Multi-period wind integrated optimal dispatch using series PSO-DE with time-varying Gaussian membership function based fuzzy selection

Abstract Wind power has emerged as the most promising option for providing sustainable eco-friendly power supply to the modern world. Due to its unpredictable nature, integration of wind power into the conventional power grid is a very challenging task having dynamic characteristics. Due to the inherent uncertainty associated with wind availability, additional spinning reserve needs to be scheduled in order to maintain security and supply reliability. Multi-period multi-objective optimal dispatch (MPMOOD) is presented for wind integrated power system with reserve constraints. The complex relationship between wind power availability, spinning reserve allocation and their impact on economic/environmental cost are analysed using an elaborate model. A new multi-objective Series PSO-DE (SPSO-DE) hybrid algorithm is proposed where the two paradigms, differential evolution (DE) and particle swarm optimization (PSO) share domain information and maintain a synergistic cooperation to overcome their individual weaknesses. For multi-objective (MO) problems, the selection operation in SPSO-DE is replaced by a 5-class time-varying fuzzy selection mechanism (TVFSM) to avoid saturation and to increase Pareto diversity. To promote convergence towards the central part of the Pareto front and to quickly isolate the boundary solutions, Guassian membership function is employed. Elitism is applied to preserve good solutions and momentum operation is used to stop premature convergence. The proposed method expedites the search for the best solution, i.e. the solution which satisfies all the objectives of the MO problems. To test the performance and computational efficiency, the proposed method is applied on two standard test power systems.

[1]  E. Sortomme,et al.  Optimizing economic/environmental dispatch with wind and thermal units , 2009, 2009 IEEE Power & Energy Society General Meeting.

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

[3]  H. T. Jadhav,et al.  Economic load dispatch including wind power using plant growth simulation algorithm , 2012, 2012 11th International Conference on Environment and Electrical Engineering.

[4]  Whei-Min Lin,et al.  Quantum genetic algorithm for dynamic economic dispatch with valve-point effects and including wind power system , 2011 .

[5]  Wilsun Xu,et al.  Economic Load Dispatch Constrained by Wind Power Availability: A Here-and-Now Approach , 2010, IEEE Transactions on Sustainable Energy.

[6]  Xian Liu,et al.  Economic Load Dispatch Constrained by Wind Power Availability: A Wait-and-See Approach , 2010, IEEE Transactions on Smart Grid.

[7]  Meei-Song Kang,et al.  Generation Cost Assessment of an Isolated Power System With a Fuzzy Wind Power Generation Model , 2007, IEEE Transactions on Energy Conversion.

[8]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[9]  Saman K. Halgamuge,et al.  Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients , 2004, IEEE Transactions on Evolutionary Computation.

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

[11]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[12]  Taher Niknam,et al.  Scenario-based dynamic economic emission dispatch considering load and wind power uncertainties , 2013 .

[13]  K. Geetha,et al.  Design of economic dispatch model for Gencos with thermal and wind powered generators , 2015 .

[14]  Ebrahim Farjah,et al.  An efficient scenario-based and fuzzy self-adaptive learning particle swarm optimization approach for dynamic economic emission dispatch considering load and wind power uncertainties , 2013 .

[15]  S. Surender Reddy,et al.  Multi-objective market clearing of electrical energy, spinning reserves and emission for wind-thermal power system , 2013 .

[16]  Lingfeng Wang,et al.  Balancing risk and cost in fuzzy economic dispatch including wind power penetration based on particle swarm optimization , 2008 .

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

[18]  Gwo-Ching Liao,et al.  Solve environmental economic dispatch of Smart MicroGrid containing distributed generation system – Using chaotic quantum genetic algorithm , 2012 .

[19]  Xian Liu.  Combined heat and power dispatch with wind power: A stochastic model and solutions , 2010, IEEE PES General Meeting.

[20]  Jin Qi,et al.  An integrated AHP and VIKOR for design concept evaluation based on rough number , 2015, Adv. Eng. Informatics.

[21]  G. Sheblé,et al.  Power generation operation and control — 2nd edition , 1996 .

[22]  Daniel S. Kirschen,et al.  Assessing the Impact of Wind Power Generation on Operating Costs , 2010, IEEE Transactions on Smart Grid.

[23]  Bikash C. Pal,et al.  Intermittent wind generation in optimal power flow dispatching , 2009 .

[24]  L. Coelho,et al.  Combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valve-point effect , 2006, IEEE Transactions on Power Systems.

[25]  P. Venkatesh,et al.  Glowworm swarm optimization algorithm with topsis for solving multiple objective environmental economic dispatch problem , 2014, Appl. Soft Comput..

