A Decision Model for an Electricity Retailer With Energy Storage and Virtual Bidding Under Daily and Hourly CVaR Assessment

• Published in: IEEE access Vol. 9; pp. 106181 - 106191
• Main Authors: Prado, Josue Campos Do, Chikezie, Ugonna
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Conditional value-at-risk (CVaR); Decision making; Electricity; electricity retailer; Electricity supply industry; Energy storage; Load modeling; Optimization; Procurement; Real-time systems; Risk management; State of charge; stochastic optimization; Stochastic processes; virtual bidding
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2021.3100815

This paper presents a short-term decision-making model for an electricity retailer with battery energy storage system (BESS) and virtual bidding through a two-stage stochastic optimization framework. In the first stage, the retailer determines the amount of power to be purchased in the day-ahead wholesale market and the optimal incremental and decremental virtual bidding strategies. In the second stage, the optimal energy storage decisions and the retailer's involvement in the real-time market are determined. The proposed model minimizes the retailer's expected procurement cost and generates the optimal power and virtual bidding curves in the day-ahead market. Two types of Conditional Value at Risk (CVaR) are integrated in the proposed model to manage the retailer's hourly and daily risks, respectively. Case studies with real-world data are performed to verify the retailer's cost reduction obtained with the integration of BESS and virtual bidding and to study how the hourly and daily risk-management strategies affect the retailer's procurement cost distribution for different risk-aversion levels.