Stackelberg game-based energy management for a microgrid with commercial buildings considering correlated weather uncertainties

This paper proposes a Stackelberg game-based optimal energy management model for a microgrid with commercial buildings (CBs), which include a cluster of flexible loads, such as a heating, ventilation, and air conditioning (HVAC) system and a lighting system. In particular, the microgrid operator (MGO) determines the optimal energy management scheme while the CBs enjoy a dynamic pricing tariff to adjust their consumption patterns for cost saving. The interactions between MGO and CBs are formulated as a bi-level optimisation problem where the MGO behaves as a leader and CBs act as followers. The proposed model is transformed into a mixed integer linear programming (MILP) problem by jointly using the Karush-Kuhn-Tucker (KKT) condition and the strong duality theory. Besides, the effects of correlated solar irradiance and solar illuminance uncertainties on the load profile are taken into account through invoking the Nataf transformation-based 2M + 1 point estimate method (PEM). Finally, case studies are served for demonstrating the feasibility and efficiency of the proposed method.