Qun Niu

TL;DR: The BBO-M uses the structure of biogeography-based optimization algorithm (BBO), and both the mutation motivated from the differential evolution (DE) algorithm and the chaos theory are incorporated into the BBO structure for improving the global searching capability of the algorithm.

TL;DR: An improved and simplified teaching-learning based optimization algorithm (STLBO) is proposed to identify and optimize parameters for PEM fuel cell as well as solar cell models by introducing an elite strategy to improve the quality of population and a local search is employed to further enhance the performance of the global best solution.

TL;DR: An improved adaptive binary Harmony Search (ABHS) algorithm is proposed in this paper to solve the binary-coded problems more effectively and outperforms the binary Harmony search algorithm, the novel global Harmony Search algorithm and the discrete binary Particle Swarm Optimization in terms of the search accuracy and convergence speed.

TL;DR: In this paper, a hybrid unit commitment framework is proposed to improve the reliability of the unit commitment by generating a range of scenarios based on multiple distributions of renewable generations under different prediction errors and extreme predicted value conditions.

TL;DR: A new constraint handling technique is developed to effectively handle various constraints in the DED problem, and the violation of ramp rate limits between the first and last scheduling intervals that is often ignored by existing approaches for DED problems is effectively eliminated.