Akademik Veri Yönetim Sistemi
Tezin Türü: Yüksek Lisans
Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümü, Türkiye
Tezin Onay Tarihi: 2019
Tezin Dili: İngilizce
Öğrenci: Kübra Pehlivanoğlu Gürbüz
Danışman: OSMAN SEVAİOĞLU
Özet:Smart grid control purposes to rise the percentage of energy production through alternative energy sources like renewable resources and to make consumers to be comprehended in grid actively, is realising importance day by day. Further to that it can help us employment opportunities and improving growth in addition to keep the power on at minimum cost to prosumers, while the participation is elucidated and enabled new products, service and markets, accommodating all generation and storage options and provided the power quality for the range of requires in the 21st century economy by smart grid control. Some methods which are able to ensure the detection, isolation forecast have been developed for load forecasting in Smart Grid Control applications which In scientific research a lot of methods have been proposed to overcome load fluctuations. The purpose of this thesis is to specify the requirement of Smart Grid Technologies in load forecasting. Our objective is to build an accurate load forecasting model in Smart Grid Control for generating reasonable forecasting using previous decades load consumption data with Artificial Neural Network (ANN). The proposed smart grid load forecasting methodology provides an applicable option for developing the perfect balance among reliability, availability, efficiency and cost for Turkey. Present state of the system was simulated in MATLAB ANN tool and 11 years of data was used on distribution lines. In the scope of this thesis, some critical parameters are prescribed as effective parameters for load forecasting. It is seen that the system presented in this study is open to improvements and suggestions to make the system to be able to work confidentially.