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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
- 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
- 기본자료저록
- Dissertations Abstracts International. 87-05A.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520260202105541
■006m o d
■007cr#unu||||||||
■020 ▼a9798265402547
■035 ▼a(MiAaPQ)AAI32315142
■035 ▼a(MiAaPQ)GeorgiaTech65050
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a620.004
■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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