A New Particle Swarm Optimization Based Strategy for the Economic Emission Dispatch Problem Including Wind Energy Sources

Authors

  • G. A. Alshammari Electrical Engineering Department, College of Engineering, University of Hail, Saudi Arabia
  • F. A. Alshammari Electrical Engineering Department, College of Engineering, University of Hail, Saudi Arabia
  • T. Guesmi Department of Electrical Engineering, University of Hail, Saudi Arabia
  • B. M. Alshammari Department of Electrical Engineering, University of Hail, Saudi Arabia
  • A. S. Alshammari Department of Electrical Engineering, University of Hail, Saudi Arabia
  • N. A. Alshammari Department of Electrical Engineering, University of Hail, Saudi Arabia
Volume: 11 | Issue: 5 | Pages: 7585-7590 | October 2021 | https://doi.org/10.48084/etasr.4279

Abstract

Power dispatch has become an important issue due to the high integration of Wind Power (WP) in power grids. Within this context, this paper presents a new Particle Swarm Optimization (PSO) based strategy for solving the stochastic Economic Emission Dispatch Problem (EEDP). This problem was solved considering several constraints such as power balance, generation limits, and Valve Point Loading Effects (VPLEs). The power balance constraint is described by a chance constraint to consider the impact of WP intermittency on the EEDP solution. In this study, the chance constraint represents the tolerance that the power balance constraint cannot meet. The suggested framework was successfully evaluated on a ten-unit system. The problem was solved for various threshold tolerances to study further the impact of WP penetration.

Keywords:

economic emission dispatch, wind energy, stochastic optimization, particle swarm optimization

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[1]
G. A. Alshammari, F. A. Alshammari, T. Guesmi, B. M. Alshammari, A. S. Alshammari, and N. A. Alshammari, “A New Particle Swarm Optimization Based Strategy for the Economic Emission Dispatch Problem Including Wind Energy Sources”, Eng. Technol. Appl. Sci. Res., vol. 11, no. 5, pp. 7585–7590, Oct. 2021.

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