Hybrid model for stochastic clearing of joint energy and reserves market

Day-ahead market clearing is usually executed by independent system operator to determine the accepted energy and reserve bids and their payments. In this study, an effective multi-objective stochastic framework is presented for joint energy and reserves market clearing problem considering the power system security. To this end, the 24 h scenarios are generated using the Monte Carlo simulation (MCS). Besides, a scenario reduction technique is also presented to reduce the computational burden of the proposed stochastic market clearing procedure. A new validation method based on MCS which is called MCVM method is proposed to verify the proposed strategy against the deterministic model. Direction scalarisation method (DSM) is proposed to solve the proposed multi-objective problem. A new method as the combination of gravitational search algorithm and primal-dual interior point method is employed to solve the proposed single-objective optimisation problem obtained by the DSM. IEEE 24-bus test system is used to address the effectiveness of the proposed framework.

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