CEPSO: A Novel Clustering Algorithm for Enhancing the Lifetime and Energy Efficiency of Wireless Sensor Networks in Power Grids

Facing numerous challenges in traditional Power Grid Wireless Sensor Networks (PGWSNs), including inaccurate node clustering, low energy efficiency, and shortened network lifetime, this study proposes an innovative energy-efficient clustering algorithm-an improved Particle Swarm Optimization algorithm (CEPSO). The algorithm employs a unique elite strategy by constructing a multi-level elite pool to retain outstanding individuals generated during iterations, thereby accelerating the iterative process. To address the complexity and diversity of the power grid environment, the algorithm incorporates Cubic chaotic mapping to enhance performance and adaptability to complex environments. By comparing and analyzing with traditional clustering methods such as LEACH, SEP and standard PSO, the CEPSO algorithm underwent extensive simulation tests on key metrics such as network delay, energy consumption reduction, and network lifetime extension. The research results indicate that the CEPSO algorithm significantly outperforms the compared algorithms in all performance metrics, providing an efficient solution for extending the lifetime of PGWSNs.