Flexibility pricing of integrated unit of electric spring and EVs parking in microgrids

• Published in: Energy (Oxford) Vol. 239; p. 122080
• Main Authors: Norouzi, Mohammadali, Aghaei, Jamshid, Pirouzi, Sasan, Niknam, Taher, Fotuhi-Firuzabad, Mahmud
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 15.01.2022; Elsevier BV
• Subjects: Constraint modelling; Distributed generation; Economic models; Electric power demand; Electric vehicles; electronics; Energy; Energy costs; Energy management; Flexibility; Flexibility services pricing; Flexibility sources; Flexible power management; Integrated unit of electric spring and electric vehicles parking; Optimization; Parameter uncertainty; Parking; Power flow; Power management; prices; Pricing; Profits; Renewable energy sources; spring; Stochastic programming; system optimization; Topology; Flexible power management; Flexibility sources; Flexibility services pricing; Integrated unit of electric spring and electric vehicles parking; Stochastic programming
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2021.122080

Electric spring (ES) as a breakthrough in power electronics has led to a revolution in demand-side management. This paper presents flexible power management (FPM) of a networked microgrid (MG) in the presence of renewable energy sources (RESs) and flexibility sources (FSs). The FSs include the novel topology of the integrated unit of ES with electric vehicles (EVs) parking (IUEE) and incentive-based demand response program (DRP). The proposed FPM model is formulated as an optimization problem that minimizes the difference between the expected energy cost and the expected profit of FSs' flexibility subject to the AC optimal power flow (AC-OPF), RESs, FSs, and MG flexibility constraints. In the proposed model, flexibility pricing is performed for both upward and downward flexibility services in which the expected flexibility profit is proportional to the product of the FSs' flexibility and flexibility incentive price (FIP). Further, this paper uses a stochastic programming to model uncertain parameters associated with load demand, energy prices, maximum RES generation capacity, and EVs’ parameters. Finally, the potential of the proposed FPM model in improving the economic, operational and flexibility conditions of the MG is investigated through implementation of the proposed model on the 32-bus radial MG. [Display omitted] •Integrated unit of ES with EVs parking is developed for demand response.•Flexible energy management of a networked microgrid with RESs is presented.•Flexibility pricing is performed for both upward and downward flexibility services.•Stochastic optimization proposed to model uncertainty of load, price, RES, and EVs.