Rachid Beguenane

Energy Management and Control System for Laboratory Scale Microgrid Based Wind-PV-Battery

This paper proposes an energy management and control system for laboratory scale microgrid based on hybrid energy resources such as wind, solar, and battery. Power converters and control algorithms have been used along with dedicated energy resources for the efficient operation of the microgrid. The control algorithms are developed to provide power compatibility and energy management between different resources in the microgrid. It provides stable operation of the control in all microgrid subsystems under various power generation and load conditions. The proposed microgrid, based on hybrid energy resources, operates in autonomous mode and has an open architecture platform for testing multiple different control configurations. A real-time control system has been used to operate and validate the hybrid resources in the microgrid experimentally. The proposed laboratory scale microgrid can be used as a benchmark for future research in smart grid applications.

Control of variable speed wind energy conversion system using a wind speed sensorless optimum speed MPPT control method

This paper presents a wind speed sensorless maximum power point tracking (MPPT) controller for variable speed wind energy conversion systems (WECS). The proposed controller generates at its output the optimum speed (OS) command for the speed control loop of the vector controlled machine side converter control system without requiring the knowledge of wind speed. The MPPT control of the WECS is achieved using optimum speed-power curve of the WECS taking into account the variation of the system efficiency while operating at various operating points due to the change in wind speed. The method is based on the fact that the optimum output power of a WECS at a certain wind speed depends upon the total mechanical power developed by the turbine and efficiency of the WECS at the corresponding OS of rotation of the turbine. The controller algorithm implementation requires the knowledge of turbine parameters and output power and air density as its inputs. The proposed concept is analyzed in a variable speed direct drive permanent magnet synchronous generator (PMSG) WECS. Experimental results show good tracking capability of the proposed controller.

Adaptive sliding mode speed control for wind turbine systems

An adaptive sliding mode control strategy for speed tracking problem in variable speed wind turbine systems is presented in this work. The proposed adaptation strategy consists on updating the sliding gain and the turbine torque, which is considered unknown by the controller. The adaptation algorithms for the sliding gain and the torque estimation are carried out using the sliding surface to overcome the drawbacks of the conventional sliding mode control. The objective is to track a speed profile to operate the wind turbine in maximum power extraction. Simulation results are provided to validate the effectiveness of the proposed control system.

Technical and financial benefits of electrical energy storage

Traditionally, electricity networks are dimensioned on peak demand. This is inevitable due to the fact that storage of substantial amounts of electricity is technically and economically infeasible. As a result, a vast amount of currently unused network capacity is available. When this could be used, much more energy could be transported with the same network so that investments on network reinforcements could be postponed or omitted. To this end, it must be possible to shift demand for electricity in time or, more precisely, to shift the transport of electricity in time. In principle, this can be done by incorporating (distributed) electricity storage in the networks. This paper attempts to summarize the current state of knowledge regarding energy storage technologies for electric power grid. It is intended to serve as a reference for policymakers interested in understanding the range of technologies and applications associated with energy storage, comparing them, when possible, in a structured way to highlight key characteristics relevant to widespread use.

Neural network based wind speed sensorless MPPT controller for variable speed wind energy conversion systems

A wind speed sensorless neural network (NN) based maximum power point tracking (MPPT) control algorithm for variable speed wind energy conversion system (WECS) is proposed. The proposed method is developed using Jordan type recurrent NN which is trained online using back-propagation. The algorithm, without requiring the knowledge of wind speed, air density or turbine parameters, generates at its output the optimum speed command for the speed control loop of the vector controlled machine side converter control system using only the instantaneous power as its input. The output of the NN is fed into a state input after a unit step delay completing the Jordan type recurrent neural network. The proposed concept is analyzed in a grid connected direct drive variable speed permanent magnet synchronous generator (PMSG) WECS with a back-to-back frequency converter. Vector control of the grid side converter is realized in the grid voltage vector reference frame. Simulation is carried out in order to verify the performance of the proposed controller.

