Tradeoff Between Risk and Cost in Economic Dispatch Including Wind Power Penetration Using Particle Swarm Optimization

A significant amount of attention has been paid to the renewable energy resources such as wind power in recent years. It has potential benefits in curbing emissions and reducing the consumption of irreplaceable fuel reserves. However, the penetration of wind power into traditional fuel- based generation systems will also cause some implications such as security concerns due to its unpredictable nature. Thus, in economic power dispatch with power penetration, a reasonable tradeoff between system risk and operational cost is desired. In this paper, a bi-objective economic dispatch problem considering wind penetration is formulated, which treats economic and security impacts as conflicting objectives. A modified multi-objective particle swarm optimization (MOPSO) algorithm is adopted to develop a power dispatch scheme which is able to achieve the compromise between economic and security requirements. The numerical simulations including sensitivity analysis are carried out based on a typical IEEE test power system to show the validity and applicability of the proposed approach.

[1]  Prakash Kumar Hota,et al.  Multiobjective Generation Dispatch Through a Neuro-Fuzzy Technique , 2004 .

[2]  S. A. Al-Baiyat,et al.  Economic load dispatch multiobjective optimization procedures using linear programming techniques , 1995 .

[3]  G. L. Viviani,et al.  Hierarchical Economic Dispatch for Piecewise Quadratic Cost Functions , 1984, IEEE Transactions on Power Apparatus and Systems.

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

[5]  Zwe-Lee Gaing,et al.  Particle swarm optimization to solving the economic dispatch considering the generator constraints , 2003 .

[6]  V. Miranda,et al.  Economic dispatch model with fuzzy wind constraints and attitudes of dispatchers , 2005, IEEE Transactions on Power Systems.

[7]  June Ho Park,et al.  Adaptive Hopfield neural networks for economic load dispatch , 1998 .

[8]  E.A. DeMeo,et al.  Wind plant integration [wind power plants] , 2005, IEEE Power and Energy Magazine.

[9]  J. C. Smith Winds of change issues in utility wind integration - Guest editorial , 2005 .

[10]  Ahlstrom,et al.  The future of wind forecasting and utility operations , 2005, IEEE Power and Energy Magazine.

[11]  R. Billinton,et al.  Evaluation of different operating strategies in small stand-alone power systems , 2005, IEEE Transactions on Energy Conversion.

[12]  E. Muljadi,et al.  Making connections [wind generation facilities] , 2005, IEEE Power and Energy Magazine.

[13]  R. Billinton,et al.  Generating capacity adequacy associated with wind energy , 2004, IEEE Transactions on Energy Conversion.

[14]  P. B. Eriksen,et al.  System operation with high wind penetration , 2005, IEEE Power and Energy Magazine.

[15]  T. Jayabarathi,et al.  Evolutionary programming techniques for different kinds of economic dispatch problems , 2005 .