This study assesses the reliability of a proposed 50 MW wind farm in Zuwara, Libya, under variable wind conditions. A 10-year wind dataset comprising 3,652 daily observations was obtained from the NASA POWER database to characterize the site wind resource. Several probability distributions were evaluated, and the Johnson SB distribution was selected based on goodness-of-fit using the Kolmogorov–Smirnov (KS) test. The resulting wind-speed model was integrated with the power characteristics of a 50-turbine wind farm, each rated at 1 MW. Monte Carlo simulation was applied to represent wind-generation variability and evaluate its effect on generation adequacy under different demand levels. Using the Resistance–Load (R–L) approach, loss-of-load conditions were identified when available wind generation was insufficient to meet the considered demand. The results show that the estimated failure probability was approximately 88.39% for a 32-MW demand and 92.99% for a 38-MW demand. Increasing the number of simulation trials reduced the statistical error and improved the stability of the estimates. The findings demonstrate the strong influence of wind variability and demand level on the reliability contribution of the proposed wind farm and highlight the need for complementary resources to improve supply adequacy.

Peak electricity demand presents a continuing challenge to power-system operation in Libya, particularly during periods of high ambient temperature. This study examines a proposed 60-MW above-ground Compressed Air Energy Storage (CAES) system intended to provide short-duration peak-power support for the GT12 gas turbine at the West Tripoli Gas Power Plant. The proposed discharge duration is 15 minutes. The assessment draws on plant operating data collected on June 2–3, 2024, and on a validated thermodynamic model used to evaluate compressor and turbine performance. The analysis considers mass-flow rate, heat input, net power output, and the sizing of the compressed-air storage system. The results demonstrate that the proposed CAES system increases the available peak power from approximately 100 MW to 135 MW by completely offsetting the compressor work. Despite an increase in fuel consumption required to compensate for the lower temperature of the injected stored air, the system achieves a significant enhancement in net electrical power output compared to the baseline. Furthermore, the proposed modular above-ground storage configuration, utilizing an array of thirty 40-bar industrialtanks, demonstrates practical feasibility for regions lacking suitable underground geological formations. The study confirms that integrating CAES with existing gas turbine plants represents a practical solution for improving grid reliability and operational flexibility .

This paper analyses the performance and environmental impacts of gas turbine plants operating on diesel and natural gas. It provides a comprehensive assessment of how varying ambient temperatures and fuel type affect gas turbine operation and pollutant emissions. This is done under identical turbine inlet temperatures and net power to eliminate their effects and to enable a clearer comparison. Based on a case study of the Tripoli West 167 MW simple-cycle power plant, a thermodynamic model developed in Excel is used to simulate GT performance. Results indicate that as ambient temperature changes, net exergy destruction is primarily influenced by the exergy destruction changes in the turbine (~45%) and the compressor (~40%), although the combustor is responsible for over 80% of the net destruction in the cycle. The results also highlight the relationships between specific fuel consumption, net thermal efficiency, and pollutant emissions. For every 10 °C rise in ambient temperature, the net thermal efficiency declines by 1.55% and 1.5%, the specific fuel consumption rises by 1.57% and 1.52%, and pollutant emissions rise by 1.58% and 1.53% for diesel and natural gas, respectively. This may link the changes in net thermal efficiency and pollutant emissions to the specific fuel consumption. Switching from diesel to natural gas significantly reduces net exergy destruction (~73%), attributed to reduced combustor exergy destruction, and boosts overall thermal efficiency by about 1%. Switching to natural gas also reduces CO2 emissions by (~24%) due to a lower carbon-to-hydrogen ratio (~15.2%) and lower fuel consumption (~10.2%). The emission factors determined by this study are 3.082 kg CO2/kg fuel for diesel and 2.612 kg CO2/kg fuel for natural gas. The change in emission factor between diesel and natural gas is similar to the change in carbon-to-hydrogen ratio between the two fuels (~15.2%). This relates the CO2 emission factor to fuel chemistry. The findings suggest that using natural gas is preferable, especially in warmer months. 

The Man-Made River (MMR) in Libya is one of the world’s largest water transfer systems, yet it consumes vast amounts of electricity to deliver water across long distances. This research addresses the challenge of energy demand by exploring the recovery of hydraulic energy that is normally wasted as pressure losses within the MMR pipelines. A hydraulic model of the pipeline was developed using EPANET, with actual design data serving as input. Four operational scenarios were evaluated (1.2, 1.3, 2.0, and 2.5 MCMD), and the results were analyzed to estimate recoverable energy and identify suitable turbine types. The methodology included simulation of head and pressure distributions, energy recovery calculations, and comparison with the system’s electricity consumption. The study found that at current operating flows (1.2–1.3 MCMD), turbines could recover between 686 and 733 MWh/day, meeting nearly half of the system’s electricity demand. At the original design capacity of 2.0 MCMD, recovery declined to about 610 MWh/day, while at 2.5 MCMD the net gain dropped to only 117 MWh/day due to pumping requirements. Francis turbines were identified as the most practical technology, with Pelton turbines as secondary options in high-head conditions. The research demonstrates that hydropower recovery from the MMR is technically feasible and environmentally beneficial. It could substantially reduce CO₂ emissions and strengthen Libya’s energy security by integrating renewable power directly into the national grid.

The examination of the flow instability is crucial in nuclear reactors to prevent the occurrence of flow excursion during a postulated accident. Instabilities can reduce the safety margins against these critical heat flux phenomena, where the fuel cladding surface temperature increases dramatically. In this paper, flow instability is investigated at the reactor of Tajoura Nuclear Research Centre with low enriched uranium (LEU) core, the recent reactor’s fuel assembly type is IRT-4M. The flow instability is assessed at the hottest cell of the reactor by implementing PLTEMP/ANL code.

