Optimizing electrical power consumption in al khums, libya, through smart meters data simulation and analysis

The challenges facing Al Khums in the energy sector are significant, including aging infrastructure, frequent power outages, and heavy reliance on fossil fuels, exacerbated by political unrest and unreliable demand management in the energy sector. Accordingly, this study proposes smart meter technology as a model solution to address these challenges, improve electricity consumption, enhance grid reliability, and support renewable energy integration. This is achieved by simulating and analyzing smart meter data using modern techniques such as Python simulation. The research aims to achieve real-time monitoring capabilities, advanced analytics, and demand management strategies to address energy efficiency shortcomings in Al Khums. The research tools utilized Python-based simulations and data extracted from traditional electronic meters to simulate smart meter functions and then compare performance metrics such as load forecasting accuracy, anomaly detection, and energy loss reduction. The main findings concluded that smart meters enable accurate insights into consumption patterns, reduce technical and non-technical losses through rapid anomaly detection, improve load management, and identify peak demand periods associated with weather and seasonal temperatures. Additionally, smart meters facilitate dynamic pricing models and demand response programs, empowering consumers to adjust usage and lowering peak demand. The implementation of smart meters in Al Khums is shown to enhance grid stability, reduce carbon emissions, and align with Libya's renewable energy goals. However, challenges such as high initial costs, cybersecurity risks, and public awareness gaps require targeted interventions. Recommendations include pilot programs, regulatory frameworks for data privacy, and infrastructure upgrades to support bidirectional communication. This study contributes a localized framework for smart grid adoption in regions with similar socio-political and infrastructural constraints, emphasizing the role of data-driven solutions in achieving sustainable energy transitions. The results underscore the viability of smart metering as a cornerstone for modernizing Libya's energy sector, offering actionable strategies for policymakers and utilities to improve efficiency, equity, and environmental outcomes.