J.A.N. Pombo

Optimal output control: Load frequency control of a large power system

This paper addresses the stabilization and performance of the load frequency regulator. The problem is solved by using the theory of the optimal control. An algorithm, based on the new technique, proposed by the authors, to overcome the difficulties of specifying the weighting matrices Q and R, is presented. The algorithm here proposed considers the multi-area electric energy system. The paper presents illustrative numerical simulation results for this model. The results indicate that the obtained controller exhibits better performance then those based on classic control.

An electric vehicle charging station: Monitoring and analysis of power quality

Electric vehicles are a relatively recent technology that is seeking for its place in the market. It has several advantages, such as the reduced greenhouse emissions, fuel savings and its ease of use. The increase of the electric vehicles in the roads raises issues about their impact on the grid, in terms of power quality. This paper presents the main considerations about power balance and the impact of an electric vehicle charge in the voltage, current, and total harmonic distortion. An experimental charging station prototype for Modes 2 and 3 is used to acquire data of voltage, current and active and reactive power for different charging profiles and battery state of charge.

Pole-shifting procedure to specify the weighting matrices for a load-frequency controller

This paper addresses the stabilization and performance of the load frequency regulator. Proposes a new technique, based on pole placement using optimal regulators, to overcome the difficulties of specifying the weighting matrices Q and R. The design method employs successive shifting of an either real pole or a pair of complex conjugate poles at a time. The proposed technique builds Q and R in such a way that the systems response also obeys conventional criteria for the system pole location. The effectiveness of the proposed method is illustrated by numerical examples.

A new controller for DC-DC converters based on particle swarm optimization

Display Omitted We propose a new algorithm to control DC-DC converters.The new algorithm is based on Particle Swarm Optimization.The proposed controller does not require any parameter search like classical controllers.We compare the proposed controller with the PI Anti-Windup controller.The proposed controller exhibits better performance in terms of settling time and steady state oscillations. We propose a new controller for DC-DC converters based on particle swarm optimization (PSO). This new converter controller uses the PSO optimization method to directly control, by itself, the output voltage of a boost DC-DC converter. In order to validate and qualify the proposed converter controller, we analyzed and implemented some variants of the PSO algorithm, namely the standard PSO and the global local best PSO. The proposed converter controller was then compared with a variant of the classic PI controller with anti-windup, for different operational conditions. The three controllers compared in this work were implemented in the microcontroller TMS320F28027 by using the code composer studio from Texas Instruments. The results show that the proposed controller exhibits better behavior in terms of settling time and overshoot. Unlike most popular DC-DC converter controllers, the proposed controller does not require any sort of optimal parameter determination.

Evaluation of a particle swarm optimization controller for dc-dc boost converters

Particle swarm optimization has been used as a tuning algorithm for dc-dc converter controllers. In this work it is proposed a novel approach where the PSO is used as the controller itself for a dc-dc boost converter. The PSO controller uses a population of particles to achieve the necessary compensation to stabilize the output at reference voltage. The algorithm uses the gain formula to reposition the particles near the required position, to stabilize the output at reference voltage, according to the disturbances in the converter. Simulations have been carried on in order to observe the controllers response to changes in reference voltage and in load variance.

PV charging station for electric vehicles: Management and interface system

The importance given to Plug-in Hybrid Electric Vehicles and Electric Vehicles and its integration in world market has increased the interest in all related with the electrification of transportation, such as batteries and fast charging options for the users of this kind of cars. This paper presents the recently work conducted by the authors in this field of interest. It proposes an interface with the customer for fast PV charging station, observing the technological requirements. Components, communications protocols and flowcharts of the developed software program are shown.

Power system stabilizer design based on output optimal control techniques

In this paper an output control Power System Stabiliser (PSS) for synchronous generator is designed. A new technique based on pole placement using optimal output feedback is proposed, improving the PSS performance. The closed-loop system performance is then evaluated when a disturbance in the mechanical torque is applied. Numerical results and illustrative figures are presented.

Particle Swarm Optimization for photovoltaic model identification

This paper proposes a comprehensive modeling and parameters extraction method of solar photovoltaic module based on the Particle Swarm Optimization algorithm. The characteristic curves of photovoltaic panel are obtained by using only the information provided by the manufacturer data-sheet, avoiding the need to carry out experimental data. The performance and the accuracy of the proposed method are evaluated by applying the one-diode model and the results are compared with those obtained by the well-known Lambert W function. The proposed method shows a higher performance.

Glowworm Swarm Optimization for photovoltaic model identification

This paper presents a new algorithm for finding the parameters that characterize a photovoltaic panel by using the Glowworm Swarm Optimization algorithm. This new algorithm shows great simplicity, flexibility and precision, being able to precisely locate the global optimum point or multiple global optimum points, independently of the initial conditions. The approach here adopted allows the utilization of the algorithm in several existing models to characterize a photovoltaic panel in the current literature.

Blueberries field irrigation management and monitoring system using PLC based control and wireless sensor network

The irrigation procedure in agriculture is a key factor in achieving good yields and plant performance. Water stress at critical times in the development of the blueberry crop can dramatically affect fruit yield and quality. However, blueberry plants may not show visual signs of stress. An automatic system of irrigation management is essential to long-term plant health. This paper presents a system capable of controlling an irrigation system autonomously. By acquiring humidity and temperature data, the system is capable of deliver proper quantity of water at the most advisable period, through the usage of a Programmable Logic Controller, optimising the water supply. The system is also accessible on the webpage created for it. The project includes wireless communication between the sensors boards and the main control board allowing the user to easily place the sensors wherever he wants.