The safety margin to flow instability is evaluated at the maximum power of the reactor (9.7 MW) by running the code at various core flow rates to find the point where FIR equals 1. The inlet coolant temperature is 45°C, the core pressure drop is 0.066 MPa, and the inlet pressure is 0.179 MPa. At the beginning, the calculations have been obtained at the flow rate of 8.1 kg/s. The results show that the maximum cladding surface temperature is 96.971°C which is less than the permissible value (102°C), the minimum FIR, ONBR, and DNBR equals to 2.034, 1.559, and 4.147, respectively. By reducing the core flow rate at the maximum power level, it is determined that FIR equals to 1.0 at the flow rate of 3.976 kg/s. Which means that the safety margin value to flow instability is 2.038. It is concluded from the safety margin value to flow instability that it is in agreement with the thermal-hydraulic safety requirements of TNRC’s reactor. 

Accurate wind speed modeling is essential for reliable wind resource assessment and wind farm planning. Although the Weibull distribution is widely used in wind energy studies, its accuracy may vary depending on regional climatic characteristics. This study evaluates the suitability of the Weibull distribution for modeling wind speed data in Libya and compares its performance with several alternative probability distributions. The analysis is based on 7,305 daily wind speed observations obtained from the NASA POWER database for the period 2004–2023 at a reference height of 50 m above Sea level for five locations in Libya: Tripoli, Ajdabiyah, Alkufra, Awbari, and Darnah. The mean wind speeds range from 6.419 m/s in Tripoli to 7.270 m/s in Darnah. Statistical analysis was performed using EasyFit and MATLAB, while the Kolmogorov–Smirnov (K–S) test was applied to evaluate the goodness of fit between observed and theoretical distributions. The results show that the Weibull distribution does not provide the best statistical representation for any of the studied locations. Instead, Johnson SB, Dagum (4P), and Burr distributions demonstrated superior performance. The estimated wind power density ranged from 52.57 W/m² in Tripoli to 78.97 W/m² in Darnah, highlighting the importance of flexible multi-parameter distributions for improving wind resource assessment and supporting more reliable wind farm planning in Libya.

This study aims to identify solutions for the early failure of roads in Libya due to the lack of a pavement management system and an effective load weighing system. The coastal highway in the city of Misrata was taken as a case study, which has high traffic volumes, especially heavy vehicles. The companies involved in the road's reconstruction provided data on average yearly temperatures and the physical properties of the construction materials, This included the modulus of elasticity and Poisson's ratio for both the asphalt mix and the soil used, The design for traffic volumes was based on ESALs reaching 24 M.S.A which is the calculated value for this road. , the ESALS were increased by 5 M.S.A and designed by using  PerRoad program, for perpetual pavement method, and the mechanical experimental method. After the design, both methodologies were compared, and the effect of increasing the number of axles and ESALs on the thickness of the asphalt layers was studied, The results showed that the design of this road using the perpetual pavement method is not affected by the increase in the number of axles and ESALs, which is suitable for achieving a design life of up to 50 years without being affected by the increase in ESALs. The asphalt layers were 25cm thick, while the subgrade layer was 20 cm thick, On the other hand, the mechanical experimental showed a clear impact from the increase in the number of axles and ESALs, as the thickness of the asphalt layer increased from 19 cm to 28 cm, and the thickness of the subgrade layer increased from 30 cm to 40 cm. This design achieves a lifespan of 20 years. The study also indicated that for designs with 15 M.S.A and above, the traditional design is considered over-designed, and the use of permanent pavement is preferred. As for the design of this road, the permanent pavement method was adopted

Gas flaring is a major source of carbon dioxide (CO2) emissions in oil-producing countries and remains an acute environmental challenge in Libya. The country’s instability has repeatedly disrupted oil and gas operations, leading to highly volatile flaring behavior and complicating long-term mitigation efforts. This study applies time-series forecasting to model and project per-capita CO2 emissions from gas flaring in Libya using two forecasting frameworks: Exponential Smoothing with additive trend (ETS) and an Autoregressive Integrated Moving Average (ARIMA) model, based on annual data from 1967 to 2024. Comparative model evaluation shows that ARIMA outperforms ETS, achieving a root mean squared error of 0.373 and a mean absolute error of 0.327, compared to 0.406 and 0.367 for ETS. Baseline ARIMA forecasts project emissions of 1.27tCO2 capita −1 by 2030, remaining well above the near-zero flaring threshold of approximately approximately 0.05tCO2 capita −1. Scenario analysis shows that attaining this target would require an average annual reduction of approximately 44% starting from 2024, far exceeding historical reduction rates observed during 1967-2024. These results indicate that, under current trends, Libya is unlikely to achieve zero routine flaring by 2030 without substantial structural, infrastructural, and regulatory intervention.

The reliable operation of power plants is essential for the continuity of modern societies. The South Tripoli Power Plant in Libya plays a crucial role within the national power grid. However, it faces significant challenges, including frequent operational failures, aging infrastructure, and ineffective maintenance practices, all of which compromise its reliability and escalate operational costs. This research is motivated by the urgent need to improve maintenance strategies in accordance with documented failure patterns, thereby establishing a comprehensive framework for effective maintenance planning. To address these challenges, a maintenance optimization framework has been developed that integrates Failure Modes, Effects, and Criticality Analysis (FMECA) with Fuzzy Logic techniques to enhance decision making processes regarding maintenance. Furthermore, a fuzzy FMECA framework has been designed to categorize maintenance strategies, thereby facilitating data driven maintenance planning. The contributions of this research are aimed at improving plant reliability, reducing the incidence of unplanned outages, and ensuring the sustainable performance of energy infrastructure.