A fast solver for combined emission and generation allocation using a Hopfield neural network

The combined economic/emission dispatch (CEED) problem is obtained by considering both the economy and emission objectives with required constraints. Many optimization techniques are slow for such complex optimization tasks and are not suitable for online use. This paper presents an optimization algorithm for solving constrained CEED, through the application of a flexible Hopfield neural network (HNN). The constrained CEED must satisfy the system load demand and practical operation constraints of generators. The feasibility of the proposed HNN using to solve CEED is demonstrated using a 3-unit test system and it is compared with the other methods in terms of solution quality and computation efficiency. The simulation results showed that the proposed HNN method was indeed capable of obtaining higher quality solutions efficiently in CEED problems with a much shorter computation time compared to other methods.