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This paper finds near equilibrium prices for electricity markets withnonconvexities due to binary variables, in order to reduce the marketparticipants' opportunity costs, such as generators' unrecovered costs. Theopportunity cost is defined as the difference between the profit when theinstructions of the market operator are followed and when the marketparticipants can freely make their own decisions based on the market prices. Weuse the minimum complementarity approximation to the minimum total opportunitycost (MTOC) model, from previous research, with tests on a much more realisticunit commitment (UC) model than in previous research, including features suchas reserve requirements, ramping constraints, and minimum up and down times.The developed model incorporates flexible price responsive demand, as inprevious research, but since not all demand is price responsive, we considerthe more realistic case that total demand is a mixture of fixed and flexible.Another improvement over previous MTOC research is computational: whereas theprevious research had nonconvex terms among the objective function's continuousvariables, we convert the objective to an equivalent form that contains onlylinear and convex quadratic terms in the continuous variables. We compare theunit commitment model with the standard social welfare optimization version ofUC, in a series of sensitivity analyses, varying flexible demand to representvarying degrees of future penetration of electric vehicles and smartappliances, different ratios of generation availability, and different valuesof transmission line capacities to consider possible congestion. The minimumtotal opportunity cost and social welfare solutions are mostly very close indifferent scenarios, except in some extreme cases.

Extended opportunity cost model to find near equilibrium electricity prices under non-convexities