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Hourly demand response in day-ahead scheduling for managing the variability of renewable energy
by
Wu, Hongyu
, Al-Abdulwahab, Ahmed
, Shahidehpour, Mohammad
in
Applied sciences
/ Disturbances. Regulation. Protection
/ economic response
/ Electrical engineering. Electrical power engineering
/ Electrical power engineering
/ Exact sciences and technology
/ forecast errors
/ general‐purpose mixed‐integer linear problem software
/ hourly‐demand response
/ integer programming
/ linear programming
/ Miscellaneous
/ Monte Carlo methods
/ Monte Carlo simulation
/ Operation. Load control. Reliability
/ power generation dispatch
/ power generation economics
/ power generation reliability
/ power generation scheduling
/ Power networks and lines
/ power system management
/ power systems
/ reliability response
/ renewable energy variability management
/ stochastic day‐ahead scheduling algorithm
/ stochastic optimisation model
/ stochastic SCUC scenario
/ stochastic security‐constrained unit commitment scenario
/ system component outage
2013
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Hourly demand response in day-ahead scheduling for managing the variability of renewable energy
by
Wu, Hongyu
, Al-Abdulwahab, Ahmed
, Shahidehpour, Mohammad
in
Applied sciences
/ Disturbances. Regulation. Protection
/ economic response
/ Electrical engineering. Electrical power engineering
/ Electrical power engineering
/ Exact sciences and technology
/ forecast errors
/ general‐purpose mixed‐integer linear problem software
/ hourly‐demand response
/ integer programming
/ linear programming
/ Miscellaneous
/ Monte Carlo methods
/ Monte Carlo simulation
/ Operation. Load control. Reliability
/ power generation dispatch
/ power generation economics
/ power generation reliability
/ power generation scheduling
/ Power networks and lines
/ power system management
/ power systems
/ reliability response
/ renewable energy variability management
/ stochastic day‐ahead scheduling algorithm
/ stochastic optimisation model
/ stochastic SCUC scenario
/ stochastic security‐constrained unit commitment scenario
/ system component outage
2013
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Hourly demand response in day-ahead scheduling for managing the variability of renewable energy
by
Wu, Hongyu
, Al-Abdulwahab, Ahmed
, Shahidehpour, Mohammad
in
Applied sciences
/ Disturbances. Regulation. Protection
/ economic response
/ Electrical engineering. Electrical power engineering
/ Electrical power engineering
/ Exact sciences and technology
/ forecast errors
/ general‐purpose mixed‐integer linear problem software
/ hourly‐demand response
/ integer programming
/ linear programming
/ Miscellaneous
/ Monte Carlo methods
/ Monte Carlo simulation
/ Operation. Load control. Reliability
/ power generation dispatch
/ power generation economics
/ power generation reliability
/ power generation scheduling
/ Power networks and lines
/ power system management
/ power systems
/ reliability response
/ renewable energy variability management
/ stochastic day‐ahead scheduling algorithm
/ stochastic optimisation model
/ stochastic SCUC scenario
/ stochastic security‐constrained unit commitment scenario
/ system component outage
2013
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Hourly demand response in day-ahead scheduling for managing the variability of renewable energy
Journal Article
Hourly demand response in day-ahead scheduling for managing the variability of renewable energy
2013
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Overview
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.
Publisher
The Institution of Engineering and Technology,Institution of Engineering and Technology,The Institution of Engineering & Technology
Subject
/ Disturbances. Regulation. Protection
/ Electrical engineering. Electrical power engineering
/ Electrical power engineering
/ Exact sciences and technology
/ general‐purpose mixed‐integer linear problem software
/ Operation. Load control. Reliability
/ power generation reliability
/ renewable energy variability management
/ stochastic day‐ahead scheduling algorithm
/ stochastic optimisation model
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