IEEE Transactions on Power Systems · 2007 · 231 citations · 18 references
EngineeringElectrical EngineeringEnergy ManagementEnergy SystemsOptimizationCongestion ManagementPower ManagementPower SystemsElectrical Power SystemsGenerator Voltage RegulationMultiobjective Particle Swarm OptimizationNetwork Congestion ManagementNonlinear OptimizationPareto Optimal SolutionParticle Swarm OptimizationPower System Optimization
This paper presents an effective method of congestion management in power systems. Congestions or overloads in transmission network are alleviated by generation rescheduling and/or load shedding of participating generators and loads. The two conflicting objectives 1) alleviation of overload and 2) minimization of cost of operation are optimized to provide pareto-optimal solutions. A multiobjective particle swarm optimization (MOPSO) method is used to solve this complex nonlinear optimization problem. A realistic frequency and voltage dependent load flow method which considers the voltage and frequency dependence of loads and generator regulation characteristics is used to solve this problem. The proposed algorithm is tested on IEEE 30-bus system, IEEE 118-bus system, and Northern Region Electricity Board, India (NREB) 390-bus system with smooth as well as nonsmooth cost functions due to valve point loading effect.
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