Optimal operation of a microturbine cluster with partial-load efficiency and emission characterization

This paper discusses optimal operation strategies of a cluster of microturbines (MTs) for electrical load-following applications. Cluster operation ensures higher operational flexibility, but raises the issue of taking into account the partial-load MT characteristics, in terms of energy efficiency and pollutant emissions. In particular, from experimental results the NO_x and CO emissions exhibit nonlinear and to some extent complementary trends at different partial-load levels. Hence, individual optimizations of fuel consumption and emission reduction are first carried out in this paper to show the conflicting nature of such objectives. Then, multi-objective optimization is performed to directly determine the best-known Pareto front. For this purpose, a procedure based on evolutionary programming is illustrated and applied to a practical case study. The results point out the degree of trade-off that can be sought when minimizing the local environmental impact of such distributed energy systems.