Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

Browse

Filters

2015 - 20183

Settings

Publication Index: search.filters.publicationIndex.WoSSubject: search.filters.subject.Energy Utilization

Search Results

Now showing 1 - 3 of 3
  • Conference Object
    Citation - WoS: 3
    Citation - Scopus: 7
    Performance Analysis of Different Modulation Schemes for Underwater Acoustic Communications
    (Institute of Electrical and Electronics Engineers Inc., 2018-09) Bahcebasi, Akif; Güngör, Vehbi Çağrı; Tuna, Gürkan
    There is an increasing interest in using Underwater Acoustic Sensor Networks (UASNs) for various oceanographic applications, such as pollution monitoring, seismic monitoring, environmental data collection, offshore exploration, and tactical surveillance. UASNs rely on acoustic communications; however, the underwater acoustic channel is highly variable and its link quality depends on environmental factors and the locations of the communicating nodes. Therefore, ensuring reliable communication in UASNs is quite difficult. Moreover, path losses and retransmissions lead to the wastage of energy resources and reduce the network lifetime. In this study, we have utilized well-known underwater modulation schemes to analyse and simulate various underwater scenarios with different depth, distance and Bit Error Rate (BER) values in order to make a fair comparison between the modulation schemes and obtain the optimal transmission power. Performance evaluations show that 32-PSK and 16-QAM techniques achieve the minimum energy consumption rates and enhance network lifetime. © 2019 Elsevier B.V., All rights reserved.
  • Conference Object
    Citation - WoS: 7
    Citation - Scopus: 10
    PI-Controlled ANN-Based Energy Consumption Forecasting for Smart Grids
    (SciTePress, 2015) Gezer, Gülsüm; Tuna, Gürkan; Κogias, DImitrios G.; Gülez, Kayhan; Güngör, Vehbi Çağrı; Kogias, Dimitris
    Although Smart Grid (SG) transformation brings many advantages to electric utilities, the longstanding challenge for all them is to supply electricity at the lowest cost. In addition, currently, the electric utilities must comply with new expectations for their operations, and address new challenges such as energy efficiency regulations and guidelines, possibility of economic recessions, volatility of fuel prices, new user profiles and demands of regulators. In order to meet all these emerging economic and regulatory realities, the electric utilities operating SGs must be able to determine and meet load, implement new technologies that can effect energy sales and interact with their customers for their purchases of electricity. In this respect, load forecasting which has traditionally been done mostly at city or country level can address such issues vital to the electric utilities. In this paper, an artificial neural network based energy consumption forecasting system is proposed and the efficiency of the proposed system is shown with the results of a set of simulation studies. The proposed system can provide valuable inputs to smart grid applications. © 2022 Elsevier B.V., All rights reserved.
  • Conference Object
    Citation - Scopus: 1
    Is the Smart Grid a Good Investment
    (Institute of Electrical and Electronics Engineers Inc., 2015-04) Onen, Ahmet; Broadwater, Robert P.
    Electric distribution design and operational goals include meeting customer reliability requirements at the lowest cost. Smart Grid investments have the potential for helping meet these goals, and this paper presents a series of analyses that evaluate the incremental economic benefits of smart grid automation investments. Smart Grid investments provide a number of benefits to customers. Here only benefits that can be objectively quantified in terms of economic savings are considered. Smart Grid automation investments in this work include investments in feeder efficiency, automated switches, and coordinated control of capacitor banks, voltage regulators and load tab changers. Benefits that come from these investments are improved efficiency, reduced demand, shortened storm restoration time, and improved performance during reconfiguration events. The analyses used in the evaluation are very detailed, involving hourly, quasi-steady state power flow analysis over a ten year period for calculating energy consumption and costs, and Monte Carlo simulations for six different storm types. The evaluation shows that similar to other industries, an investment in automation can be justified in terms of hard dollars. © 2017 Elsevier B.V., All rights reserved.