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The introduction of advanced control algorithms may improve considerably the efficiency of wind turbine systems. This work proposes a high order sliding mode (HOSM) control scheme based on the super twisting algorithm for regulating the wind turbine speed in order to obtain the maximum power from the wind. A robust aerodynamic torque observer, also based on the super twisting algorithm, is included in the control scheme in order to avoid the use of wind speed sensors. The presented robust control scheme ensures good performance under system uncertainties avoiding the chattering problem, which may appear in traditional sliding mode control schemes. The stability analysis of the proposed HOSM observer is provided by means of the Lyapunov stability theory. Experimental results show that the proposed control scheme, based on HOSM controller and observer, provides good performance and that this scheme is robust with respect to system uncertainties and external disturbances.

This work proposes a robust controller for a variable speed wind turbine system with a doubly feed induction generator. The controller aims at tracking the optimal speed of the wind turbine so that extracts the maximum power from the wind. Also, a robust aerodynamic torque observer is proposed in order to avoid the use of wind speed sensors. This torque observer allows to estimate the aerodynamic torque to be used by the controller in order to calculate the value of the optimal reference speed for the wind turbine. The vector control theory is applied in the present approach, and thereby the stator flux-oriented control is used for controlling the speed of the wind turbine generator. The proposed robust control law is based on sliding mode control theory, which has proved to provide good performance under system uncertainties. The stability of the proposed controller under disturbances and parameter uncertainties has been analyzed using the Lyapunov stability theory. Finally, real time experimental results show that, on the one hand, the proposed controller provides high-performance dynamic characteristics, and on the other hand, this scheme is robust with respect to the uncertainties that usually appear in this kind of systems.

Taking into account the restricted ability of polymer electrolyte membrane fuel cell (PEMFC) to generate energy, it is compulsory to present techniques, in which an efficient operating power can be achieved. In many applications, the PEMFC is usually coupled with a high step-up DC-DC power converter which not only provides efficient power conversion, but also offers highly regulated output voltage. Due to the no-linearity of the PEMFC power systems, the application of conventional linear controllers such as proportional-integral (PI) did not succeed to drive the system to operate precisely in an adequate power point. Therefore, this paper proposes a robust non-linear integral fast terminal sliding mode control (IFTSMC) aiming to improve the power quality generated by the PEMFC; besides, a digital filter is designed and implemented to smooth the signals from the chattering effect of the IFTSMC. The stability proof of the IFTSMC is demonstrated via Lyapunov analysis. The proposed control scheme is designed for an experimental closed-loop system which consisted of a Heliocentric hy-Expert™ FC-50W, MicroLabBox dSPACE DS1202, step-up DC-DC power converter and programmable DC power supplies. Comparative results with the PI controller indicate that a reduction of 96% in the response time could be achieved using the suggested algorithm; where, up to more than 91% of the chattering phenomenon could be eliminated via the application of the digital filter.

Due to the nonlinear dynamics and uncertainties usually present in wave energy conversion systems, the efficiency of these devices can be enhanced employing a robust control algorithms. Wave energy converters are constructed using electric generators of variable velocity, like double feed induction generator (DFIG) since they may improve the system efficiency to generate power when compared to fixed speed generators. The main reason is that this generators with variable speed may adapt the speed of the turbine in order to maintain the optimal flow coefficient values which improves the efficiency of the Wells turbine. However, a suitable speed controller is required in these systems first in order to avoid the stalling phenomenon and second in order to track the optimal turbine reference velocity that optimizes the power generation. In this paper a real time sliding mode control scheme for wave energy conversion systems that incorporate a Wells turbine and a DFIG is proposed. The Lyapunov stability theory is used to analyse the stability of this control scheme under parameter uncertainties and system disturbances. Next, the proposed control scheme is validated first by means of some simulation examples using the Matlab/Simulink software and second using a real-time experimental platform based on a dSPACE DS1103 control board.

Studies in complex energy networks devoted to the modeling of electrical power grids, were extended in previous work, where a computational multi-layered ontology, implemented using agent-based methods, was adopted. This structure is compatible with recently introduced Multiplex Networks which using Multi-linear Algebra generalize some of classical results for single-layer networks, to multilayer networks in steady state. Static results do not assist overly in understanding dynamic networks in which the values of the variables in the nodes and edges can change suddenly, driven by events, and even where new nodes or edges may appear or disappear, also because of other events. To address this gap, a computational agent-based model is developed to extend the multi-layer and multiplex approaches. In order to demonstrate the benefits of a dynamical extension, a model of the energy network in a hybrid car is presented as a case study.

