A Stochastic Bilevel Model for an Electricity Retailer in a Liberalized Distributed Renewable Energy Market

This article presents a short-term decision-making model for an electricity retailer using bilevel stochastic programing. In the proposed model, a liberalized distributed renewable energy (DRE) market in which the retailer competes with other load serving entities (LSEs) for procuring DRE is propose...

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Bibliographic Details
Published in:IEEE Power & Energy Society General Meeting p. 1
Main Authors: Campos do Prado, Josue, Qiao, Wei
Format: Conference Proceeding
Language:English
Published: IEEE 17.07.2022
Subjects:
Costs
Decision making
Procurement
Production
Real-time systems
Renewable energy sources
Stochastic processes
ISSN:1944-9933
Online Access:Get full text
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Summary:This article presents a short-term decision-making model for an electricity retailer using bilevel stochastic programing. In the proposed model, a liberalized distributed renewable energy (DRE) market in which the retailer competes with other load serving entities (LSEs) for procuring DRE is proposed. The retailer, in the upper level, decides its level of involvement in the day-ahead and real-time markets, as well as the price bids offered to DRE producers for every time period, with the goal of minimizing its expected procurement cost at a predefined risk level. On the other hand, DRE producers, in the lower level, react to the price bids offered by the retailer under study and other LSEs, to maximize their total revenues. The stochastic nature of day-ahead and real-time market prices, DRE production, electricity demand, and price bids of the retailer's rival market agents (RMAs) is taken into the formulation of the proposed model. By using the Karush-Kuhn-Tucker (KKT) optimality conditions and duality theory, the bilevel problem is transformed into its equivalent single-level mixed-integer linear programming (MILP) problem. Case studies are performed to show the effectiveness of the proposed model.
ISSN:1944-9933
DOI:10.1109/PESGM48719.2022.9917108