CA3212040A1

CA3212040A1 - Integrated regional renewable energy control system

Info

Publication number: CA3212040A1
Application number: CA3212040A
Authority: CA
Inventors: Ji Hun Shin; Hyun Gu Yeo
Original assignee: Bitek Information & Communication Inc
Current assignee: Bitek Information & Communication Inc
Priority date: 2021-01-28
Filing date: 2021-11-29
Publication date: 2022-08-04
Also published as: KR20220109124A; KR102625403B1; WO2022163994A1

Abstract

An embodi ment of the present i nventi on provi des an i ntegrated regi onal renewabl e energy control system compri si ng: a renewabl e energy cont rol i nf rast r uct ure whi ch i s connect ed t o a gr i d syst em t hat col l ects renewabl e energy gener at i on i nf or mat i on about a renewabl e energy generati on source wi t hi n each renewabl e energy generati on zone i n a regi on, and col I ects gri d data i ncl udi ng t he renewabl e energy generat i on i nf or mat i on; and an appl i cat i on uni t whi ch communi cat es wi t h t he renewabl e energy cont rol i nf rastructure to recei ve the gri d data, determi nes the stabi l i ty of a power grid in the regi on on the basi s of the gri d data, and generates output control i nf ormati on accordi ng to the stabi I i ty of the power gri d, wherei n the gri d system col l ects the renewabl e energy generati on i nformati on about the renewabl e energy generati on source through a pl ural i ty of i nf ormati on col l ecti on termi nal s, and the renewabl e energy control i nf rast ruct ure cant rol s t he amount of renewabl e ener gy generati on of each renewabl e energy generati on zone wi t hi n the regi on accordi ng to the output control i nformati on.

Description

INTEGRATED REGIONAL RENEWABLE ENERGY CONTROL SYSTEM
TECHNICAL FIELD
[1] The present i nventi on rel at es to an i ntegrated regi onal renewable energy control system, and more particularly, to an i ntegrated regi onal renewabl e energy control system capabl e of determi ni ng the i mpact of renewabl e energy generati on on the power gri d of a regi on and control I i ng the amount of renewabl e energy generation of each renewable energy generation zone wi thi n the regi on accordi ng to the determi nati on resul ts.
BACKGROUND ART

[2] I n the 2011 Durban General Assembly, it was agreed to form a new climate regi me after 2020 i n which both devel oped and developing countries part i ci pate as a follow-up to the Kyoto Protocol . I n addi ti on, with the si gni ng of the Par i s Agreement i n December 2015, the new cl i mate regi me bei ng applied to all countries was i ntroduced i n 2020, and in Ii ne with thi s new cl i mate regi me, new energy i ndust ri es centered on renewabl e energy are bei ng promoted.

[3] Renewabl e energi es refer to energi es whi ch are renewabl e i ncl udi ng sunl i ght, water, preci pi tat i on, bi ol ogi cal organi sms and the I i ke, and power generati on usi ng them i ncl udes sol ar energy, wi nd energy, hydroelectric energy and the I i ke.

[4] These renewabl e energi es have advantages of bei ng cl ean and no fear of depl et i on, as well as bei ng renewable without poll uti on, but have di sadvantages that the amount of generati on is less and that the amount of generati on is al so affected by weather conditions compared to basel oad generation such as petrol eum, coal , nucl ear power and the I i ke.

[5] Specifically, the renewable energy has charact er i st i cs of the uncert ai nty that is di f f i cult to predict an out put for generati on and high van i ability i n the amount of output because the renewable energy is dependent on natural condi ti ons (solar i rradi ance, temperature, wi nd and the I i ke).

[6] As an example, in the case of solar generation, the amount of generati on is intermittent because it is greatly affected by weather condi ti ons such as the amount of sunlight, and the uncertainty of the amount of generati on is al so high because it is difficult to accurately predict the weather condi ti ons, .

[7] Fl G. 1 is a di agram for expl ai ni ng the necessi ty of managi ng reserve power due to the intermittence of the amount of renewable energy generation.

[8] As shown i n Fl G. 1, a renewabl e energy generated i n each generati on zone 1 i s suppl i ed to an power network 3. I n addi ti on, an energy generated from the basel oad generati on means 2 such as petrol eum, coal and nucl ear i s al so suppl i ed to the power network 3, and thus the renewable energy and the basel oad generati on energy are combined in the power network 3.

[9] As an example, in case that the renewable energy is an energy created by solar generation, as shown in a grape of FIG.

1, the amount of basel oad generati on requi red dun i ng the dayti me i s reduced, and the power reserve capacity requi red after the sunset becomes hi gher than dun i ng the dayti me.

[10] On the other hand, i n case that the amount of renewabl e energy generati on dun i ng the dayti me is reduced due to weather condi ti ons, the amount of the basel oad generati on is further requi red as much as the reduced amount of renewable energy generati on and for the above reasons, if the predi cti on error for the generati on of renewable energy i ncreases, a difference occurs between the amount of the pl anned generati on and the actual amount of power supply and therefore, it is necessary to i ncrease the reserve power to cope with the predi cti on error.
This has a probl em I eadi ng to an i ncrease i n generati on costs.

[11] Therefore, there needs to be an i ntegrated renewabl e energy control system that can respond to renewabl e energy vol at i I i ty and generati on acceptance issues by predicting and controlling the amount of renewabl e energy generati on and stably operate (moni t or i ng, predi cti ng, control I i ng and the I i ke) the regi onal power grid.
DETAILED DESCRIPTION OF THE INVENTION
TECHNICAL TASKS

[12] A techni cal task to be achi eyed by the present i nventi on i s to pr ovi de an i nt egr at ed regi onal renewabl e energy control system capabl e of determi ni ng the i mpact of renewabl e energy generati on on the regi onal power grid and control I i ng the renewable energy production through the processes of the output predi cti on, stability/acceptance I i mi t eval uati on and output control of each renewable energy generation zone in the region according to the determi nati on result.

[13] Other technical task to be achieved by the present invention is to provi de an i n- memory application database unit optimized for control of a regional power grid.

[14] Another techni cal task to be achieved by the present i nventi on i s to provi de an appl i cat i on i nf rastructure that provi des an envi ronment for renewabl e energy output predi cti on, stability/acceptance I i mi t eval uati on and output control performance i n conj uncti on with a renewabl e energy generati on source and a grid system in the region.

[15] Still another techni cal task to be achieved by the present invention is to provi de an analysis infrastructure capable of warehousing by distributed-parallel processing grid data, weather data and a pl ural i ty of i nf ormati on generated i n the course of eval uati ng the stability/acceptance I i mi t of the power gri d, and anal yzi ng the warehoused bi g data i n real ti me.

[16] The techni cal tasks to be achi eyed by the present i nventi on are not limited to the above-mentioned techni cal tasks, and other techni cal tasks not menti oned above will be cl early understood by those ski I I ed i n the art from the descri pti on bel ow.
TECHNI CAL SOLUTI ON

[17] I n or der to achi eve the above t echni cal tasks, one embodi ment of the present i nventi on provi des an i ntegrated regional renewable energy control system comprising:
a renewable energy control i nf rastructure bei ng connected to a gri d system that aggregates renewabl e energy generati on information from a renewable energy generati on source in each renewable energy generati on zone i n a region for col I ecti ng gri d data i ncl udi ng the renewable energy generati on i nf ormati on; and an appl i cat i on unit for communi cat i ng with the renewabl e energy control i nf rast r uct ur e to receive the grid data, determining power grid stability of the region based on the grid data, and generati ng output control i nf ormati on accordi ng to the power gri d stability, wherei n the gri d system col I ects the renewable energy generati on i nf ormati on of the renewable energy generation source by means of a plurality of information col I ecti on termi nal s, and wherei n the renewable energy control i nf r ast r uct ur e control s the amount of renewable energy generation of each renewable energy generation zone in the regi on accordi ng to the output control i nf ormati on.

[18] The grid system comprises a Supervisory Control And Data Acqui si ti on( SCADA) module for communicating with each of the pl ural i ty of i nf ormati on col I ecti on termi nal s i n real ti me to col I ect the renewabl e energy generati on i nf or mat i on.

[19] The grid system includes an energy management system ( EMS) for col I ecti ng basel oad generati on data, power facility information and power facility characteristic information in the regi on, the gri d data further i ncl udi ng data collected by the EMS
when the renewabl e energy generati on i nf or mat i on i s col I ected, wherei n the power facility i nf ormati on is i nf ormati on on power facilities connected to the power gri d of the regi on, and wherei n the power facility char act er i sti c i nf or mat i on i s i nf or mat i on i ndi cat i ng characteri sti cs of each of power facilities connected to the power gri d of the regi on.

