CN105576825A - An energy management system and method for a smart micro-grid comprising a plurality of renewable energy sources - Google Patents
An energy management system and method for a smart micro-grid comprising a plurality of renewable energy sources Download PDFInfo
- Publication number
- CN105576825A CN105576825A CN201510859522.1A CN201510859522A CN105576825A CN 105576825 A CN105576825 A CN 105576825A CN 201510859522 A CN201510859522 A CN 201510859522A CN 105576825 A CN105576825 A CN 105576825A
- Authority
- CN
- China
- Prior art keywords
- module
- micro
- grid
- data analysis
- battery
- 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.)
- Pending
Links
Classifications
-
- 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
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P80/00—Climate change mitigation technologies for sector-wide applications
- Y02P80/10—Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
- Y02P80/14—District level solutions, i.e. local energy networks
Landscapes
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses an energy management system and method for a smart micro-grid comprising a plurality of renewable energy sources. The system comprises a man-machine communication module, a data analysis module, a prediction module, a decision optimization module and a display module. The data analysis module carries out analysis on output characteristic of a micro power source and operation condition of a current micro-grid system according to information obtained by the man-machine communication module and the prediction module to obtain an optimal control scheme; and the optimal control scheme is executed by the decision optimization module. The optimal control scheme is obtained through the analysis of the data analysis module to maintain power balance of internal power of the micro-grid and the load and stabilization of voltage and frequency, so that a distributed power supply is allowed to be made fullest use of, the advantages of low carbon and economy of the micro-grid is given full play to, and system safety and power supply reliability of the micro-grid are improved.
Description
Technical field
The present invention relates to electric power system technical field of new energy power generation, particularly a kind of intelligent micro-grid EMS containing multiple renewable energy sources and method.
Background technology
Intelligent micro-grid refer to collected by distributed power source, energy storage device, energy conversion device, associated loadings and monitoring, protective device be small-sizedly transported to electric system; it by the scheduling between the energy, can improve the power supply reliability of distributed generation system and the utilance of terminal energy sources.
The micro battery that micro-capacitance sensor comprises, the power output as photovoltaic generation unit, wind power generation unit has the feature of intermittence and randomness, and the power consumption of load is also vary constantly, drastically influence the stable operation of intelligent micro-grid.The renewable generator unit of spatter property that micro-capacitance sensor comprises simultaneously is vulnerable to extraneous interference, and randomness is strong, greatly compromises the fail safe of system.Therefore need to carry out energy management to micro battery, load and energy storage device in intelligent micro-grid.Existing intelligent micro-grid energy management technology, intelligent micro-grid energy management method is formulated mainly through adopting the mode of analog simulation, do not solve generating randomness, the unsteadiness because of micro battery, these destabilizing factors such as the mobility of load bring impact on micro-capacitance sensor, thus cause differing with actual conditions comparatively large, affect the security of system of micro-capacitance sensor, power supply reliability, the precision of Systematical control and validity.Therefore, how solving the above problems, is problem demanding prompt solution.
Summary of the invention
Object of the present invention aims to provide a kind of intelligent micro-grid EMS containing multiple renewable energy sources
Another object of the present invention is to coordinate above-mentioned system, and provides a kind of intelligent micro-grid energy management method containing multiple renewable energy sources.The present invention can draw optimization control scheme by data analysis module analysis, maintain stablizing of the power-balance of micro-capacitance sensor internal power and load and voltage and frequency, distributed power source is maximized the use, give full play to micro-capacitance sensor low-carbon (LC), economic advantage, improve security of system, the power supply reliability of micro-capacitance sensor.
For realizing above-mentioned object, technical scheme of the present invention is: a kind of intelligent micro-grid EMS containing multiple renewable energy sources, comprising man-machine communication's module, data analysis module, prediction module, decision optimization module and display module, man-machine communication's module, prediction module are connected with data analysis module respectively, data analysis module and decision optimization model calling, described man-machine communication's module, prediction module, data analysis module are connected with display module respectively with decision optimization module.
