A Hybrid Metaheuristic Approach for the Solution of Renewables-Incorporated Economic Dispatch Problems

This paper presents a hybrid metaheuristic optimization algorithm developed to solve the Economic Dispatch Problem (EDP) encountered in different combinations of power plants. The algorithm is developed by assimilating the prominent features of Particle Swarm Optimization (PSO) and Bat Algorithm (BA) and improves cost reduction and convergence with lesser computational time. The developed algorithm is employed for the solution of EDP consisting of only Renewable Energy Sources (RESs) implemented at various locations in Pakistan. The all RES based EDP consists of scenarios composed of sub-scenarios having no constraints, with time-varying loads and multi-area economic dispatch (MAED). The algorithm is also tested for three different combinations of power plants, comprising of RES integrated with thermal power plants (TPPs), the small-scaled thermal power system with constraints, and a large-scaled power system with Valve Point Loading (VPL) effect. The comparative analysis of the results for the developed metaheuristic algorithm with various existing techniques shows a reasonable reduction in the cost, improved computational time, and fast convergence.

[1]  M. Imran,et al.  An Overview of Particle Swarm Optimization Variants , 2013 .

[2]  A. Immanuel Selvakumar,et al.  Optimization using civilized swarm: Solution to economic dispatch with multiple minima , 2009 .

[3]  Malabika Basu,et al.  Artificial bee colony optimization for multi-area economic dispatch , 2013 .

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

[5]  Zwe-Lee Gaing.  Closure to "Discussion of 'Particle swarm optimization to solving the economic dispatch considering the generator constraints'" , 2004 .

[6]  Amir Hossein Gandomi,et al.  Chaotic bat algorithm , 2014, J. Comput. Sci..

[7]  Vahid Vahidinasab,et al.  A modified harmony search method for environmental/economic load dispatch of real-world power systems , 2014 .

[8]  Anne L. Olsen.  Using pseudocode to teach problem solving , 2005 .

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

[10]  Jason Gu,et al.  Solution of an Economic Dispatch Problem Through Particle Swarm Optimization: A Detailed Survey - Part I , 2017, IEEE Access.

[11]  Loi Lei Lai,et al.  Levelized cost of electricity for photovoltaic/biogas power plant hybrid system with electrical energy storage degradation costs , 2017 .

[12]  Dinu Calin Secui,et al.  A new modified artificial bee colony algorithm for the economic dispatch problem , 2015 .

[13]  Xiujuan Lei,et al.  Solving non-convex/non-smooth economic load dispatch problems via an enhanced particle swarm optimization , 2017, Appl. Soft Comput..

[14]  Flore Remouit,et al.  Variability assessment and forecasting of renewables: A review for solar, wind, wave and tidal resources , 2015 .

[15]  T. Mahmood,et al.  Prospects and Implementation of Solar Energy Potential in Pakistan: Based on Hybrid Grid Station employing Incremental Conductance technique , 2018 .

[16]  M. Basu,et al.  Squirrel search algorithm for multi-region combined heat and power economic dispatch incorporating renewable energy sources , 2019, Energy.

[17]  Chao-Lung Chiang,et al.  Improved genetic algorithm for power economic dispatch of units with valve-point effects and multiple fuels , 2005, IEEE Transactions on Power Systems.

[18]  A. Selvakumar,et al.  A New Particle Swarm Optimization Solution to Nonconvex Economic Dispatch Problems , 2007, IEEE Transactions on Power Systems.

[19]  Xin-She Yang,et al.  Binary bat algorithm , 2013, Neural Computing and Applications.

[20]  Anjum Munir,et al.  Current status and overview of renewable energy potential in Pakistan for continuous energy sustainability. , 2016 .

[21]  W. T. Elsayed,et al.  A Fully Decentralized Approach for Solving the Economic Dispatch Problem , 2015, IEEE Transactions on Power Systems.

[22]  Jason Gu,et al.  Solution of an Economic Dispatch Problem Through Particle Swarm Optimization: A Detailed Survey – Part II , 2017, IEEE Access.

[23]  Tanuj Sen,et al.  A new approach to solve Economic Dispatch problem using a Hybrid ACO–ABC–HS optimization algorithm , 2016 .

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

[25]  Selim Yilmaz,et al.  A new modification approach on bat algorithm for solving optimization problems , 2015, Appl. Soft Comput..