[20] The integrated regional renewable energy control system further compri ses a di st r i but ed parallel processi ng unit for provi di ng weather data of the regi on to the renewable energy control infrastructure, wherei n the appl i cat i on unit compri ses:
a weather prediction modul e for generati ng weather predi cti on information of the renewable energy generati on zone based on the weather data;
a renewabl e energy output predi cti on modul e for generati ng output predi cti on i nf ormati on of the renewable energy generati on zone based on the weather predi cti on i nf ormat i on and the gri d data;
other grid analysis module being configured to operate based on power facility char act eri sti c i nf or mat i on and power facility i nf or mat i on, wherei n the other gri d anal ysi s module cal cul at es the exact magni tude and phase angl e of a bus vol tage based on the dynamic and stat i c i nf ormati on of the power facility and generates state est i mat i on result i nf ormat i on by detect i ng an over I oad of I i ne and transformer, a viol at i on of bus voltage const rai nt and a vi ol at i on of reactive power const rai nt of generator and synchronous condenser based on the cal cul at ed val ue;
a stability eval uat i on modul e for generat i ng a stability eval uat i on i nf or mat i on of the regi onal power grid based on at least two or more of the out put predi ct i on i nf ormat i on, state estimation result information, power facility characteristic i nf or mat i on and power facility i nf ormat i on;
an acceptance limit evaluation module for generating acceptance limit eval uat i on i nf ormat i on based on the voltage standard viol at i on, facility and t ransmi ssi on I i ne overl oad, t ransi ent stability and renewabl e energy I ow vol t age ri de through ( LVRT) and the magnitude of the fault current of the regi onal power gri d; and a renewable energy output control module for generat i ng the out put control i nf or mat i on based on the stability eval uat i on i nf or mat i on and the acceptance limit eval uat i on i nf or mat i on, wherei n the application unit returns the weather predi ct i on i nf or mat i on, the out put predi ct i on i nf or mat i on, the state est i mat i on result i nf or mat i on, the stability eval uat i on i nf or mat i on, the acceptance limit eval uat i on i nf or mat i on and the out put control i nf or mat i on to the renewable energy control i nf rastructure.

[21] The renewable energy generati on source is a wi nd generati on source, and the renewable energy output prediction module can col I ect wi nd speed and wi nd generati on data of a predetermi ned period of the renewable energy generati on source; set an ARI MAX
model based on at I east some of the wi nd speed and wi nd generati on data of the predetermi ned period of ti me to esti mate a f i rst amount of generati on; set a polynomial regressi on model based on at I east some of the wi nd speed and wi nd generati on data of the predetermi ned period of ti me to esti mate a second amount of generati on; esti mate a t hi rd amount of generati on based on wi nd speed data at a poi nt near the renewable energy generati on source; and generate out put predi cti on i nf or mat i on based on an anal og ensembl e by usi ng the f i rst amount of generati on, the second amount of generati on, the t hi rd amount of generati on and the past wi nd speed and wi nd generati on data of the renewabl e energy generati on source.

[22] The renewabl e energy output predi cti on modul e can col I ect wi nd speed predi cti on data at a poi nt near the renewabl e energy generati on source and spatial data near the renewable energy generati on source; predict the wi nd speed at the I ocati on of the renewable energy generati on source based on a Kr i gi ng technique;
correct the wi nd speed accor di ng to the altitude of the renewabl e energy generati on source based on the Deacon equati on;
and esti mate the t hi rd amount of generati on based on the corrected wi nd speed.

[23] The renewable energy management i nf rastructure i ncl udes an infrastructure management unit, wherei n the i nf rastruct ure management unit i ncl udes an i memory database management modul e, an i nt egr at ed process management modul e, an al arm/event management modul e, and a I og management modul e, wherei n the i n- memory database management module controls the executi on, control, state management of the i n- memory database unit and the process of modul es bel ongi ng to the appl i cat i on unit, wherei n the i ntegrated process management module controls the process of each component i n the renewabl e energy control i nf r ast r uct ur e based on process management i nf or mat i on, a predetermi ned pri or i ty and a current state of each component i n the renewable energy control i nf r ast r uct ur e, and stores and handl es the al arm and event generated i n the control process, wherei n the alarm/event management module stores and handl es al arm and event information generated in the grid system and transmits the al arm and event i nf or mat i on to the i nt egr at ed control unit and di stri buted parallel processi ng unit, and wherei n the log management module generates a log file by ref erri ng to the process log i nf ormati on stored i n the i n- memory database unit, records log i nf ormati on i n the I og file accordi ng to a log level and del et es the log i nf ormati on of the log file accordi ng to a predetermi ned cycl e.

[24] The renewable energy management i nf rast ruct ure further i ncl udes an i nf rastructure management i nf or mat i on memory whi ch is connected to the infrastructure management unit and which stores the process management i nf ormati on, the meta i nf ormati on of the in-memory database, the power facility modeling i nf or mat i on, the power facility char act er i sti c i nf or mat i on and module information of the SCADA module.

[25] The di stri but ed paral I el processi ng uni t recei ves the weather data of the region from an external weather database or weather server and provide the weather data to the renewable energy control infrastructure.

[26] The renewable energy control i nf rast r uct ure i ncl udes a real-time database and wherein the real-time database stores the grid data and i nf ormati on returned from the application unit.

[27] The di stri but ed parallel processi ng unit compr i ses:
a data collection unit that collects data and i nf or mat i on stored in the real -ti me database;
a data I oadi ng unit for di stri but i ng the data or i nf ormati on collected by the data collection unit and I oadi ng the data or i nf ormati on i nto a non- rel at i onal database or a di stri but ed file system;
a data processi ng search unit for queryi ng the data or i nf or mat i on I oaded i nto the data I oadi ng unit, convert i ng the data or i nf ormati on i nto a predetermi ned format and warehousi ng the converted data; and a data analysis application unit for secondly analyzing the stability of the regional power grid.

[28] The data collection unit i ncl udes a f i rst di st ri but ed queue module, a grid data col I ecti on/ I oadi ng module, a second distributed queue module, and a weather data col I ect i on/ I oadi ng modul e, wherein the first distributed queue module is connected to the real-time database to receive data stored in the real-time database, and pushes the recei ved data to the grid data collection/loading module, and wherei n the second di stri buted queue modul e i s connected to at I east one of an power di st r i but i on aut omat i on system, a meteri ng data management system and a weather database or a weather server, and receives data from the connected configuration and pushes the received data to the weather data col I ect i on/ I oadi ng modul e.

[29] The data processi ng search uni t i ncl udes a SQL processi ng engi ne, an aggregate i nf ormati on generati on module, an aggregate i nf or mat i on generati on hi story management modul e and a data warehousi ng modul e, wherei n the SQL processi ng engi ne queri es data I oaded i n the non- rel at i onal database or the di st ri but ed file system and loads the data i n the data warehousi ng modul e, wherei n the aggregate i nf ormati on generati on module generates aggregate i nf or mat i on of data loaded i n the non- r el at i onal database or di stri buted file system and loads the aggregate i nformati on i n the data warehousi ng modul e, and wherei n the aggregate i nformati on gener at i on hi story management module generates generat i on hi story i nformati on of the aggregate i nformati on, key aggregates and stati sti cal meta i nformati on and I oads them i nto the data warehousi ng modul e.

[30] The data analysis appl i cat i on unit i ncl udes an art i f i ci al neural network model whi ch I earns based on the data stored i n the data warehousi ng module, receives at least some of the data I oaded i n the non- rel at i onal database or the di stri but ed file system as an i nput val ue and esti mates the amount of renewabl e energy generati on i n the regi on.

[31] The integrated regional renewable energy control system further compri ses an i ntegrated control unit which recei ves the data warehoused into the data loading unit and visualizes the data to provi de to a user, wherei n the i nt egrat ed control unit generates a control message i n response to a user' s i nput, and wherei n the control message control s the amount of renewabl e energy generation in each renewable energy generation zone in the regi on i n preference to the output control i nformati on.

[32] The renewable energy generation source is connected to an i nverter, the output control i nformati on i s transmitted to the i nformati on col I ecti on termi nal , and the i nformati on col I ecti on termi nal control s the amount of generat i on of the renewabl e energy generation source by controlling the inverter.

[33] The i nf or mat i on coil ect i on t ermi nal is a remote t ermi nal unit and wherei n the i nterval that the i nf or mat i on coil ecti on t ermi nal coil ect s the renewable energy generati on i nf or mat i on i s 1 second or I ess.
EFFECTS OF THE INVENTION

[34] Accordi ng to an embodi ment of the present i nventi on, based on the grid data collected through the SCADA module of the grid system, the power usage envi ronment data of the regi on and the weather data, the out put amount of the renewabl e energy generati on source i n the regi on is predi cted to generate output control information, and the amount of generation of each renewable generati on zone in the regi on or the renewable energy generati on source belonging to the each renewable generati on zone i s control led usi ng the output control i nf ormati on, thereby reduci ng the I oad of the power gri d due to the i ntermi ttency of the renewabl e energy.

[35] In addition, according to an embodiment of the present i nventi on, it is possi bl e to predict the output of a renewabl e energy generati on source, thereby establ i shi ng an a generati on pl an i n advance based on the predi cted val ue and reduci ng power grid operati ng costs through automati c control .

[36] In addition, according to an embodiment of the present i nventi on, a vast amount of gri d data and i nf ormati on generated by the oper at i on of the appl i cat i on unit are stored/ managed/anal yzed by the di st ri but ed parallel processi ng unit, thereby i mprovi ng the overall data processi ng capability of the i ntegrated regi onal renewabl e energy control system.

