is correspondingly simplified according to the actual calculation difficulty, the calculation precision is in direct proportion to the measurement frequency, and the method is not influenced by the geographic position on the annual time scale due to the consideration of the influence of the environmental temperature.
Description
Technical Field
The invention relates to the field of new energy power generation, in particular to a capacity configuration method of an energy storage battery based on distributed photovoltaic centralized absorption.
Background
At present, politics and economic situations of petroleum and natural gas production places are swaying, traditional energy sources are gradually exhausted, environmental problems are increasingly prominent, governments around the world are promoted to attach importance to the development of renewable energy sources, and solar energy resources are necessarily important points of development. The solar energy and the solar energy are integrated, and the solar energy are integrated, so that the solar energy and the solar energy are integrated, and the solar energy are integrated into a whole. Solar radiation in the middle and western regions of China is unevenly distributed, so that a large amount of photovoltaic power generation in the western region cannot be consumed, the intelligent agriculture concept is well provided, agriculture in the western region is developed, agricultural loads become multiple, and the internal requirements of western power utilization loads are enlarged. The distributed photovoltaic power generation system in the western region is disadvantageous to the concentrated load of agricultural product processing in each region, so that an energy storage battery capacity configuration method based on the concentrated absorption of the distributed photovoltaic is needed to solve the problems.
In the existing technology for absorbing photovoltaic based on the energy storage technology, the stabilizing fluctuation effect of energy storage in the whole photovoltaic system is generally analyzed, the charging and discharging strategy of the whole photovoltaic power station is formulated, a model is built according to the service life of the energy storage device, and finally, economic evaluation is made, and the capacity of the energy storage device is rarely configured from the angle of the absorption method, as in Chinese patent CN 111245105A, although a pre-installed energy storage power station capacity configuration method is provided, the method is not applied to the photovoltaic power generation system; the Chinese patent CN 111224414A also considers the actual load condition of the photovoltaic power generation output power and the electric power, but does not give a specific calculation method of the capacity of the energy storage device, does not consider the influence of the local environment temperature on the energy storage battery, and does not mention the centralized consumption of redundant distributed photovoltaic power generation by using the energy storage battery in the existing method.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a capacity configuration method of an energy storage battery based on centralized absorption of distributed photovoltaic.
The aim of the invention can be achieved by the following technical scheme:
an energy storage battery capacity configuration method based on distributed photovoltaic centralized absorption comprises the following steps:
1) Establishing a preliminary storage battery capacity model considering external influence factors, and determining the preliminary storage battery capacity according to the preliminary storage battery capacity model;
2) Establishing a mathematical model of the relative capacity of the storage battery and the change of the environmental temperature taking into consideration the internal influence factors of the storage battery;
3) And determining the final capacity of the storage battery by combining the initial capacity of the storage battery and the relative capacity of the storage battery.
The step 1) specifically comprises the following steps:
11 Acquiring power generation power change data of each distributed photovoltaic power generation system;
12 Acquiring user base load electricity utilization data corresponding to each distributed photovoltaic power generation system;
13 A preliminary battery capacity model is established.
In the step 13), the expression of the preliminary storage battery capacity model is as follows:
wherein W is Battery For the primary capacity of the accumulator, P pv(i) Generating instantaneous power, P, for an ith group of distributed photovoltaic systems load(i) For the i-th group of user base load instantaneous power, t 0 To calculate the starting time point of the cycle, t 1 To calculate the end time point of the cycle, n is the maximum number of groups of the distributed photovoltaic system and dt is the differential amount of time.
In the step 13), since the differential value dt of time cannot be accurately measured in practical application, the preliminary capacity model of the storage battery is simplified once as follows:
where m is the total number of measurements,
the measurement frequency is represented, and j represents the number of measurements during the measurement.
In order to ensure the feasibility of calculation, the primary capacity model of the storage battery after primary simplification is secondarily simplified into:
wherein Δt is the frequency of actual data acquisition.
The step 2) specifically comprises the following steps:
21 Measuring the relation between the relative capacity of the storage battery and the change of the ambient temperature;
22 Drawing a connection line between the relative capacity of the storage battery and an ambient temperature change point;
23 A mathematical model of the relative capacity of the storage battery and the change of the ambient temperature is established.
In the step 23), the expression of the mathematical model of the relative capacity of the storage battery and the change of the ambient temperature is as follows:
C R ＝A 2 +(A 1 -A 2 )/(1+exp((T-T 0 )/dT)
wherein C is R Is the relative capacity of the storage battery, T is the local environment temperature, A 1 、A 2 、T 0 Are fitting estimation constants.
