Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Conference Object Citation - WoS: 1Citation - Scopus: 8Short Term Electricity Load Forecasting: A Case Study of Electric Utility Market in Turkey(Institute of Electrical and Electronics Engineers Inc., 2015-04) Ishik, Muhammed Yasin; Göze, Tolga; Ozcan, Ihsan; Güngör, Vehbi Çağrı; Aydin, Zafer; Yasin, MuhammedWith the recent developments in energy sector, the pricing of electricity is now governed by the spot market where a variety of market mechanisms are effective. After the new legislation of market liberalization in Turkey, competition-based on hourly price has received a growing interest in the energy market, which necessitated generators and electric utility companies to add new dimensions to their scope of operation: short-term load and price forecasting. The field has several opportunities though not free from challenges. The dynamic behavior of the market price has caused the electric load to become variable and non-stationary. Furthermore, the number of nodes, in which the load must be predicted, is not constant anymore and can no longer be estimated by experts alone. In this competitive scenario, statistical forecasting methods that can automatically and accurately process thousands of data samples are essential. The purpose of this study is to demonstrate the importance of short-term load forecasting, how it has received a growing interest in Turkey and to propose an artificial neural network that can forecast the short term electricity load. Through detailed performance evaluations, we demonstrate that our forecasting method is capable of predicting the hourly load accurately. © 2017 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 10Security and Privacy Challenges, Solutions, and Open Issues in Smart Metering: A Review(Institute of Electrical and Electronics Engineers Inc., 2021-09-15) Win, Lae Lae; Tonyali, SametThe traditional power grid becomes ‘smart’ when it is combined with the communication and information technology. Along with smart grid, the traditional meter is replaced with smart meter. Smart meters play an important role in energy consumption reporting and, thereby, billing. Besides smart meters, the smart grid communication network is composed of heterogeneous devices that are communicating through public networks. Therefore, smart metering communications are susceptible to cyber-attacks and privacy breaches which are still under debating. This paper gives a brief overview of smart grid, smart metering, and the communication networks. Then, the privacy and security requirements of the smart grid network are derived. The various kind of cyber-attacks are discussed, after that, the different schemes and approaches that have been proposed in previous papers are reviewed. Lastly, the open issues on security and privacy of smart grid metering communications are highlighted. © 2022 Elsevier B.V., All rights reserved.Conference Object Citation - WoS: 1Performance Evaluations of Next Generation Networks for Smart Grid Applications(Institute of Electrical and Electronics Engineers Inc., 2015-04) Tuna, Gürkan; Ayana, Esra Kaya; Gülez, Kayhan; Kiokes, George C.; Güngör, Vehbi Çağrı; Kaya, EsraSmart Grid (SG) can be described as the concept of modernizing the traditional electrical grid. Through the addition of SG technologies traditional electrical grids become more flexible, robust and interactive, and are able to provide real time feedback by employing innovative services and products together with communication, control, intelligent monitoring, and self-healing technologies. For being fully functional, utility operators deploy various SG applications to handle the key requirements including delivery optimization, demand optimization and asset optimization needs. The SG applications can be categorized into two main classes: grid-focused applications and customer-focused applications. Although these applications differ in terms of security, Quality of Service (QoS) and reliability, their common requirement is a communication infrastructure. In this paper, we focus on the use of Next Generation Networks (NGNs) for SG applications. We also present a detailed analysis of a NGN-based communication infrastructure for SG applications in terms of global network statistics and node-level statistics. © 2018 Elsevier B.V., All rights reserved.Conference Object Citation - WoS: 7Citation - Scopus: 10PI-Controlled ANN-Based Energy Consumption Forecasting for Smart Grids(SciTePress, 2015) Gezer, Gülsüm; Tuna, Gürkan; Κogias, DImitrios G.; Gülez, Kayhan; Güngör, Vehbi Çağrı; Kogias, DimitrisAlthough 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 Next Generation Networks for Telecommunications Operators Providing Services to Transnational Smart Grid Operators(SciTePress, 2015) Tuna, Gürkan; Kiokes, George C.; Zountouridou, Erietta I.; Güngör, Vehbi ÇağrıDue to the networking expertise, services and technical support of telecommunications operators, Smart Grid (SG) operators prefer telecommunications operators for their communications needs instead of creating private networks. In this paper, the use of Next Generation Networks (NGNs) by telecommunications operators to provide services to transnational SG operators for SG applications is evaluated. NGNs are all IP networks which are packet based and use IP to transport the various types of traffic such as data, voice, video, and signalling over converged fixed and mobile networks. The main idea of transnational SG operators is simple. By creating a huge single infrastructure for energy, more than one countries and nations can be powered at once. For this, it is not needed to install very huge power plants. Simply creating a complex network of power grid connections to each participating country is enough. The results of a set of simulation studies