Jul 2026· Applied System Innovation· Vol 9, pp. 151· 0 citations· 132 references
Abstract
The rapid digitalization and decarbonization of electrical power systems have brought increased operational complexity and new occupational risk dynamics. This transition renders traditional compliance-based safety models inadequate for managing the emerging complexities of cyber–physical and socio-technical systems. This paper develops a conceptual socio-technical safety architecture for occupational risk management in electrical power systems, grounded in the concepts of systems innovation and socio-technical modeling. A structured narrative review of international standards, accident investigations, and emerging technologies is conducted to reinterpret hazards as interacting subsystems within a dynamic, adaptive framework. The proposed framework synthesizes technical safety controls, human reliability factors, and artificial intelligence-driven predictive maintenance within a single architecture, supported by dynamic feedback loops. The model addresses nonlinear risk propagation across smart grid applications, hydrogen systems, and battery energy storage systems. By transitioning from a reactive to a proactive, adaptive approach to safety governance, the architecture enhances the resilience of electrical power systems, reduces the potential for cascading failures, and aligns occupational safety with infrastructure modernization strategies for electrical power systems. The framework provides a conceptual basis for integrating technology innovation with occupational risk management across complex energy infrastructures undergoing digital transformation.
With the accelerated construction of new power systems dominated by new energy, the traditional equipment management model centered on “fault repair” and “regular maintenance” is no longer able to meet the high reliability, high flexibility, and high resilience requirements of power grid operation. This article propose...
Meng-Hua Huang· International Conference on...· 0 citations
This paper assesses the value-add of AI in safety performance by deeply integrating advanced industrial safety engineering risk analysis methodologies, including Hazard Identification and Risk Assessment (HIRA), Fault Tree Analysis (FTA), and Failure Mode and Effects Analysis (FMEA).
Shruti Pawar and Dr Neeta Banger· International Journal of Adv...· 0 citations
This study presents an advanced safety management framework for “Wave Energy Converter” (WEC) projects, addressing the inherent uncertainty, technological complexity, and environmental exposure of offshore renewable energy systems. By collaborating “Failure Modes and Effects Analysis” (FMEA) and “Hazard and Operabili...
Panagiotis K. Marhavilas, Konstantinos Douitsis, Nick Delianidis et al.· Safety Science and Technolog...· 0 citations
Driven by the "dual carbon" goals, a new power system with new energy as the mainstay is accelerating its evolution. Its "dual high" characteristics and source-load uncertainties pose unprecedented systemic risk challenges to the safe operation of the power grid. Traditional equipment risk management models, which are...
Meng-Hua Huang· International Conference on...· 0 citations
A hierarchical, CPS-specific structure of resilience domains spanning safety, engineering, organisational, governance and contextual attributes is defined, and a domain-attributed trajectory model is developed that maps each domain to the phase of disturbance it dominantly shapes and to the corresponding NIST cyber res...
K. Perrett, I. D. Wilson· Environment Systems and Deci...· 0 citations
A systematic risk minimization framework that integrates proactive and reactive measures: from the deployment of specialized intrusion detection systems (IDS) optimized for industrial control protocols to the implementation of adaptive load management algorithms that mitigate the effects of malicious demand-side manipu...
B. Pokhodenko· Information Technologies and...· 0 citations
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