Above-mentioned intelligent micro-grid EMS, described data analysis module comprises database and statistics storehouse, and database is connected with man-machine communication's module and prediction module respectively, described statistics storehouse and DataBase combining.
Above-mentioned intelligent micro-grid EMS, the forecasting object of described prediction module comprises information on load, renewable energy source information and market guidance information.
System of the present invention adopts above-mentioned technical scheme, whole system is made up of man-machine communication's module, data analysis module, prediction module, decision optimization module and display module, carry out data interaction with data analysis module respectively by man-machine communication's module, prediction module, data analysis module can carry out safety analysis according to this and from the micro battery power producing characteristics of prediction module and payload data by from the micro battery of man-machine communication's module and load species number; Carry out data interaction by data analysis module and decision optimization module, after decision optimization module receiving and analyzing result, make final decision; Be connected with display module respectively with decision optimization module by man-machine communication's module, prediction module, data analysis module, achieve the technical purpose of the system aspects state of micro-capacitance sensor being carried out to effective monitoring, staff can be made to understand the operating mode of real time execution, and the situation for randomness makes timely process.
Containing an intelligent micro-grid energy management method for multiple renewable energy sources, it comprises the following steps
Step one: the information obtaining various micro battery, load and storage battery;
Step 2: the information according to obtaining judges whether the sum of exerting oneself of various micro battery is greater than electric energy needed for load; If so, one is then carried into execution a plan; If not, then two are carried into execution a plan;
Scheme one: judge whether current battery capacity has residual capacity, if there is residue, then to charge in batteries, if do not remain, then to grid power transmission;
Scheme two: judge whether current battery capacity has residual capacity, if there is residue, then from electrical network power taking; If no residue, then by battery discharging.
Above-mentioned intelligent micro-grid energy management method, in step one, the information of described micro battery, load and storage battery is followed successively by micro-source category of micro battery and power producing characteristics, the kind of load and size and accumulator electric-quantity information.
Above-mentioned intelligent micro-grid energy management method, the micro-source category of described micro battery and load kind are obtained by man-machine communication's module.
Above-mentioned intelligent micro-grid energy management method, described micro battery power producing characteristics and payload are obtained by prediction module.
By data analysis module, above-mentioned intelligent micro-grid energy management method, in step 2, judges whether exerting oneself of micro battery is greater than electric energy needed for load, and to be carried into execution a plan one or scheme two by decision optimization module.
Method of the present invention adopts above-mentioned technical scheme, the information of various micro battery, load and storage battery is obtained by man-machine communication's module and prediction module, by data analysis module, analyzing and processing is carried out to information and draw optimum results, decision optimization module performs optimum results, to meet the thermoelectricity workload demand in system, guarantee the operation agreement between micro-capacitance sensor and major network system, make energy resource consumption and system loss reach minimum, make the operational efficiency of distributed power source reach the highest.The method is not only applicable to the micro-capacitance sensor under isolated power grid pattern, also parallel net type micro-capacitance sensor is applicable to, and it is pioneering by judging whether the sum of exerting oneself of various micro battery is greater than electric energy needed for load, carry out cutting load according to the significance level of load or enable stand-by power supply or from electrical network power taking, to maintain the stable of the power-balance of system internal power and load and voltage and frequency, improve the security of system of micro-capacitance sensor, power supply reliability.
Accompanying drawing explanation
Below in conjunction with the specific embodiment in accompanying drawing, the present invention is described in further detail, but does not form any limitation of the invention.
Fig. 1 is the syndeton block diagram of present system;
Fig. 2 is the flow chart of the inventive method.
In figure: 1 is man-machine AC module, 2 is data analysis module, and 21 is database, and 22 is statistics storehouse, and 3 is prediction module, and 4 is decision optimization module, and 5 is display module.
