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Fateme Daneshfar

Fateme Daneshfar

Academic rank: Assistant Professor
ORCID:
Education: PhD.
ScopusId: 35078447100
Faculty: Faculty of Engineering
Address: Department of Computer Engineering, Faculty of Engineering, University of Kurdistan
Phone:

Research

Title
Reinforcement learning based multi-agent LFC design concerning the integration of wind farms
Type
Presentation
Keywords
Load-frequency control- Reinforcement learning- Multi-agent systems-Wind power generator
Year
2010
Researchers Hassan Bevrani ، Fateme Daneshfar ، Puria Daneshmand ، Takashi Hiyama

Abstract

Frequency regulation in interconnected networks is one of the main challenges posed by wind turbines in modern power systems. The wind power fluctuation negatively contributes to the power imbalance and frequency deviation. This paper presents an intelligent agent based load frequency control (LFC) for a multi-area power system in the presence of a high penetration of wind farms, using multi-agent reinforcement learning (MARL). Nonlinear timedomain simulations on a 39-bus test power system are used to demonstrate the capability of the proposed control scheme.