The Prediction of Electrical Vehicles' Growth Rate and Management of Electrical Energy Demand in Turkey

Yılmaz, Musa

doi:10.1109/greentech.2017.23

Cited by 5 publications

(2 citation statements)

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“…Accurate forecasting of the active power from a wind turbine is critical for analyzing the energy demand [1], efficiency [2], and economic sustainability [3] of wind power plants. These forecasts are used to meet energy demand and reduce energy costs by influencing the structure of the energy grid [4]. Furthermore, the design and maintenance of wind turbines also rely on the predictions.…”

Section: Introductionmentioning

confidence: 99%

Multilayer LSTM Model for Wind Power Estimation in the Scada System

ÇELEBİ,

KARAMAN

2023

EJT

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Wind energy is clean energy that does not pollute the environment. However, the complex and variable operating environment of a wind turbine often makes it difficult to predict the instantaneous active power generated. In this study, a wind turbine active power estimation system based on a short-term memory network (LSTM) using time series analysis is proposed. The data obtained from the wind turbine SCADA system is used as input variables. In the proposed method, a multilayer LSTM architecture is designed to train the model. The first LSTM network consists of 64 units, and the second one consists of 32 units. This is followed by a dense layer consisting of 16 neurons. In the last layer, the architecture is finalized by using a linear activation function for the prediction process. The proposed deep learning (DL)-based LSTM prediction model takes into account environmental factors such as wind speed and wind direction for active power forecasting. The results show that the LSTM-based time series analysis method is capable of effectively capturing time series features among the data. Thus, the proposed architecture can realize high-accuracy active power forecasting.

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Section: Introductionmentioning

confidence: 99%

Multilayer LSTM Model for Wind Power Estimation in the Scada System

ÇELEBİ,

KARAMAN

2023

EJT

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“…These cars emit no emissions whatsoever. Pure battery EVs currently hold much of the market share for EVs and have earned their place as mainstream models [5,6]. This is due to the ongoing development of new battery technologies, the rapid construction of charging facilities, and people's pursuit of low-carbon travel in recent years.…”

Section: Introductionmentioning

confidence: 99%

Turkey’s Domestic Car TOGG in the Framework of New Trends in Electric Vehicles and Consumer Ethnocentrism

ŞENYAPAR

Tür

2023

Balkan Journal of Electrical and Computer Engineering

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Rising energy demands, and technological requirements are causing the world to focus more and more on Electric Vehicles (EVs). Developing technologies for these needs accelerate the development of smart and sustainable transportation and builds smart cities of the future. In this context, Turkey’s Automobile Enterprise Group, known as TOGG, was established in Turkey in 2018 with six partners and joined the EV market. In this study, new trends and emerging EV technologies such as wireless charging, smart power distribution, vehicle-to-home and vehicle-to-grid systems, connected vehicles, and autonomous driving for EVs are compared with TOGG technology; and its potential effects on the market are evaluated within the framework of consumer ethnocentrism. It also provides perspectives and recommendations for future smart transportation to serve as a guide for the future technological development and commercialization of EVs

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