Recently, there have been great advances in internet of things (IoT) and wireless sensor networks (WSNs) technologies for promoting electricity industrial upgrades and even allow the introduction of the fourth industrial revolution, namely, Smart Grid Industry (SGI) 4.0. The main functions of SGI4.0 are: Display omitted •We propose a novel BMO-based dynamic clustering algorithm to balance the data traffic and energy consumption load evenly among clusters in the smart grid.•We propose an innovative BMO-based routing algorithm to solve energy consumption and QoS-aware reliable data transmission in the smart grid.•The performance evaluations show that EQRP has successfully minimized the end-to-end delay and has improved the other routing QoS performance metrics, such as packet delivery ratio, efficient memory utilization, residual energy, and throughput. Recently, there have been great advances in internet of things (IoT) and wireless sensor networks (WSNs) leading to the fourth industrial revolution in power grid, namely, Smart Grid Industry 4.0 (SGI 4.0). In the Smart Grid Industry 4.0 framework, the WSNs have the potential to improve power grid efficiency by cable replacement, deployment flexibility, and cost reduction. However, the smart grid (SG) environment that the WSNs operate in is very challenging because of equipment noise, dust, heat, electromagnetic interference, multipath effects and fading, which make it difficult for current WSNs to provide reliable communication. For SGI 4.0 to come true, a WSN-based highly reliable communication infrastructure is essential for successful operation of the next-generation electricity power grids. To address this need, in this paper a novel dynamic clustering based energy efficient and quality-of-service (QoS)-aware routing protocol (called EQRP), which is inspired by the real behavior of the bird mating optimization (BMO), has been proposed. The proposed distributed scheme improves network reliability significantly and reduces excessive packets retransmissions for WSN-based SG applications. Performance results show that the proposed protocol has successfully reduced the end-to-end delay and has improved packet delivery ratio, memory utilization, residual energy, and throughput.