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Multiobjective Decentralized Congestion Management Using Modified NSGA-II

  • Research Article - Electrical Engineering
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Abstract

This paper proposes a model for the decentralized multiobjective congestion management problem in the deregulated forward power market by considering conflicting objectives of the maximization of social welfare and the minimization of emission impacts. An elitist evolutionary multiobjective optimization algorithm called Modified Non-dominated Sorting Genetic Algorithm II (MNSGA-II) with controlled elitism and a dynamic crowding distance is applied. To validate the model, an IEEE 30-bus test system with three multilateral transactions is considered. The valve-point effect is included in the social welfare function. Voltage and reactive power effects are also incorporated. The closeness of the results of multiobjective decentralized and centralized congestion management demonstrates the validity of the proposed multiobjective decentralized model. The proposed model provides a set of alternative solutions to the market participants to manage congestion. The effectiveness of the proposed approach is demonstrated by comparing the obtained Pareto front with a reference Pareto front generated with multiple runs of the Covariance Matrix Adapted Evolution Strategy algorithm with respect to minimum spacing, diversity and convergence metric performance measures.

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Authors and Affiliations

  1. Department of EEE, St. Joseph’s College of Engineering, Chennai, 600119, India

    S. Visalakshi

  2. Centre for Advanced Research in Evolutionary Computation (CAREC), Thiagarajar College of Engineering, Madurai, 625015, India

    S. Baskar

Authors
  1. S. Visalakshi
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  2. S. Baskar
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Correspondence to S. Visalakshi.

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Visalakshi, S., Baskar, S. Multiobjective Decentralized Congestion Management Using Modified NSGA-II. Arab J Sci Eng 36, 827–840 (2011). https://doi.org/10.1007/s13369-011-0079-z

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  • DOI: https://doi.org/10.1007/s13369-011-0079-z

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