Energy, exergy, economic, environmental (4E) and frequency distribution analysis of train wind gust with real-time data for energy harvesting

Abstract

Abstract The wind gust velocity of trains are above the cut in speed of wind turbines. Multiple cases studies estimate the available wind energy and potential electrical output with numerical and computational models. These gust velocities are dynamic nature. This work collects real time data of wind gust using data acquisition, conducted 4E and Weibull frequency distribution analysis. The acquired data is further used as a velocity signal to Simulink and wind emulator wind energy harvesting systems. This distinguishes in producing benchmarking results when compared with numerical and computational models. From data interpretation and analysis, the wind gust are non-uniform and gust velocity ranges from 2.3 to 7.1 m s−1 is recorded with a Weibull scale parameter value(A) of 5.54 m s−1. The maximum power available for harvesting is after considering Betz limit is 159.6 W, whilst Simulink and emulator energy harvesting systems produces 126.4 W and 123.08 W with a maximum exergy efficiency of 49.38 and 49.14%. The estimated wind energy available for 1KM range with wind energy systems on both side of traction poles is about 3.3 KW/KM. The compared environmental and economic analysis reconfirms the feasibility of the proposed model with capacity factor 5.74%. Other findings are the corresponding variation in output with respect to dynamic-wind velocities is limited due to inertia and stored kinetic energy of system, the role of location, weather statistics and influence of tail winds in shaping wind gust velocity is also adjudged as crucial factors.