Work

An Improved Binary Cuckoo Search Algorithm for Solving Unit Commitment Problems: Methodological Description

Year: 2018

Type: article

Abstract: The unit commitment problem is a large-scale, nonlinear, and mixed-integer optimization problem in an electric power system. Numerous researchers concentrate on minimizing its total generation cost. Cuckoo search is an efficient metaheuristic swarm-based approach that balances between local and global search strategy. Owing to its easy implementation and rapid convergence, it has been successfully used to solve a wide variety of optimization problems. This paper proposes an improved binary cuckoo search algorithm (IBCS) for solving the unit commitment problem. A new binary updating mechanism is introduced to help the IBCS choose a right search direction, and a heuristic search method based on a novel priority list can prevent it from being trapped into local optima. A 4-unit system is used as an example to validate the effectiveness of the proposed method.

Source: IEEE Access

DOI: 10.1109/access.2018.2861319

Authors: Jian Zhao, Shixin Liu, Mengchu Zhou, Xiwang Guo, Liang Qi

Institutions: University of Science and Technology Liaoning, Northeastern University, New Jersey Institute of Technology, Shandong University of Science and Technology

Language: English

Topic: Electric Power System Optimization

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,075