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Microgrid Energy Management System with Ancillary Services to the Grid
Microgrid Energy Management System with Ancillary Services to the Grid
Microgrid Energy Management System with Ancillary Services to the Grid

Detailed Information

자료유형  
 학위논문 서양
최종처리일시  
20260202105541
ISBN  
9798265402547
DDC  
620.004
저자명  
Alowaifeer, Maad.
서명/저자  
Microgrid Energy Management System with Ancillary Services to the Grid
발행사항  
[Sl] : Georgia Institute of Technology, 2021
발행사항  
Ann Arbor : ProQuest Dissertations & Theses, 2021
형태사항  
220 p
주기사항  
Source: Dissertations Abstracts International, Volume: 87-05, Section: A.
주기사항  
Advisor: Meliopoulos, A.P.
학위논문주기  
Thesis (Ph.D.)--Georgia Institute of Technology, 2021.
초록/해제  
요약Climate change has increased the frequency and intensity of severe weather conditions leading to catastrophic power interruptions. To mitigate these interruptions, the adoption of microgrids (µGs) emerged. A µG is a cluster of interconnected loads and distributed energy resources (DERs) that may be managed collectively to achieve given operational objectives. Concurrently to the adoption of µGs, large amounts of renewable resources have been integrated into the grid. Renewable resources are characterized by variable and uncertain power output which creates operational challenges to grid operators. Grid operators are faced with an increasing need for flexible resources that are able to absorb the variability and uncertainty in operation. Part of the need can be met by µGs; a µG may be optimized to provide different ancillary services to the grid.We propose a microgrid energy management system (µGEMS) that optimally plans the operations, and control the DERs while committing, holding, dispatching, and maintaining different ancillary services for the grid in a reliable and economical manner. Reserve, regulation, and voltage support services can be supplied simultaneously via the µGEMS. The proposed µGEMS may be used to commit the services a Day-Ahead (DA) in advance to dispatch, or in Real-Time (RT) (i.e., DA and RT Commitments). Commitment rules that the µGEMS can consider include minimum acceptable capacities, required time to respond, and required time to maintain. We model the µG as an AC network using the current formulation to obtain a model that is mostly linear. Bus voltage, circuit loading, and point of common coupling (PCC) power factor limits are enforced during the commitment, the holding, the dispatching, and the maintaining stages of services. The proposed µGEMS consists of a collection of interacting optimization problems each with a certain task, planning horizon, and frequency of solve. The optimization problems are generally mixed-integer quadratically constrained programming (MIQCP) problems. A solution methodology for the optimization problems is proposed based on successive linear programming (SLP) which promises efficient handling of discrete variables.
일반주제명  
Test systems
일반주제명  
Violations
일반주제명  
Motivation
일반주제명  
Mathematical models
일반주제명  
Clean technology
일반주제명  
Planning
일반주제명  
Energy management
일반주제명  
Circuits
일반주제명  
Power supply
일반주제명  
Linear programming
일반주제명  
Energy storage
일반주제명  
Energy resources
일반주제명  
Markov analysis
일반주제명  
Alternative energy
일반주제명  
Electrical engineering
일반주제명  
Mathematics
일반주제명  
Sustainability
기타저자  
Georgia Institute of Technology.
기본자료저록  
Dissertations Abstracts International. 87-05A.
전자적 위치 및 접속  
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■1001  ▼aAlowaifeer,  Maad.
■24510▼aMicrogrid  Energy  Management  System  with  Ancillary  Services  to  the  Grid
■260    ▼a[Sl]▼bGeorgia  Institute  of  Technology▼c2021
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2021
■300    ▼a220  p
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  87-05,  Section:  A.
■500    ▼aAdvisor:  Meliopoulos,  A.P.
■5021  ▼aThesis  (Ph.D.)--Georgia  Institute  of  Technology,  2021.
■520    ▼aClimate  change  has  increased  the  frequency  and  intensity  of  severe  weather  conditions  leading  to  catastrophic  power  interruptions.  To  mitigate  these  interruptions,  the  adoption  of  microgrids  (µGs)  emerged.  A  µG  is  a  cluster  of  interconnected  loads  and  distributed  energy  resources  (DERs)  that  may  be  managed  collectively  to  achieve  given  operational  objectives.  Concurrently  to  the  adoption  of  µGs,  large  amounts  of  renewable  resources  have  been  integrated  into  the  grid.  Renewable  resources  are  characterized  by  variable  and  uncertain  power  output  which  creates  operational  challenges  to  grid  operators.  Grid  operators  are  faced  with  an  increasing  need  for  flexible  resources  that  are  able  to  absorb  the  variability  and  uncertainty  in  operation.  Part  of  the  need  can  be  met  by  µGs;  a  µG  may  be  optimized  to  provide  different  ancillary  services  to  the  grid.We  propose  a  microgrid  energy  management  system  (µGEMS)  that  optimally  plans  the  operations,  and  control  the  DERs  while  committing,  holding,  dispatching,  and  maintaining  different  ancillary  services  for  the  grid  in  a  reliable  and  economical  manner.  Reserve,  regulation,  and  voltage  support  services  can  be  supplied  simultaneously  via  the  µGEMS.  The  proposed  µGEMS  may  be  used  to  commit  the  services  a  Day-Ahead  (DA)  in  advance  to  dispatch,  or  in  Real-Time  (RT)  (i.e.,  DA  and  RT  Commitments).  Commitment  rules  that  the  µGEMS  can  consider  include  minimum  acceptable  capacities,  required  time  to  respond,  and  required  time  to  maintain.  We  model  the  µG  as  an  AC  network  using  the  current  formulation  to  obtain  a  model  that  is  mostly  linear.  Bus  voltage,  circuit  loading,  and  point  of  common  coupling  (PCC)  power  factor  limits  are  enforced  during  the  commitment,  the  holding,  the  dispatching,  and  the  maintaining  stages  of  services.  The  proposed  µGEMS  consists  of  a  collection  of  interacting  optimization  problems  each  with  a  certain  task,  planning  horizon,  and  frequency  of  solve.  The  optimization  problems  are  generally  mixed-integer  quadratically  constrained  programming  (MIQCP)  problems.  A  solution  methodology  for  the  optimization  problems  is  proposed  based  on  successive  linear  programming  (SLP)  which  promises  efficient  handling  of  discrete  variables.
■590    ▼aSchool  code:  0078.
■650  4▼aTest  systems
■650  4▼aViolations
■650  4▼aMotivation
■650  4▼aMathematical  models
■650  4▼aClean  technology
■650  4▼aPlanning
■650  4▼aEnergy  management
■650  4▼aCircuits
■650  4▼aPower  supply
■650  4▼aLinear  programming
■650  4▼aEnergy  storage
■650  4▼aEnergy  resources
■650  4▼aMarkov  analysis
■650  4▼aAlternative  energy
■650  4▼aElectrical  engineering
■650  4▼aMathematics
■650  4▼aSustainability
■690    ▼a0363
■690    ▼a0544
■690    ▼a0405
■690    ▼a0796
■690    ▼a0640
■71020▼aGeorgia  Institute  of  Technology.
■7730  ▼tDissertations  Abstracts  International▼g87-05A.
■790    ▼a0078
■791    ▼aPh.D.
■792    ▼a2021
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17360525▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

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