Embodiment
As shown in Figure 1, a kind of intelligent micro-grid EMS containing multiple renewable energy sources, it comprises man-machine communication's module 1, data analysis module 2, prediction module 3, decision optimization module 4 and display module 5, man-machine communication's module 1, prediction module 3 are connected with data analysis module 2 respectively, data analysis module 2 is connected with decision optimization module 4, and man-machine communication's module 1, data analysis module 2, prediction module 3 are connected with display module 5 respectively with decision optimization module 4; Data analysis module 2 comprises database 21 and statistics storehouse 22, and database 21 is connected with man-machine communication's module 1 and prediction module 3 respectively, and statistics storehouse 22 is connected with database 21; The forecasting object of prediction module 3 comprises information on load, renewable energy source information and market guidance information.
In the specific implementation, man-machine communication's module 1 sets micro battery kind and the load kind of micro-capacitance sensor, and real time information is gathered, the database 21 of data analysis module 2 stores the real time data from man-machine communication's module 1, the historical data that prediction module 3 stores according to data analysis module 2, to information on load, renewable energy source information and market guidance are predicted, the database 21 of data analysis module 2 stores predicting the outcome from prediction module 3, data analysis module 2 according in database predict the outcome and historical data carry out System Safety Analysis, decision optimization module 4 carries out decision-making according to the analysis result from data analysis module 2, perform optimal case, and all results of man-machine communication's module 1, data analysis module 2, prediction module 3, decision optimization module 4 all transfer to display module 5, staff is monitored by display module 5 pairs of network systems, the topological structure of micro-capacitance sensor and the access situation of all electric components can be checked by display module 5, and the state of energy real-time operation switch and disconnecting link, control the working method of micro-capacitance sensor.The operation information of system will show in display module 5, the real time data such as the voltage facilitating staff's real-time monitoring system to gather, electric current, meritorious, idle, temperature.
As depicted in figs. 1 and 2, a kind of intelligent micro-grid energy management method containing multiple renewable energy sources, comprises the following steps
Step one: the information obtaining various micro battery, load and storage battery; The micro-source category of micro battery and load kind is obtained, the micro battery power producing characteristics obtained by prediction module 3 and payload by man-machine communication's module 1; Wherein, micro battery can be photovoltaic generation, wind power generation and other distributed power sources.
Step 2: judge whether the sum of exerting oneself of various micro battery is greater than electric energy needed for load according to the information obtained by data analysis module 2; If so, one is then carried into execution a plan; If not, then two are carried into execution a plan; Wherein, scheme one or scheme two are realized by decision optimization module 4;
Scheme one: system of the present invention still has some residual electric energy after giving corresponding load by power delivery, if when now remaining battery capacity does not also reach maximum permission charging capacity, system is just to charge in batteries; If electric energy still has residue, just to grid power transmission after storage battery is full of electricity.
Scheme two: system of the present invention makes up electric energy breach from battery discharging or from electrical network power taking, if now storage battery can not discharge again or will dump energy discharge after still can not meet the electrical energy demands of load, cutting load will be carried out according to the significance level of load or enable stand-by power supply or from electrical network power taking.
In sum, the present invention, as specification and diagramatic content, makes actual sample and through repeatedly use test, from the effect of use test, provable the present invention can reach its desired object, and practical value is unquestionable.Above illustrated embodiment is only used for conveniently illustrating the present invention, not any pro forma restriction is done to the present invention, such as data prediction device, data correction device can be integrated and predict power output and revise, have in any art and usually know the knowledgeable, if do not depart from the present invention carry in the scope of technical characteristic, utilize the Equivalent embodiments that the done local of disclosed technology contents is changed or modified, and do not depart from technical characteristic content of the present invention, all still belong in the scope of the technology of the present invention feature.
Claims (8)
1. the intelligent micro-grid EMS containing multiple renewable energy sources, it is characterized in that: comprise man-machine communication's module (1), data analysis module (2), prediction module (3), decision optimization module (4) and display module (5), man-machine communication's module (1), prediction module (3) is connected with data analysis module (2) respectively, data analysis module (2) is connected with decision optimization module (4), described man-machine communication's module (1), data analysis module (2), prediction module (3) is connected with display module (5) respectively with decision optimization module (4).