[26]  E. Ela,et al.  Studying the Variability and Uncertainty Impacts of Variable Generation at Multiple Timescales , 2012, IEEE Transactions on Power Systems.

[27]  Ye Er-lan,et al.  The Introduction of Particle Swarm Optimization , 2010 .

[28]  Jagdish C. Patra,et al.  Orthogonal PSO algorithm for economic dispatch of thermal generating units under various power constraints in smart power grid , 2017, Appl. Soft Comput..

[29]  Waree Kongprawechnon,et al.  Application of multiple tabu search algorithm to solve dynamic economic dispatch considering generator constraints , 2008 .

[30]  Xin-She Yang,et al.  Economic dispatch using chaotic bat algorithm , 2016 .

[31]  Xin-She Yang,et al.  Bat algorithm: a novel approach for global engineering optimization , 2012, 1211.6663.

[32]  Li Cheng,et al.  A New Metaheuristic Bat-Inspired Algorithm , 2010 .

[33]  Hari Mohan Dubey,et al.  Economic load dispatch of wind-solar-thermal system using backtracking search algorithm , 2017 .

[34]  Xiaoxin Zhou,et al.  Economic Dispatch With Non-Smooth Objectives—Part II: Dimensional Steepest Decline Method , 2015, IEEE Transactions on Power Systems.

[35]  Anders Malmquist,et al.  Feasibility study of using a biogas engine as backup in a decentralized hybrid (PV/wind/battery) power generation system : Case study Kenya , 2015 .

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

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

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

[39]  Muhammad Kamran,et al.  Current status and future success of renewable energy in Pakistan , 2018 .

[40]  P. K. Chattopadhyay,et al.  Evolutionary programming techniques for economic load dispatch , 2003, IEEE Trans. Evol. Comput..

[41]  Zhigang Lu,et al.  A Line Flow Granular Computing Approach for Economic Dispatch With Line Constraints , 2017, IEEE Transactions on Power Systems.

[42]  Raheel Zafar,et al.  Evaluating wind energy potential in Pakistan's three provinces, with proposal for integration into national power grid , 2016 .

[43]  Xin-She Yang,et al.  A New Metaheuristic Bat-Inspired Algorithm , 2010, NICSO.

[44]  A. Ebenezer Jeyakumar,et al.  Hybrid PSO–SQP for economic dispatch with valve-point effect , 2004 .

[45]  Jizhen Liu,et al.  Economic dispatch of wind-thermal power system by using aggregated output characteristics of virtual power plants , 2016, 2016 12th IEEE International Conference on Control and Automation (ICCA).

[46]  Imran Khan,et al.  Sugarcane Biofuels and Bioenergy Production in Pakistan: Current Scenario, Potential, and Future Avenues , 2019, Sugarcane Biofuels.

[47]  E. Kyriakides,et al.  A GA-API Solution for the Economic Dispatch of Generation in Power System Operation , 2012, IEEE Transactions on Power Systems.

[48]  Mashood Nasir,et al.  Recent Approaches of Forecasting and Optimal Economic Dispatch to Overcome Intermittency of Wind and Photovoltaic (PV) Systems: A Review , 2019 .

[49]  K. Chandram,et al.  Equal embedded algorithm for economic load dispatch problem with transmission losses , 2011 .

[50]  T. Jayabarathi,et al.  Economic dispatch using hybrid grey wolf optimizer , 2016 .

[51]  Xin-She Yang,et al.  Bat algorithm: literature review and applications , 2013, Int. J. Bio Inspired Comput..

[52]  Anton Ianakiev,et al.  Features of fully integrated renewable energy atlas for Pakistan; wind, solar and cooling , 2018, Renewable and Sustainable Energy Reviews.

[53]  W. Grady,et al.  A Practical Approach to Unit Commitment, Economic Dispatch and Savings Allocation for Multiple-Area Pool Operation with Import/Export Constraints , 1980, IEEE Transactions on Power Apparatus and Systems.

[54]  Josef Tlusty,et al.  A novel weight-improved particle swarm optimization algorithm for optimal power flow and economic load dispatch problems , 2010, IEEE PES T&D 2010.

[55]  Jianming Zhang,et al.  Particle swarm optimization algorithm for constrained problems , 2009 .

[56]  Muhammad Naqvi,et al.  Potential of biomass for bioenergy in Pakistan based on present case and future perspectives , 2018 .