[37] It shoul d be understood that effects of the present i nventi on are not limited to the effects descri bed above and encompass all effects that can be i nf er red from the conf i gur at i on descri bed i n the descri pt i on of the present i nventi on or the cl ai ms.
BRI EF DESCRI PTI ON OF THE DRAW! NGS

[38] Fi gure 1 i s a di agram for expl ai ni ng a process i n whi ch a load is generated in the power network due to the intermittency of renewable energy generation.
Fi gure 2 i s a bl ock di agram schemati call y showi ng an i ntegrated r egi onal renewabl e energy control system accor di ng to an embodiment of the present invention.
Fi gure 3 i s a di agram for expl ai ni ng a renewabl e power gener at i on i nf ormati on col I ecti on unit and a gri d system associated therewith according to an embodiment of the present i nventi on.
Fi gure 4 i s a bl ock di agram for expl ai ni ng a renewabl e energy control i nf rastruct ure and an appl i cat i on unit accordi ng to an embodiment of the present invention.
Fi gure 5 i s a di agram for expl ai ni ng a process i n whi ch a renewable energy control i nf rastructure is associ ated with an i ntegrated control unit and a di stri but ed parallel processi ng unit according to an embodiment of the present invention.

Fi gure 6 i s an exempl ary di agram for expl ai ni ng a process i n which a renewable energy out put prediction module generates output predi cti on i nf ormati on of a generati on zone i n a regi on accordi ng to an embodi ment of the present i nventi on BEST MODE FOR CARRY! NG OUT THE I NVENTI ON
[44] Her ei naf ter, the present i nventi on will be descri bed with reference to the accompanyi ng drawi ngs. However, the present invention may be embodied in many different forms and thus is not I i mi ted to the embodi ments descri bed herei n. I n addi ti on, i n order to cl early expl ai n the present i nventi on i n the drawi ngs, parts i r rel evant to the descri pt i on are omitted, and si mi I ar reference numeral s denotes si mi I ar parts throughout the speci f i cat i on.
[45] In the entire specification, when a part is said to be "connected (coup! ed, contacted, combi ned) " with another part, t hi s i ncl udes not only the case of bei ng "di rect I y connected"
but al so the case of being "i ndi rect I y connected" with another member i n between.
I n addi ti on, when a part " compr i ses" a certai n component, it means that it may further i ncl ude other components not excl udi ng other components unl ess ot herwi se stated.
[46] Terms used in this specification are only used to descri be specific embodi ments, and are not i ntended to limit the present i nventi on. Si ngul ar expressi on i ncl udes pl ural expressi on unl ess the context clearly dictates otherwise.
It should be understood that the terms "compri se" or "have" in this specification are i ntended to desi gnate that a feature, number, step, operati on, component, part or combi nati on thereof descri bed i n the speci f i cat i on exi sts and that the possi bi I i ty of the presence or addition of one or more other features or numbers, steps, oper at i ons, components, parts, or combi nati ons thereof i s not excl uded i n advance.
[47]
[48] Her ei naf t er, embodi ment s of the present i nvent i on will be descri bed i n detail with reference to the accompanyi ng drawi ngs.
[49] Figure 2 is a block di agram schematically showi ng an i ntegrated regi onal renewable energy control system accordi ng to an embodi ment of the present i nventi on.
[50] As shown i n FIG. 2, the i ntegrated r egi onal r en ewa b I e energy control system may i ncl ude a renewable generati on i nf ormati on collection unit 100, a grid system 200, a renewabl e energy control i nf rastructure 300, an appl i cat i on unit 400, an i ntegrated control unit 50 and a di stri but ed parallel processi ng uni t 600.
[51] The renewabl e gener at i on i nf or mat i on col I ect i on unit 100 may col I ect gener at i on i nf or mat i on of each renewabl e energy generation zone in the region. As an example, the renewable gener at i on i nf or mat i on col I ecti on unit 100 may i ncl ude a pl ur al i ty of i nf or mat i on collection t ermi nal s 110, 120 and 130 and may be respectively i nst al led i n a pl ural i ty of renewabl e energy generat i on zones. Speci f i cal I y, the pl ur al i ty of i nf or mat i on coil ecti on termi nal s 110, 120 and 130 may be f i el d termi nal devi ces i nst al I ed to monitor, measure and control the renewable energy generati on source within each renewable energy generati on zone.
[52]
As an example, the renewable generati on information col I ecti on unit 100 can perform the f unct i ons of digital conversi on of meter CT and PT measurement val ues and data transmission to the renewable generati on data linkage module, conversi on and rel ay transmi ssi on i n an i nf ormati on communication manner requested by the renewable generati on data I i nkage modul e, and col I ecti on and transmi ssi on of basic power qual i ty i nf ormati on.
[53] As an example, the generati on i nf ormati on collected by each of the i nf or mat i on col I ecti on termi nal s 110, 120 and 130 bel ongi ng to the renewabl e generati on i nf or mat i on col I ecti on uni t 100 may be converted i nto a predetermi ned protocol and transmitted to the grid system 200.
[54] The gri d system 200 may monitor the state of the power gri d i n the regi on based on the col I ected generati on i nf ormati on. I n addi ti on, the grid system 200 may col I ect and manage the generati on i nf ormati on from not only renewable energy generati on zones in the region but al so basel oad generati on zones P.
[55] In addition, the grid system 20 may transmit the collected i nf ormati on to the renewable energy control i nf rastructure 300.
Herei naf ter, i nf ormati on transmitted by the gri d system 200 to the renewabl e energy control i nf rastructure 300 will be ref erred to as system data.
[56] On the other hand, the renewable energy control i nf rastructure 300 provi des an executi on envi ronment necessary for perf ormi ng the overall f uncti ons of the i ntegrated regi onal renewable energy control system.
[57] As an example, the renewable energy control infrastructure 300 may be associ ated with the appl i cat i on unit 400, and based on gri d data, provi de weather predi cti on, renewabl e energy out put pr edi ct i on, power gri d stability eval uat i on, renewabl e energy out put control , i nput/ out put data management and an executi on envi ronment for perf ormi ng al arm processi ng.
[58] Al so, the renewable energy control i nf rastructure 300 i s connected to each component i ncl udi ng the gri d system 200, the appl i cat i on unit 400, the i ntegrated control unit 500 and the di st r i but ed parallel processi ng unit 600 which bel ong to the integrated regi onal renewable energy control system, and can control the overall process of the i ntegrated regi onal renewabl e energy control system.
[59] The components and f uncti ons thereof f ormi ng the renewabl e energy control i nf rastructure 300 will be descri bed i n detail with reference to FIG. 4.
[60]
In addi ti on, the application unit 400 may predict or cal cul ate van i ous i nf or mat i on requi red for st abl e oper at i on of the power grid in association with the renewable energy control i nf rast ruct ure 300.

[061] As an example, the application unit 400 may receive gri d data from the renewable energy control i nf rastructure 300. I n addi ti on, based on the grid data, the appl i cation unit 400 may perform weather predi cti on, renewabl e energy output predi cti on, gri d safety eval uat i on, acceptance I i mi t eval uat i on, and other grid analysis, and generate renewable energy out put control i nformati on based on the performed results. I n addi ti on, the appl i cat i on unit 400 may return the i nformati on generated i n each preformed process to the renewable energy control i nf rast ruct ure 300.
[062] I n addi ti on, the out put control i nformati on may be transmitted to each i nformati on col I ecti on termi nal s 110 and 120 via the grid system 200, and the amount of generation of each renewable energy generation source may be controlled based on the output control i nformati on. Of course, a series of these control processes may be performed automat i cal I y.
[063] In addi ti on, the i ntegrated control unit 500 may be connected to the renewable energy control i nf rastructure 300.
The i ntegrated control unit 500 may receive i nformati on from the renewable energy control infrastructure 300 ( or information start i ng from the renewabl e energy control i nf rastructure 300 and passi ng through the di stri but ed parallel processi ng unit 600) and vi sual i ze the recei ved i nformati on to provi de to the user.
As an example, the integrated control unit 500 may provide the information to the user using a web-based user interface.

[064] In addi ti on, the di st ri but ed parallel processi ng unit 600 may receive grid data from the renewable energy control i nf rastructure 300, and may process the recei ved gri d data i n a di st r i but ed way or i n parallel . As an exampl e, the di st r i but ed paral I el processi ng unit 600 may perform f uncti ons of col I ecti ng, I oadi ng, processi ng, searchi ng, anal yzi ng and appl yi ng the gri d data. The detail ed conf i gur at i on and functions of t hi s di st ri but ed parallel processi ng unit 600 will be descri bed i n detail with reference to FIG. 5.
[065] Figure 3 is a diagram for explaining the renewable generati on i nf ormat i on collection unit 100 and the grid system 200 associated with it according to an embodiment of the present i nvent i on.
[066] As shown i n FIG. 3, the renewabl e generati on i nf ormati on col I ecti on unit 100 may i ncl ude a pl ural i ty of i nf or mat i on col I ecti on termi nal s. I n FIG. 3, for conveni ence of descri pti on, it is assumed that the renewable generation information col I ecti on unit 100 i ncl udes a f i rst i nf or mat i on col I ecti on termi nal 110 and a second i nf ormati on collection termi nal 120.
[67] The f i rst i nf ormat i on collection termi nal 110 may be connected to a fi rst renewable energy generati on source R11 wi t hi n a f i rst generati on zone. As an exampl e, the f i rst renewable energy generati on source R11 may be wind generation.
[68] As an example, the f i rst renewable energy generati on source R11 may be sequenti ally connected to a transformer R12, a ci rcui t breaker R13 and the f i rst i nf ormati on coil ecti on termi nal 110 through a di stri but i on I i ne.
[69] The transformer may boost the electrical energy produced by the f i rst renewabl e energy generati on source R11 to a distribution level voltage.
[70] The ci rcui t breaker may be i nstal I ed on the di stri but i on I i ne and can detect whether abnormal currents occur due to overcurrent short circuits and earth faults. In addition, the circuit breaker can block the flow of current when an abnormal current occurs. As an exampl e, the ci rcui t breaker may be a vacuum circuit breaker (VCB).
[71] I n addi ti on, the f i rst i nf ormati on collection termi nal 110 may be connected to a meter i ng poi nt of a di stri but i on I i ne through which renewable energy is transmitted or the circuit breaker R13. Al so, the f i rst i nf ormati on collection termi nal 110 may measure power i nformati on of a meter i ng poi nt or a ci rcui t breaker. As an example, the f i rst i nf ormati on col I ecti on termi nal may be connected to the met en i ng poi nt through a PT, CT
cabl e for met eri ng.
[72] I n addi ti on, the f i rst i nf ormati on collection termi nal 110 may transmit the measured power i nf ormati on to the grid system 200.
Herei n, the f i rst i nf or mat i on collection termi nal 110 may convert the power i nf or mat i on accor di ng to a predet ermi ned protocol . As an exampl e, the predetermi ned protocol may be any one of Modbus, DNP and K- DNP.

