Open AccessStochastic multi‐objective frequency control in joint energy and reserve markets considering power system security
Author(s) -
Jadid Shahram,
Rabbanifar Payam
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.2011.0842
Subject(s) - joint (building) , electric power system , automatic frequency control , computer science , control (management) , energy (signal processing) , power (physics) , mathematical optimization , control theory (sociology) , mathematics , telecommunications , engineering , statistics , physics , quantum mechanics , architectural engineering , artificial intelligence
This study presents a novel stochastic multi‐objective model for precise scheduling of energy and reserve services in day‐ahead markets. This model is based on a security‐constrained market clearing with an emphasis on preservation of system frequency. A frequency index that is derived from the total system frequency profile during post‐contingency intervals has been defined as an extra objective function to control system frequency after the occurrence of a contingency. The model is capable of scheduling the tertiary regulation interval through appropriate generators’ reference power setting instructions made by the ISO based on participants’ bids for energy and reserve services. The reference power settings are obtained by an optimisation model and can be performed directly by the speed changers. The load dependency on frequency has also been analysed in the proposed model. This approach could be used by ISOs to make a trade‐off concurrently between system frequency profile and total operating cost to operate the power system securely in an economically efficient manner. The developed multi‐objective programming is analysed through two case studies; a three‐bus system scheduled over 1 h and the IEEE 24‐bus reliability test system over 24 h, solved by means of mixed‐integer linear programming methods.