Optimal Bidding Strategy for Physical Market Participants With Virtual Bidding Capability in Day-Ahead Electricity Markets

Virtual bidding provides a mechanism for financial players to participate in wholesale day-ahead (DA) electricity markets. The price difference between DA and real-time (RT) markets creates arbitrage opportunities players. Physical market participants (MP), referred as with physical assets this paper, can also take advantage of virtual but different way, which is further amplify the value their assets. Therefore, work proposes model such MPs maximize profits. This employs bi-level optimization approach, where upper-level subproblem maximizes total profit from both generations transactions while lower-level mimics multi-period network-constrained clearing process. In model, uncertainties associated other well RT prices are considered. Moreover, conditional value-at-risk (CVaR) metric utilized measure risk diverse strategies. optimal strategy strategic MP derived by solving model. proposed transformed single level mixed integer linear programming (MILP) using Karush-Kuhn-Tucker (KKT) optimality conditions duality theory. Case studies show effectiveness method reveal may choose deploy very way than pure MPs.