[73] On the other hand, the f i rst i nf ormat i on coil ecti on termi nal 110 may be connected to the first renewable energy generati on source R11 with a fi rst control devi ce R14 i nterposed t her ebet ween.
As an exampl e, the f i rst i nf ormat i on col I ecti on termi nal 110 may receive output control i nf ormati on from the grid system 200. I n addi ti on, the f i rst i nf or mat i on col I ecti on termi nal 110 may control the output of the f i rst renewable energy generati on source R11 using the first control devi ce R14 based on the recei ved output control i nf ormat i on.
[74] Speci f i cal I y, the f i rst i nf or mat i on collection termi nal 110 may recei ve, through a modem, the moni t or i ng and met er i ng control i nf ormati on recei ved from the renewabl e generati on data I i nkage modul e connected to the grid system 200. I n addi ti on, the f i rst i nf ormat i on col I ecti on termi nal 110 sends a cor r espondi ng request to a sub- dest i nat i on (for example, the f i rst control devi ce R14) accordi ng to a predetermi ned protocol (for example, Modbus) address wherein the sub- desti nati on may be an i nverter ( not shown) connected to the f i rst renewabl e energy generati on source R11.
[75] I n short, the f i rst i nformati on col I ecti on termi nal 110 can control the f i rst renewable energy generati on source R11 based on the output control i nf ormati on recei ved from the grid system so that the amount of generati on of the f i rst renewabl e energy generati on source R11 increases or decreases.

[76] On the other hand, the second i nf or mat i on coil ect i on termi nal 120 may be connected to a second renewabl e energy generation source R21 in the second generation zone. As an example, the second renewable energy generation source R21 may be a solar gener at i on. Herei naf ter, a descri pt i on of a conf i gurat i on over appi ng with the f i rst i nf or mat i on col I ect i on termi nal 110 among the conf i gurati ons of the second i nf ormati on col I ect i on termi nal 120 will be omitted.
[77] As an example, the second renewable energy generation source R21 may be sequentially connected to an inverter R22, a transformer R23, a ci rcui t breaker R24, and the second i nf or mat i on collection termi nal 120 through a di st r i but i on I i ne.
[78] The i nverter R22 may convert DC energy stored i n the collector plate of the second renewable energy generation source R21, that i s, the sol ar col I ect or pl ate, i nto AC energy.
[79] I n addi ti on, the second i nf or mat i on collection termi nal 120 may be connected to a met er i ng poi nt of a di stri but i on I i ne through which renewable energy is transmitted or a ci rcui t breaker R24. Al so, the second i nf or mat i on col I ect i on termi nal may measure power i nf ormat i on of the met er i ng poi nt or ci rcui t breaker R24.
[80] On the other hand, the second i nf ormat i on col I ect i on termi nal 120 may be di rect I y connected to the i nverter R22.
Al so, the second i nf or mat i on col I ect i on termi nal 120 may receive out put control i nf ormat i on transmitted through the grid system 200.

