Exploring potential storage-based flexibility gains of electric vehicles in smart distribution grids

• Published in: Journal of energy storage Vol. 52; p. 105056
• Main Authors: Pirouzi, Afshin, Aghaei, Jamshid, Pirouzi, Sasan, Vahidinasab, Vahid, Jordehi, Ahmad Rezaee
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 25.08.2022
• Subjects: Electric vehicle parking lot; Linear flexible power management; Renewable energy sources; Smart distribution network; Stochastic multiobjective formulation; Uncertainty; Electric vehicle parking lot; Renewable energy sources; Uncertainty; Smart distribution network; Linear flexible power management; Stochastic multiobjective formulation
• ISSN: 2352-152X; 2352-1538
• DOI: 10.1016/j.est.2022.105056

Flexibility is one of the most important solutions for facilitating the variability of renewable energy sources (RESs) in a distribution network. It is predicted that electric vehicles (EVs) can play an effective role in improving it in the distribution networks. So, this paper presents multiobjective scheduling of batteries of EVs in parking lots (EVPLs) to improve the storage-based flexibility of smart distribution networks (SDNs). The proposed formulation minimizes the energy cost and the voltage deviation function and maximizes the system flexibility (SF) as multiobjective functions that will be optimized subject to the AC load flow, RES and EV constraints, and the allowable limits of the flexibility and operation indices. The resulting model is in the form of a nonlinear programming (NLP) model. Therefore, an equivalent linear programming (LP) formulation is obtained for the original problem to achieve the global optimum result. The stochastic programming approach is used to model uncertainties of the load, active power generation of RESs, price of energy, and EV parameters. The flexible power management is formulated as one of the objective functions of the proposed multiobjective framework, which is solved by using the ε-constraint method, reaching the best possible compromise solution by a fuzzy decision-maker. The proposed framework is tested by using a 33-bus radial test distribution network in the GAMS software environment to evaluate the EVs capability in improving the flexibility indices. Based on the numerical results, it is observed that the proposed scheme with optimal energy management of EVs is able to obtain a high flexibility for SDN. It can also reduce energy losses in terms of network operation and provide a rather smooth voltage profile. [Display omitted] •Electric Vehicles (EVs) are used for flexibility management in smart distribution grids.•Flexible power management is formulated as an objective function in the operation.•Multiobjective optimization is proposed to activate the capabilities of storage-based flexibility of EVs.•The multiobjective framework is solved using an enhanced ε-constraint method.