Fractional Order Control and Simulation of Wind-Biomass Isolated Hybrid Power System Using Particle Swarm Optimization

In this work, a fractional order (FO) proportional–integral–derivative (PID) (FO-PID) controller is considered for load-frequency control (LFC) of the isolated hybrid power system, comprising of a biomass-based diesel engine generator and a wind turbine generator. The FO-PID controllers are PID controller only, and the difference lies in the order of the integral and derivative part of the controllers. In FO controllers, the order of the integral and derivative part are fractional in nature. In this paper, particle swarm optimization (PSO) algorithm has been engaged to carry out the above mentioned LFC for the considered wind-biomass isolated hybrid power system. A comparison of FO control strategy with conventional based controller techniques is made. The FO-PID controller outperforms the conventional PID controllers. And, robustness analysis is also done for the FO-PID controller.

[1]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[2]  Igor Podlubny,et al.  Fractional-order systems and PI/sup /spl lambda//D/sup /spl mu//-controllers , 1999 .

[3]  Kenneth A. Kobe,et al.  Gas producers and blast furnaces , 1951 .

[4]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[5]  C. M. Kinoshita,et al.  Power Generation Potential of Biomass Gasification Systems , 1997 .

[6]  Salvina Gagliano,et al.  Hybrid solar/wind power system probabilistic modelling for long-term performance assessment , 2006 .

[7]  Ajith Abraham,et al.  Design of fractional-order PIlambdaDµ controllers with an improved differential evolution , 2009, Eng. Appl. Artif. Intell..

[8]  Vivekananda Mukherjee,et al.  Fractional order fuzzy PID controller for wind energy-based hybrid power system using quasi-oppositional harmony search algorithm , 2017 .

[9]  Francisco Jurado,et al.  An adaptive control scheme for biomass-based diesel–wind system , 2003 .

[10]  Vivekananda Mukherjee,et al.  Energy storage systems for mitigating the variability of isolated hybrid power system , 2015 .

[11]  Frede Blaabjerg,et al.  Renewable energy resources: Current status, future prospects and their enabling technology , 2014 .

[12]  Tarkeshwar Mahto,et al.  Evolutionary optimization technique for comparative analysis of different classical controllers for an isolated wind-diesel hybrid power system , 2016, Swarm Evol. Comput..

[13]  Simone Espey,et al.  Renewables portfolio standard: a means for trade with electricity from renewable energy sources? , 2001 .

[14]  P. Balamurugan,et al.  An Optimal Hybrid Wind-biomass Gasifier System for Rural Areas , 2011 .

[15]  Sandip Deshmukh,et al.  Modeling of hybrid renewable energy systems , 2008 .

[16]  I. Podlubny Fractional-order systems and PIλDμ-controllers , 1999, IEEE Trans. Autom. Control..