Showing posts with label load. Show all posts
Showing posts with label load. Show all posts

Saturday, 4 November 2023

Analysis of the External Forces Affecting the Tractor Trailer Lifting-Tipping Device | Chapter 6 | Advances and Challenges in Science and Technology Vol. 8

 The item discusses the movement of a lifting and tilting device for a worm trailer. The impact of outside loads on the device, estimation of the trailer's load volume and tilt angle, analysis of changes in their limits.

Author(s) Details:

Khakimzyanov R. R.,
Department of Automative and Manufacturing Engineering, Tashkent State Transport University, St. Temiryulchilar, Tashkent, 100167, Uzbekistan.

Shermukhamedov A. A.,
Higher Attestation Commission under the Cabinet of Ministers of the Republic of Uzbekistan, Tashkent 100047, Republic of Uzbekistan.

Please see the link here: https://stm.bookpi.org/ACST-V8/article/view/12360

Friday, 29 July 2022

Evaluation and Analysis of Least Square and Exponential Regression Techniques for Consumer Energy Consumption Requirement | Chapter 8 | Technological Innovation in Engineering Research Vol. 6

 

 The analysis of the load projection and energy consumption is the main objective of this work. For a twenty-year (20 years) prediction in the Nigerian power system, this study used the least-square regression and exponential regression models to predict long-term power consumption. The Matlab platform implementation of the model plots the residential load demand, business load demand, and industrial load demand. The results show that each generating station's output of energy, including the Sapele Thermal Power Station and the Egbin Thermal Power Station in Lagos, among others, is appallingly inadequate. The results also show a difference between the available power and the anticipated energy demand (MW) (or capacity allocated). Evidently, the least-square exhibits linear behavior, while the exponential exhibits non-linear behavior, in the comparison plot for the linear and exponential models, which show a similar pattern of prediction, the linear model delivers results that are more accurate than the exponential.

Author(s) Details:

S. L. Braide,
Department of Electrical/Computer Engineering, Rivers State University, Port Harcourt, Rivers State, Nigeria.

Please see the link here: https://stm.bookpi.org/TIER-V6/article/view/7605