The step 3) specifically comprises the following steps:
31 Acquiring the minimum value C of the relative capacity of the storage battery according to the change interval of the local annual environment temperature Rmin ；
32 Primary capacity W of the battery calculated from the primary capacity model of the battery Battery And minimum value of relative capacity of battery C Rmin And calculating the final capacity of the deposit battery.
The step 31) specifically comprises the following steps:
fitting by combining the change interval of the local annual environment temperature to obtain the relative capacity C of the storage battery R And obtain the phase of the energy storage batteryMinimum value for capacity C Rmin 。
In the step 32), the primary capacity W of the energy storage battery is combined Battery Calculating the capacity of the energy storage battery suitable for local distributed photovoltaic concentrated absorption, namely the final capacity W of the battery Battery-end The following steps are:
compared with the prior art, the invention has the following advantages:
1. the invention determines the capacity of the energy storage battery for the purpose of distributed photovoltaic absorption, utilizes the energy storage of the battery to solve the regional concentrated load, comprehensively considers the internal and external factors influencing the capacity of the energy storage battery, comprehensively considers the power generation time-by-time power of each distributed photovoltaic system and the corresponding load time-by-time power thereof, and secondly considers the influence of the environmental temperature on the relative capacity of the battery, correspondingly simplifies the model according to the actual calculation difficulty, has the calculation precision in direct proportion to the measurement frequency, and can effectively improve the calculation precision.
2. The relative capacity and ambient temperature relation model of the storage battery has strong applicability.
3. The capacity allocation method can be used for capacity allocation of the optical storage station, the selection interval of the relative capacity can be used for stabilizing power of the optical storage system, the capacity of the same energy storage device is not required to be increased, the capacity allocation method can be applied to constant volume of the optical storage system, the capacity allocation method has the advantages of simplicity and high efficiency, and the capacity allocation method of the storage battery does not influence intervention of other energy storage technologies.
4. The invention considers the influence of the ambient temperature on the storage battery, and has strong applicability in geographic position and time scale.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a conceptual diagram of an application area in an embodiment of the present invention.
Fig. 3 is a graph of single photovoltaic digestion in an embodiment of the present invention.
Fig. 4 is a graph showing the relative capacity of the energy storage battery versus the ambient temperature in an embodiment of the invention.
The figure indicates:
100. 200 parts of single photovoltaic power generation system, 200 parts of regional photovoltaic power generation system cluster, 300 parts of photovoltaic power generation and corresponding load combined system, 400 parts of energy storage battery, 500 parts of regional concentrated load, 600 parts of regional load cluster, 700 parts of serial number, 800 parts of single photovoltaic power generation system corresponding load.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples. The present embodiment is implemented on the premise of the technical scheme of the present invention, and a detailed implementation manner and a specific operation process are given, but the protection scope of the present invention is not limited to the following examples.
Examples
As shown in fig. 1, the invention provides a capacity configuration method of an energy storage battery based on distributed photovoltaic centralized absorption, wherein the external factors influencing the energy storage battery are composed of the power output of each distributed photovoltaic and the corresponding basic power load of a user, and are also key influencing factors, a relation curve is drawn by considering the relation between the relative capacity of the battery and the ambient temperature, a theoretical relation curve mathematical model is established, a local environment temperature change interval is considered, a relative capacity change interval of the battery in the local area is calculated, and the initial capacity of the battery is combined, so that the final capacity of the battery is finally obtained.
As shown in fig. 2, the combined photovoltaic power generation and corresponding load system 300 mainly comprises a single photovoltaic power generation system 100 and a single photovoltaic power generation system corresponding load 800. Establishing a mathematical model of the generated time-by-time power of the single photovoltaic power generation system 100 and the corresponding load 800 power of the single photovoltaic power generation system on a time scale, wherein a specific load change curve is shown in fig. 3, and the preliminary capacity determination relation of the energy storage battery is as follows:
in which W is Battery For storing energyThe preliminary capacity of the battery 400; p (P) pv(i) Distributing the instantaneous power of the photovoltaic system for the ith group; p (P) load(i) Instantaneous power for the i-th group of user base loads; t is t 0 For calculating a starting time point of the cycle; t is t 1 Calculating an ending time point of the period; n represents the maximum group number of the distributed photovoltaic system; dt represents the differentiation in time.
The serial number 700 is derived from the subscript i in the above equation in order to rank all photovoltaic power generation within the area with the corresponding load for convenient calculation in combination with the system 300.
In the practical application process, the time differential dt cannot be measured accurately, and the model needs to be simplified to obtain:
wherein m represents the number of measurements;
representing the measurement frequency; j represents the measurement order, and the feasibility of calculation for guarantee can be simplified as follows:
wherein, the liquid crystal display device comprises a liquid crystal display device,
is the frequency of actual data acquisition.