Traditionally, the wind turbine system uses the conventional PID controller. However, the performance of the wind turbine systems can be enhanced using a more advanced control schemes. In this paper, a high order sliding mode (HOSM) control scheme is developed. First, the control scheme presents a robust aerodynamic torque observer based on super twisting algorithm in order to eliminate the sensors for the wind speed measurement. Second, a robust wind turbine speed control using a super twisting algorithm is also designed in order to regulate the rotor currents. The high order sliding mode control theory is employed in order to design this robust control scheme because as it is well known this control theory presents a good response in the presence of system uncertainties. Moreover, the high order sliding mode controller do not presents the problem of the chattering that usually turn up in the conventional sliding mode control schemes.

In this paper a sliding mode position control for high-performance real-time applications of induction motors is developed. The design also incorporates a sliding mode rotor flux estimator in order to avoid the flux sensors. The proposed control scheme presents a low computational cost and therefore can be implemented easily in a real-time applications using a low cost Digital Signal Processor (DSP). The stability analysis of the observer and the controller, under parameter uncertainties and load torque disturbances, is provided using the Lyapunov stability theory. Finally simulated and experimental results show that the proposed controller with the proposed observer provides a good trajectory tracking and that this scheme is robust with respect to plant parameter variations and external load disturbances.

In order to analyse the possibilities of improving grid stability on island systems by local demand response mechanisms, a multi-agent simulation model is presented. To support the primary reserve, an under-frequency load shedding (UFLS) using refrigerator loads is modelled. The model represents the system at multiple scales, by recreating each refrigerator individually, and coupling the whole population of refrigerators to a model which simulates the frequency response of the energy system, allowing for cross-scale interactions. Using a simple UFLS strategy, emergent phenomena appear in the simulation. Synchronisation effects among the individual loads were discovered, which can have strong, undesirable impacts on the system such as oscillations of loads and frequency. The phase transition from a stable to an oscillating system is discussed.

The efficiency of the wind power conversions systems can be greatly improved using an appropriate control algorithm. In this work, an adaptive control scheme based on sliding mode control theory is proposed. In the control scheme, a robust aerodynamic torque observer based on super twisting algorithm is designed in order to avoid the wind speed sensors. The proposed robust observer is based on the high order sliding mode (HOSM) theory, that presents a good performance under system uncertainties and avoids the chattering problem that can appear in the traditional sliding mode observers. The stability analysis of the proposed HOSM observer is provided using the Lyapunov stability theory. Finally simulated results show that the proposed adaptive sliding mode control scheme provides a good performance and demonstrates that this control scheme is robust with respect to system uncertainties and external disturbances.

Wave power conversion systems are nonlinear dynamical systems that must endure strong uncertainties. Efficiency is a key issue for these systems, and the application of robust control algorithms can improve it considerably. Wave power generation plants are typically built using variable speed generators, such as the doubly fed induction generator (DFIG). These generators, compared with fixed speed generators, are very versatile since the turbine speed may be adjusted to improve the efficiency of the whole system. Nevertheless, a suitable speed controller is required for these systems, which must be able to avoid the stalling phenomenon and track the optimal reference for the turbine. This paper proposes a sliding mode control scheme aimed at oscillating water column (OWC) generation plants using Wells turbines and DFIGs. The contributions of the paper are (1) an adaptive sliding mode control scheme that does not require calculating the bounds of the system uncertainties, (2) a Lyapunov analysis of stability for the control algorithm against system uncertainties and disturbances, and (3) a validation of the proposed control scheme through several simulation examples with the Matlab/Simulink suite. The performance results, obtained by means of simulations, for a wave power generation plant (1) evidence that this control scheme improves the power generation of the system and (2) prove that this control scheme is robust in the presence of disturbances. This research was partially funded by the Basque Government through the project ETORTEK KK-2017/00033 and by the UPV/EHU through the project PPGA18/04.

The efficiency of the wind power conversions systems can be greatly improved using an appropriate control algorithm. In this work, an adaptive robust control for a variable speed wind power generation is described. A robust aerodynamic torque observer is also designed in order to avoid the wind speed sensors. The proposed adaptive robust control law is based on a sliding mode control theory, that presents a good performance under system uncertainties. The stability analysis of the proposed controller under disturbances and parameter uncertainties is provided using the Lyapunov stability theory. Finally simulated results show, on the one hand that the proposed controller provides high-performance dynamic characteristics, and on the other hand that this scheme is robust with respect to plant parameter variations and external disturbances.

