International Journal of Energy Optimization and Engineering, 1(1), 19-38, January-March 2012 19 Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Keywords: Augmented Lagrange Hopield Network, Hybrid Systems, Large-Scale Power System, Nonlinear Constraints, Real Power Dispatch INTRODUCTION In optimal power generation, the real power dispatch problem has been extensively studied due to its huge benefit in economic generation operation (Chowdhury & Rahrnan, 1990; Xia & Elaiw, 2010; Mahor, Prasad, & Rangnekar, 2009). The objective of the real power dispatch problem is to determine the total amount of real power contributed by online thermal generating units satisfying load demand at any time subject Real Power Dispatch on Large Scale Power Systems by Augmented Lagrange Hopield Network Vo Ngoc Dieu, Ho Chi Minh City University of Technology, Vietnam Peter Schegner, Technische Universität Dresden, Germany ABSTRACT This paper proposes an augmented Lagrange Hopield network (ALHN) for real power dispatch on large- scale power systems. The proposed ALHN is a continuous Hopield network with its energy function based on augmented Lagrange function. For this combination, the ALHN method can easily deal with large-scale problems with nonlinear constraints. The proposed ALHN has been tested on systems from 40 units to 240 units, IEEE 118-bus and IEEE 300-bus systems, and the obtained results have been compared to those from other methods. The test results have shown that the ALHN method can obtain better solutions than the com- pared methods in a very fast manner. Therefore, the proposedALHN could be favorable for implementation on the real power dispatch problems for large-scale systems. to generator limits so as their total generation cost is minimized. This is a real time problem, thus it is very important to solve the problem as quickly and precisely as possible. However, for dealing with large-scale systems it requires solution methods having ability to find optimal solution in a short time which can respond to the time frame required for the problem. Although there have been several search methods based on population developed for solving complex optimization problems, these methods are appropriate for medium scale problems since they need to be run several times to obtain best DOI: 10.4018/ijeoe.2012010102