Optimal Dynamic Pricing for Peer-to-Peer Transactions in Electricity Markets - دانشکده فنی و مهندسی
Optimal Dynamic Pricing for Peer-to-Peer Transactions in Electricity Markets
نوع: Type: Thesis
مقطع: Segment: PHD
عنوان: Title: Optimal Dynamic Pricing for Peer-to-Peer Transactions in Electricity Markets
ارائه دهنده: Provider: Hossein Asadi
اساتید راهنما: Supervisors: Alireza Hatami
اساتید مشاور: Advisory Professors:
اساتید ممتحن یا داور: Examining professors or referees: Mohammad Hassan Moradi-Iraj Ahmadi-Kazem Zare
زمان و تاریخ ارائه: Time and date of presentation: 2026
مکان ارائه: Place of presentation: seminar
چکیده: Abstract: This dissertation presents an integrated and comprehensive framework for dynamic pricing and energy management in solar microgrids, combining three pricing strategies, namely Supply to Demand Ratio (SDR), Dynamic Supply to Demand Ratio (DSDR), and Time of Use Supply to Demand Ratio (TOU SDR), within a bi-level iterative model that accounts for photovoltaic generation uncertainty and user discomfort cost. A two-stage framework is also proposed for integrating demand response and peer to peer trading, in which the first stage performs optimal scheduling of smart appliances, batteries, and electric vehicles using a Binary Genetic Algorithm, and the second stage executes energy trading based on three state internal prices. In addition, a novel temporal resolution enhancement from one hour to 30, 20, and 15 minute intervals with a floating time approach is introduced. Simulation results demonstrate that the proposed pricing strategies lead to reduced net costs and increased economic revenues; battery integration further reduces costs; and increased temporal resolution reduces peak demand and grid imports while increasing prosumer revenues. The proposed framework provides a practical tool for microgrid operators, distribution companies, and energy policymakers in designing pricing structures and participation incentives in local energy markets. Keywords: Dynamic Pricing, Peer to Peer Trading, Demand Response, Solar Microgrid, Binary Genetic Algorithm, Generation Uncertainty, Discomfort Cost, Temporal Resolution.