2. intelligent micro-grid EMS according to claim 1, it is characterized in that: described data analysis module (2) comprises database (21) and statistics storehouse (22), database (21) is connected with man-machine communication's module (1) and prediction module (3) respectively, and described statistics storehouse (22) is connected with database (21).
3. intelligent micro-grid EMS according to claim 1, is characterized in that: the forecasting object of described prediction module (3) comprises information on load, renewable energy source information and market guidance information.
4., containing an intelligent micro-grid energy management method for multiple renewable energy sources, its feature comprises the following steps
Step one: the information obtaining various micro battery, load and storage battery;
Step 2: the information according to obtaining judges whether the sum of exerting oneself of various micro battery is greater than electric energy needed for load; If so, one is then carried into execution a plan; If not, then two are carried into execution a plan;
Scheme one: judge whether current battery capacity has residual capacity, if there is residue, then to charge in batteries, if do not remain, then to grid power transmission;
Scheme two: judge whether current battery capacity has residual capacity, if there is residue, then from electrical network power taking; If no residue, then by battery discharging.
5. intelligent micro-grid energy management method according to claim 4, it is characterized in that: in step one, the information of described micro battery, load and storage battery is followed successively by micro-source category of micro battery and power producing characteristics, the kind of load and size and accumulator electric-quantity information.
6. intelligent micro-grid energy management method according to claim 5, is characterized in that: the micro-source category of described micro battery and load kind are obtained by man-machine communication's module.
7. intelligent micro-grid energy management method according to claim 5, is characterized in that: described micro battery power producing characteristics and payload are obtained by prediction module.
8. intelligent micro-grid energy management method according to claim 4, is characterized in that: in step 2, judges whether exerting oneself of micro battery is greater than electric energy needed for load by data analysis module, and to be carried into execution a plan one or scheme two by decision optimization module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510859522.1A CN105576825A (en) | 2015-11-30 | 2015-11-30 | An energy management system and method for a smart micro-grid comprising a plurality of renewable energy sources |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510859522.1A CN105576825A (en) | 2015-11-30 | 2015-11-30 | An energy management system and method for a smart micro-grid comprising a plurality of renewable energy sources |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105576825A true CN105576825A (en) | 2016-05-11 |
Family
ID=55886638
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510859522.1A Pending CN105576825A (en) | 2015-11-30 | 2015-11-30 | An energy management system and method for a smart micro-grid comprising a plurality of renewable energy sources |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105576825A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111082464A (en) * | 2019-11-29 | 2020-04-28 | 广东工业大学 | Micro-grid energy real-time management system |
| CN115689167A (en) * | 2022-10-11 | 2023-02-03 | 国网浙江省电力有限公司 | Micro-grid energy optimization scheduling system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102097828A (en) * | 2010-12-30 | 2011-06-15 | 中国电力科学研究院 | Wind power optimal scheduling method based on power forecast |
| CN102361328A (en) * | 2011-10-25 | 2012-02-22 | 中国科学技术大学 | Wind and light complement distributed micro-grid system for comprehensively utilizing commercial power |
| CN102710013A (en) * | 2012-05-23 | 2012-10-03 | 中国电力科学研究院 | Park energy-network energy optimizing management system based on microgrids and implementing method thereof |
| CN102856930A (en) * | 2012-10-11 | 2013-01-02 | 天津市电力公司 | Micro-grid economic dispatching control method |