[26]  Manisha Sharma,et al.  Environmental economic dispatch in multi-area power system employing improved differential evolution with fuzzy selection , 2015, Appl. Soft Comput..

[27]  Aniruddha Bhattacharya,et al.  Multi-objective economic emission load dispatch solution using gravitational search algorithm and considering wind power penetration , 2013 .

[28]  I J Nagrath,et al.  Power System Engineering , 2007 .

[29]  Wilsun Xu,et al.  Minimum Emission Dispatch Constrained by Stochastic Wind Power Availability and Cost , 2010, IEEE Transactions on Power Systems.

[30]  K. Lakshmi,et al.  Gencos wind–thermal scheduling problem using Artificial Immune System algorithm , 2014 .

[31]  Gang Liu,et al.  Dynamic economic dispatch for wind-thermal power system using a novel bi-population chaotic differential evolution algorithm , 2012 .

[32]  Chun-Lung Chen,et al.  Multi-area economic generation and reserve dispatch considering large-scale integration of wind power , 2014 .

[33]  Jie Wang,et al.  Multi-objective economic emission dispatch considering wind power using evolutionary algorithm based on decomposition , 2014 .

[34]  Bijaya K. Panigrahi,et al.  Joint energy and spinning reserve dispatch in wind-thermal power system using IDE-SAR technique , 2013, 2013 IEEE Symposium on Swarm Intelligence (SIS).

[35]  Ronnie Belmans,et al.  Revision of reserve requirements following wind power integration in island power systems , 2013 .

[36]  Manisha Sharma,et al.  Large-scale multi-zone optimal power dispatch using hybrid hierarchical evolution technique , 2014 .

[37]  Taher Niknam,et al.  Probabilistic multiobjective wind-thermal economic emission dispatch based on point estimated method , 2012 .

[38]  Xiaoli Zhao,et al.  Joint environmental and economic power dispatch considering wind power integration: Empirical analysis from Liaoning Province of China , 2013 .

[39]  Bijay Ketan Panigrahi,et al.  Hybrid flower pollination algorithm with time-varying fuzzy selection mechanism for wind integrated multi-objective dynamic economic dispatch , 2015 .

[40]  Cheng-Chien Kuo,et al.  Wind energy dispatch considering environmental and economic factors , 2010 .

[41]  Manjaree Pandit,et al.  An improved bacterial foraging algorithm for combined static/dynamic environmental economic dispatch , 2012, Appl. Soft Comput..

[42]  G. S. Piperagkas,et al.  Stochastic PSO-based heat and power dispatch under environmental constraints incorporating CHP and w , 2011 .

[43]  S. Roy,et al.  Inclusion of Short Duration Wind Variations in Economic Load Dispatch , 2012, IEEE Transactions on Sustainable Energy.

[44]  Bijay Ketan Panigrahi,et al.  Energy and spinning reserve scheduling for a wind-thermal power system using CMA-ES with mean learning technique , 2013 .

[45]  Ranjit Roy,et al.  An application of craziness based shuffled frog leaping algorithm for wind-thermal generation dispatch considering emission and economy , 2011, 2011 10th International Conference on Environment and Electrical Engineering.

[46]  Gwo-Ching Liao,et al.  A novel evolutionary algorithm for dynamic economic dispatch with energy saving and emission reducti , 2011 .

[47]  Manjaree Pandit,et al.  Static/dynamic optimal dispatch of energy and reserve using recurrent differential evolution , 2013 .

[48]  Ranjit Roy,et al.  Gbest guided artificial bee colony algorithm for environmental/economic dispatch considering wind power , 2013, Expert Syst. Appl..

[49]  Behnam Mohammadi-Ivatloo,et al.  Optimal operation scheduling of wind power integrated with compressed air energy storage (CAES) , 2013 .

[50]  C.-l. Chen,et al.  Simulated annealing-based optimal wind-thermal coordination scheduling , 2007 .

[51]  Manjaree Pandit,et al.  Particle swarm optimization with time varying acceleration coefficients for non-convex economic power dispatch , 2009 .

[52]  Bijaya K. Panigrahi,et al.  Dynamic economic load dispatch with wind energy using modified harmony search , 2010, Int. J. Bio Inspired Comput..

[53]  Chuangxin Guo,et al.  Optimal generation dispatch with renewable energy embedded using multiple objectives , 2012 .

[54]  I. A. Farhat,et al.  Dynamic adaptive bacterial foraging algorithm for optimum economic dispatch with valve-point effects and wind power , 2010 .

[55]  A. R. Abhyankar,et al.  Market clearing for a wind-thermal power system incorporating wind generation and load forecast uncertainties , 2012, 2012 IEEE Power and Energy Society General Meeting.