Strategic Bidding in Electricity Markets with Convexified AC Market-Clearing Process
Arash Farokhi Soofi, Saeed D. Manshadi

TL;DR
This paper develops a convexified AC optimal power flow-based market-clearing framework for strategic bidding in electricity markets, enhancing profit and price accuracy over traditional DC models.
Contribution
It introduces a tractable mathematical programming approach for AC market clearing that incorporates reactive power and improves profit and price accuracy.
Findings
Strategic bidding with ACOPF yields 52.3% more profit for GENCO.
ACOPF-based market clearing improves location marginal prices accuracy.
The method addresses real/reactive power, ramping, and line flow constraints.
Abstract
This paper presents a framework to solve the strategic bidding problem of participants in an electricity market cleared by employing the full AC Optimal Power Flow (ACOPF) problem formulation. Traditionally, the independent system operators (ISOs) leveraged DC Optimal Power Flow (DCOPF) problem formulation to settle the electricity market. The main quest of this work is to find what would be the challenges and opportunities if ISOs leverage the full ACOPF as the market-clearing Problem (MCP)? This paper presents tractable mathematical programming with equilibrium constraints for the convexified AC market-clearing problem. Market participants maximize their profit via strategic bidding while considering the reactive power dispatch of generation units. The equilibrium constraints are procured by presenting the dual form of the relaxed ACOPF problem. The strategic bidding problem with…
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