Al so, the second i nf ormati on coil ect i on termi nal 120 may control the amount of generation of the second renewable energy generat i on source R21 by control I i ng the i nverter R22 based on the recei ved output control i nf ormati on.
[81] I n the above, it has been descri bed that the f i rst i nf or mat i on coil ect i on termi nal 110 and the second i nf or mat i on coil ect i on termi nal 120 control the amount of generat i on of the renewable energy generation source using the first control device R14 and the inverter R22, respectively. However, a conf i gurat i on i n whi ch each i nf or mat i on coil ect i on termi nal s and 120 control other conf i gurati ons wi t hi n each generation zone to control the amount of generati on i s al so i ncl uded i n the techni cal i dea of the present i nventi on.
[82] On the other hand, each of the i nf or mat i on coil ect i on termi nal s 110 and 120 bel ongi ng to the r enewabl e gener at i on i nf ormati on coil ecti on unit 100 may be a remote termi nal uni t ( RTU) .
I n addi ti on, the i nf or mat i on coil ect i on termi nal may measure the power i nf ormat i on of the met eri ng poi nts at i nterval s of up to 1 second. Thi s i s because it is necessary to moni tor and anal yze the i nst ant aneous gri d effects i n vi ew of the characteri sti cs of renewable energy generation source with very fast out put f I uct uat i ons and I arge fl uctuat i ons.
[83] I n other words, each i nf ormat i on coil ect i on termi nal s 110 and 120 measure the power i nf ormat i on at i nterval s of up to 1 second, so that the current state of renewable generation can be accurately t i me- synchroni zed.
[84] I n addi ti on, the generati on i nf ormat i on, that is, the power i nf or mat i on col I ected by the renewabl e generati on i nf or mat i on collection unit 100 may be transmitted to the grid system 200 via the renewable generation data linkage module.
[85] Renewabl e generati on data I i nkage modul e Ti may col I ect generati on i nf ormati on transmitted from the renewable generati on i nf or mat i on collection unit 100 and transmit it to the gri d system 200. In addition, the renewable generation data linkage module Ti may transmit the control signal received from the grid system 200 to each i nf ormati on collection termi nal s 110 and 120 bel ongi ng to the renewabl e generati on i nf or mat i on col I ect i on uni t 100.
[86] On the other hand, the gri d system 200 may monitor the state of the power grid in the regi on based on the collected generati on i nf or mat i on.
[87] To t hi s end, the gri d system 200 may i ncl ude a Supervi sory Control and Data Acqui si t i on( SCADA) module 210 for controlling generation sources in each renewable generation zone and collecting the information. The SCADA module 210 may collect generati on i nf ormat i on generated i n each generati on zone i n the regi on i n real ti me.
[88] In addition, the grid system 200 may include an energy management system ( EMS) 220 that col I ect s basel oad generati on data of basel oad generation sources in the regi on and power usage envi ronment data on the amount of consumption i n the regi on. I n thi s case, the basel oad generati on source refers to other generati on source that is not a renewable energy generati on source i n the regi on. However, it goes without sayi ng that the EMS 220 may col I ect generati on data of all generati on sources i n the regi on. Al so, the EMS 220 may f uncti onal I y i ncl ude the SCADA modul e 210.
[89] Figure 4 is a block diagram for explaining the renewable energy control i nf rastructure 300 and the application unit 400 accordi ng to an embodi ment of the present i nventi on.
[90] As shown in FIG. 4, the renewable energy control i nf rastructure 300 may i ncl ude a grid system I i nkage unit 310, an i n- memory database unit 320, an i nf rastructure management unit 330, an i nf rastructure management i nf ormati on memory 340 and a real -ti me I i nkage unit 350.
[91] The grid system I i nkage unit 310 may i ncl ude a grid data receiving module 311 and a control message transmission module 312.
[92] The grid data recei vi ng modul e 311 may receive facility i nf or mat i on and real-ti me generation i nf or mat i on necessary for the operati on of the appl i cat i on unit 400 from the grid system 200.
[93] As an example, the grid data receiving module 311 may receive real -ti me generati on information of each generati on zone i n the regi on from the SCADA modul e 210. I n addi ti on, the gri d data receiving module 311 may receive facility information of each generati on zone in the region from the EMS system 220.
[94] In addition, the grid data receiving module 311 may receive weather data from the di stri buted parallel processi ng unit 600.
As an example, the weather data may be data collected by the di stri buted paral I el processi ng unit 600 from an external server.
As an example, the weather data may i ncl ude at least one of numer i cal weather predi ct i on data, met eorol ogi cal admi ni strati on observati on data, generati on compl ex data, and sol ar i rradi ance measurement data. It goes without sayi ng that the weather data may be collected by other components bel ongi ng to a renewabl e energy control system such as the grid system 200 i n addi ti on to the di stri buted parallel processi ng unit 600.
[95] In addition, the control message transmission module 312 may transmit the output control i nf ormati on generated through the I i nkage between the renewable energy control i nf rastructure 300 and the application unit 400 to the grid system 200. As an exampl e, the output control i nf ormati on may be delivered to each i nf ormati on col I ecti on termi nal s 110 and 120 of each generati on zone in the region via the SCADA module 210.
[96] The i n- memory database unit 320 may i ncl ude a real -ti me database 321 and an appl i cat i on database 322.
[97] The real -ti me database 321 may store facility information, real -ti me generation i nf or mat i on, weather data and the I i ke received by the grid data receiving modul e311 from the grid system 200. I n addi ti on, the real -ti me database 321 may provi de the appl i cat i on unit 400 with stored facility i nf or mat i on, real -time generati on i nf ormati on, weather data and the I i ke.
[98] I n addi ti on, the appl i cat i on unit 400 may i ncl ude a weather i nf or mat i on predi cti on modul e 410, a renewabl e energy out put predi cti on module 420, a stability eval uati on modul e 430, an acceptance limit evaluation module 440, a renewable energy output control module 450 and other grid analysis modul es 460.
[99] The weather information prediction module 410 may generate weather predi cti on i nf ormati on of a renewabl e energy generati on zone i n the regi on based on weather data. As an exampl e, weather predi cti on i nf ormat i on may be predi cted val ues of sol ar i rradi ance, wi nd speed and temperature and the I i ke.
[100] I n addi ti on, the renewable energy out put predi cti on modul e 420 may generate out put prediction i nf ormati on of each renewabl e energy generati on zone i n the regi on based on the weather predi cti on i nf ormati on and grid data. The out put predi cti on i nf ormati on may be the amount of generati on predi cted to be generated i n each renewabl e energy generati on zone.
[101] I n addi ti on, the stability eval uati on module 430 may generate stability eval uati on i nf or mat i on of the power gr i d based on at least two or more of output predi cti on i nf ormati on, state est i mat i on result i nf ormat i on, power facility characteristic i nf ormat i on, and power facility i nf ormat i on.
[102] Her ei n, the power facility character i st i c i nf or mat i on i s i nf ormati on for managi ng the characteri st i cs of each power facility and may be i nf ormat i on such as facility name, capaci ty, facility type, dynamic i nf ormati on, the amount of generati on, frequency, and power factor. Also, the power facility i nf or mat i on may be power facility i nf or mat i on I i nked to the power gri d. As an exampl e, a power facility I i nked to a power grid may be a generator, a transformer, or a switch. I n addi ti on, the state est i mat i on result i nf or mat i on is based on power facility characteristic information and power facility i nf ormati on, cal cul ates the magnitude and phase angl e of the correct bus voltage based on the dynami c and static i nf ormati on of the power facility and based on the calculated value. It may be i nf ormati on that detects overl oad of I i nes and transformers, viol at i on of bus voltage const rai nts, and viol at i on of reactive power constrai nts of generators and synchronous ancestors. Such power facility characteri sti c i nf ormati on, power facility i nf or mat i on, and state esti mat i on result i nf ormati on may be generated by other system anal ysi s modul es 460. Meanwhile, the power facility char act eri sti c i nf or mat i on and the power facility i nf or mat i on may be i nf or mat i on recei ved from the gr i d system.
[ 103] I n addi ti on, the stability eval uati on i nf or mat i on may be i nf or mat i on that eval uat es transi ent stability, voltage stability and the I i ke dun i ng a normal state or a transi ent state before and after a di sturbance by ref I ecti ng the dynami c characteristics of the power facility based on the static state of the power grid.
[ 104] Next, the acceptance limit eval uati on module 440 is a modul e for anal yzi ng the acceptance I i mi t to respond to the output van i ability of renewabl e energy, and can pen i odi call y eval uat e the acceptance I i mi t for the processed gr i d data i ncl udi ng output predi cti on i nf or mat i on.
[ 105] As an example, the acceptance limit eval uati on module 440 may generate acceptance I i mi t eval uati on i nf or mat i on based on voltage standard violation degree, facility and transmission I i ne over! oad degree, t ransi ent stability, r enewabl e energy LVRT
( Low Vol tage Ride Through), and fault current size.
[ 106] Here, the degree of vol tage standard vi ol at i on can be determi ned based on the vol tage change anal ysi s resul t or the voltage mai ntenance standard and vol tage regul at i on target violation analysis result according to the regional power grid due to the conti ngency. Here, the conti ngency means a hypot het i cal si ngl e or multi pl e power facility fail ure that may occur in the power grid.
[ 107] I n addi ti on, the facility and the degree of transmi ssi on I i ne overl oad can be determi ned based on the result of anal yzi ng the transformer and transmi ssi on I i ne overl oad i n the gri d due to the conti ngency or on the result of anal yzi ng the change of power flow due to the change in renewable energy output.
[ 108] In addition, the transient stability can be determi ned based on the phase angl e i nstabi I i ty anal ysi s resul t after the conti ngency. Herei n, a screeni ng through I i near i zati on can be performed pri or to determi ni ng the t ransi ent stability.
[ 109] I n addi ti on, the renewabl e energy LVRT can be determi ned based on the LVRT standard violation analysis result of the renewable energy t ransi ent voltage waveform dun i ng the cont i ngency.
[ 110] I n addi ti on, the fault current magnitude may be a fault current magnitude cal cul at ed based on the power contri but i on of renewabl e energy.
[ 111] Next, the renewable energy output control module 450 can generate out put control i nf or mat i on based on the stability eval uat i on i nf ormat i on and the acceptance I i mi t eval uat i on i nf or mat i on. As an exampl e, the out put control i nf or mat i on may be generat i on control i nf or mat i on of each renewabl e energy generation zone in the region.
[ 112] I n addi ti on, the application unit 400 can return the output control i nf ormati on and each i nf ormati on generated i n the process of generati ng the output control i nf ormat i on to the renewable energy control i nf rastruct ure 300. As an example, the appl i cation unit 400 can return power facility charact eri st i c i nf or mat i on, power facility i nf or mat i on, out put control i nf or mat i on, out put predi ct i on i nf or mat i on, weather pr edi ct i on i nf ormat i on, state est i mat i on result i nf ormat i on, stability eval uat i on i nf or mat i on, and acceptance limit eval uat i on information to the renewable energy control infrastructure 300.
[ 113] Speci f i cal I y, i nf or mat i on returned from the appl i cat i on unit 400 can be returned to the application database 322 in the in-memory database unit 320. Al so, the returned i nf ormati on may be recorded in the real-time database 321.

