Jose Maria Gonzalez de Durana

A Complex Systems Modelling Approach for Decentralised Simulation of Electrical Microgrids

The structure and behaviour of Electrical Grids share many of the properties of Complex Computer Systems, with microgrids and other decentralised electrical systems attached to them, so they can be interpreted as Systems of Systems. Furthermore, the evolution of future electrical systems will bring a higher degree of decentralisation, especially concerning 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 modelling. By mixing these approaches the different entities of the electrical system (production, demand, storage, etc.) have been represented. Through the individual behaviour of the agents it is possible to reproduce the complex behaviour of the system as a whole. This can produce expected and unexpected emergent effects on the interconnected system that are analysed through the simulation. A case study is presented to analyse the capabilities of such 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.

A neural network based wind speed estimator for a wind turbine control

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.

Object oriented simulation of Hybrid Renewable Energy Systems focused on Supervisor Control

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.

A real-time estimation and control scheme for induction motors based on sliding mode theory

Abstract 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.

A robust position control for induction motors using a load torque observer

The design of a robust position control scheme for an induction motor drive using the field oriented control theory is proposed. The proposed sliding-mode control law incorporates an adaptive sliding gain in order to adjust the sliding gain to the system uncertainties. Moreover, the sliding gain adaptation avoids having to calculate the upper limit for the system uncertainties. The design also incorporates a load torque observer in order to obtain the load torque applied to the induction motor without the use of the load torque sensor. The proposed observer is based on the system dynamical equation and uses the rotor speed and the stator current in order to obtain the load torque. The stability analysis of the proposed controller under parameter uncertainties and load torque variations 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 uncertainties and load torque variations.

HYBRID MODELING OF OPEN LOOP DC-DC CONVERTERS

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 wellknown dc-dc converters named buck and boost, using Matlab-Simulink-Stateflow, is presented.

Adaptive robust control to maximizing the power generation of a variable speed wind turbine

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.

Agent-Based Simulation of Wind Farm Generation at Multiple Time Scales

Since the past decade, energy systems are undergoing a deep paradigm shift, caused by the liberalisation of energy markets, the introduction of renewable energies, and the emergence of new, distributed producers that feed into the grid at almost every level of the system. The general trend towards the introduction of renewable energy sources in the industrialised countries implies one of the greatest changes in the structure of energy systems. These systems are moving away from a centralised and hierarchical energy system, where the production follows a top-down principle under the strict control of the electricity supply companies towards a new system where diverse actors influence the energy supply. The production is no longer limited to large energy providers, as small decentralised producers now exist and inject energy at much lower voltage levels than before. These energy systems are suffering the consequences of such a paradigm change. This change basically consists in new regulations and the introduction of new energy production technologies that transform traditional centralised systems into decentralised ones. This whole process is part of the framework of the fight against the causes of climate change, which is mostly due to CO2 emissions. This paradigm change encompasses new tools and methods that can deal with decentralised decision-making, planning and self-organisation. The large amount of new actors and technologies in the energy production chain requires a shift from a top-down to a more bottom-up approach. Multi-scale simulation systems offer several advantages over classical models. The ability to run simulations on different time scales using the same model is an important issue for the upcoming modelling of energy systems. The main advantages are that there are fewer models and no need to port data between platforms. This leads to a more efficient simulation run and decision-making support. The challenges of these kind of simulations are that a multi-scale model for the moment will not be as accurate as a purpose made model. So, the modelling method, the parameters, etc. included must be carefully chosen to ensure both flexibility and accuracy. The work presented in this chapter concerns the wind generation module of an agent-based model for integral energy systems (developed at the European Institute for Energy Research 14

A robust position control for induction machines

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

Geometric multiplicity margin for a submatrix

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.