In this paper, a real time sliding mode control scheme for a variable speed wind turbine that incorporates a doubly feed induction generator is described. In this design, the so-called vector control theory is applied, in order to simplify the system electrical equations. The proposed control scheme involves a low computational cost and therefore can be implemented in real-time applications using a low cost Digital Signal Processor (DSP). The stability analysis of the proposed sliding mode controller under disturbances and parameter uncertainties is provided using the Lyapunov stability theory. A new experimental platform has been designed and constructed in order to analyze the real-time performance of the proposed controller in a real system. Finally, the experimental validation carried out in the experimental platform shows, on the one hand that the proposed controller provides high-performance dynamic characteristics, and on the other hand that this scheme is robust with respect to the uncertainties that usually appear in the real systems.

Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed. The financial support from EPSRC for Liz Varga on project entitled "Transforming Utilities’ Conversion Points" (no. EP/J005649/1) is gratefully acknowledged.

An adaptive sliding mode position control for induction motors using field oriented control theory is presented. The proposed sliding-mode control law incorporates an adaptive switching gain to avoid calculating an upper limit of the system uncertainties. The design incorporates a flux estimator that operates on the principle of flux and current observer. The proposed observer is basically an estimator that uses a plant model and a feedback loop with measured stator voltages and currents. The stability analysis of the proposed controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. Finally experimental results show that the proposed controller with the proposed observer provides high-performance dynamic characteristics and that this scheme is robust with respect to plant parameter variations and external load disturbances.

The actual wind turbines are provided with adjustable speed generators, like the double feed induction generator, that are capable to work in variable speed operations. One of the main advantage of adjustable speed generators is that they improve the system efficiency compared to fixed speed generators because turbine speed is adjusted as a function of wind speed to maximize output power. However this systems requires a suitable speed controller in order to track the optimal wind turbine reference speed. In this work, an adaptive robust control for variable speed wind power generator is described. The proposed robust control law is based on a sliding mode control theory, that presents a good performance under system uncertainties. The proposed sliding-mode control law incorporates an adaptive switching gain, which avoids having to calculate an upper limit of the system uncertainties that is necessary in the traditional sliding-mode control laws. The stability analysis of the proposed controller under disturbances and parameter uncertainties is provided using the Lyapunov stability theory. Finally simulated results show, on the one hand that the proposed controller provides high-performance dynamic characteristics, and on the other hand that this scheme is robust with respect to plant parameter variations and external disturbances.

The smart grid is a highly complex system that is being formed from the traditional power grid, adding new and sophisticated communication and control devices. This will enable integrating new elements for distributed power generation and also achieving an increasingly automated operation so for actions of the utilities as for customers. In order to model such systems, a bottom-up method is followed, using only a few basic elements which are structured into two layers: a physical layer for the electrical power transmission and one logical layer for element communication. A simple case study is presented to analyze the possibilities of simulation. It shows a microgrid model with dynamic load management and an integrated approach that can process both electrical and communication flows.

Under-frequency load shedding (UFLS) is a technique in which the power grid frequency is used as an indicator to shed down electrical loads at critical periods, which can increase the resilience of the system. We present a multi-scale agent-based model to simulate the impact of UFLS on an energy system. The model allows a representation from a complex system point of view, allowing for crossscale interactions which is not evident in standard grid simulations. Each refrigerator is modelled individually but the population has a heterogeneous configuration. The refrigerators are coupled to a simplified energy system model to represent the grid frequency.Using a simple UFLS strategy we discovered synchronisation effects among the refrigerator population. An emergent oscillation which would be fatal for the system was detected. The model allows to explore the origin of this phenomenon as well as to determine the phase transition which occurs in the system.

POWERENG 2011 The actual wind turbines are provided with adjustable speed generators, like the double feed induction generator, that are capable to work in variable speed operations. One of the main advantage of adjustable speed generators is that they improve the system efficiency compared to fixed speed generators because turbine speed is adjusted as a function of wind speed to maximize output power. However this systems requires a suitable speed controller in order to track the optimal wind turbine reference speed. In this work, an adaptive robust control for variable speed wind power generator is described. The proposed robust control law is based on a sliding mode control theory, that presents a good performance under system uncertainties. The proposed sliding-mode control law incorporates an adaptive switching gain, which avoids having to calculate an upper limit of the system uncertainties that is necessary in the traditional sliding-mode control laws. The stability analysis of the proposed controller under disturbances and parameter uncertainties is provided using the Lyapunov stability theory. Finally simulated results show, on the one hand that the proposed controller provides high-performance dynamic characteristics, and on the other hand that this scheme is robust with respect to plant parameter variations and external disturbances.