[114] That is, the real -ti me database 321 can store all i nf or mat i on i ncl udi ng gri d data obtai ned from the gri d system 200, weather data obtained from the distributed parallel processing unit 600 and each i nf ormat i on returned from the appl i cation unit 400.
[115] I n addi ti on, the i nf or mat i on stored i n the real-ti me database 321 can be provided to the integrated control unit 500 or the di st r i but ed parallel processi ng unit 600.
Further, generation sources belonging to each renewable generation zone i n the r egi on may be control I ed based on the returned i nf or mat i on.
[116] On the other hand, the i nf rastructure management unit 330 can i ncl ude an in-memory database management module 331, an i ntegrated process management modul e 332, an al arm/event management modul e 333 and a I og management modul e 334.
[117] The in-memory database management module 331 can perform execut i on, control and state management of the i n- memory database unit 320. Further, the in-memory database management module 331 can execute and manage a management process ( node management, i ntegrated management process, etc. ) for control I i ng applications operating based on the in-memory database unit 320.
[118] The i ntegrated process management modul e 332 can refer to the i nf or mat i on (process management i nf or mat i on, pr i or i t y, current state, etc.) stored in the i n- memory database unit 320 and perform process executi on, control , schedul i ng management, state management, process al arm and event handl i ng of each component i n the renewabl e energy control i nf rastructure.
[ 119] The al arm/event management modul e 333 can store and handl e al arm and event i nf ormati on generated i n the gri d system 200 and transmit the al arm and event i nf ormat i on to the i nt egrat ed control unit 500 and the di stri but ed parallel processi ng unit 600.
[ 120] The log management module 334 can refer to the process log information stored i n the in-memory database unit 320 to create a log file, record the log i nf ormati on i n the I og file accordi ng to the I og I evel , and del ete the I og i nf ormati on of the I og file accordi ng to a predetermi ned cycl e.
[ 121]
I n addi ti on the i nf rastructure management i nf or mat i on memory 340 can store process management i nf ormati on requi red for dri vi ng each module in the i nf rastructure management unit 330, in-memory database meta i nf ormati on, power facility model i ng i nf ormati on, power facility character i sti c i nf ormati on, and SCADA modul e 210 i nf ormati on. That i s, the i nf rastructure management unit 330 may access the i nf rastructure management i nf ormati on memory 340 when dri vi ng a modul e bel ongi ng thereto to load and use data necessary for driving.
[ 122] In addition, the real-time linkage unit 350 can include a real-time transmission module 351, a real-time control module 352 and a real-time receiving module 353 and perform communi cat i ons among the renewabl e energy control i nf rastructure 300, the i nt egr at ed control unit 500 and the di stri but ed paral I el processi ng uni t 600.
[ 123] Fig. 5 i s a diagram for expl ai ni ng a process i n which the renewable energy control i nf rast r uct ur e 300 accor di ng to an embodi ment of the present i nvent i on is associ at ed with the i nt egr at ed control unit 500 and the di stri but ed par al I el processi ng uni t 600.
[ 124] As shown in FIG. 5, the real-time transmission module 351 may transmit information stored in the in-memory database unit 320 to the di stri buted paral I el processi ng unit 600.
[ 125] Di stri but ed paral I el processi ng unit 600 can provide a di stri but ed par al I el processi ng envi ronment for di stri but i ng and quickly processi ng data obtained in large quantities from the grid system 200 associated with the renewable energy control i nf rast ruct ure 300.
[ 126] Thi s i s because the amount of gri d data acqui red i n r el at i on to renewabl e energy gener at i on i nf or mat i on and data created as a result of the operati on of the appl i cat i on unit 400 i s enormous. These data have hi gh uti I i zati on as basi c data for analysis and prediction of the degree of grid risk due to the i ncr ease i n renewabl e energy, but when i nf ormati on is collected i n multi pl e regi ons, it is not easy to store and analyze the i nf ormati on due to the I arge amount of data.
[ 127] That i s, the di stri but ed parallel processi ng unit 600 accordi ng to an embodi ment of the present i nventi on can store and analyze large-capacity data, and functions to more accurately cal cul ate regi onal gri d stability and rel i ability for renewable energy through tools such as the visualization analysis module 641 and the like.
[ 128] Speci f i cal 1 y, the di stri buted parallel processi ng unit 600 can i ncl ude a data col I ecti on unit 610, a data 1 oadi ng unit 620, a data processing search unit 630, and a data analysis application unit 640.
[ 129] Data col I ecti on unit 610 can collect data from the renewable energy control infrastructure 300 or an external network or server.
[ 130] To this end, the data collection unit 610 can include a f i rst di stri buted queue module 611, a grid data collection/loading module 612, a second distributed queue module 613, and a weather data col I ecti on/1 oadi ng module 614.
[ 131] The first distributed queue module 611 may receive data stored in the real -ti me database 321 in the in-memory database unit 320 from the real-time transmission module 351. As an example, the first distributed queue module 611 may be grid data or a pl ural i ty of i nformati on data generated by the appl i cat i on unit 400. I n addi ti on, the f i rst di stri buted queue modul e 611 can push the received data.
[ 132] I n addi ti on, the grid data col I ecti on/ I oadi ng module 612 can pull the data loaded i nto the f i rst di stri buted queue modul e 611 to receive the data and load the received data into the non-rel at i onal database 621 or the di stri buted fi I e system 622 i n the data I oadi ng unit 620. As an exampl e, the non- r el at i onal database 621 may be No-SQL. As an example, the distributed file system 622 may be a Hadoop Di st ri but ed File System ( HDFS) .
[ 133] On the other hand, the second di st ri but ed queue modul e 613 can be connected to an external network, system or server.
[ 134] As an example, the second distributed queue module 613 can be connected to a distribution aut omat i on system ( DAS) (11) and receive i nf or mat i on about the state i nf or mat i on, current, voltage or fail ure presence or absence of di st ri but i on facilities from a di st ri but i on I i ne aut omat i on termi nal devi ce.
[ 135] As another example, the second distributed queue module 613 can be connected to a Meter Data Management System ( MDMS) ( 12) to receive metering data.
[ 136] As another example, the second distributed queue module 613 can be connected to the weather database 13 or weather server 13 to recei ve regi onal weather data.
[ 137] I n addi ti on, the second di stri but ed queue module 613 can transmit information to the weather data col I ect i on/ I oadi ng module 614. I n addi ti on, the grid data col I ect i on/ I oadi ng module 612 can pul 1 data I oaded i n the second di st ri but ed queue modul e 613 to receive the data and load the received data into the non-rel at i onal database 621 i n the data I oadi ng unit 620 or the di st r i but ed file system 622.
[ 138] On the other hand, the loaded weather data may be transmitted to the real-ti me recei vi ng modul e 353 vi a the f i rst distributed queue module or the second distributed queue module.
In addition, the weather data received by the real-time receiving module 353 can be transferred to the real-time database 321 and used as a basis for creating the weather predi cti on i nf ormati on.
[139] The memory cache 623 can function as a cache memory in the process of stori ng data recei ved by the f i rst di stri buted queue modul e 611 i n the non- rel at i onal database 621 or the di stri buted file system 622.
[140] The data processi ng search uni t 630 can i ncl ude a SQL
processi ng engi ne 631, a data warehousi ng modul e 632, an aggregate information creati on module 633 and an aggregate information creati on hi story management module 634.
[141] The SQL processi ng engi ne 631 can query, manage, or process the loaded data in association with the non-relational database 621 or the di stri buted file system 622.
[142] After creati ng the aggregate information based on the load data of the non- rel at i onal database 621 or the di stri buted fi I e system 622, the aggregate i nf ormati on creati ng modul e 633 can load the created aggregate i nformati on i nto the data warehousi ng modul e 632.
[143] I n addi ti on, the aggregate i nf ormati on creati on hi story management module 634 can create hi story information, creati on hi story i nf or mat i on or mai n aggregate/statistic meta i nf or mat i on when creati ng aggregate i nf ormati on, and load them i nto the data warehousi ng modul e 632.
[ 144] In addition, the data warehousing module 632 may be connected to the SQL processi ng engi ne 631. As an exampl e, the data warehousi ng modul e 632 may be a database that converts data loaded by the SQL processi ng engine from the non-relational database 621 or the di stri but ed file system 622 i nto a predetermi ned format and that manages the converted data. I n addition, the data warehousi ng module 632 may transmit the data converted i nto a predetermi ned format to the i ntegrated control unit 500 upon request from the integrated control unit 500.
[ 145] I n addi ti on, the data anal ysi s appl i cat i on unit 640 may perform a secondary analysis on the stability of the regi onal power gri d for renewabl e energy usi ng the vi sual i zati on anal ysi s modul e 641. As an example, the visualization analysis module may vi sual i ze data stored i n the data warehousi ng modul e 632 by analyzing power data. In addition, the data analysis application unit 640 may include an artificial neural network model ( not shown) that I earns based on the data stored i n the data warehousi ng module 632 and that receives at least some grid data as an i nput val ue to predi ct the amount of renewabl e energy generati on i n the regi on.
[ 146] Meanwhi I e, the i ntegrated control unit 500 can receive data from the di stri buted paral I el processi ng unit 600, that i s, the data warehousi ng modul e 632, vi sual i ze the recei ved data and provi de it to the user. Herei n, the i ntegrated control unit 500 may receive data that did not go through the di stri but ed paral I el processi ng uni t 600. That i s, the i ntegrated control unit 500 may receive data di rect I y from the renewable energy control infrastructure 300.

39 [147] As an example, the integrated control unit 500 can include a real-ti me moni t or i ng module 510, an infrastructure resource moni t or i ng modul e 520, a di stri but ed paral I el resource moni t or i ng modul e 530, a power facility i nf ormati on management modul e 540, a renewable energy moni t or i ng/control process management modul e 550, an i nf rast r uct ur e process management modul e 560, and statistics and aggregate i nf ormati on management modul e 570.
[148] The real-time monitoring module 510 can provide various information requi red for power grid management.
[149] As an example, based on the data received from the di st ri but ed parallel processi ng unit 600, the real-ti me moni t or i ng module 510 can provide real-ti me renewable gener at i on comprehensive state i nf or mat i on, real-ti me weather i nf or mat i on comprehensive state information and real-ti me line-specific I i nkage state i nf ormati on to the user i n real ti me.
[ 150] I n addi ti on, the real-ti me moni t or i ng module 510 monitors the states of the SCADA module 210, the EMS system 220, the di st ri but i on automation system 11, the meteri ng data management system 12, or the weather database I 3 and sets a threshold val ue (collection cycle, speed, I/O and the like) to thereby provide an al arm f uncti on when the threshol d i s exceeded.
[ 151] 1 n addi ti on, the real-ti me moni t or i ng module 510 can provide a function capable of monitoring Mvar information, control lab! e capacity i nf ormati on, facility capacity and weather

40 i nf ormati on sui tabl e for the type of generator of each renewabl e energy generation source in the region.
[ 152] I n addi ti on, the real-ti me moni t or i ng module 510 can provi de a function capabl e of moni t or i ng voltage, supply capacity, current I oad, output and the I i ke for each DL uni t generator.
[ 153] I n addi ti on, the real-ti me moni t or i ng module 510 can provi de a function capable of moni tor i ng i nf or mat i on on renewabl e energy generati on sources, measured val ues for current outputs, predi cted output val ues, weather predi cti on i nf ormati on and the like.
[ 154] 1 n addi ti on, the real-ti me moni t or i ng module 510 may provi de real-ti me event i nf ormat i on of renewable energy generation sources and provi de an al arm function when exceeding or fall i ng short of a predetermi ned threshol d val ue.
[ 155] I n addi ti on, the i nf rast ructure resource moni tor i ng modul e 520 may provi de a f uncti on capabl e of moni tori ng the CPU usage rate, memory usage rate, di sk usage rate, RTDB state i nf ormati on and the 1 i ke of the configuration i n the renewable energy control infrastructure 30.
[ 156] In addi ti on, the di stri but ed parallel resource moni t or i ng module 530 provi des a function capable of monitoring a real-time DI SK I 0, cl uster CPU usage rate, network I 0, di stri but ed fi I e system ( 622) 10 and the 1 i ke.

