CN102135760A - Neural network energy coordinated controller for microgrid - Google Patents
Neural network energy coordinated controller for microgrid Download PDFInfo
- Publication number
- CN102135760A CN102135760A CN2010105924879A CN201010592487A CN102135760A CN 102135760 A CN102135760 A CN 102135760A CN 2010105924879 A CN2010105924879 A CN 2010105924879A CN 201010592487 A CN201010592487 A CN 201010592487A CN 102135760 A CN102135760 A CN 102135760A
- Authority
- CN
- China
- Prior art keywords
- power
- microgrid
- controller
- neural network
- control
- 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
Images
Landscapes
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention belongs to the field of distributed power generation and smart power grid control, relates to a neural network-based microgrid energy coordination central processor, and particularly provides a smart energy central controller which can utilize a BP (Back Propagation) neural network to control a microgrid comprising a wind power generation unit, a gas turbine generation unit, a PV (photovoltaic) generation unit, a load tap changing transformer, various loads and other units. In the implementing process, actual power of each micro-power supply, loaded actual power and system frequency are utilized as 9 input nodes of the neural network controller; and a network mapping relationship between the 9 input nodes and 11 output nodes is constructed by using a single hidden layer BP neural network containing 12 hidden layer nodes, so that energy balance management of a microgrid system is controlled, and self-adaptive connection between the microgrid and large grids is realized.
Description
Technical field
The invention belongs to distributed power generation and intelligent grid control field, be specifically related to a kind of energy and coordinate central controller based on neural network.
Background technology
Along with the development of world economy and the aggravation of energy crisis, there has been support energetically in China to microgrid and intelligent development thereof during 11th Five-Year, and has obtained certain achievement.Between 12 periods of expansion, country will further advance the construction and the practicability development thereof of microgrid and intelligent microgrid by means of the development opportunity of intelligent grid.The intelligence microgrid is exactly the intellectuality of microgrid, utilize advanced equipment and advanced control device that multiple generating set and terminal user are optimized management in microgrid, making it provides more reliable higher-quality electric energy and provides the measure of service all to belong to the research category of intelligent microgrid for big electrical network for the user.
At present, the related content of microgrid research mainly comprises independently wind-power electricity generation, photovoltaic generation and wind light mutual complementing and the Control System Design of honourable bavin cogeneration etc.The generation mode of certain regenerative resource generally has the shortcoming of intermittent generating separately, so microgrid more trends towards multiple distributed power source is joined together to generate electricity.In order to improve system effectiveness, also often co-design is carried out in cooling, heat supply and generating simultaneously.In design microgrid electricity generation system, generally the method for designing of Cai Yonging is that the power consumption according to load, the Sun Day of microgrid address shine radiation intensity and wind-force mean intensity etc., determines the capacity of interior renewable energy power generation control system of microgrid and relevant energy-storage units.Operation control and optimum management for this novel hybrid power system of microgrid also relate to less.Using intelligent algorithms such as fuzzy and neural network comparatively ripe in the modern control field that the microgrid electricity generation system is optimized control is one of trend of microgrid intelligent development from now on.Especially, the power division of the micro power in the microgrid and load coupling are to need the gordian technique that solves in the microgrid management control, there are problems such as control accuracy is low, efficient is low in traditional the power control and the control of load switching that rule of thumb micro power are provided, and the utilization Based Intelligent Control will overcome above shortcoming.
Summary of the invention
The present invention answers the demand of intelligent microgrid development just, and a kind of intelligent controller that can utilize Based Intelligent Control to realize microgrid self-energy Rational flow is provided, and reaches the power of each micro power and load node is controlled.Realize the optimized distribution of interior each micro power of microgrid, and be connected with the self-adaptation of big electrical network to load.For this reason, the present invention adopts following technical scheme:
Described little electrical network comprises that wind-power electricity generation micro power and local area controller 1 thereof (contain fling-cut switch S
1), gas turbine power generation micro power and local area controller 2 thereof (contain fling-cut switch S
2), photovoltaic generation micro power and local area controller 3 thereof (contain fling-cut switch S
3), load and change-over switch S thereof
Load, central energy controller.In addition, after different distributions formula power supply is formed little electrical network, be connected with electrical network in conjunction with ULTC S.
