Squirrel search algorithm for multi-region combined heat and power economic dispatch incorporating renewable energy sources

Abstract This paper suggests squirrel search algorithm (SSA) for solving intricate multi-region combined heat and power economic dispatch problem with integration of renewable energy sources. The valve point effect and proscribed workable area of thermal generators and solar and wind power uncertainty have been pondered. SSA is a newly developed swarm intelligence algorithm which emulates the dynamic scavenging activities of squirrels. The efficiency of the suggested method is revealed on a three region test system. Simulation outcomes of the suggested method have been evaluated with those attained by grey wolf optimization (GWO), particle swarm optimization (PSO), differential evolution (DE) and evolutionary programming (EP). It has been examined from the assessment that the suggested SSA has the capability to bestow with better-quality solution.

[1]  C. Wang,et al.  Decomposition Approach to Nonlinear Multiarea Generation Scheduling with Tie-line Constraints Using Expert Systems , 1992, IEEE Power Engineering Review.

[2]  Li Li,et al.  A differential evolution particle swarm optimizer for various types of multi-area economic dispatch problems , 2016 .

[3]  R. R. Shoults,et al.  A Practical Approach to an Interim Multi-Area Economic Dispatch Using Limited Computer Resources , 1985, IEEE Power Engineering Review.

[4]  Vijander Singh,et al.  A novel nature-inspired algorithm for optimization: Squirrel search algorithm , 2019, Swarm Evol. Comput..

[5]  N. Chen,et al.  Direct Search Method for Solving the Economic Dispatch Problem Considering Transmission Capacity Constraints , 2001, IEEE Power Engineering Review.

[6]  Peter D. Weigl,et al.  Dynamic Foraging Behavior in the Southern Flying Squirrel (Glaucomys volans): Test of a Model , 1998 .

[7]  Hamdi Abdi,et al.  Combined heat and power economic dispatch problem using gravitational search algorithm , 2016 .

[8]  Malabika Basu,et al.  Group search optimization for combined heat and power economic dispatch , 2016 .

[9]  Tao Guo,et al.  An algorithm for combined heat and power economic dispatch , 1996 .

[10]  Karl Vernes,et al.  GLIDING PERFORMANCE OF THE NORTHERN FLYING SQUIRREL (GLAUCOMYS SABRINUS) IN MATURE MIXED FOREST OF EASTERN CANADA , 2001 .

[11]  Tian Pau Chang,et al.  Investigation on Frequency Distribution of Global Radiation Using Different Probability Density Functions , 2010 .

[12]  Manisha Sharma,et al.  Reserve constrained multi-area economic dispatch employing differential evolution with time-varying mutation , 2011 .

[13]  Osvaldo R. Saavedra,et al.  EFFICIENT EVOLUTIONARY STRATEGY OPTIMISATION PROCEDURE TO SOLVE THE NONCONVEX ECONOMIC DISPATCH PROBLEM WITH GENERATOR CONSTRAINTS , 2005 .

[14]  P. S. Manoharan,et al.  Evolutionary algorithm solution and KKT based optimality verification to multi-area economic dispatch , 2009 .

[15]  F. J. Rooijers,et al.  Static economic dispatch for co-generation systems , 1994 .

[16]  David C. Yu,et al.  An Economic Dispatch Model Incorporating Wind Power , 2008, IEEE Transactions on Energy Conversion.

[17]  M. J. Short,et al.  Neural networks approach for solving economic dispatch problem with transmission capacity constraints , 1998 .

[18]  D. Streiffert,et al.  Multi-area economic dispatch with tie line constraints , 1995 .

[19]  Hao Yin,et al.  Crisscross optimization algorithm for solving combined heat and power economic dispatch problem , 2015 .

[20]  Nitin Narang,et al.  Combined heat and power economic dispatch using integrated civilized swarm optimization and Powell's pattern search method , 2017, Appl. Soft Comput..

[21]  Thang Trung Nguyen,et al.  Cuckoo search algorithm for combined heat and power economic dispatch , 2016 .

[22]  G. Sheblé,et al.  Genetic algorithm solution of economic dispatch with valve point loading , 1993 .

[23]  Ching-Tzong Su,et al.  An incorporated algorithm for combined heat and power economic dispatch , 2004 .

[24]  V.H. Quintana,et al.  Constrained Economic Dispatch of Multi-Area Systems Using the Dantzig-Wolfe Decomposition Principle , 1981, IEEE Transactions on Power Apparatus and Systems.

[25]  Lingfeng Wang,et al.  Stochastic combined heat and power dispatch based on multi-objective particle swarm optimization , 2006, 2006 IEEE Power Engineering Society General Meeting.

[26]  M. Fesanghary,et al.  Combined heat and power economic dispatch by harmony search algorithm , 2007 .

[27]  Kit Po Wong,et al.  Evolutionary programming approach for combined heat and power dispatch , 2002 .

[29]  Elnaz Davoodi,et al.  A GSO-based algorithm for combined heat and power dispatch problem with modified scrounger and ranger operators , 2017 .

[30]  B. Mohammadi-ivatloo,et al.  Combined heat and power economic dispatch problem solution using particle swarm optimization with time varying acceleration coefficients , 2013 .

[31]  Ruey-Hsun Liang,et al.  A Fuzzy-Optimization Approach for Generation Scheduling With Wind and Solar Energy Systems , 2007, IEEE Transactions on Power Systems.

[32]  P. Subbaraj,et al.  Enhancement of combined heat and power economic dispatch using self adaptive real-coded genetic algorithm , 2009 .