Optimal demand response strategies to mitigate wind power variability and gas-supply uncertainty in a multi-resolution robust security constrained unit commitment

17Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.

Abstract

With the increasing penetration rate of renewable energy sources, variability impacts, aside from uncertainty, will increase the need for operational flexibility resources in power systems. Accordingly, in this study, flexibility provision from both generation and demand sides are considered in a day-ahead scheduling problem. Fast start gas-fired units, due to their agility in starting-up and high ramping capabilities are considered as generation side flexibility providers. However, the normal operation of these units strictly depends on a secure gas supply through connected gas pipelines. Thus, gas-supply uncertainty is considered in the proposed model to mimic the impacts of deviations in gas volume through pipelines. On the other hand, demand response programs (DRPs) with their specific characteristics are among powerful demand side flexibility providers. However, unlike the existing literature that considers a supplementary role for DRPs, this study introduces the main role for DRPs as flexibility providers through comprehensive modelling of versatile DRPs. The proposed day-ahead scheduling problem is a multi-resolution robust security constrained unit commitment that the robustness comes from the decision making against sub-hourly gas-supply uncertainty and wind power variability. The applicability of the proposed model is tested on both an 8-bus and IEEE-118-bus standard test systems.

Cite

CITATION STYLE

APA

Safipour, H., Abdollahi, A., Hajmohammadi, M. S., & Alizadeh, M. I. (2020). Optimal demand response strategies to mitigate wind power variability and gas-supply uncertainty in a multi-resolution robust security constrained unit commitment. IET Generation, Transmission and Distribution, 14(14), 2740–2750. https://doi.org/10.1049/iet-gtd.2019.1752

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free