Described ULTC adopts DSP that it is carried out Electronic Control.Described local area controller 1 and local area controller 3 adopt sagging control mode, and local area controller 2 adopts the PQ power control mode.
Described central energy controller adopts the BP neural network control method, flux matched with energy is target, set up the relation of real power and reference power, fling-cut switch and ULTC S, realize power optimization management and bearing power matching problem each micro power in the microgrid.
The intelligent microgrid energy tuning controller that the present invention proposes based on neural network, adopt the BP neural network that the power of each node in the microgrid is optimized control, intelligent microgrid energy controller has the reference power and the fling-cut switch control function of regulating each miniature source according to the actual loading demand automatically.Simultaneously, this controller has self-adaptation and regulates inference function, and self study and parallel computation function.
Particularly, have following technology beneficial effect:
1) microgrid adopts ULTC to be connected with big electrical network, has seamless self-adaptation linkage function;
2) ULTC has the mobile function of power bi-directional;
3), realize the realtime power coupling control of arbitrary node in the microgrid according to the load node variable power;
4) microgrid central authorities energy controller adopts distinctive nerual network technique, has intelligent characteristics such as self study, parallel computation;
5) local area controller has defencive functions such as overvoltage, overload, and central controller then also has remote control function.
Description of drawings
Fig. 1 is microgrid topological structure and control chart thereof.
Fig. 2 coordinates central controller based on the energy of neural network.
Embodiment
Fig. 1 is the microgrid topology control structure figure based on central energy controller, and wherein power distribution network is responsible for powering to the load in microgrid self electricity shortage.S is a ULTC, is responsible for being connected and separating between power distribution network and microgrid.Distributed power source comprises in the microgrid: wind-power electricity generation micro power, gas turbine micro power, PV micro power.The wind-power electricity generation micro power is jointly controlled by local area controller 1 and central energy controller; The gas turbine micro power is jointly controlled by local area controller 2 and central energy controller; The PV micro power is jointly controlled by local area controller 3 and central energy controller.Load is made up of each type load, comprises constant-impedance load 1, motor load 2 and nonlinear load 3.Fig. 2 is central energy controller schematic diagram, is specially to adopt 9 input nodes, the feed-forward type BP nerve network controller of 12 hidden nodes and 11 output nodes.
As shown in Figure 1, microgrid of the present invention at first utilizes voltage, current sensor to obtain voltage and current signal with central energy controller and calculates wind-power electricity generation micro generation unit real power P
1And Q
1, gas turbine micro power generator unit real power P
2And Q
2, PV micro power generator unit real power P
3And Q
3Utilize the frequency pressure converter to obtain the frequency signal f of system then.So, central authorities' energy controller has just obtained 9 input node signals, adopt the BP nerve network controller of 12 hidden nodes (output function of each node is the logsigmoid function) and 11 output nodes (each node function is the tansigmoid function) designs corresponding three layers (single hidden layers) then, obtain the required reference input P of local area controller
Ref1, Q
Ref1, P
Ref2, Q
Ref2, P
Ref3And Q
Ref3, and micro power fling-cut switch S
1, S
2, S
3Control signal, load fling-cut switch S
LoadSignal and Loading voltage regulator S control signal.Normal operation is (minimum load power demand＜miniature source provides general power＜maximum load power demand) down, and central energy controller only carries out the reference power input to three micro generation unit and regulates control, does not carry out load switching and micro power switching.The maximum general power that can provide when micro power is during less than the load power demand, and nerve network controller is with output load fling-cut switch S
LoadControl signal and ULTC S control signal are carried out the system capacity Balance Control.The power that provides when micro power is during much larger than the required power of load, and nerve network controller will be exported micro power fling-cut switch S
1, S
2, S
3Control signal is carried out the system capacity Balance Control, thereby reaches the energy-saving run effect.By above control strategy, realize that finally the energy automatic equalization of microgrid system is distributed, guaranteed the normal reliable operation of microgrid.Simultaneously, central energy controller has also designed remote communicating function, makes the microgrid system have remote control function.
