Enhanced augmented lagrange hopfield network for constrained economic dispatch with prohibited operating zones

摘要

This paper proposes an enhanced augmented Lagrange Hopfield network (EALHN) for solving constrained economic dispatch (CED) problem with units having prohibited operating zones (POZ). The proposed EALHN is an augmented Lagrange Hopfield network (ALHN) based method supported by heuristic search for repairing constraint violations, in which ALHN is formed by a continuous Hopfield neural network with its energy function based on augmented Lagrangian function. EALHN solves the CED problem with POZ in three phases. In the first phase, ALHN is used for solving the CED problem neglecting POZ of units. In the second phase, a heuristic search procedure is conducted to determine the most feasible search space for units with POZ if the prohibited zones are violated. In the last phase, ALHN is used again to solve the problem with the new feasible search space. The proposed method is tested on various systems and compared to other methods available in literature. Test results have shown that the proposed method is efficient and would be a competent method for solving CED problems with POZ from generating units, especially for large-scale systems.