Final calculated preliminary capacity W of battery 400 Battery 。
As shown in fig. 4, the data of the relative capacity of the energy storage battery 400 according to the change of the ambient temperature are obtained through experiments, the points of the data are connected into a line, and the following mathematical model is used for fitting:
C R ＝A 2 +(A 1 -A 2 )/(1+exp((T-T 0 )/dT)
wherein C is R The relative capacity of the storage battery is expressed in units of; t represents a ringAmbient temperature, in degrees celsius; a is that 1 、A 2 、 T 0 dT is the fit estimate constant.
Fitting to obtain a smooth curve, and calculating the minimum value C of the relative capacity of the energy storage battery in combination with the local annual environmental temperature change interval Rmin Finally, the initial capacity of the energy storage battery is combined to calculate the capacity of the energy storage battery suitable for local distributed photovoltaic concentrated digestion, and the method comprises the following steps:
the invention is not a matter of the known technology.
The above embodiments are provided to illustrate the technical concept and features of the present invention and are intended to enable those skilled in the art to understand the content of the present invention and implement the same, and are not intended to limit the scope of the present invention. All equivalent changes or modifications made in accordance with the spirit of the present invention should be construed to be included in the scope of the present invention.
Claims (2)
1. The energy storage battery capacity configuration method based on distributed photovoltaic centralized absorption is characterized by comprising the following steps of:
1) Establishing a preliminary storage battery capacity model considering external influence factors, and determining the preliminary storage battery capacity according to the preliminary storage battery capacity model;
11 Acquiring power generation power change data of each distributed photovoltaic power generation system;
12 Acquiring user base load electricity utilization data corresponding to each distributed photovoltaic power generation system;
13 Establishing a preliminary storage battery capacity model;
the expression of the preliminary storage battery capacity model is:
wherein W is Battery For the primary capacity of the accumulator, P pv(i) Generating instantaneous power, P, for an ith group of distributed photovoltaic systems load(i) For the i-th group of user base load instantaneous power, t 0 To calculate the starting time point of the cycle, t 1 For calculating the ending time point of the period, n is the maximum group number of the distributed photovoltaic system, and dt is the differential amount of time;
in practical application, the time differential dt cannot be accurately measured, so that the initial capacity model of the storage battery is simplified into:
where m is the total number of measurements,
representing the measurement frequency, j representing the number of measurements during the measurement;
in order to ensure the feasibility of calculation, the primary capacity model of the storage battery after primary simplification is secondarily simplified into:
wherein Δt is the frequency of actual data acquisition;
2) Establishing a mathematical model of the relative capacity of the storage battery and the change of the environmental temperature taking into consideration the internal influence factors of the storage battery;
21 Measuring the relation between the relative capacity of the storage battery and the change of the ambient temperature;
22 Drawing a connection line between the relative capacity of the storage battery and an ambient temperature change point;
23 Establishing a mathematical model of the relative capacity of the storage battery and the change of the ambient temperature;
the expression of the mathematical model of the relative capacity of the storage battery and the change of the ambient temperature is as follows:
C R ＝A 2 +(A 1 -A 2 )/(1+exp((T-T 0 )/dT)
wherein C is R Is the relative capacity of the storage battery, T is the local environment temperature, A 1 、A 2 、T 0 Are fitting estimated value constants;
3) Determining the final capacity of the storage battery by combining the initial capacity of the storage battery and the relative capacity of the storage battery;
31 Acquiring the minimum value C of the relative capacity of the storage battery according to the change interval of the local annual environment temperature Rmin ；
32 Primary capacity W of the battery calculated from the primary capacity model of the battery Battery And minimum value of relative capacity of battery C Rmin Calculating the final capacity of the deposit battery;
combined with the preliminary capacity W of the energy storage battery Battery Calculating the capacity of the energy storage battery suitable for local distributed photovoltaic concentrated absorption, namely the final capacity W of the battery Battery-end The following steps are:
2. the method for configuring the capacity of the energy storage battery based on the centralized absorption of the distributed photovoltaic system according to claim 1, wherein the step 31) is specifically:
fitting by combining the change interval of the local annual environment temperature to obtain the relative capacity C of the storage battery R And obtaining the minimum value C of the relative capacity of the energy storage battery Rmin 。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011535546.9A CN112583038B (en) | 2020-12-22 | 2020-12-22 | Energy storage battery capacity configuration method based on distributed photovoltaic centralized absorption |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011535546.9A CN112583038B (en) | 2020-12-22 | 2020-12-22 | Energy storage battery capacity configuration method based on distributed photovoltaic centralized absorption |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112583038A CN112583038A (en) | 2021-03-30 |
