The development of control of a power system that supply electricity is a major concern in the world. Some trends have led to power systems becoming overstated including the rapid growth in the demand for electrical power, the increasing penetration of the system from renewable energy, and uncertainties in power schedules and transfers. To deal with these challenges, power control has to overcome several structural hurdles, a major one of which is dealing with the high dimensionality of the system.
Dimensionality reduction of the controller structure produces effective control signals with reduced computational load. In most of the existing studies, the topology of the control and communication structure is known prior to synthesis, and the design of distributed control is performed subject to this particular structure. However, in this thesis we present an advanced model of design for distributed control in which the control systems and their communication structure are designed simultaneously. In such cases, a structure optimization problem is solved involving the incorporation of communication constraints that will punish any communication complexity in the interconnection and thus will be topology dependent. This structure optimization problem can be formulated in the context of Linear Matrix Inequalities and l1-minimization.
Interconnected power systems typically show multiple dominant inter-area low-frequency oscillations which lead to widespread blackouts. In this thesis, the specific goal of stability control is to suppress these inter-area oscillations. Simulation results on large-scale power system are presented to show how an optimal structure of distributed control would be designed. Then, this structure is compared with fixed control structures, a completely decentralized control structure and a centralized control structure