41 [157] I n addi ti on, the power facility i nf or mat i on management modul e 540 may manage power facility characteristic i nf or mat i on, modeling ( I ayer/ I i nk) information, and information acqui red by the SCADA module 210.
[ 158] In addition, the renewable energy monitoring/control process management module 550 can monitor the state of each renewable energy generating source belonging to each renewable generation zone in the region. As an example, the renewable energy monitoring/control process management module 550 can monitor real-time generation i nf ormat i on of each renewable energy generation source collected by the SCADA module 210. As an example, the renewable energy monitoring/control process management module 550 can obtain real-time generation information of each renewable energy generation source from the grid data.
[ 159] In addition, the renewable energy monitoring/control process management modul e 550 may moni tor al arm and event i nf ormat i on. Herei n, the monitored i nf ormat i on may be vi sual i zed and provided to the user.
[ 160] I n addi ti on, the i nf rast ruct ure process management modul e 560 provides a function capable of managing schedule inquiry, regi strati on, modi f i cat i on, del et i on, and execut i on of each component i n the renewabl e energy control i nf rast ructure 300.
[ 161] I n addi ti on, the st at i st i cs and aggregated i nf or mat i on management module 570 provides the statistics management

42 function for data collection state, al arm data, event data and grid data.
[ 162] On the other hand, the renewable energy detection/control process management module 550 may transmit a control message to the real -ti me control module 352 i n the real -ti me I i nkage unit 350 of the renewabl e energy control i nf rast r uct ure 300. I n addition, the real-time control module 352 may transmit the control message to a termi nal device of each generati on zone i n the regi on through the control message transmission module 312 i n the gri d system I i nki ng unit 310. Herei n, the control message generated by the renewable energy detection/control process management module can be appl i ed with priority over the control command transmitted to each renewabl e energy generati on zone i n the regi on, that is, each i nf ormati on collection termi nal . As an example, the control message may be applied with priority over out put control i nf or mat i on.
[ 163] Fl G. 6 i s an exempl ary di agram for expl ai ni ng a process i n which the renewable energy output prediction module 420 accordi ng to an embodi ment of the present i nventi on generates output predi cti on i nf ormati on of a generati on zone i n a regi on.
[ 164] In FIG. 6, for convenience of explanation, the renewable energy generati on source located i n the generati on zone will be descri bed as an exampl e of a wi nd generati on source.
[ 165] First, as shown in FIG. 6(a), a step of collecting wind speed and wind generati on data of a renewable energy generati on source for a certain period of ti me may be perf ormed( S510) .

43 [166] Herei n, when the renewable energy generati on source is not a wi nd generati on source, wi nd speed and wi nd generati on data can be repl aced with weather data, of course.
[167] I n addi ti on, a step of esti mat i ng the f i rst amount of generati on by sett i ng an ARI MAX model based on at least some of the wi nd speed and wi nd generati on data among the data col I ected in step S510 may be perf ormed( S520).
[168] I n addi ti on, a step of esti mat i ng the second amount of generati on by sett i ng a polynomial regressi on model based on at least some wi nd speed and wi nd generati on data among the data collected i n step S510 may be perf ormed( S530) .
[169] I n addi ti on, a step of esti mat i ng the t hi rd amount of generati on based on wi nd speed data at a poi nt near the renewable energy generati on source may be perf ormed( S540) .
[170] I n addi ti on, a step of cal cul at i ng the predi cted val ue of the amount of generati on based on the analog ensemble using the f i rst amount of generati on, the second amount of generati on, the t hi rd amount of generati on, and past data among the data col I ected i n the step S510 may be performed( S550).
[171] FIG. 6( b) is a flowchart for explaining the process of esti mat i ng the t hi rd amount of generati on i n step S540.
[172] As shown in FIG. 6( b), a step of collecting wi nd speed predi cti on data of a poi nt near a renewabl e energy generati on source and spatial data near the renewable energy generati on source may be perf ormed( S541).

44 [173] I n addi ti on, a step of predi ct i ng the wi nd speed i n the point of the renewable energy generation source based on the Kri gi ng technique may be perf ormed( S542) .
[174] Herei n, the wi nd speed predi cti on may have been performed i n advance by the weather i nf or mat i on predi ct i on module 410.
[175] I n addi ti on, based on the Deacon equat i on, a step of cor r ect i ng the wi nd speed based on the altitude may be perf or med( S543) .
[176] I n addi ti on, a step of est i mat i ng the t hi rd amount of gener at i on based on the corrected wi nd speed may be perf or med( S544) .
[177] The above descri pt i on of the present i nventi on i s for ill ust rat i ve purposes, and it will be appreci at ed that those ski I I ed in the art to which the present invention pertains can easily be modi f i ed i nto other speci fic forms without changi ng the t echni cal spi r i t or essent i al features of the present i nvent i on. Therefore, the embodi ment s descri bed above shoul d be understood as ill ust rat i ve i n all respects and not I i mi ti ng. For exampl e, each component descri bed as a si ngl e type may be i mpl emented i n a di st ri but ed manner, and si mi I ar I y, components descri bed as di st ri but ed may be implemented i n a combi ned form.
[178] The scope of the present invention is indicated by the cl ai ms to be descri bed I at er, and all changes or modi f i cat i ons derived from the meaning and scope of the claims and equivalent concepts should be construed as bei ng i nd l uded i n the scope of the present invention.

45 MODES FOR CARRYING OUT THE INVENTION
[179] Modes for carryi ng out the i nventi on have been descri bed together i n the best modes for carryi ng out the i nventi on.
I NDUSTRI AL APPLI CABI LI TY
[180] The present i nventi on rel ates to an i ntegrated regi onal renewable energy control system, and more particularly, to an i ntegrated regi onal renewabl e energy control system capabl e of determi ni ng the i mpact of renewabl e energy generati on on the regi onal power grid of a regi on and controlling the amount of the renewable energy production of each renewable energy generation zone i n the regi on accordi ng to the determi nati on resul ts. The system can be used i n van i ous f aci I iti es that manage renewabl e energi es and thus has the i ndustri al appl i cabi I i ty.

Claims

CLAI MS

1.
An i nt egr at ed r egi onal renewabl e energy cont r ol syst em compri si ng:
a renewabl e energy control i nf rastructure bei ng connected to a gr i d syst em t hat aggr egat es r enewabl e ener gy gener at i on i nf ormati on f rom a renewabl e energy generati on source i n each renewabl e energy generati on zone i n a regi on f or col l ecti ng gri d data i ncl udi ng the renewabl e energy generat i on i nf ormati on; and an appl i cat i on uni t f or communi cat i ng wi t h t he renewabl e ener gy cont r ol i nf rast r uct ur e t o recei ve t he gr i d dat a, determi ni ng power gri d stabi I i ty of the regi on based on the gri d data, and generati ng output control i nf ormati on accordi ng to the power gri d stabi l i ty, wher ei n t he gr i d syst em col l ect s t he r enewabl e ener gy generati on i nf ormati on of the renewabl e energy generati on source by means of a pl ural i ty of i nf ormati on col l ecti on termi nal s, and wherei n the renewabl e energy control i nf rast ructure control s the amount of renewabl e energy generati on of each renewabl e energy generati on zone i n the regi on accordi ng to the output cont r ol i nf or mat i on.

2. The system accordi ng to cl ai m 1, wherei n the gri d system compri ses a Supervi sory Cont rol And Data Acqui si ti on( SCADA) modul e f or communi cat i ng wi th each of t he pl ur al i ty .. of i nf or mat i on col I ecti on termi nal s i n real ti me to col I ect the renewabl e energy generat i on i nf or mat i on.

3. The system accordi ng to cl ai m 2, wherei n the gri d system i ncl udes an energy management system ( EMS) f or col I ecti ng base gener at i on data, power f aci I i ty i nf ormati on and power f aci I i ty characteri sti c i nf ormati on i n the regi on, the gri d data f urther i ncl udi ng data col l ected by t he EMS when t he renewabl e energy gener at i on i nf ormat i on i s col l ected, wherei n t he power f aci I i ty i nf ormati on i s i nf ormati on on power f aci l i ti es connected to the power gri d of the regi on, and wher ei n t he power f aci I i ty char act er i st i c i nf or mat i on i s i nf or mat i on i ndi cat i ng characteri sti cs of each of power f aci I i ti es connected to the power gri d of the regi on.

4. The system accordi ng to cl ai m 3, f urt her compri si ng a di st ri but ed par al l el processi ng uni t f or provi di ng weat her data of the regi on to the renewabl e energy control i nf rastructure, wherei n the appl i cat i on uni t compri ses:
a weat her predi cti on modul e f or generati ng weather predi cti on i nf ormati on of the renewabl e energy generati on zone based on t he weat her dat a;
a renewabl e energy output predi cti on modul e f or generati ng output predi cti on i nf ormati on of the renewabl e energy generati on zone based on the weat her predi cti on i nf ormat i on and the gri d data;
ot her gri d anal ysi s modul e bei ng conf i gured to operate based on power f aci I i ty char act eri sti c i nf or mat i on and power f aci I i ty i nf or mat i on, wherei n t he ot her gr i d anal ysi s modul e cal cul at es the exact magni tude and phase angl e of a bus vol t age based on the dynami c and st at i c i nf ormat i on of the power f aci I i ty and generates state est i mat i on resul t i nf ormat i on by detect i ng an over I oad of l i ne and t ransf or mer, a vi ol at i on of bus vol t age const rai nt and a vi ol at i on of react i ve power const rai nt of gener at or and synchr onous condenser based on t he cal cul at ed val ue;
a stabi l i ty eval uat i on modul e f or generat i ng a stabi l i ty eval uat i on i nf or mat i on of t he regi onal power gr i d based on at I east two or more of t he out put predi ct i on i nf ormat i on, state est i mat i on resul t i nf ormat i on, power f aci I i ty characteri st i c i nf or mat i on and power f aci l i ty i nf ormat i on;
an acceptance I i mi t eval uat i on modul e f or generat i ng acceptance l i mi t eval uat i on i nf ormat i on based on t he vol t age standard vi ol at i on, f aci l i ty and t ransmi ssi on l i ne overl oad, t ransi ent stabi l i ty and renewabl e energy l ow vol t age ri de through ( LVRT) and the magni tude of the f aul t current of the regi onal power gri d; and a renewabl e energy out put cont rol modul e f or generat i ng t he out put cont rol i nf or mat i on based on t he st abi I i ty eval uat i on i nf or mat i on and t he acceptance l i mi t eval uat i on i nf or mat i on, wherei n t he appl i cat i on uni t returns t he weat her predi ct i on i nf or mat i on, t he out put pr edi ct i on i nf or mat i on, t he st at e est i mat i on resul t i nf or mat i on, t he stabi I i ty eval uat i on i nf or mat i on, t he acceptance l i mi t eval uat i on i nf or mat i on and t he out put cont r ol i nf or mat i on t o t he r enewabl e energy cont r ol i nf rast ruct ure.

