Abstract
This paper proposes a Hopfield Lagrange Network (HLN) based method (HLNM) for economic emission dispatch of fixed head hydrothermal systems. 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. In the proposed method, HLN is used to find a set of non-dominated solutions and a fuzzy based mechanism is then exploited to determine the best compromise solution among the obtained ones. The proposed method has been tested on four hydrothermal systems and the obtained results in terms of total fuel cost, emission, and computational time have been compared to those other methods in the literature. The result comparisons have indicated that the proposed method is favorable for solving the economic emission dispatch problem of fixed-head hydrothermal systems.
Highlights
The short term hydro-thermal scheduling (HTS) problem is to determine the power generation among the available thermal and hydro power plants so that the total fuel cost of thermal units is minimized over a scheduled time of a single day or a week while satisfying both equality and inequality constraints including power balance, available water, and generation limits of both thermal and hydro plants [1]
A non-dominated sorting genetic algorithm-II (NSGA II) method [12] has been applied to economic environmental dispatch of fixed head hydrothermal scheduling problem with both convex and non-convex fuel cost and emission functions
Another method based on integration of predator-prey optimization and Powell search method (PPO-PS) [13] has been implemented for solving economic emission dispatch for fixed-head hydrothermal systems
Summary
The short term hydro-thermal scheduling (HTS) problem is to determine the power generation among the available thermal and hydro power plants so that the total fuel cost of thermal units is minimized over a scheduled time of a single day or a week while satisfying both equality and inequality constraints including power balance, available water, and generation limits of both thermal and hydro plants [1]. A non-dominated sorting genetic algorithm-II (NSGA II) method [12] has been applied to economic environmental dispatch of fixed head hydrothermal scheduling problem with both convex and non-convex fuel cost and emission functions. Another method based on integration of predator-prey optimization and Powell search method (PPO-PS) [13] has been implemented for solving economic emission dispatch for fixed-head hydrothermal systems. The HLN cannot deal with systems where fuel cost and emission functions are represented as nonconvex curves.In the proposed method, HLN is used to find a set of nondominated solutions and a fuzzy based mechanism is exploited to determine the best compromise solution among the obtained ones. The proposed method has been tested on four hydrothermal systems and the obtained results in terms of total fuel cost, emission, and computational time have been compared to those other methods in the literature
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