Supervisory predictive control of a hybrid solar panels, microturbine and battery power generation plant

Abstract The main objective of this work is to design a supervisory predictive controller which optimizes the power flow of a renewable hybrid system (solar panels, microturbine and battery. Short time predictions of the solar power and the power reference will be embedded in the supervisor. Unlike expertise-based algorithms, the design of a generic and flexible strategy based on dynamic models is proposed. The performance index integrates the environmental impact, the cost of fuel, battery cycling and the energy delivery. Simulations and a real-time application in a Hardware-in-the-Loop plant are carried out to illustrate the applicability and effectiveness of the proposed supervisory predictive control design.

[1]  G. Venkataramanan,et al.  Optimal Technology Selection and Operation of Commercial-Building Microgrids , 2008, IEEE Transactions on Power Systems.

[2]  Fernando Tadeo,et al.  Implementation of predictive controllers as outer-loop controllers , 2009 .

[3]  V. Dinavahi,et al.  Tools for Analysis and Design of Distributed Resources—Part IV: Future Trends , 2011, IEEE Transactions on Power Delivery.

[4]  T. Rutherford,et al.  THE EU 20/20/2020 targets: An overview of the EMF22 assessment , 2009 .

[5]  K. Miu,et al.  Electric Power Engineering Education Resources 2005–2006 IEEE Power Engineering Society Committee Report. The Power Engineering Education Committee (PEEC) Task Force on Educational Resources , 2008, IEEE Transactions on Power Systems.

[6]  Weerakorn Ongsakul,et al.  A simulation model for predicting the performance of a solar photovoltaic system with alternating current loads , 2002 .

[7]  Xianzhong Chen,et al.  Supervisory Predictive Control of Standalone Wind/Solar Energy Generation Systems , 2011, IEEE Transactions on Control Systems Technology.

[8]  Rodolfo Dufo-López,et al.  Design and control strategies of PV-Diesel systems using genetic algorithms , 2005 .

[9]  Panagiotis D. Christofides,et al.  A distributed control framework for smart grid development: Energy/water system optimal operation and electric grid integration , 2011 .

[10]  P. Seferlis,et al.  Power management strategies for a stand-alone power system using renewable energy sources and hydrogen storage , 2009 .

[11]  Vincent Courtecuisse,et al.  A methodology to design a fuzzy logic based supervision of Hybrid Renewable Energy Systems , 2010, Math. Comput. Simul..

[12]  Heikki N. Koivo,et al.  System modelling and online optimal management of MicroGrid using Mesh Adaptive Direct Search , 2010 .

[13]  Shyh-Jier Huang,et al.  Design and Operation of Power Converter for Microturbine Powered Distributed Generator with Capacity Expansion Capability , 2008, IEEE Transactions on Energy Conversion.

[14]  Amin Hajizadeh,et al.  Intelligent power management strategy of hybrid distributed generation system , 2007 .

[15]  Cyril Voyant,et al.  Forecasting of preprocessed daily solar radiation time series using neural networks , 2010 .

[16]  T. Gjengedal,et al.  A qualitative approach to economic-environment dispatch-treatment of multiple pollutants , 1992 .

[17]  K. Strunz,et al.  A review of hybrid renewable/alternative energy systems for electric power generation: Configurations, control and applications , 2011, 2012 IEEE Power and Energy Society General Meeting.