Pereira, MPS; Fitiwi, DZ; Santos, SF; Catalao, JPS;
Conference Proceedings - 2017 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017
In the last decade, the level of variable renewable energy sources (RESs) integrated in distribution network systems have been continuously growing. This adds more uncertainty to the system, which also faces all traditional sources of uncertainty and those pertaining to other emerging technologies such as demand response and electric vehicles. As a result, distribution system operators are finding it increasingly difficult to maintain an optimal daily operation of such systems. Such challenges/limitations are expected to be alleviated when distribution systems undergo the transformation process to smart grids, equipped with appropriate technologies such as energy storage systems (ESSs) and switchable capacitor banks (SCBs). These technologies offer more flexibility in the system, allowing effective management of the uncertainty in RESs. This paper presents a stochastic mixed integer linear programming (SMILP) model, aiming to optimally operate distribution network systems, featuring variable renewables, and minimizing the impact of RES uncertainty on the system's overall performance via ESSs and SCBs. A standard 41-bus distribution system is employed to show the effectiveness of the proposed S-MILP model. Simulation results indicate that strategically placed ESSs and SCBs can substantially alleviate the negative impact of RES uncertainty in the considered system. © 2017 IEEE.
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