The rapid adoption of electric vehicles (EVs) has increased the need for sustainable charging infrastructure supported by renewable energy. This study presents a comprehensive techno-economic and environmental analysis of private EV charging stations in Kuwait powered by grid-connected solar and wind systems using the HOMER Pro 3.18.4 optimization software. Four configurations—grid-only, grid–solar, grid–wind, and grid–solar–wind—were modelled and evaluated in terms of energy output, cost performance, and carbon emission reduction under Kuwait’s climatic conditions. HOMER simulated 484 systems, of which 244 were technically feasible. The optimal configuration, combining grid, 5 kW photovoltaic (PV) (BEIJIAYI 600 W panels), and a 5.1 kW AWS wind turbine, achieved a renewable fraction of 78%, reducing grid dependency by 78.1% and annual CO₂ emissions by approximately 7027 kg. Although the hybrid system required a higher initial investment (USD 7662) than the grid-only setup (USD 1765), it achieved the lowest Levelized Cost of Energy (LCOE = USD 0.017/kWh) and long-term cost competitiveness through reduced operating expenses. Sensitivity analysis confirmed the hybrid system’s robustness against ±15% variations in wind speed and ±10% changes in solar irradiance. The results highlight that hybrid solar–wind systems can effectively mitigate intermittency through diurnal complementarity, where daytime solar generation and nighttime wind activity ensure continuous supply. The findings demonstrate that integrating renewables into Kuwait’s EV charging infrastructure enhances economic viability, energy security, and environmental sustainability. The study provides practical insights to guide renewable policy development, pilot deployment, and smart grid integration under Kuwait Vision 2030’s clean-energy framework.

This study uses HOMER simulation software to present the optimization and economic analysis of a mobile solar charging station for Mini Electric Vehicles (MEVs) in Kuwait. The primary goal is to design a mobile solar charging station that serves rural areas lacking infrastructure, aligning with Kuwait’s Vision 2035 for sustainable energy and pollution reduction. MEVs have gained popularity in India, China, the Association of Southeast Asian Nations, and other countries. These vehicles are well suited for rapid transportation between classrooms, hospital transfers, and special events on a busy campus, as well as firefighting, ambulance, and medical assistance. The station is expected to produce approximately 15.2 kilowatt-hours per day, serving three vehicles with a 10-kW engine, each travelling 30 km/day. The system integrates solar photovoltaic panels with battery storage to create a self-sufficient charging station that can operate in remote areas. By comparing several system configurations using HOMER, this study identifies the most cost-effective design, considering factors such as energy production, battery autonomy, station weight, and installation area. The results highlight the potential of solar-powered MEV charging stations to support sustainable transportation in Kuwait, especially in regions with high solar radiation.

Accurate unit transportation cost estimates are important for pricing, budgeting, and fleet planning, but conclusions based on a single representative vehicle may be misleading when operating conditions vary across fleets, routes, operators, and years. This study develops a multi-source Kuwait framework that combines deterministic vehicle-level sensitivity analysis with independent truck, route, operator, and fleet evidence. One-at-a-time perturbations, sensitivity-index ranking, local elasticity, factorial stress tests, and fuel-price scenarios are applied to published freight-truck and passenger-bus cost cases. The principal contribution is a cross-resolution framework that links equation-level cost sensitivity with independently observed operational heterogeneity while preserving the analytical resolution of each dataset and avoiding inappropriate pooling of incompatible sources. In the vehicle-level sensitivity core, annual kilometers is the leading truck parameter (SI = 16.54%), followed by maintenance cost (6.18%) and driver/worker salary (5.67%), whereas bus occupancy rate (20.79%) and annual kilometers (16.45%) are dominant. As independent contextual evidence, historical Kuwait truck observations show mean transported loads of 2.0–5.0 t/truck, while KPTC route offered-capacity utilization ranges from 13.3% to 99.7%. The results show that productive activity and utilization strongly influence unit transportation cost, but their effects are context dependent. The framework therefore improves the practical interpretation and transferability of deterministic vehicle-level sensitivity results without overstating cross-source validation.

