DC–DC converters with voltage boost capability are widely used in a large number of power conversion applications, from fraction-of-volt to tens of thousands of volts at power levels from milliwatts to megawatts. The literature has reported on various voltage-boosting techniques, in which fundamental energy storing elements (inductors and capacitors) and/or transformers in conjunction with switch(es) and diode(s) are utilized in the circuit. These techniques include switched capacitor (charge pump), voltage multiplier, switched inductor/voltage lift, magnetic coupling, and multistage/-level, and each has its own merits and demerits depending on application, in terms of cost, complexity, power density, reliability, and efficiency. To meet the growing demand for such applications, new power converter topologies that use the above voltage-boosting techniques, as well as some active and passive components, are continuously being proposed. The permutations and combinations of the various voltage-boosting techniques with additional components in a circuit allow for numerous new topologies and configurations, which are often confusing and difficult to follow. Therefore, to present a clear picture on the general law and framework of the development of next-generation step-up dc–dc converters, this paper aims to comprehensively review and classify various step-up dc–dc converters based on their characteristics and voltage-boosting techniques. In addition, the advantages and disadvantages of these voltage-boosting techniques and associated converters are discussed in detail. Finally, broad applications of dc–dc converters are presented and summarized with comparative study of different voltage-boosting techniques.

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Step-Up DC–DC Converters: A Comprehensive Review of Voltage-Boosting Techniques, Topologies, and Applications

This paper presents an optimal power management mechanism for grid connected photovoltaic (PV) systems with storage. The objective is to help intensive penetration of PV production into the grid by proposing peak shaving service at the lowest cost. The structure of a power supervisor based on an optimal predictive power scheduling algorithm is proposed. Optimization is performed using Dynamic Programming and is compared with a simple ruled-based management. The particularity of this study remains first in the consideration of batteries ageing into the optimization process and second in the “day-ahead” approach of power management. Simulations and real conditions application are carried out over one exemplary day. In simulation, it points out that peak shaving is realized with the minimal cost, but especially that power fluctuations on the grid are reduced which matches with the initial objective of helping PV penetration into the grid. In real conditions, efficiency of the predictive schedule depends on accuracy of the forecasts, which leads to future works about optimal reactive power management.

Optimal Power Flow Management for Grid Connected PV Systems With Batteries

This paper reviews state of the art maximum power point tracking (MPPT) algorithms for wind energy systems. Due to the instantaneous changing nature of the wind, it is desirable to determine the one optimal generator speed that ensures maximum energy yield. Therefore, it is essential to include a controller that can track the maximum peak regardless of wind speed. The available MPPT algorithms can be classified as either with or without sensors, as well as according to the techniques used to locate the maximum peak. A comparison has been made between the performance of different MPPT algorithms on the basis of various speed responses and ability to achieve the maximum energy yield. Based on simulation results available in the literature, the optimal torque control (OTC) has been found to be the best MPPT method for wind energy systems due to its simplicity. On the other hand, the perturbation and observation (P&O) method is flexible and simple in implementation, but is less efficient and has difficulties determining the optimum step-size.

A review of maximum power point tracking algorithms for wind energy systems

Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This textbook brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Aimed at advanced undergraduate and beginning graduate students in the engineering and physical sciences, the text presents a range of topics and methods from introductory to state of the art.

Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control

This paper introduces a method to improve the primary frequency contribution of grid connected variable speed wind turbine generators (WTGs). Using their energy reserve margins, deloaded WTGs are controlled to provide relief to the grid during depressed frequency conditions. The frequency support from individual WTGs is regulated based on the available reserve, which depends on the prevailing wind velocities. By continuously adjusting the droop of the WTG in response to wind velocities, its primary frequency response is significantly improved in terms of reduced stresses on WTGs during low wind speeds. The impact of variable droop operation on two aspects of WTG operation is investigated-primary frequency contribution and smoothening power fluctuations caused due to changes in wind speed. Also highlighted is the usefulness of this control when adopted by wind farms.

