A risk-constrained optimal bidding strategy for a generation company by IWAPSO

In this paper, an optimal bidding strategy for a generation company by the inertia weight approach particle swarm optimization (IWAPSO) is proposed. The expected profit maximization and risk (profit variance) minimization are combined into the objective function of the optimization problem. Nonconvex operating cost functions of thermal generation units and minimum up/down time constraints are formulated to find the optimal bid prices for multi-hourly trading in a uniform price spot market. The rivals' behavior is approximated through the Monte Carlo (MC) simulation. The proposed method based on the IWAPSO and MC simulation can provide the efficient set of bid prices which is the best combinations between expected profit and risk. The mean-standard deviation ratio (MSR) index is used to select the optimal risky bid prices. The proposed approach is a profitable tool for a producer who needs to compromise between expected profit and risk in spot market. Moreover, this approach can be applied to different market models.