Adaptive robust operation of the active distribution network including renewable and flexible sources. (June 2021) - Kiani, Hossein; Hesami, Kamal; Azarhooshang, Alireza; Pirouzi, Sasan; Safaee, Sheila
Abstract: This paper presents the optimal scheduling model of the active distribution network (ADN) containing renewable energy sources (RESs) and flexible sources (FSs) such as non-RESs (NRESs) and electric vehicles (EVs) parking lot based on the adaptive robust optimization (ARO). In the deterministic programming, a two-objective optimization model is expressed. It minimizes the difference between the network and NRES operation cost and the revenue of the RES, NRES and FS due to the sale of active and reactive power in the first objective function, and the second objective function considers the minimizing of the voltage deviation. Also, this problem considers AC optimal power flow constraints for the ADN in the presence of the RES, NRES and EVs parking lot. This method is as the non-linear programming (NLP). It is converted to the linear programming (LP) model based on the conventional linearization approaches to achieve the optimal solution at a short computational time. Then, the proposed approach is modeled as a single-objective optimization formulation using ε -constraint-based Pareto optimization. This problem contains uncertainty of load, market price, EVs and RES characteristics; therefore, the ARO is used in this paper to model/obtain these uncertain parameters/robust capabilities of renewable and flexible sources to improve the network operation indices. The proposed scheme is implemented on the IEEE 33-bus ADN to improve the network indices such as voltage profile with determining optimal and robust scheduling of RES and FS according to numerical results.