In this paper we present a system architecture and suitable control methodologies for the management and control of Distributed Generation (DG) units, Renewable Energy Resources (RES) and Active Demand (AD). Within the proposed platform, control methodologies allow to adapt unit generation profiles and active loads to ensure economic benefits to each actor. The key aspect is the organization in two levels of control: at residential level a Smart Home Controller (SHC) monitors and controls smart appliances while at higher level a Community Energy Management System (CEMS) coordinates generation units, set of SHCs and power grid energy withdrawals. Proposed control methodologies involve the solution of a Walrasian market equilibrium and the design of a distributed algorithm.

 This paper proposes a new robust control strategy to prevent the current ripple propagation into the dc-dc converter input, thus avoiding converter malfunctions. Concretely, we apply the new strategy to a buck-boost converter. The strategy is based on LMI control and use readily, fast convex optimization algorithms to obtain the solution. The control objective is maximizing the current disturbance rejection, where current ripple propagation and usual, prescribed dynamic performances are ensured. The paper describes the control design procedure, besides an illustrative example and simulation verifications. Simulation waveforms are in perfect agreement with objective function and performances constraints of the control design. That is, the current ripple propagation is almost zero and other prescribed constraints are satisfied.

 This paper deals with the problem to guarantee system stability and voltage regulation in multimachine power systems. The power system is decomposed in $n$ subsystems each one containing a synchronous generator. For each subsystem two input-output models of low order are derived modelling the electrical and mechanical dynamics, respectively. Each model presents parameter uncertainties and input disturbance. A voltage controller based on the internal model control is designed and sequentially a stabilizing controller (PSS) is designed so as to enhance swing damping. According to the decentralized approach, the controllers use only locally available measurements. Numerical simulation studies conducted on a three machine test power system show the performance obtained in the presence of severe contingencies.

 A new combined method based on optimal control is proposed to enhance load frequency control dynamics. This method include of PSO and optimal output feedback controller. In the output feedback method only the measurable state variables within each control area is required to use for feedback. The optimal control law is determined by minimizing a performance index under the output feedback conditions leading to a coupled matrix equation. But for more accuracy and better design for this controller, PSO algorithm is applied to find the gain matrix of the controller. The results of the simulation are shown that with using this method, the load frequency control requirements in a practical environment are satisfied and also better dynamic responses are accessible.