Improved Merit Order and Augmented Lagrange Hopfield Network for Ramp Rate and Transmission Constrained Unit Commitment

Abstract

This paper proposes an improved merit order (IMO) and augmented Lagrange Hopfield neural network (ALHN) for solving ramp rate and transmission constrained unit commitment (RTUC) problem. The IMO is a merit order enhanced by a heuristic search algorithm based on average production cost of units, and the ALHN is a continuous Hopfield network with its energy function based on augmented Lagrangian relaxation. In the proposed method, IMO is used for solving unit scheduling and repairing constraint violations such as minimum up/down time, ramp rate, transmission limit, and 15 minute spinning reserve response time, and ALHN is applied for solving economic dispatch based on the obtained unit scheduling by the IMO. The proposed IMO-ALHN is tested on 24-bus IEEE Reliability Test System with 26 units and compared to dynamic priority list (DPL), enhanced adaptive Lagrangian relaxation (ELR), and advanced hybrid genetic algorithm (AHGA). The results show that the proposed method obtains less total costs than the others. Therefore, the proposed method is favorable for unit commitment with ramp rate and transmission constraints.