System modeling and optimization of microgrid using genetic algorithm

Microgrid has caused increasing attention for its high efficiency and low emissions. In this article a microgrid including a wind turbine, pv array and a CHP system consisting of fuel cells and a microturbine is studied and then the modeling of various DERs is conducted and the objective functions and constraints are developed. In the end the generic algorithm is employed to solved the optimal model and an operation scheme is achieved while meeting various constraints on the basis of tariff details, equipment performance, weather conditions and forecasts, load details and forecasts and other necessary information and then the economic costs and environmental impacts are analyzed and a conclusion that the multi-objective model can achieve high environmental benefits and spend as low operation cost as possible.

[1]  Adam Hawkes,et al.  Modelling high level system design and unit commitment for a microgrid , 2009 .

[2]  Su Ling Research on Economic Operation of Grid-Connected Microgrid , 2010 .

[3]  M. Abido Environmental/economic power dispatch using multiobjective evolutionary algorithms , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[4]  N.W. Miller,et al.  Dynamic modeling of GE 1.5 and 3.6 MW wind turbine-generators for stability simulations , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[5]  H.N. Koivo,et al.  MicroGrid Online Management and Balancing Using Multiobjective Optimization , 2007, 2007 IEEE Lausanne Power Tech.

[6]  Jin Hongguang Part-load Performance of CCHP with Gas Turbine and Storage System , 2006 .

[7]  S. Velumani,et al.  Proposal of a hybrid CHP system: SOFC/microturbine/absorption chiller , 2010 .

[8]  Z. Wu,et al.  Microgrid economic optimal operation of the combined heat and power system with renewable energy , 2010, IEEE PES General Meeting.

[9]  Hendrik Neumann,et al.  Optimal operation of dispersed generation under uncertainty using mathematical programming , 2006 .

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

[11]  Heikki N. Koivo,et al.  Multiobjective optimization using modified game theory for online management of microgrid , 2011 .

[12]  Marcelo Godoy Simões,et al.  PV-Microgrid Operational Cost Minimization by Neural Forecasting and Heuristic Optimization , 2008, 2008 IEEE Industry Applications Society Annual Meeting.

[13]  Hong-Tzer Yang,et al.  Bi-objective power dispatch using fuzzy satisfaction-maximizing decision approach , 1997 .

[14]  A. A. El-Keib,et al.  Thermal energy management of a CHP hybrid of wind and a grid-parallel PEM fuel cell power plant , 2009, 2009 IEEE/PES Power Systems Conference and Exposition.

[15]  David W. Coit,et al.  Multi-objective optimization using genetic algorithms: A tutorial , 2006, Reliab. Eng. Syst. Saf..

[16]  Pedro Rodriguez,et al.  Optimization of an experimental hybrid microgrid operation: Reliability and economic issues , 2009, 2009 IEEE Bucharest PowerTech.

[17]  Chris Marnay,et al.  Energy manager design for microgrids , 2005 .

[18]  M. A. Abido Environmental/economic power dispatch using multiobjective evolutionary algorithms , 2003 .