Open AccessHourly demand response in day‐ahead scheduling for managing the variability of renewable energy
Author(s) -
Wu Hongyu,
Shahidehpour Mohammad,
AlAbdulwahab Ahmed
Publication year - 2013
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2012.0186
Subject(s) - demand response , scheduling (production processes) , renewable energy , computer science , mathematical optimization , power system simulation , monte carlo method , operations research , electric power system , reliability engineering , engineering , power (physics) , mathematics , electricity , statistics , physics , quantum mechanics , electrical engineering
This study proposes a stochastic optimisation model for the day‐ahead scheduling in power systems, which incorporates the hourly demand response (DR) for managing the variability of renewable energy sources (RES). DR considers physical and operating constraints of the hourly demand for economic and reliability responses. The proposed stochastic day‐ahead scheduling algorithm considers random outages of system components and forecast errors for hourly loads and RES. The Monte Carlo simulation is applied to create stochastic security‐constrained unit commitment (SCUC) scenarios for the day‐ahead scheduling. A general‐purpose mixed‐integer linear problem software is employed to solve the stochastic SCUC problem. The numerical results demonstrate the benefits of applying DR to the proposed day‐ahead scheduling with variable RES.