Multi-Fuel Power Dispatch in an Interconnected Power System using Ant Lion Optimizer: Multi-Fuel Dispatch Considering Tie-Line Limits

Multi-Fuel Power Dispatch in an Interconnected Power System using Ant Lion Optimizer: Multi-Fuel Dispatch Considering Tie-Line Limits

Balachandar P (Annamalai University, Department of Electrical Engineering, Chidambaram, India), Ganesan S (Annamalai University, Department of Electrical Engineering, Chidambaram, India), Jayakumar N (Annamalai University, Department of Electrical Engineering, Chidambaram, India) and Subramanian S (Annamalai University, Department of Electrical Engineering, Chidambaram, India)
Copyright: © 2017 |Pages: 26
DOI: 10.4018/IJEOE.2017070102
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Abstract

The electrical power generation from fossil fuel releases several contaminants into the air and this become excrescent if the generating unit is fed by Multiple Fuel Sources (MFS).The ever more stringent environmental regulations have forced the power producers to produce electricity not only at the cheapest price but also at the minimum level of pollutant emissions. Inclusion of this issue in the operational task is a welcome perspective. The cost effective and environmental responsive power system operations in the presence of MFS can be recognized as a multi-objective constrained optimization problem with conflicting operational objectives. The modern meta-heuristic algorithm namely, Ant Lion Optimizer (ALO) has been applied for the first time to obtain the feasible solution. The fuzzy decision-making mechanism has been integrated to determine the Best Compromise Solution (BCS) in the multi-objective framework. The intended algorithm is implemented on the standard test systems considering valve-point effects, CO2 emission and tie-line limits.
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Nomenclature

  • αij, βijij emission coefficients of generating unit i for fuel type j

  • aij, bij,cij, eij, fij fuel cost coefficients of generating unit i for fuel type j

  • Bij network loss coefficients

  • Pimin, Pimax Minimum and maximum real power generation limits of unit i in MW

  • -Tipmax power flow limit from area i to area p

  • Tipmax power flow limit from area p to area i

  • µi fuzzy membership function of objective i

  • µk normalised membership function value of candidate k

  • Ai,k position of ith ant at iteration k

  • ALj,k position of jth ant lion at iteration k

  • Ei(Pi) pollutant emission function of generator i with real power output of Pi in kg/h

  • Fi(Pi) fuel cost function of generator i with real power output of Pi in $/h

  • itermax maximum iteration number

  • mi,k maximum of all variables at ant i

  • mi,k maximum of variable i at iteration k

  • mk maximum of all variables at iteration k

  • N number of generating units

  • NA number of area

  • Nd number of decision variables

  • Pd real power demand in MW

  • Pi real power output of generator i in MW

  • Pij real power output of generator i using fuel j in MW

  • PL real power loss in MW

  • Ps number of search agents

  • qi,k minimum of all variables for ant i

  • qi,k minimum of variable i at iteration k

  • qk minimum of all variables at iteration k

  • RA,k random walk around the ant lion selected by the roulette wheel at iteration k

  • RB,k random walk around the elite at iteration k

  • ri, mi minimum and maximum random walks of variable i

  • Tik tie line real power transfer from area i to area k

  • Xik value of variable i at iteration k

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