Claims (3)
1. central controller of realizing microgrid energy control based on the BP neural network, described microgrid comprises wind-power electricity generation unit, gas turbine power generation unit, PV generator unit, ULTC and all kinds of loads etc., after different distributions formula power supply is formed microgrid, be connected with power distribution network in conjunction with ULTC, wherein, all micro power unit all adopt central energy controller and local area controller to jointly control mode to control.
2. central energy controller according to claim 1, it is characterized in that: adopt the real power of real power, load of each micro power and system frequency 9 input nodes as nerve network controller, with the single hidden layer BP neural network that comprises 12 hidden nodes, construct the network mapping relation of 9 input nodes and 11 output nodes, thereby the energy automatic equalization of control microgrid system is distributed, and realizes that microgrid is connected with the self-adaptation of power distribution network.
3. local area controller according to claim 1 is characterized in that: the miniature gas turbine micro power adopts the PQ power control mode with local area controller, and PV generating micro power and wind-power electricity generation micro power adopt sagging control mode with local area controller.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2010105924879A CN102135760A (en) | 2010-12-16 | 2010-12-16 | Neural network energy coordinated controller for microgrid |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2010105924879A CN102135760A (en) | 2010-12-16 | 2010-12-16 | Neural network energy coordinated controller for microgrid |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN102135760A true CN102135760A (en) | 2011-07-27 |
Family
ID=44295564
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2010105924879A Pending CN102135760A (en) | 2010-12-16 | 2010-12-16 | Neural network energy coordinated controller for microgrid |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102135760A (en) |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102494430A (en) * | 2011-10-23 | 2012-06-13 | 西安交通大学 | Cold-electricity cogeneration system comprising wind power and gas combined cycle unit and method for scheduling cold-electricity cogeneration system |
| CN102545255A (en) * | 2011-12-26 | 2012-07-04 | 重庆大学 | Photovoltaic and micro gas turbine mixed micro grid coordinated operation control method |
| WO2013120347A1 (en) * | 2012-02-17 | 2013-08-22 | 中国电力科学研究院 | Control method for unifying self-balancing and self-smoothing of micro-grid |
| CN103825363A (en) * | 2014-02-26 | 2014-05-28 | 中国农业大学 | Wind-solar low voltage storage micro-grid group protection coordinating controller |
| CN104184166A (en) * | 2014-08-29 | 2014-12-03 | 东南大学 | Micro-grid system with functions of improving operation, control and protection performance |
| CN105278484A (en) * | 2014-07-17 | 2016-01-27 | 国家电网公司 | Coordination apparatus and coordination method for hydroelectric power generation and energy storage device in power distribution network |
| CN105305500A (en) * | 2014-07-17 | 2016-02-03 | 国家电网公司 | Output coordination device and output coordination method for wind power generation equipment and photovoltaic power generation equipment of power distribution network |
| CN105811405A (en) * | 2016-03-25 | 2016-07-27 | 贵州电网有限责任公司 | Optimization control method of wind, power and moisture power generation unified operation wide system |
| CN106842909A (en) * | 2015-09-09 | 2017-06-13 | 爱默生过程管理电力和水解决方案公司 | For the sign based on model of the pressure/load relation of power plant spatial load forecasting |
| CN110601246A (en) * | 2019-08-14 | 2019-12-20 | 上海电力大学 | Direct-current micro-grid current sharing method based on radial basis function neural network prediction |
| CN110705029A (en) * | 2019-09-05 | 2020-01-17 | 西安交通大学 | Flow field prediction method of oscillating flapping wing energy acquisition system based on transfer learning |
