Two-stage stochastic energy and reserve market clearing model considering real-time offering strategy of renewable energy

With the introduction of decarbonization policies worldwide, renewable energy, especially wind and solar power, is gradually taking a significant share in the power system. The two-stage stochastic optimization methods are generally adopted to address the uncertainty issues and the two-stage stochastic market clearing models are established with the participation of renewable energy. However, most existing two-stage stochastic market clearing models usually intuitively presume the offering quantities of renewable energy are equal to their forecast values, neglecting the potential impacts of the strategic offerings on the market results and thus affecting the secure operation of power systems. To fill the gaps, this paper incorporates the strategic offering models of renewable energy into the two-stage stochastic energy and reserve market clearing model. Within the two-stage framework, the first day-ahead stage serves for energy and reserve market clearing, while the second real-time stage considers the adjustments on offering quantities of renewable energy according to the fluctuations of renewable generations. The two-stage stochastic market clearing model is formulated as a mixed-integer non-linear programming problem, and an iterative algorithm is devised to obtain market clearing results after proper linearizations. The effectiveness of the proposed method is validated using the extended IEEE-118 test system.