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195191 https://hdl.handle.net/2286/R.2.N.195191 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved 2024 123 pages Masters Thesis Academic theses Text eng Pudukkarai Srinivas, Nirupama Khorsand Hedman, Mojdeh MKH Wu, Meng MW Ranjram, Mike MR Arizona State University Partial requirement for: M.S., Arizona State University, 2024 Field of study: Electrical Engineering Global traction towards meeting energy demand through sustainable technologies due to imperative ecological damage and resource depletion has increased attention towards renewable energy resources and Distributed Energy Resources (DERs). The inherent intermittent behavior associated with renewable resources pose hurdles to the successful integration of DERs in the electricity market as they struggle to compete with the deterministic behavior of traditional power-generating resources. Furthermore, previous market regulations made the participation of DERs challenging due to requirements related to size and performance. Federal Energy Regulatory Commission (FERC) Order No. 2222 paved the way for DERs to participate in the market via aggregations to meet regulatory requirements. However, it is necessary to develop bidding strategies unique to DER aggregators due to the uncertainty and low operational cost. Multiple works in literature investigate the bidding strategy of DER Aggregators, considering the risk of failing obligations which pose financial risks to the aggregator. This work proposes a bidding strategy for a DER aggregator whose resource mix comprises Photovoltaic (PV) units and Energy Storage Resources (ESRs) participating in the day ahead and real-time components of the energy and ancillary service market. This work covers the day-ahead model with a vision of real-time. Regulation-up is the only service considered concerning the participation of ancillary services. The framework uses a scenario-based modeling approach for market price and PV output power uncertainty. The model produces price-quantity offer curves for the day-ahead energy and ancillary service market. Electrical Engineering Bidding Strategy Distributed Energy Resources Electricity Markets Optimization A Day-Ahead Bidding Strategy Algorithm for Distributed Energy Resource Aggregators