Earticle

초록

영어

In this paper, a Hopfield Lagrange network (HLN) is proposed for solving economic emission load dispatch (EELD) problem with multiple fuel options (MFO). Economic load dispatch (ELD) problem with MFO has been solved for recent years. However, it is more realistic to add CO2 emission to objective of ELD problem because generating units not only use fuels but also release emissions to the air. Consequently, ELD problem becomes EELD problem. HLN is a combination of Lagrange function and continuous Hopfield neural network where the Lagrange function is directly used as the energy function for the continuous Hopfield neural network. By using equivalent cost function and HLN, the paper proposed an effective method to solve EELD problem with MFO. The proposed method is tested on one test system consisting of ten generating units with various load demands and compared to other methods. In addition, the best compromise from the set of obtained solutions is found and compared to this from lamda-iteration (LI) method. The result comparisons have indicated that the proposed method is a highly effective method.

목차

Abstract
 1. Introduction
 2. Related Work
 3. Problem Formulation
 4. Implementation of QP-HLN
  4.1. Equivalent Fuel Cost and Emission Coefficients
  4.2. HLN Implementation
  4.3. Overall Procedure
 5. Overall Procedure of QP and lamda-iteration based method
 6. Best Compromise Solution by Fuzzy-Based Mechanism
 7. Results and Discussions
  7.1. Economic Dispatch
  7.2. Determination of the Best Compromise Solution
 8. Conclusion and Future Work
 References

키워드

저자

• Nguyen Trung Thang [ Ton Duc Thang University, HCM city, VietNam ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Advanced Science and Technology

• 간기

  월간

• pISSN

  2005-4238

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605