Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleAçık Erişim2023Design and implementation of a real-time demonstration setup for dynamic highway tunnel lighting control research studies
Çakmak, Recep; Dündar, Ayhan
This study presents the design and implementation of a computer-based real-time demonstration setup for dynamic highway tunnel lighting control research studies. The energy-efficient and controllable lighting systems stand out worldwide because of energy efficiency objectives and carbon footprint reduction goals of the countries. An LED (Light Emitting Diode) armature-based highway lighting systems are frequently utilized in recent years due to lighting efficiency, energy efficiency, long life, environmentally and cost-friendly structure of the LEDs as well as zero ultraviolet emissions of them. In this study, the LED-based dynamic tunnel lighting control approach has been implemented through the proposed demonstration setup which is a typical real-time software-controlled hardware. The parts of the proposed demonstration setup have been introduced and detailed to help with some upgrade studies in the future. The demonstration setup has been tested in some case studies, then the obtained results have been discussed and introduced. In the future, the proposed system can be upgraded and utilized for advanced control studies thanks to its computer-based and simulation environment connection capability.
- MakaleYalnız künye2020A novel billing approach for fair and effective demand side management: Appliance level billing (AppLeBill)
Çakmak, Recep; Altaş, İsmail Hakkı
Demand side management (DSM) is an important part of smart electrical grid studies due to high energy efficiency it provides. Effective DSM techniques are hinged on participation level of the customers and control manner of their loads so if there is no fair and appropriate management, customers will not embrace demand side management applications. Besides, the customers might not participate to the demand response process willingly if their comforts are not considered. Therefore, the DSM systems must consider fairness and customer's comfort as well as distribution system objectives. Multifarious DSM systems have been proposed in the literature, however, the fair billing has not included as a parameter in most of these studies. This paper introduces a novel billing approach based upon appliance level billing (AppLeBill) for fair and effective demand side management. The proposed AppLeBill idea offers a billing strategy such that time-shiftable appliances (TSAs) in a residence may have a separate billing rate rather than a single billing rate for total electricity usage. The proposed AppLeBill concept includes three different schemes which are explained and simulated in order to compare each other in terms of their potential benefits.
- BildiriYalnız künye2020A fuzzy decision maker to determine optimal starting time of shiftable loads in the smart grids
Altaş, Ismail Hakkı; Çakmak, Recep
Smart grid studies have been increased tremendously for past ten years in order to modernise and solve problems of current electrical grids. One of the aim of the smart grids is to react autonomously to the problems in electrical networks by means of artificial intelligence and decision maker. Fuzzy logic-based embedded control systems simulate human thoughts and decision making processes. So, fuzzy logic and fuzzy decision makers can be utilised in smart grids for automated system management. In this paper, a fuzzy decision maker has been proposed to manage time-shiftable loads in residences. The proposed fuzzy decision maker determines optimal starting time of time-shiftable loads in residential areas in order to provide balanced power curve and decrease peak load consumptions by scheduling the loads. Design stage of the proposed fuzzy decision maker have been introduced and presented clearly. Finally, a design example has been given to show the decision results.
- MakaleYalnız künye2019Forecasting of Turkey’s monthly electricity demand by seasonal artificial neural network
Hamzaçebi, Coşkun; Es, Hüseyin Avni; Çakmak, Recep
Electricity is one of the most important end-user energy types in today’s world and has an effective role in development of societies and economies. Stability of electricity supply is provided by matching of generated and consumed electricity amount during the all-day. So, electricity consumption forecasting is an essential issue for electric utilities. In this study, the monthly electricity demand of Turkey has been predicted. To model the effects of seasonality and trend, four different ANN models have been developed and selected the superior one. In addition, the selected ANN model has been compared with SARIMA model in order to increase the acceptability and reliability of the ANN model. The monthly electricity demand of Turkey has been predicted between 2015 and 2018 via the ANN model that can make successful and high-accuracy predictions according to the performance measures. The forecasting values will help in determining the medium-term and stable energy policies.
