In this paper, two robust decentralized control design methodologies for load frequency control (LFC) are proposed. The first one is based on control design using linear matrix inequalities (LMI) technique in order to obtain robustness against uncertainties. The second controller has a simpler structure, which is more appealing from an implementation point of view, and it is tuned by a proposed novel robust control design algorithm to achieve the same robust performance as the first one. More specifically, genetic algorithms (GAs) optimization is used to tune the control parameters of the proportional-integral (PI) controller subject to the constraints in terms of LMI. Hence, the second control design is called GALMI. Both proposed controllers are tested on a three-area power system with three scenarios of load disturbances to demonstrate their robust performances.

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This paper presents a technique for PSS design which is based on multiobjective optimization. The technique has the ability to tune multiple PSS controllers by simultaneously enhancing the damping based performance index and robustness index specifi ed via the IIHlloo norm of the system. To illustrate the proposed design technique two case studies are presented, including a two-area benchmark system and a fifty-machine test system. To allow the proposed tools to be applied for PSS control design, the authors developed a MATLAB interface to the Micro GA optimization solver.