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A mixed binary‐continuous particle swarm optimisation algorithm for unit commitment in microgrids considering uncertainties and emissions

Ahmad Rezaee Jordehi

2020International Transactions on Electrical Energy Systems41 citationsDOI

Abstract

Objective Using a mixed binary continuous particle swarm optimisation (PSO) with V-shaped quadratic transfer for solving UC in demand response integrated MGs, while the uncertainties are considered. Method A mixed binary continuous particle swarm optimisation (PSO) is used for optimisation. Results The UC results have been achieved for 6 different scenarios. The potential of load curtailment as an incentive-based demand response program has been approved in decreasing operation cost of MGs and the effect of emissions, spinning reserve constraint and bid functions on operation cost of MG has been investigated. Discussion The achieved results in different scenarios approve the outperformance of the proposed PSO over some benchmark optimisation algorithms.

Topics & Concepts

Benchmark (surveying)Particle swarm optimizationMathematical optimizationBinary numberSpinningComputer scienceDemand responseAlgorithmEngineeringMathematicsElectricityGeodesyMechanical engineeringArithmeticGeographyElectrical engineeringMicrogrid Control and OptimizationSmart Grid Energy ManagementElectric Power System Optimization
A mixed binary‐continuous particle swarm optimisation algorithm for unit commitment in microgrids considering uncertainties and emissions | Litcius