Dynamic Economic/Environmental Dispatch Problem Considering Prohibited Operating Zones

  • A. Torchani College of Engineering, University of Hail, Saudi Arabia | University of Tunis, ENSIT, LISIER Laboratory, Tunisia
  • A. Boudjemline College of Engineering, University of Hail, Saudi Arabia
  • H. Gasmi College of Engineering, University of Hail, Saudi Arabia | University of Tunis El-Manar, ENIT, Tunisia
  • Y. Bouazzi College of Engineering, University of Hail, Saudi Arabia and University of Tunis El Manar, ENIT, Tunisia
  • T. Guesmi College of Engineering, University of Hail, Saudi Arabia and University of Sfax, ENIS, Tunisia
Volume: 9 | Issue: 5 | Pages: 4586-4590 | October 2019 | https://doi.org/10.48084/etasr.2904

Abstract

Along with economic dispatch, emission dispatch has become a key problem under market conditions. Thus, the combination of the above problems in one problem called economic emission dispatch (EED) problem became inevitable. However, due to the dynamic nature of today’s network loads, it is required to schedule the thermal unit outputs in real-time according to the variation of power demands during a certain time period. Within this context, this paper presents an elitist technique, the second version of the non-dominated sorting genetic algorithm (NSAGII) for solving the dynamic economic emission dispatch (DEED) problem. Several equality and inequality constraints, such as valve point loading effects, ramp rate limits and prohibited operating zones (POZ), are taken into account. Therefore, the DEED problem is considered as a non-convex optimization problem with multiple local minima with higher-order non-linearities and discontinuities. A fuzzy-based membership function value assignment method is suggested to provide the best compromise solution from the Pareto front. The effectiveness of the proposed approach is verified on the standard power system with ten thermal units.

Keywords: dynamic environmental/economic dispatch, prohibited operating zones, multi-objective optimization, non-dominated sorting genetic algorithm

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