| CN104852373A (en) * | 2015-04-29 | 2015-08-19 | 南方电网科学研究院有限责任公司 | Dynamic economic dispatch optimization method for independent power grid containing intermittent energy |
-
2015
- 2015-11-30 CN CN201510859522.1A patent/CN105576825A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102097828A (en) * | 2010-12-30 | 2011-06-15 | 中国电力科学研究院 | Wind power optimal scheduling method based on power forecast |
| CN102361328A (en) * | 2011-10-25 | 2012-02-22 | 中国科学技术大学 | Wind and light complement distributed micro-grid system for comprehensively utilizing commercial power |
| CN102710013A (en) * | 2012-05-23 | 2012-10-03 | 中国电力科学研究院 | Park energy-network energy optimizing management system based on microgrids and implementing method thereof |
| CN102856930A (en) * | 2012-10-11 | 2013-01-02 | 天津市电力公司 | Micro-grid economic dispatching control method |
| CN104852373A (en) * | 2015-04-29 | 2015-08-19 | 南方电网科学研究院有限责任公司 | Dynamic economic dispatch optimization method for independent power grid containing intermittent energy |
Non-Patent Citations (3)
| Title |
|---|
| 吴雄等: "微电网能量管理系统研究综述", 《电力自动化设备》 * |
| 陈深等: "微电网中储能技术研究进展与展望", 《广东电力》 * |
| 雒志秀等: "微网平滑切换的控制策略研究", 《可再生能源》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111082464A (en) * | 2019-11-29 | 2020-04-28 | 广东工业大学 | Micro-grid energy real-time management system |
| CN115689167A (en) * | 2022-10-11 | 2023-02-03 | 国网浙江省电力有限公司 | Micro-grid energy optimization scheduling system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Reddy et al. | A review of Integration, Control, Communication and Metering (ICCM) of renewable energy based smart grid | |
| Li et al. | The comprehensive evaluation of smart distribution grid based on cloud model | |
| CN104715340A (en) | Cloud computing energy management system and method based on green energy resources | |
| CN103020853A (en) | Method for checking short-term trade plan safety | |
| CN111009895B (en) | Microgrid optimal scheduling method, system and equipment | |
| AL-Jumaili et al. | Advancements in intelligent cloud computing for power optimization and battery management in hybrid renewable energy systems: A comprehensive review | |
| CN104348205A (en) | SOC-SOH (state of charge-state of health)-based distributed BMS (Battery Management System) | |
| CN104319774A (en) | Monitoring method and device for intelligent community | |
| Casini et al. | Optimal energy management and control of an industrial microgrid with plug-in electric vehicles | |
| CN107154626A (en) | Distributed photovoltaic intelligent energy manages SaaS systems with energy storage | |
| CN103887792B (en) | A kind of low-voltage distribution network modeling method containing distributed power source | |
| CN104932281A (en) | Household micro-power-grid energy-using system and realization method for intelligent electricity consumption interaction thereof | |
| CN116799844B (en) | Portable distributed energy storage system | |
| CN106159998A (en) | Regenerative resource micro-capacitance sensor Optimal Scheduling | |
| CN105046593A (en) | Intelligent power distribution and utilization evaluation method conforming to low-carbon energy policy | |
| Shahab et al. | Advanced optimal design of the IoT based university campus microgrid considering environmental concerns and demand response | |
| CN115063052A (en) | Electric energy metering chip-based electric power data processing method and computer equipment | |
| CN105550788A (en) | Intelligentized data processing and analyzing method for microgrid | |
| Yang et al. | Review on vulnerability analysis of power distribution network | |
| CN105576825A (en) | An energy management system and method for a smart micro-grid comprising a plurality of renewable energy sources | |
| CN105321050A (en) | Method for measuring false data injection attack damage to dynamic micro-grid division in smart power grid | |
| CN112186785A (en) | Source network load storage balance system based on platform district intelligent terminal | |
| CN106651113A (en) | Dispatcher operation risk evaluation method based on advanced N-1 analysis | |
| CN115706413A (en) | Micro-grid scheduling device and method | |
| CN109768568A (en) | Distributed generation resource based on big data analysis accesses distribution network planning remodeling method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20160511 |
|
| RJ01 | Rejection of invention patent application after publication |