Nonlinear Optimal Control for the Synchronization of Distributed Marine-turbine Power Generation Units

Abstract

Power generation from marine-turbines offers a vast potential for raising the contribution of renewable energy sources to the electricity grid. Typically, marine-turbine power units comprise marine-turbines that receive mechanical excitation from sea currents or tidal streams and synchronous or asynchronous generators that are finally connected to the electricity grid. Due to connection to the same transmission lines, interactions between the excitations of the individual generators appear. To achieve stabilization of the generators’ functioning, as well as synchronization to the grid’s frequency the generators’ control has to compensate for such interactions. The article proposes a nonlinear optimal control approach for distributed marine-turbine power units that use synchronous generators. First, the dynamic model of the distributed power system undergoes approximate linearization around a temporary operating point which is re-computed at each time-step of the control algorithm. The linearization relies on first-order Taylor series expansion and on the computation of the associated Jacobian matrices. For the approximately linearized model of the distributed power system a stabilizing H-infinity (optimal) feedback controller is designed. To compute the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each time-step of the control method. The global stability properties of the control scheme are proven through Lyapunov analysis. The proposed control method retains the advantages of optimal control, that is fast and accurate tracking of the reference setpoints, under moderate variations of the control inputs. Among the advantages of the proposed control method one can note: (i) the presented nonlinear optimal control method has improved performance when compared against other nonlinear control schemes that one can consider for the dynamic model of the distributed marine power system (actually other control methods are neither of proven optimality, nor of proven global stability), (ii) avoids complicated state-space transformations and the related appearance of singularities in the computation of the control inputs which are applied to the nonlinear model (iii) minimizes the consumption of energy by the control system of the distributed marine-turbine generators, thus also reducing the functioning cost of such power units.

Keywords:

• distributed power generation
• marine turbines
• synchronous generators
• nonlinear H-infinity control
• nonlinear optimal control
• Riccati equations
• global stability

Additional information

Funding

This article was funded by the Unit of Industrial Automation / Industrial Systems Institute, under Research Grant No 6065 / “Advances in Applied Nonlinear Optimal Control”.

Notes on contributors

Gerasimos Rigatos

Gerasimos Rigaatos obtained a diploma (1995) and a Ph.D. (2000) both from the Department of Electrical and Computer Engineering, of the National Technical University of Athens (NTUA), Greece. He holds an Editor’s position in the Journal of Advanced Robotic Systems. According to Elsevier Scopus his research comprising 330 publications, has received 2400 citations with an H-index of 24. Since 2007, he has been awarded visiting professor positions at several academic institutes (Université Paris XI France, Harper-Adams University College UK, University of Northumbria UK, University of Salerno Italy, Ecole Centrale de Nantes, France). He has led related research cooperation agreements and projects which have resulted into accredited results in the areas of nonlinear control, nonlinear filtering and control of distribute parameter systems. His results appear in 7 research monographs and in several journal articles.

Nikos Zervos

Nikos Zervos is an Emeritus Researcher Director at the Industrial Systems Institute, Greece. He holds a Ph.D. in electrical engineering from the University of Toronto, Canada, a M.Sc. in systems and computing science form Carleton University, Ottawa, Canada, and a Diploma in electrical engineering from the National Technical University of Athens, Greece.Dr. Zervos was at Bell Laboratories first with AT&T and next with Lucent Technologies, as Acting Technical Manager of Multimedia Access Communication Networks. He is one of the world’s experts in bandwidth-efficient digital transmission and author of several patents in the areas of data transmission and digital signal processing. During the last years his research work has been much concerned with renewable power generation systems and related topics of electric machines and power electronics.

Pierluigi Siano

Pierluigi Siano received the M.Sc. degree in electronic engineering and the Ph.D. degree in information and electrical engineering fromthe University of Salerno, Salerno, Italy, in 2001 and 2006, respectively. He is Associate Professor of Electrical Energy Engineering with the Department of Management and Innovation Systems, University of Salerno. He has coauthored more than 330 papers including more than 170 international journal papers. His research activities are foxused on demand response, on the integration of distributed energy resources in smart grids and on planning and management of power systems.

Masoud Abbaszadeh

Masoud Abbaszadeh obtained a B.Sc and a M.Sc in Electrical Engineering from Amirkabir University of Technology and Sharif University of Technology, in Iran, respectively. Next, he received a Ph.D. degree in Electrical Engineering (Controls) in 2008 from the University of Alberta, Canada. From 2011 to 2013, he was a Senior Research Engineer at United Technologies Research Center, East Hartford, CT, USA, working on advanced control systems, and complex systems’ modeling and simulation. From 2008 to 2011, he was with Maplesoft, Waterloo, Ontario, Canada, as a Research Engineer. He was the principal developer of MapleSim Control Design Toolbox and was a member of a research team working on the Maplesoft-Toyota jointModel Simplification and HLMT (High Level Modeling Tool) projects. He contributed to the development of the MapleSim electrical machines component library. Since 2013 he has been with General Electric Co, GE Global Research, Niskayuna, NY USA, where he works as a lead control systems engineer. His research interests include robust and nonlinear control and observer design, aswell as stochastic estimation and optimal filtering. He has over 70 peer-reviewed publications and several registered patents.

Mohamed Hamida

Mohamed Assaad Hamida was born in El Oued, Algeria, in 1985. He received the B.Sc. degree in electrical engineering from the University of Batna, Batna, Algeria, in 2009, the M.Sc. degree in automatic control from Ecole Nationale Supérieure d’Ingénieurs de Poitiers (ENSIP), Poitiers, France, in 2010, and the Ph.D degree in automatic control and electrical engineering from Ecole centrale de Nantes, Nantes, France, in 2013. From 2013 to 2017, he was an Associate Professor of Electrical Engineering with the University of Ouargla, Algeria. In 2017, he joined the Ecole Centrale de Nantes and the Laboratory of Digital Sciences of Nantes (LS2N), as an Associate Professor. Dr. Hamida is the local coordinator of the European project E-PiCo on Electric Vehicles Propulsion and Control at Ecole Centrale of Nantes and the head of the real-time systems unit in the same university. His research interests include robust nonlinear control (higher order sliding mode, backstepping, adaptive control, optimal control), theoretical aspects of nonlinear observer design, control and fault diagnosis of electrical systems and renewable energy applications. His current research interests include robust nonlinear control, theoretical aspect of nonlinear observer design, control, and fault diagnosis of electrical systems and renewable energy applications.