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Short Term Scheduling of Gencos eith Renewable Units for Participation in Electricity Market

Kabiri Renani, Yahya | 2017

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 49855 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Ehsan, Mehdi; Shahidehpour, Mohammad; Mohammadi Ivatloo, Behnam
  7. Abstract:
  8. Restructuring in the electrical industry, is one of the most important change in this industry which cause profit based decision making in all parts of the electrical network, especially in the generation part. In a real incomplete market environment, uncertainties associated with input parameters of the GenCos’ self-scheduling problem such as market price and accessible renewable generation would be one of the most important factors that affects the profits of GenCos and energy resources. Nowadays, increased use of distributed energy resources (DERs) such as distributed generations (DGs), energy storage units, and demand response, has led to a paradigm shift within the electric power industry which challenges the optimal and reliable operation of distribution networks and cause that, the electricity power generation is not limited to generation units in transmission network anymore. In this dissertation, we proposes a GenCo’s self-scheduling method in which individual GenCos forecast the hourly LMPs by simulating the ISO’s market clearing process. In this process of simulating the ISO, a GenCo does not have the complete information on other GenCos’ offers. In this case, we model the GenCo’s self-scheduling problem as an incomplete game to analyze the opponents’ offers in a competitive market. To solve the GenCo’s incomplete game problem, the opponents’ unknown information is modeled using certain types of operation scenarios corresponding to cost functions. GenCo’s opponents are selected from hypothetical populations containing opponents’ types which are represented by joint probability distribution functions. In our study, the robust optimization method is utilized to model uncertainties associated with forecast error of renewable generation and LMPs error. The other part of the dissertation, considers the DERs penetration in distribution networks and proposes a framework for the DSO’s role in the secure and optimum operation of local distribution areas (LDA). In this framework, the ISO is responsible for the secure operation of bulk power systems by interacting with large GenCos and loads as well as individual DSOs that would link retail customers to bulk power systems at the wholesale market level. In the proposed framework, DSOs operate a transactive market at the local distribution level by calculating DLMPs via an iterative method. Each DSO is responsible for the optimal and the secure operation of its LDA as they interact with distribution level prosumers, including microgrid operators (MGOs), DERs, load aggregators (LAs) and demand response aggregators (DRAs) and also interacts with ISO as the wholesale power market operator. The proposed framework allows DERs to transact with the wholesale power market and prosumers
  9. Keywords:
  10. Uncertainty Modeling ; Generating Planning ; Day-ahead Energy Market ; Participation ; Distributed System ; Distributed Energy Resorurces (DER) ; Distribution System Operator (DSO)

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