Toggle Main Menu Toggle Search

Open Access padlockePrints

Integration of wind generation uncertainties into frequency dynamic constrained unit commitment considering reserve and plug in electric vehicles

Lookup NU author(s): Dr Mansoureh Zangiabadi

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Abstract

© 2020 Elsevier LtdIncreased penetration of renewable resources in power systems and consequently cut back in the inertia of the whole power system is a significant concern for Unit Commitment (UC) in terms of energy scheduling and frequency dynamics management. The new modeling of the UC problem presented in this paper provides optimal scheduling of the energy and reserve considering the frequency dynamics of the power system. In this work, impact of Wind Turbines (WT) as the clean generation and Plug-in Electric Vehicles (PEV) as the energy storage system are investigated considering a less conservative probabilistic modeling uncertainty of the wind. The paper targets to protect the security of frequency dynamics taking into account the Demand Response (DR) program and contribution of PEVs succeeding a generation loss. The Frequency Dynamics-constrained Unit Commitment (FDUC) considering PEVs was formulated as a Mixed-Integer Non-Linear Programming (MINLP) problem taking into consideration DR and WTs uncertainties. The proposed MINLP problem was then reformulated by the Reformulation-Linearization Technique (RLT) to derive a Mixed-Integer Linear Programming (MILP) problem. An IEEE 6-bus power system was served as a test system to evaluate the proposed approach and simulation results of four different Case study scenarios were obtained. Results revealed that the proposed approach can ensure frequency security and reduce the operational costs.


Publication metadata

Author(s): Mousavi-Taghiabadi SM, Sedighizadeh M, Zangiabadi M, Fini AS

Publication type: Article

Publication status: Published

Journal: Journal of Cleaner Production

Year: 2020

Volume: 276

Online publication date: 18/09/2020

Acceptance date: 15/09/2020

ISSN (print): 0959-6526

Publisher: Elsevier Ltd

URL: https://doi.org/10.1016/j.jclepro.2020.124272

DOI: 10.1016/j.jclepro.2020.124272


Altmetrics

Altmetrics provided by Altmetric


Share