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

机译:考虑相关天气不确定性的基于Stackelberg游戏的商业建筑微电网能源管理

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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.
机译:本文为带有商业建筑(CB)的微电网提出了一个基于Stackelberg游戏的最佳能源管理模型,该模型包括一组柔性负载,例如供暖,通风和空调(HVAC)系统和照明系统。尤其是,微电网运营商(MGO)确定了最佳的能源管理方案,而可转换银行则享受动态定价,以调整其消费模式以节省成本。 MGO和CB之间的交互被描述为一个双层优化问题,其中MGO充当领导者,而CB充当追随者。结合Karush-Kuhn-Tucker(KKT)条件和强对偶理论,将提出的模型转换为混合整数线性规划(MILP)问题。此外,通过调用基于Nataf变换的2M +1点估计方法(PEM),考虑了太阳辐照度和太阳照度不确定性对负载分布的影响。最后,通过案例研究证明了该方法的可行性和有效性。

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