Variable speed wind generation systems are more attractive than fixed-speed systems because of the more efficient energy production improved power quality, and improved dynamic performance during grid disturbances. In this sense, to implement maximum wind power extraction, most controller designs of the variable-speed wind turbine generators employ anemometers to measure wind speed in order to derive the desired optimal shaft speed for adjusting the generator speed. In this paper it is proposed a new Neural Network Based Wind Speed Estimator for a wind turbine control. The design uses an feedforward Artificial Neural Network (ANN) to implement a rotor speed estimator, and simulated results show that the proposed observer provides high-performance dynamic characteristics.

ICEM 2010 A robust position control for induction motors using field oriented control theory is presented. The proposed controller is based on variable structure control and provides global asymptotic position tracking in the presence of unknown parameters and load torque variations. The proposed design incorporates an improved method of flux estimation that operates on the principle of flux and current observer. The proposed observer is basically an estimator that uses a plant model and a feedback loop with measured stator voltages and currents. The stability analysis of the proposed controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. Finally simulated results show that the proposed controller with the proposed observer provides high-performance dynamic characteristics and that this scheme is robust with respect to plant parameter variations and external load disturbances

ICECCS 2010 The structure and behavior of Electrical Grids share many of the properties of Complex Computer Systems, with microgrids and other decentralized electrical systems attached to them, so they can be interpreted as Systems of Systems. Furthermore, the evolution of the future electrical system will bring a higher degree of decentralization concerning specially production and control. To deal with this paradigm change, new models and tools are necessary. In this paper a model of an electrical microgrid is presented. The approach used in the development of the model is Agent-Based in combination with System Dynamics. By mixing these approaches the different entities of the electrical system (production, demand, storage, etc.) have been represented. Through the individual behavior of the agents it is possible to reproduce the complex behavior of the system as a whole. This behavior can produce expected and unexpected emergent properties on the interconnected system that can be analyzed through simulation. A case study is presented to analyze the capabilities of such kind of models. The example shows the simulation of an integrated microgrid system, where different components such as renewable energy sources and storage have been implemented. The simulation results of this case study are discussed.

With eyes focused on simulation the authors review some of the main topics of Hybrid Renewable Energy Systems (HRES). Then they describe an Object Oriented model of a simple example of one of such systems, a micro-grid, oriented to designing a decentralized Supervisor Control. The model has been implemented using AnyLogic.

The efficiency of the wind power conversions systems can be greatly improved using an appropriate control algorithm. In this work, a robust control for variable speed wind power generation that incorporates a doubly feed induction generator is described. The electrical systems incorporates a wound rotor induction machine with back-to-back three phase power converter bridges between its rotor and the grid. In the presented design it is applied the so called vector control theory. The proposed control scheme uses stator flux-oriented control for the rotor side converter bridge control and grid voltage vector control. The proposed robust control law is based on a sliding mode control theory, that, as it is well known, presents a good performance under system uncertainties. The stability analysis of the proposed controller under disturbances and parameter uncertainties is provided using the Lyapunov stability theory. Finally simulated results show, on the one hand that the proposed controller provides high-performance dynamic characteristics, and on the other hand that this scheme is robust with respect to the uncertainties that usually appear in the real systems.

Power electronic converters always have been circuits of difficult modelling because differential equations that describe them have discontinuities. Although this situation has been improved since the appearance of the Hybrid Systems theory, able to jointly describe both continuous and discrete behaviors exhibited by some physical systems, nowadays it is possible to obtain very precise models which help us in the study and design of such circuits. An excellent option for the discrete part model (reactive system) is to use statecharts, since this powerful language has recently been implemented and named Stateflow as a part of the Simulink toolbox of Matlab. So, today, the complete modeling of some hybrid systems within Matlab environment is possible. In this work the open loop hybrid modeling and simulation of the well-known dc-dc converters named buck and boost, using Matlab-Simulink-Stateflow, is presented

AMS Classification: 15A18, 15A21, 15A60. Let G be a square complex matrix with less than k nonconstant invariant factors. We find a complex matrix that gives an optimal approximation to G among all possible matrices that have more than or equal to k invariant factors, obtained by varying only the entries of a bottom right submatrix of G. Supported by the Ministerio de Educación y Cultura (DGESIC), Proyecto PB97-0599-CO3-01.