Primary frequency regulation by deloaded wind turbines using variable droop

Wind is recognized worldwide as a cost-effective, environmentally friendly solution to energy shortages, and wind energy is currently the fastest-growing energy source in the world. Wind power investment worldwide is expected to expand threefold in the next decade, from about $18 billion in 2006 to $60 billion in 2016 [1]. While the cost of wind energy is already very competitive with energy from coal and natural gas, there are still many unsolved challenges in expanding wind power. From bearings under constant friction to blades that must be able to handle gusts, lightning, and constantly changing wind conditions, today’s wind turbines need increasingly sophisticated component designs, sensors, and control systems. Further, better wind forecasting methods are needed to improve site selection, optimize operations, and mitigate load fluctuations on the power grid. Although the United States receives only about 1% of its electrical energy from wind [2], the corresponding figure in Denmark is more than 15% [3]. The integration of more than 20% penetration of wind energy into the grid will require modifications of the grid design and operation, with the possible addition of new transmission lines and energy storage systems. Despite the amazing growth in the installed capacity of wind turbines in recent years, engineering and science challenges still exist. These large, flexible structures operate in uncertain environments and lend themselves nicely to advanced control solutions. Advanced controllers can help achieve the overall goal of decreasing the cost of wind energy by increasing the efficiency, and thus the energy capture, or by reducing structural loading and increasing the lifetimes of the components and turbine structures. Wind energy literature has been similarly expanding with the growing interest in the area. Several tomes cover the subject from a broad perspective, and these tend to blend reference and tutorial material in their presentation [4], [5]. As such they contain large sections that essentially serve as introductions to atmospheric sciences, aerodynamics, structural dynamics, electrical power systems, generator dynamics, power electronics, control systems, and the economics of the power industry. That is the nature of the beast for any book that undertakes the ambitious goal of providing a technical foundation for those interested in the wind industry. Unfortunately, for the controls engineer, the research literature tends to be an expanse of narrowly focused studies with only a few that are tutorial in nature. Further, research is typically focused on control of wind turbines in a particular operating region such as maximizing power in partial load conditions, mitigating loads in above-rated

Optimal Control of Wind Energy Systems: Towards a Global Approach

This paper investigates the issues of ensuring global power optimization for cascaded dc-dc converter architectures of photovoltaic (PV) generators irrespective of the irradiance conditions. The global optimum of such connections of PV modules is generally equivalent with performing the maximum power point tracking (MPPT) on all the modules. The most important disturbance occurs when the irradiance levels of modules happen to be sensibly different from a module to another - in this case, voltage-limitation requirements may be broken. The proposed supervisory algorithm then attempts to establish the best suboptimal power regime. Validation has been achieved by MATLAB/Simulink numerical simulation in the case of a single-phase grid-connected PV system, where individual MPPTs have been implemented by an extremum-seeking control, a robust and less-knowledge-demanding perturb-and-observe method.

Cascaded DC–DC Converter Photovoltaic Systems: Power Optimization Issues

New Challenges in Power Electronics Systems.- Part I: Modelling of Power Electronics Systems.- Introduction to Power Electronics Modelling.- Switched Model.- Classical Average Model.- Equivalent Average Generator Model.- Generalized Average Model.- Part II: Control of Power Electronics Systems.- General Principles.- Linear Approach.- Linear Control Methods for Grid-connected Converters.- General Overview of Nonlinear Control Methods.- Linearization via Feedback Control.- Stabilization Control.- Passive Control.- Variable-structure Control and Its Associated Sliding Modes.- General Conclusion.

Power Electronic Converters Modeling and Control: with Case Studies

Optimization of variable speed wind power systems based on a LQG approach

This paper deals with the experimental validation of a Matlab-Simulink simulation tool of marine current turbine (MCT) systems. The developed simulator is intended to be used as a sizing and site evaluation tool for MCT installations. For that purpose, the simulator is evaluated within the context of speed control of a permanent magnet synchronous generator-based (PMSG) MCT. To increase the generated power, and therefore the efficiency of an MCT, a nonlinear controller has been proposed. PMSG has been already considered for similar applications, particularly wind turbine systems using mainly PI controllers. However, such kinds of controllers do not adequately handle some of tidal resource characteristics such as turbulence and swell effects. Moreover, PMSG parameter variations should be accounted for. Therefore, a robust nonlinear control strategy, namely second-order sliding mode control, is proposed. The proposed control strategy is inserted in the simulator that accounts for the resource and the marine turbine models. Simulations using tidal current data from Raz de Sein (Brittany, France) and experiments on a 7.5-kW real-time simulator are carried out for the validation of the simulator.

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Experimental Validation of a Marine Current Turbine Simulator: Application to a Permanent Magnet Synchronous Generator-Based System Second-Order Sliding Mode Control

Iulian Munteanu

Papers

Optimal Control of Wind Energy Systems: Towards a Global Approach

Cascaded DC–DC Converter Photovoltaic Systems: Power Optimization Issues

Power Electronic Converters Modeling and Control: with Case Studies

Optimization of variable speed wind power systems based on a LQG approach

Experimental Validation of a Marine Current Turbine Simulator: Application to a Permanent Magnet Synchronous Generator-Based System Second-Order Sliding Mode Control