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In this paper, a stochastic multiobjective framework is proposed for day-ahead joint market clearing. The proposed multiobjective framework can concurrently optimize competing objective functions including augmented generation offer cost and security indices (overload index, voltage drop index, and voltage stability margin). Besides, system uncertainties including generating units and branches contingencies and load uncertainty are explicitly considered in the stochastic market clearing scheme. The solution methodology consists of two stages, which firstly, employs roulette wheel mechanism and Monte Carlo simulation (MCS) for random adaptive 24-h scenario generation wherein the stochastic multiobjective market clearing procedure is converted into its respective deterministic equivalents (scenarios). In the second stage, for each deterministic scenario, a multiobjective mathematical programming (MMP) formulation based on the epsiv -constrained approach is implemented for provision of spinning reserve (SR) and nonspinning reserve (NSR) as well as energy. The MMP formulation of the market clearing process is optimized while meeting AC power flow constraints and expected interruption cost (EIC). The IEEE 24-bus Reliability Test System (RTS 24-bus) is used to demonstrate the performance of the proposed method.
Amjady et al. (Tue,) studied this question.