- BildiriYalnız künye2018Hourly Solar Irradiation Prediction by Artificial Neural Network Based on Similarity Analysis of Time Series
Ulutas, Ahsen; Çakmak, Recep; Altas, Ismail Hakki; Ozyildirim, BM; Yildirim, T
Solar energy is a renewable energy source which has intermittent and variable characteristic. Solar irradiation must be predicted in advance in an electrical grid which has solar energy based electrical power generation systems in order to operate the electrical grid stable and efficient. In this study, a multi-layered, feed forward artificial neural network (ANN) has been designed to predict the hourly solar irradiation of next day. The designed ANN has been trained by data which has been obtained via similarity analysis. Total solar irradiation on horizontal plane, relative humidity and temperature data of Trabzon province for 2015-2017 have been used as the training data set. Hourly solar irradiation prediction has been performed by utilizing the designed ANN and test data set. The prediction results have been evaluated as to root mean square (RMS), mean absolute error (MAE) and mean absolute percentage error (MAPE) performance criteria. The obtained performance criteria results show that the proposed ANN could make prediction with acceptable error.
- BildiriYalnız künye2017A Day Ahead Hourly Solar Radiation Forecasting by Artificial Neural Networks: A Case Study for Trabzon Province
Çevik, Sibel; Çakmak, Recep; Altas, Ismail Hakk
The integration of renewable energy sources to the electrical grid leads to some issues in the grid because of intermittent and variable characteristics of renewable energy sources such as wind and solar. It has been predicted that the solar based electricity production will has highest annual increase rate among the other renewable sources. Due to the intermittent and volatile nature of the solar energy in an electricity grid where photovoltaic systems are intensive, load planning is essential. Therefore, day ahead solar radiation forecasting will contribute to the load planning studies. Artificial neural networks are one of the methods that are applied frequently and successfully in forecasting studies. In this study, a cause effect based artificial neural network (ANN) has been designed and performed for day ahead hourly solar radiation forecasting in Trabzon province. A similar day selection algorithm has been utilized to get more accurate forecasting by the ANN. The designed ANN has been trained and tested in MATLAB simulation environment without using ready codes of MATLAB ANN toolbox. The obtained results reveal that the designed ANN forecasts the solar radiation with acceptable error for a place such as Trabzon which has rainy and cloudy weather conditions.
- BildiriYalnız künye2017A day ahead hourly solar radiation forecasting by artificial neural networks: A case study for Trabzon province; [Yapay Sinir Aǧlari ile Gün Öncesi Saatlik Güneş Radyasyonu Tahmini: Trabzon İli Örneǧi]
Çevik, Sibel; Çakmak, Recep; Altaş, Ismail Hakki
The integration of renewable energy sources to the electrical grid leads to some issues in the grid because of intermittent and variable characteristics of renewable energy sources such as wind and solar. It has been predicted that the solar based electricity production will has highest annual increase rate among the other renewable sources. Due to the intermittent and volatile nature of the solar energy in an electricity grid where photovoltaic systems are intensive, load planning is essential. Therefore, day ahead solar radiation forecasting will contribute to the load planning studies. Artificial neural networks are one of the methods that are applied frequently and successfully in forecasting studies. In this study, a cause effect based artificial neural network (ANN) has been designed and performed for day ahead hourly solar radiation forecasting in Trabzon province. A similar day selection algorithm has been utilized to get more accurate forecasting by the ANN. The designed ANN has been trained and tested in MATLAB simulation environment without using ready codes of MATLAB ANN toolbox. The obtained results reveal that the designed ANN forecasts the solar radiation with acceptable error for a place such as Trabzon which has rainy and cloudy weather conditions.
- BildiriYalnız künye2016Solar Energy Potential of Eastern Black Sea Region of Turkey: A Case Study for Trabzon Province
Çakmak, Recep; Altas, Ismail Hakki
In electricity generation, there is a tendency towards renewable energy sources in order to supply the increased electricity demand and in an effort to generate electricity with less environmental damages. The Sun is a significant renewable energy source and photovoltaic (PV) panels are one of the most commonly used systems in electricity generation by utilizing solar energy. Germany is the leader country in the world in terms of installed PV watt per capita. In this paper, potential of electricity generation by utilizing solar energy in Trabzon Province has been studied and compared with that of Germany. Solar energy data of Trabzon Province, which is provided from four different sources, have been presented and amount of electricity power that can be generated by PV systems in Trabzon Province have been given. By presenting the PV power plant examples from Germany, the quantity of electricity that can be generated in case of the same systems installed in Trabzon Province have been given. By analyzing the obtained data, it is aimed to create awareness about the potential of electricity generation from solar energy in Province of Trabzon in Turkey and to subvert prejudices about the solar energy potential in Eastern Black Sea Region of Turkey.