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Solution Methods of Large-Scale Powe...

Ke, Xinda.

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Solution Methods of Large-Scale Power System Resource Scheduling and Dispatch Problems.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Solution Methods of Large-Scale Power System Resource Scheduling and Dispatch Problems./
作者:	Ke, Xinda.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2016,
面頁冊數:	136 p.
附註:	Source: Dissertations Abstracts International, Volume: 78-09, Section: B.
Contained By:	Dissertations Abstracts International78-09B.
標題:	Computer Engineering. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10583439
ISBN:	9781369621181

Solution Methods of Large-Scale Power System Resource Scheduling and Dispatch Problems.
Ke, Xinda.

Solution Methods of Large-Scale Power System Resource Scheduling and Dispatch Problems. - Ann Arbor : ProQuest Dissertations & Theses, 2016 - 136 p.

Source: Dissertations Abstracts International, Volume: 78-09, Section: B.

Thesis (Ph.D.)--North Carolina State University, 2016.

This item is not available from ProQuest Dissertations & Theses.

Power grid infrastructure is undergoing unprecedented changes with an increasing number of renewable generation resources and distributed energy resources being integrated into the grid from both the transmission and distribution levels. Uncertainties, variabilities, and an explosion of system variables and their operational constraints caused by the consideration of high penetration of renewable energy resources and distributed energy resources are making the power system scheduling and dispatch problems one of the hardest optimization problems to formulate and solve with satisfactory optimality, robustness, and speed. Those new challenges in problem formulation and solving process must be addressed for the economical, reliable, and safe operation of the modern power grid. Therefore, in this thesis, I focused my effort on developing and advancing the problem formulation and solution methodologies for large-scale power system resource scheduling and dispatch problems. First, I proposed a problem reformulation for dimension reduction of the Mixed Integer Linear Programming Unit Commitment (MILP-UC) problems and a two-step hybrid solving method to improve the solving speed of UC problems. The validation of the proposed methods was performed by benchmarking their performance against a commercial unit commitment software package, PROMOD. Using the developed tool, I was able to quantify the impacts of heat waves on power system reliability and production cost at much higher time resolution for a broader range of scenarios. Second, I extended the power system resources scheduling and dispatch problem from centralized generation resources to decentralized aggregator-controllable energy resources using the dispatch of plug-in electric vehicles (PEV) as an example. A real-time, greedy-index based dispatching policy (GIDP), which allows a PEV service aggregator to account for reward-of-service, penalty-of-service-delays, and compensation for accelerated PEV battery degradation, was proposed to dispatch and dispatch PEVs for providing ancillary service. Simulation results show that the proposed GIDP can be used by the PEV service aggregators to provide ancillary services that are equivalent to those provided by the generation resources. This will allow us to formulate the scheduled and dispatch of the distributed energy resources into the generation scheduling process. The developed methodologies have been implemented as components of the Energy Operation Model (EOM), an open source production tool developed at the Pacific Northwest National Laboratory. My future research direction is to develop co-optimization methods for managing hydro power plants considering water management constraints, thermal-hydro coordination, as well as renewable integration needs.

ISBN: 9781369621181Subjects--Topical Terms:

1567821
Computer Engineering.
Subjects--Index Terms:

Ancillary service

Solution Methods of Large-Scale Power System Resource Scheduling and Dispatch Problems.
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520 $a Power grid infrastructure is undergoing unprecedented changes with an increasing number of renewable generation resources and distributed energy resources being integrated into the grid from both the transmission and distribution levels. Uncertainties, variabilities, and an explosion of system variables and their operational constraints caused by the consideration of high penetration of renewable energy resources and distributed energy resources are making the power system scheduling and dispatch problems one of the hardest optimization problems to formulate and solve with satisfactory optimality, robustness, and speed. Those new challenges in problem formulation and solving process must be addressed for the economical, reliable, and safe operation of the modern power grid. Therefore, in this thesis, I focused my effort on developing and advancing the problem formulation and solution methodologies for large-scale power system resource scheduling and dispatch problems. First, I proposed a problem reformulation for dimension reduction of the Mixed Integer Linear Programming Unit Commitment (MILP-UC) problems and a two-step hybrid solving method to improve the solving speed of UC problems. The validation of the proposed methods was performed by benchmarking their performance against a commercial unit commitment software package, PROMOD. Using the developed tool, I was able to quantify the impacts of heat waves on power system reliability and production cost at much higher time resolution for a broader range of scenarios. Second, I extended the power system resources scheduling and dispatch problem from centralized generation resources to decentralized aggregator-controllable energy resources using the dispatch of plug-in electric vehicles (PEV) as an example. A real-time, greedy-index based dispatching policy (GIDP), which allows a PEV service aggregator to account for reward-of-service, penalty-of-service-delays, and compensation for accelerated PEV battery degradation, was proposed to dispatch and dispatch PEVs for providing ancillary service. Simulation results show that the proposed GIDP can be used by the PEV service aggregators to provide ancillary services that are equivalent to those provided by the generation resources. This will allow us to formulate the scheduled and dispatch of the distributed energy resources into the generation scheduling process. The developed methodologies have been implemented as components of the Energy Operation Model (EOM), an open source production tool developed at the Pacific Northwest National Laboratory. My future research direction is to develop co-optimization methods for managing hydro power plants considering water management constraints, thermal-hydro coordination, as well as renewable integration needs.
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