SOLVING COMBINED ECONOMIC AND EMISSION DISPATCH PROBLEM USING A ONE LAYER DYNAMIC NEURAL NETWORK
DOI:
https://doi.org/10.59277/RRST-EE.2026.2.2Keywords:
Economic load dispatch (ELD), Dynamic neural network (DNN), Power generation, Cost optimizationAbstract
In this paper, a one-layer dynamic neural network (OL-DNN) has been proposed to find optimal solutions to combined economic and emission dispatch (CEED) problems. The goal of the CEED problem is to schedule generators to meet load demand and operational constraints while minimizing fuel costs and emissions. The fuel cost and emission objectives of the generating units are taken into account when formulating the CEED problem from a multi-objective to a bi-objective problem. This is done by applying a price penalty factor. The new algorithm is applied to and tested on three examples from the literature, and the solution is then compared with those obtained by other algorithms to demonstrate the superiority and effectiveness of the proposed algorithm.
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