| CN111682593A (en) * | 2020-05-29 | 2020-09-18 | 黑龙江苑博信息技术有限公司 | Thermal power generating unit coordination optimization method based on neural network model state observer |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040124812A1 (en) * | 2002-12-27 | 2004-07-01 | General Electric Company | Distributed resource (DR) stabilization control for microgrid applications |
| CN2679901Y (en) * | 2003-04-18 | 2005-02-16 | 新疆新能源股份有限公司 | Larege power intelligence optical-net-firewood mutual compensating power station |
| JP2008061382A (en) * | 2006-08-31 | 2008-03-13 | Toshiba Corp | Microgrid power supply and demand adjusting system |
| WO2008109263A1 (en) * | 2007-03-01 | 2008-09-12 | Wisconsin Alumni Research Foundation | Non-inverter based distributed energy resource for use in a dynamic distribution system |
| DE102008057199A1 (en) * | 2008-11-13 | 2009-07-02 | Daimler Ag | Controller arrangement for motor vehicle, has artificial neural network comprising neurons, which are interlaced together by bus system i.e. controller area network bus in simple topology |
| CN101630840A (en) * | 2009-08-12 | 2010-01-20 | 电子科技大学 | Intelligent control system for microgrid energy |
| CN101719667A (en) * | 2009-12-01 | 2010-06-02 | 深圳市科陆电子科技股份有限公司 | Distributed type management and transfer method of load |
-
2010
- 2010-12-16 CN CN2010105924879A patent/CN102135760A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040124812A1 (en) * | 2002-12-27 | 2004-07-01 | General Electric Company | Distributed resource (DR) stabilization control for microgrid applications |
| CN2679901Y (en) * | 2003-04-18 | 2005-02-16 | 新疆新能源股份有限公司 | Larege power intelligence optical-net-firewood mutual compensating power station |
| JP2008061382A (en) * | 2006-08-31 | 2008-03-13 | Toshiba Corp | Microgrid power supply and demand adjusting system |
| WO2008109263A1 (en) * | 2007-03-01 | 2008-09-12 | Wisconsin Alumni Research Foundation | Non-inverter based distributed energy resource for use in a dynamic distribution system |
| DE102008057199A1 (en) * | 2008-11-13 | 2009-07-02 | Daimler Ag | Controller arrangement for motor vehicle, has artificial neural network comprising neurons, which are interlaced together by bus system i.e. controller area network bus in simple topology |
| CN101630840A (en) * | 2009-08-12 | 2010-01-20 | 电子科技大学 | Intelligent control system for microgrid energy |
| CN101719667A (en) * | 2009-12-01 | 2010-06-02 | 深圳市科陆电子科技股份有限公司 | Distributed type management and transfer method of load |
Cited By (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102494430A (en) * | 2011-10-23 | 2012-06-13 | 西安交通大学 | Cold-electricity cogeneration system comprising wind power and gas combined cycle unit and method for scheduling cold-electricity cogeneration system |
| CN102545255A (en) * | 2011-12-26 | 2012-07-04 | 重庆大学 | Photovoltaic and micro gas turbine mixed micro grid coordinated operation control method |
| WO2013120347A1 (en) * | 2012-02-17 | 2013-08-22 | 中国电力科学研究院 | Control method for unifying self-balancing and self-smoothing of micro-grid |
| CN103825363B (en) * | 2014-02-26 | 2015-11-18 | 中国农业大学 | A kind of wind-light storage low pressure micro-capacitance sensor group protection coordination controller |
| CN103825363A (en) * | 2014-02-26 | 2014-05-28 | 中国农业大学 | Wind-solar low voltage storage micro-grid group protection coordinating controller |
| CN105305500B (en) * | 2014-07-17 | 2018-06-19 | 国家电网公司 | A kind of power distribution network wind power plant and photovoltaic power generation equipment output conditioning unit and output coordination approach |
| CN105278484A (en) * | 2014-07-17 | 2016-01-27 | 国家电网公司 | Coordination apparatus and coordination method for hydroelectric power generation and energy storage device in power distribution network |
| CN105305500A (en) * | 2014-07-17 | 2016-02-03 | 国家电网公司 | Output coordination device and output coordination method for wind power generation equipment and photovoltaic power generation equipment of power distribution network |
| CN105278484B (en) * | 2014-07-17 | 2018-05-15 | 国家电网公司 | A kind of power distribution network hydroelectric generation and energy storage device conditioning unit and coordination approach |
| CN104184166B (en) * | 2014-08-29 | 2016-01-20 | 东南大学 | The micro-grid system that a kind of operation, control and protection performance improve |