5. The system accordi ng to cl ai m 4, wherei n the renewabl e energy generati on source i s a wi nd generati on source, wherei n t he renewabl e energy output predi cti on modul e i s adopt ed t o:
col I ect wi nd speed and wi nd generati on data of a predetermi ned per i od of the renewabl e energy generati on source;
set an ARI MAX model based on at I east some of the wi nd speed and wi nd generati on data of the predetermi ned peri od of ti me to esti mate a f i rst amount of generati on;
set a pol ynomi al regressi on model based on at I east some of the wi nd speed and wi nd generati on data of the predetermi ned peri od of ti me to esti mate a second amount of generati on;
esti mate a t hi rd amount of generati on based on wi nd speed data at a poi nt near the renewabl e energy generati on source; and generate output predi cti on i nf ormati on based on an anal og ensembl e by usi ng the f i rst amount of generati on, the second amount of generati on, the t hi rd amount of generati on and the past wi nd speed and wi nd generati on data of the renewabl e energy gener at i on source.

6. The system accordi ng to cl ai m 5, wherei n the renewabl e energy output predi cti on modul e i s adopted to:
col I ect wi nd speed pr edi ct i on dat a at a poi nt near t he renewabl e energy generati on source and spat i al data near the renewabl e energy generati on source;

predi ct the wi nd speed at t he I ocati on of t he renewabl e energy generati on source based on a Kr i gi ng techni que;
correct the wi nd speed accordi ng to t he al ti tude of the renewabl e energy generati on source based on the Deacon equati on;
and est i mat e t he t hi rd amount of gener at i on based on t he corrected wi nd speed.

7. The system accordi ng to cl ai m 4, wher ei n t he r enewabl e energy management i nf rast r uct ur e i ncl udes an i nf rast ructure management uni t, wherei n the i nf rastruct ure management uni t i ncl udes an i n-memory dat abase management modul e, an i nt egr at ed process management modul e, an al arm/event management modul e, and a I og management modul e, wherei n the i n- memory database management modul e control s the executi on, control , state management of the i n- memory database uni t and t he process of modul es bel ongi ng to the appl i cat i on uni t, wherei n the i ntegrated process management modul e control s the process of each component i n the renewabl e energy control i nf r ast r uct ur e based on pr ocess management i nf or mat i on, a predetermi ned pri or i ty and a current state of each component i n t he r enewabl e energy cont r ol i nf r ast r uct ur e, and st or es and handl es the al arm and event generated i n the control process, wherei n the al arm/ event management modul e stores and handl es al arm and event i nf ormati on generated i n t he gri d system and t ransmi ts t he al arm and event i nf ormat i on t o t he i nt egr at ed cont rol uni t and di stri buted paral l el processi ng uni t, and wherei n the I og management modul e generates a I og fi I e by ref erri ng to the process l og i nf ormati on stored i n the i n- memory database uni t, records I og i nf ormati on i n the I og file accordi ng to a I og I evel and del et es the I og i nf ormati on of the I og file accordi ng to a predetermi ned cycl e.

8. The system accordi ng to cl ai m 7, wherei n the renewabl e energy management i nf rast ruct ure f urt her i ncl udes an i nf rast ruct ure management i nf ormati on memory whi ch i s connected to the i nf rast ruct ure management uni t and whi ch st ores t he process management i nf or mat i on, t he met a i nf or mat i on of t he i n- memory database, t he power f aci l i ty model i ng i nf or mat i on, t he power f aci I i ty characteri st i c i nf ormat i on and modul e i nf ormat i on of the SCADA modul e.

9. The system accordi ng to cl ai m 4, wherei n the di stri buted paral I el processi ng uni t recei ves the weather data of the regi on f rom an external weather database or weather server and provi de the weather data to the renewabl e energy control i nf rastructure.

10. The system accor di ng to cl ai m 4, wherei n t he renewabl e energy control i nf rastructure i ncl udes a real - ti me database and wherei n t he real - t i me dat abase st ores t he gr i d dat a and i nf or mat i on r et urned f rom t he appl i cat i on uni t .

11. The system accordi ng to cl ai m 10, wherei n the di stri buted paral l el processi ng uni t compri ses:

a dat a col l ect i on uni t t hat col l ect s data and i nf or mat i on stored i n the real - ti me database;
a data l oadi ng uni t for di stri but i ng the data or i nf ormati on col I ected by the data col I ecti on uni t and I oadi ng the data or i nf ormati on i nto a non- rel at i onal database or a di stri but ed file system;
a data processi ng search uni t f or queryi ng the data or i nf or mat i on l oaded i nt o t he dat a l oadi ng uni t, convert i ng t he data or i nformati on i nto a predetermi ned format and warehousi ng the converted data; and a data anal ysi s appl i cat i on uni t f or second! y anal yzi ng the stabi I i ty of the regi onal power gri d.

12. The system accor di ng t o cl ai m 11, wherei n the data col l ecti on uni t i ncl udes a f i rst di stri but ed queue modul e, a gri d dat a col I ect i on/ I oadi ng modul e, a second di st ri but ed queue modul e, and a weather data col l ecti on/ l oadi ng modul e, wherei n the f i rst di stri buted queue modul e i s connected to the real -ti me database to recei ve data stored i n the real -ti me dat abase, and pushes t he recei ved dat a t o t he gr i d dat a col I ecti on/ I oadi ng modul e, and wherei n the second di stri buted queue modul e i s connected to at l east one of an el ectri c power di stri but i on automat i on system, a meter i ng data management system and a weather database or a weat her server, and recei ves dat a f rom t he connect ed conf i gurati on and pushes the recei ved data to the weather data col l ecti on/ l oadi ng modul e.

13.
The system accor di ng to cl ai m 11, wherei n the data processi ng search uni t i ncl udes a SQL processi ng engi ne, an aggregate i nf ormati on gener at i on modul e, an aggregate i nf or mat i on gener at i on hi story management modul e and a data warehousi ng modul e, wherei n the SQL processi ng engi ne queri es data I oaded i n the non- rel at i onal database or the di stri buted file system and I oads the data i n the data warehousi ng modul e, wherei n the aggregate i nf ormati on generati on modul e generates aggregate i nf ormati on of data l oaded i n the non- r el at i onal database or di stri buted file system and I oads the aggregate i nformati on i n the data warehousi ng modul e, and wherei n t he aggregat e i nf or mat i on gener at i on hi st ory management modul e generat es generat i on hi story i nf or mat i on of the aggregate i nf ormati on, key aggregates and stati sti cal meta i nformati on and l oads them i nto the data warehousi ng modul e.

14. The system accordi ng to cl ai m 13, wherei n the data anal ysi s appl i cat i on uni t i ncl udes an art i f i ci al neural network model whi ch I earns based on the data stored i n the data warehousi ng modul e, recei ves at I east some of the data I oaded i n the non-rel at i onal database or the di stri buted file system as an i nput val ue and esti mates the amount of renewabl e energy generati on i n the regi on.

15. The system accordi ng to cl ai m 11, f urther compri si ng an i ntegrated control uni t whi ch recei ves the data warehoused i nto the data I oadi ng uni t and vi sual i zes t he data to provi de to a user, wher ei n t he i nt egr at ed cont r ol uni t gener at es a cont r ol message i n response to a user' s i nput, and wherei n t he control message control s t he amount of renewabl e energy generati on i n each renewabl e energy generati on zone i n the regi on i n pref erence to the output cont rol i nf ormati on.

16. The syst em accor di ng t o cl ai m 1, wher ei n t he r enewabl e energy generati on source i s connected to an i nverter, t he output cont rol i nf or mat i on i s t ransmi tted to t he i nf ormat i on col l ecti on termi nal , and t he i nf ormat i on col I ecti on termi nal cont rol s t he amount of generati on of t he renewabl e energy generati on source by cont rol l i ng t he i nvert er .

17. The system accordi ng to cl ai m 1, wherei n t he i nf ormati on col l ect i on termi nal i s a remote termi nal uni t and wherei n t he i nterval that t he i nf ormat i on col l ecti on termi nal col l ects t he renewabl e energy generati on i nf ormati on i s 1 second or I ess.