Development of a Multifactor Model for Determining Energy Costs at a Compressor Station Pryazovskyi State Technical University

Format:

Book

Conference/Event

Author/Creator:

Volodarets, Mykyta, author.

Contributor:

Ahieiev, Maksym

Belousov, Evgen

Gritsuk, Igor

Litikova, Oleksandra

Nosov, Pavlo

Pohorletskyi, Dmytro

Satsiuk, Aleksandr

Sumtsov, Andrii

Tkachuk, Kateryna

Conference Name:

Automotive Technical Papers (2022-01-01 : Warrendale, Pennsylvania, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2022

Summary:

It is a known fact that the existing compressor stations on the sorting humps of the railways have significant overconsumption of electricity. First, this is due to the lack of automatic regulation of the compressed air capacity, which takes into account the technological processes at the station and the weather conditions within this section. In order to solve this problem, as a first approximation, it is necessary to analyze all the factors affecting the energy consumption of the compressor station and develop a mathematical model, which will link these indicators. In this work, a correlation analysis of the weather-related factors and specifics of the technological process (breaking up of the train), which affect the energy consumption of the compressor unit (CU), is carried out. Based on the analysis, there was a strong correlation between the factors described and the power consumption at the station. A regression model was developed. The issue of the distribution of energy levels as the cut rolls down from the hump to the destination point is reviewed in detail. Borrowing the principles of air navigation, the analysis of the effect of air masses on a moving car is carried out. This made it possible to develop a predictive multifactorial mathematical model of the power consumption of the compressor plant depending on the type and weight-dimensional parameters of the rolling car and the peculiarities of the sorting hump elements operating in different weather conditions. This model makes it possible with a high probability to predict the cost of electricity for the disassembly of one train in order to supply a required level of system performance. This will reduce the economic costs of energy consumption due to the optimal efficiency management of the compressor stations through the implementation of variable frequency control systems. In addition, this model makes it possible to build a fully automatic system for regulating the efficiency of a CU, relying on the data of the full-scale sheet, which can be obtained from the automated control system for marshalling yards (ACS MY) and data received from meteorological stations. In this way, incorrect operator actions are eliminated. The proposed model has been tested on the example of an actual disassembly of a train. The obtained simulation results showed significant savings in electricity during the period of decoupling of the train

Notes:

Vendor supplied data

Publisher Number:

2022-01-5079

Access Restriction:

Restricted for use by site license