| CN104184166A (en) * | 2014-08-29 | 2014-12-03 | 东南大学 | Micro-grid system with functions of improving operation, control and protection performance |
| CN106842909A (en) * | 2015-09-09 | 2017-06-13 | 爱默生过程管理电力和水解决方案公司 | For the sign based on model of the pressure/load relation of power plant spatial load forecasting |
| CN105811405A (en) * | 2016-03-25 | 2016-07-27 | 贵州电网有限责任公司 | Optimization control method of wind, power and moisture power generation unified operation wide system |
| CN110601246A (en) * | 2019-08-14 | 2019-12-20 | 上海电力大学 | Direct-current micro-grid current sharing method based on radial basis function neural network prediction |
| CN110601246B (en) * | 2019-08-14 | 2022-12-06 | 上海电力大学 | Direct-current micro-grid current sharing method based on radial basis function neural network prediction |
| CN110705029A (en) * | 2019-09-05 | 2020-01-17 | 西安交通大学 | Flow field prediction method of oscillating flapping wing energy acquisition system based on transfer learning |
| CN111682593A (en) * | 2020-05-29 | 2020-09-18 | 黑龙江苑博信息技术有限公司 | Thermal power generating unit coordination optimization method based on neural network model state observer |
| CN111682593B (en) * | 2020-05-29 | 2023-04-18 | 黑龙江苑博信息技术有限公司 | Thermal power generating unit coordination optimization method based on neural network model state observer |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102135760A (en) | Neural network energy coordinated controller for microgrid | |
| CN102832706B (en) | Distributed power stratified coordination control system of microgrid and method | |
| CN102074952B (en) | Independent micro-grid system | |
| Sun et al. | Advances on distributed generation technology | |
| CN103872701A (en) | Energy-storage type alternating current and direct current mixed micro-grid and control method thereof | |
| CN106385024A (en) | Modular electric energy router device and implementation method thereof | |
| CN109066822A (en) | A kind of multi-point dispersion formula distribution system dispatching method based on electric power electric transformer | |
| CN108039722A (en) | A kind of distribution type renewable energy system Optimal Configuration Method suitable for alternating current-direct current mixing | |
| CN109193803A (en) | Multiple-energy-source intelligent control integratedization system and multiple-energy-source intelligent control method | |
| CN103117564A (en) | Coordinated control system and method for wind-solar hybrid power generation | |
| CN104333036A (en) | Multi-source coordination control system | |
| CN202798010U (en) | Micro-grid distributed power supply layering coordination control system | |
| CN105426985B (en) | Urban distribution network voltage distribution optimization method suitable for roof photovoltaic access | |
| CN203596618U (en) | Cabinet-type DC power supply system | |
| CN108418245A (en) | A kind of direct-current grid interconnection constant-power control method of simplification | |
| CN109524985A (en) | A kind of wireless electric vehicle charging device and method based on wind-light storage | |
| CN103378604A (en) | Smart micro-grid | |
| CN205070576U (en) | Hybrid -type circuit topology structure | |
| CN105048505B (en) | A kind of wind-solar complementary type micro-grid system for intelligent residential district | |
| CN106786744A (en) | A kind of circuit topology of the single-point type electric power energy collector of integrated distributed plant-grid connection | |
| CN106300425B (en) | A kind of distributed energy management method based on users'comfort | |
| CN115864475A (en) | Wind and light storage capacity optimal configuration method and system | |
| CN113131497B (en) | Small hydropower microgrid power balance control method for electric automobile participating in planned island | |
| CN204230929U (en) | A kind of multi-source coordinated control system | |
| CN210867281U (en) | Multifunctional complementary park intelligent micro-grid system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C02 | Deemed withdrawal of patent application after publication (patent law 2001) | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20110727 |