Neural networks approach for solving economic dispatch problem with transmission capacity constraints 论文

1998IEEE Transactions on Power Systems引用 241
Energy Load and Power ForecastingNeural Networks and ApplicationsElectric Power System Optimization

摘要

This study presents a new approach using Hopfield neural networks for solving the economic dispatch (ED) problem with transmission capacity constraints. The proposed method is based on an improved Hopfield neural network which was presented by Gee et al. (1994). The authors discussed a new mapping technique for quadratic 0-1 programming problems with linear equality and inequality constraints. The special methodology improved the performance of Hopfield neural networks for solving combinatorial optimization problems. The authors have now modified Gee and Prager's (GP) method in order to solve ED with transmission capacity constraints. Constraints are handled using a combination of the GP model and the model of Abe et al. (1992). The proposed method (PHN) has achieved efficient and accurate solutions for two-area power systems with 3, 4, 40 and 120 units. The PHN results are very close to those obtained using the quadratic programming method.