are given to show the efficiency of the NGN-based communication infrastructure for SG applications in terms of important network performance metrics. The results show that NGN-based communication infrastructures can carry packets based on their priority levels and bandwidth allocations in order to meet the specific requirements of SG applications. © 2022 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 1Is 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.Book Part Cognitive Radio Networks for Smart Grid Communications: Potential Applications, Protocols, and Research Challenges(CRC Press, 2017-12-19) Κogias, DImitrios G.; Tuna, Gürkan; Güngör, Vehbi ÇağrıA smart grid (SG) is the next generation of power grid, where transmission, distribution, power generation, utilization, and management are fully upgraded to improve efficiency, agility, environmental friendliness, economy, security, and reliability [1-4]. It offers two-way communication between the base stations and power generation sites [2-5], and optimizes the overall system performance by taking the advantage of wireless sensor networks (WSNs) [6-13], using smart sensor devices, and implementing renewable energy solutions. Since SG consists of many different applications with different communication and quality of service (QoS) requirements, it involves heterogeneous communication technologies based on a multitier communication infrastructure. © 2019 Elsevier B.V., All rights reserved.Conference Object Citation - WoS: 7Citation - Scopus: 12Ambient Energy Harvesting for Low Powered Wireless Sensor Network Based Smart Grid Applications(Institute of Electrical and Electronics Engineers Inc., 2019-04) Faheem, Muhammed Yasir; Ashraf, Muhammad Waqar; Butt, Rizwan Aslam; Raza, Basit; Ngadi, M. A.; Güngör, Vehbi ÇağrıLimited battery lifetime is one of the most critical issues for wireless sensor networks (WSNs)-based smart grid (SG) applications. Recently, ambient energy harvesting (AEH) has been considered to significantly improve the network lifetime of the WSNs-based SG applications. However, extracting a significant amount of energy from the ambient energy resource due to time varying links quality affected by power grid environments is the main issue for WSNs-based applications in SG. In this paper, we propose a novel multi-source energy harvesting mechanisms for WSNs-based SG applications. The propose hybrid ambient energy harvesting framework through the designed circuitry successfully harvests massive power density by capturing the radial electric field (EF) and ambient radio frequency WiFi 2.4GHz band signals present in the vicinity of 500kV power grid station. The design energy harvesting schemes have been implemented on the recently developed routing protocol for SG applications. The experiments using EstiNet9.0, demonstrate that the designed framework is efficient in terms of energy harvesting capabilities to enable a long-lasting lifetime of the WSNs-based smart grid applications. © 2020 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 19A Novel Feature Design and Stacking Approach for Non-Technical Electricity Loss Detection(Institute of Electrical and Electronics Engineers Inc., 2018-05) Aydin, Zafer; Güngör, Vehbi ÇağrıNon-technical electricity losses continue to jeopardize economic and social well-being of many countries. In this work, we develop machine learning classifiers that can identify anomalous electricity consumption in Turkey. Starting from weekly electricity usage data, we develop new features that capture statistical and frequency domain characteristics of the customers and their consumption patterns. We analyze the effect of reducing number of feature descriptors through dimensionality reduction and feature selection techniques. To overcome the class imbalance problem, we implement several ensemble methods and compare their prediction accuracy to those of the standard classifiers. The proposed features and combining strengths of different classifiers bring significant improvements on performance metrics, which is demonstrated through detailed simulations on shopping mall sector. We anticipate that advances in this field will contribute to the economies considerably. © 2018 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 29A Hybrid Energy Harvesting Framework for Energy Efficiency in Wireless Sensor Networks Based Smart Grid Applications(Institute of Electrical and Electronics Engineers Inc., 2018-06) Yildiz, Huseyin Ugur; Güngör, Vehbi Çağrı; Tavli, BülentIn smart grid applications, Wireless Sensor Net-works (WSNs) which consist of battery limited sensor nodes are used on critical equipments of power distribution grids for monitoring purposes. WSN nodes have tight energy constraints hence it is important to reduce the energy consumption of sensor nodes due to harsh propagation characteristics of smart grid environment. One possible way to reduce the energy consumption is to utilize transmission power control where transmission powers are adjusted according to channel conditions. Another technique is to employ energy harvesting schemes to provide additional power for nodes by using environmental energy sources. Solar and electromagnetic energies are two possible environmental energy sources in outdoor substation environments. Solar energy can be efficiently exploited in a sunny day. On the other hand, electromagnetic energy can be used at any time. In this work, we propose a hybrid energy harvesting model that exploits both solar and electromagnetic energies and develop a Mixed Integer Programming (MIP) method to minimize the energy dissipation of sensor nodes. By using the MIP framework, we quantify the impact of the proposed hybrid energy harvesting model as well as transmission power control on the energy saving of nodes. © 2018 Elsevier B.V., All rights reserved.