Implementation of Sliding Mode Control System for Generator and Grid Sides Control of Wind Energy Conversion System

This paper presents a second order sliding mode control strategy to control the generator and the grid sides of a variable speed experimental wind energy conversion system. At the generator side, the rotational speed is controlled to track a profile generated from the power curve of the wind turbine for maximum power extraction. At the grid side, the dc-link voltage is regulated for a proper transfer of power. The control strategy is based on a disturbed single input-single output error model and a second order sliding mode control algorithm. The proposed second order sliding mode control strategy offers interesting characteristics such as robustness to parametric uncertainties in the turbine and the generator as well as external disturbances. The proposed strategy, for speed and dc-link voltage control in wind energy conversion system, is validated on an emulated wind turbine driven by the OPAL-RT real-time simulator (OP5600). Experimental results show that the proposed control strategy is effective in terms of speed and dc-link voltage control. The sliding mode control approach is robust against unknown disturbances, parametric variations, and uncertainties in the system. Furthermore, it produces no chattering in the generated torque, which reduces the mechanical stress on the wind turbine.

Modeling solar photovoltaic cell and simulated performance analysis of a 250W PV module

The main purpose of this study is to develop the mathematical model of solar photovoltaic (PV) cell and to simulate its behavior. The study includes the performance analysis of a 250W PV module and its behavior on different temperature conditions, irradiance levels. It also focuses on the effects of varying shunt and series resistances. The model has been developed considering possible environmental effects on solar PV generation. The results of the characteristics curves in this paper are compared to the curves provided by the CS6P-250M PV module datasheet. Using this model it is possible to simulate the behavior of any large scale PV array or solar Photovoltaic Energy Conversion Systems (PVECS). The model was developed by using Matlab®/Simulink” software. This model can be used for further simulation based research and analysis on PVECS.

Trends in naval ship propulsion drive motor technology

Electric drive propulsion system for naval ships is a very active and fast-growing research area driven by the rapid growth in power electronics and advancement in machine design. Propulsion motors and associated drive control systems form the heart of modern all-electric ships (AES). This paper presents the technology trends in propulsion drive motors for AES propulsion systems. The induction motor (IM), permanent magnet synchronous motor (PMSM), the high temperature superconducting synchronous motor (HTSSM) and the superconducting homopolar DC motor (SHDCM) are examined. These machines are preferred over others mainly because of their higher power densities and efficiencies, allowing a more compact and efficient propulsion system design.

Nonlinear model predictive controller with state observer for speed sensorless induction generator–wind turbine systems

In this article, the problem of tracking control for variable speed induction generator–wind energy conversion system is investigated using nonlinear predictive control. A rotor speed predictive control algorithm has been designed to control the angular speed of the machine in order to allow the wind energy conversion system to operate with maximum power extraction. The generator torque and uncertainties are estimated and injected into the control law to improve the tracking performance. Control action is carried out assuming that all the states are known by measurement. Then, a state observer is implemented and Lyapunov method is used to prove the global stability of the complete continuous control scheme. Simulation is carried out to verify the performance of the proposed control system.

An optimum speed MPPT controller for variable speed PMSG wind energy conversion systems

A maximum power point tracking (MPPT) controller for variable speed permanent magnet synchronous generator (PMSG) wind energy conversion systems (WECS) is proposed. The proposed controller, without requiring the knowledge of wind speed, generates at its output, the optimum speed (OS) reference signal for the speed control loop of the vector controlled machine side converter control system, thus, allowing maximum power extraction. Optimum speed - power curve of the WECS, used by the controller, takes into account the changes in system efficiency while operating at different operating points due to the change in wind speed. The method proposed is based on the fact that the optimum output power of a WECS at a certain wind speed depends upon the total mechanical power developed by the turbine and efficiency of the WECS at the corresponding OS of rotation of the turbine. The controller requires the active power and air density as its inputs to generate optimum reference speed. The proposed controller is validated experimentally in a variable speed direct drive PMSG WECS using a wind turbine emulator.