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This study presents a single-phase grid-tied photovoltaic (PV) system based on a global maximum power point tracking (MPPT) technique, which is performed by means of the particle swarm optimisation (PSO) method. The PSObased MPPT technique is employed to solve problems related to mismatching phenomena, such as partial shading, in which the PV arrays are commonly submitted. Considering the search of the global maximum power point under partial shading, the effectiveness of the PSO-based MPPT technique is highlighted when compared with the wellknown perturb and observe MPPT technique, since both the mentioned MPPT techniques are used to determine the dcbus voltage reference to ensure a proper grid-tied inverter operation. A current generator algorithm based on a synchronous reference frame is proposed, which operates in conjunction with a dc-bus controller and MPPT algorithms, computing the reference current of the grid-tied inverter. In addition, the current generator controls the energy processed by the PV system to avoid over power rating of the grid-tied inverter, since the active power injection into the grid, reactive power compensation and harmonic currents suppression are carried out simultaneously. The performance and feasibility of the grid-tied PV system are evaluated by means of simulation and experimental results.

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Abstract-The note presents an algorithm for the average cost control problem of continuous-time Markov jump linear systems. The controller assumes a linear state-feedback form and the corresponding control gain does not depend on the Markov chain. In this scenario, the control problem is that of minimizing the long-run average cost. As an attempt to solve the problem, we derive a global convergent algorithm that generates a gain satisfying necessary optimality conditions. Our algorithm has practical implications, as illustrated by the experiments that were carried out to control an electronic dc-dc buck converter. The buck converter supplied a load that suffered abrupt changes driven by a homogeneous Markov chain. Besides, the source of the buck converter also suffered abrupt Markov-driven changes. The experimental results support the usefulness of our algorithm.

This study deals with the development of a photovoltaic (PV) electronic emulator (PVEE), operating integrated with a graphic computing platform, for teaching topics related to PV systems in either undergraduate or postgraduate courses. The PVEE is deployed by a DC-DC buck converter to emulate on its output terminals several characteristic curves of a specific PV system, in which climate conditions such as solar irradiation and temperature are taken into account. Emulation of the PV module characteristic curves is embedded in a digital signal controller, which is based on a mathematical model that represents the electric circuit of the PV cell. The educational platform makes possible the following tasks: (i) define and change the PV cell model, (ii) define the number of PV modules, (iii) define and change the solar irradiation and temperature that the PV modules are subjected to, and (iv) visualise voltage and current quantities that are synthesised by the PVEE. From experimental tests, the PVEE is evaluated considering climatic variations involving solar irradiation, temperature, and load transients, whose purpose is to validate the theoretical development. Furthermore, the DC-DC boost converter is employed to perform the maximum power point tracking. Experimental results demonstrate the effectiveness of the proposed system.