Used engine oil (UEO) is a hazardous waste stream that poses significant environmental risks when improperly managed. However, its high heating value makes it a promising candidate for energy recovery. In Kuwait, rising vehicle ownership has led to increasing quantities of UEO, while the power sector remains heavily dependent on conventional fossil fuels. Although extensive research has examined UEO treatment methods and combustion characteristics, limited attention has been given to its integration into utility-scale power-generation systems. This study presents a national-scale techno-economic and environmental assessment of using UEO as a supplementary fuel for electricity generation in Kuwait. East Doha Power Station was selected as a representative case study to evaluate fuel-substitution potential and the practicality of integrating UEO into existing power-generation infrastructure. Historical vehicle-registration data were used to estimate UEO generation, and future availability was projected through 2035 based on vehicle-growth trends. The corresponding thermal energy potential, equivalent electricity generation, fuel-displacement capacity, economic benefits, and environmental impacts were subsequently evaluated. The results indicate that annual UEO generation is projected to increase from approximately 181,800 tonnes/year in 2024 to 303,300 tonnes/year in 2035. This quantity corresponds to about 12,126 TJ/year of recoverable thermal energy and an equivalent electricity-generation potential of approximately 1.1 TWh/year (4000 TJ/year), assuming a power-plant efficiency of 33%. The recovered UEO could displace approximately 311,000 tonnes/year of heavy oil or 287,000 tonnes/year of crude oil, with estimated net annual fuel-cost savings of approximately 28–30 million KD. Based on literature-reported emission factors, UEO utilization could reduce combustion-related CO₂ emissions by up to 19.0% and NO_x emissions by up to 45.5% compared with heavy oil. Sensitivity analysis further confirmed the robustness of the findings under a range of recovery and operating conditions. To the best of the authors’ knowledge, this study represents the first comprehensive national-scale assessment of the potential use of UEO for utility-scale power generation in Kuwait. The findings indicate that UEO has the potential to serve as a strategic secondary energy resource that supports waste reduction, fuel conservation, economic savings, and circular-economy objectives. However, practical implementation will require appropriate collection and treatment infrastructure together with further technical validation, pilot-scale demonstration, and regulatory evaluation.

A reduced-order, mass- and energy-conserving combustion-capacity model was developed to represent premixed and mixing-controlled heat release in a direct-injection diesel engine. Unlike conventional reduced-order formulations that prescribe heat-release shape or correlate heat release directly with fitted functions, the proposed framework first determines the fuel mass physically capable of combustion from the simultaneous availability of injected fuel and stoichiometric air. Fuel prepared during the ignition-delay period forms a finite premixed reservoir that is consumed through an analytical depletion law. After the start of combustion, the remaining fuel and entrained air define a continuously evolving mixing-controlled combustion capacity consumed through a finite-rate formulation. Explicit fuel-allocation and conservation constraints prevent double-counting between the two combustion stages and limit cumulative heat release to the available fuel chemical energy. The model was evaluated using experimentally derived apparent heat-release-rate histories at six engine speeds from 1200 to 2200 rpm and brake torques of 150 and 200 N·m. The premixed combustion-rate coefficient was determined for each operating condition from the corresponding average fuel-injection pressure difference, while the mixing-controlled coefficient was maintained constant. Across the 12 operating conditions, the root-mean-square error (RMSE) ranged from 0.0055 to 0.0224 kJ/°CA, the mean absolute error (MAE) from 0.0032 to 0.0113 kJ/°CA, and R² from 0.446 to 0.968. The absolute peak heat-release-rate error remained below 3% for 10 of the 12 cases. The results demonstrate that the proposed framework reproduces the principal apparent heat-release characteristics while maintaining explicit separation and conservation of the premixed and mixing-controlled fuel reservoirs.