Hybrid stochastic/robust flexible and reliable scheduling of secure networked microgrids with electric springs and electric vehicles

• Published in: Applied energy 2021-10, Vol.300, p.117395, Article 117395
• Main Authors: Norouzi, Mohammadali, Aghaei, Jamshid, Pirouzi, Sasan, Niknam, Taher, Fotuhi-Firuzabad, Mahmud, Shafie-khah, Miadreza
• Format: Article
• Language: English
• Subjects: Electric spring; Electric vehicle parking lot; electronics; energy; energy costs; Hybrid stochastic/robust optimization; Power management strategy; renewable energy sources; spring; Technical and economic model
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2021.117395

•Electric spring model is developed for demand-side management.•Flexibility of EVs is used to increase wind energy.•EVs and electric spring are modeled as flexibility tools to transfer energy.•The paper deals with day-ahead operation of smart microgrids.•Hybrid stochastic/robust optimization is proposed to handle uncertainty. Electric spring (ES) as a novel concept in power electronics has been developed for the purpose of dealing with demand-side management. In this paper, to conquer the challenges imposed by intermittent nature of renewable energy sources (RESs) and other uncertainties for constructing a secure modern microgrid (MG), the hybrid distributed operation of ESs and electric vehicles (EVs) parking lot is suggested. The proposed approach is implemented in the context of a hybrid stochastic/robust optimization (HSRO) problem, where the stochastic programming based on unscented transformation (UT) method models the uncertainties associated with load, energy price, RESs, and availability of MG equipment. Also, the bounded uncertainty-based robust optimization (BURO) is employed to model the uncertain parameters of EVs parking lot to achieve the robust potentials of EVs in improving MG indices. In the subsequent stage, the proposed non-linear problem model is converted to linear approximated counterpart to obtain an optimal solution with low calculation time and error. Finally, the proposed power management strategy is analyzed on 32-bus test MG to investigate the hybrid cooperation of ESs and EVs parking lot capabilities in different cases. The numerical results corroborate the efficiency and feasibility of the proposed solution in modifying MG indices.