| CN112583038B true CN112583038B (en) | 2023-06-02 |
Family
ID=75138871
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011535546.9A Active CN112583038B (en) | 2020-12-22 | 2020-12-22 | Energy storage battery capacity configuration method based on distributed photovoltaic centralized absorption |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112583038B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102005807A (en) * | 2010-12-24 | 2011-04-06 | 华北电力大学（保定） | Method for regulating photovoltaic power generation system through super capacitor energy storage system |
| CN108923446A (en) * | 2018-06-07 | 2018-11-30 | 国网天津市电力公司电力科学研究院 | The configuration method of stored energy capacitance in a kind of photovoltaic/energy storage integrated system |
| CN109378842A (en) * | 2018-11-01 | 2019-02-22 | 国网辽宁省电力有限公司电力科学研究院 | Electric heat accumulation load and battery energy storage, which are coordinated to maximize, reduces peak valley difference method |
| CN110707737A (en) * | 2019-11-28 | 2020-01-17 | 国网内蒙古东部电力有限公司经济技术研究院 | High-permeability new energy power grid battery capacity configuration method based on cloud computing |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP6556649B2 (en) * | 2016-03-14 | 2019-08-07 | 株式会社東芝 | Storage battery evaluation device, storage battery, storage battery evaluation method, and program |
-
2020
- 2020-12-22 CN CN202011535546.9A patent/CN112583038B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102005807A (en) * | 2010-12-24 | 2011-04-06 | 华北电力大学（保定） | Method for regulating photovoltaic power generation system through super capacitor energy storage system |
| CN108923446A (en) * | 2018-06-07 | 2018-11-30 | 国网天津市电力公司电力科学研究院 | The configuration method of stored energy capacitance in a kind of photovoltaic/energy storage integrated system |
| CN109378842A (en) * | 2018-11-01 | 2019-02-22 | 国网辽宁省电力有限公司电力科学研究院 | Electric heat accumulation load and battery energy storage, which are coordinated to maximize, reduces peak valley difference method |
| CN110707737A (en) * | 2019-11-28 | 2020-01-17 | 国网内蒙古东部电力有限公司经济技术研究院 | High-permeability new energy power grid battery capacity configuration method based on cloud computing |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112583038A (en) | 2021-03-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107294122B (en) | Layered dynamic control method for hybrid energy storage system | |
| CN104037793B (en) | A kind of energy-storage units capacity collocation method being applied to active distribution network | |
| CN108599138B (en) | Energy storage system capacity configuration method considering micro-grid distributed energy uncertainty | |
| CN101950980B (en) | Capacity configuration method of energy storing device for regulating and controlling synchronization of distributed photovoltaic power supply | |
| CN103248048B (en) | Abandoned wind electric quantity estimation method | |
| CN106374498B (en) | A kind of micro-capacitance sensor tidal current computing method considering the control of secondary voltage frequency | |
| CN105552969A (en) | Power prediction-based distributed output power smoothing method and system for photovoltaic generation | |
| CN108487994A (en) | A kind of micro- energy net composite energy storage system | |
| CN103326388A (en) | Power prediction based micro-grid energy storage system and capacity configuration method | |
| CN103326389A (en) | Power prediction based micro-grid energy storage system and capacity configuration method | |
| CN113159423A (en) | Multi-energy combined optimization scheduling operation method based on wind, fire and light storage coordination | |
| CN112381375A (en) | Power grid economic operation domain rapid generation method based on power flow distribution matrix | |
| CN115330021A (en) | Comprehensive energy operation optimization system and method considering methane electric heat utilization ratio | |
| CN112968515B (en) | Energy management strategy and system for emergency power supply of fuel cell | |
| CN112583038B (en) | Energy storage battery capacity configuration method based on distributed photovoltaic centralized absorption | |
| CN117411007A (en) | Distribution network low-voltage treatment method combining distributed photovoltaic and energy storage | |
| CN112636340A (en) | Optimized operation method of wind power-pumped storage combined power generation system | |
| CN104485672A (en) | Photovoltaic inverter group self-balancing control method and system applicable to micro grid | |
| CN109617183B (en) | Intelligent power supply method of multi-battery system | |
| CN103489043B (en) | The optimization method of a kind of wind-powered electricity generation installation and energy-storage battery capacity ratio | |
| Luo et al. | Mutual information for evaluating renewable power penetration impacts in a distributed generation system | |
| Xie et al. | Tie-line Power Smoothing Strategy of Integrated Energy System Using Separate Storage of Heat and Electricity | |
| CN104485685A (en) | Solar and storage integrated self-balancing control method and system applicable to distribution network | |
| CN104485679A (en) | Wind and storage integrated self-balancing control method and system applicable to distribution network | |
| CN105373844A (en) | Day-ahead power generation planning method and system based on wind power heating system with heat storage |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |