Load curve classification for the evaluation of demand side management programs

Date

2016-09-25

Author

Yumak, K.
Tosun, G.
Varlik, B.
Bağrıyanık, Mustafa

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

231
views

0
downloads

The demand side management of electrical power systems is an issue of growing concern. In this study, annual load curves those have been obtained by field measurements on MV (31.5kV) feeders in an electricity distribution company in Turkey have been studied. Feeders supplying different type of customers (Agricultural irrigation, Commercial & Industrial and Residential) are classified through Peak and Night Ratio for the assessment of convenient incentive or price based methods. Statistical parameters, such as peak-to-average ratio, load factor and standard deviation are calculated. Active power deviations on annual and daily load curves are discussed.

URI

https://hdl.handle.net/11511/67493

DOI

https://doi.org/10.1088/1757-899x/161/1/012111

Conference Name

20th Innovative Manufacturing Engineering and Energy Conference (IManEE)

Collections

Unclassified, Conference / Seminar

Suggestions

OpenMETU
Core

Data mining methods for clustering power quality data collected via monitoring systems installed on the electricity network Güder, Mennan; Çiçekli, Fehime Nihan; Department of Computer Engineering (2009) Increasing power demand and wide use of high technology power electronic devices result in need for power quality monitoring. The quality of electric power in both transmission and distribution systems should be analyzed in order to sustain power system reliability and continuity. This analysis is possible by examination of data collected by power quality monitoring systems. In order to define the characteristics of the power system and reveal the relations between the power quality events, huge amount of d...
Supplementing demand management programs with distributed generation options Fahrioglu, Murat; Alvarado, F. L.; Lasseter, R. H.; Yong, T. (2012-03-01) Ever increasing electrical energy demand is forcing power serving entities around the world to use various demand management programs to help in stressful times of the electric power grid. Demand management programs aim to control electrical energy demand among customers and create load relief for electric utilities. Recently demand management contracts have been designed in which incentives are offered to customers who willingly sign up for load interruption. In recent years much technological advancement ...
Short-Term Electricity Consumption Forecast using Datasets of Various Granularities ARSLAN, YUSUF; ŞİMŞEK DİLBAZ, AYBİKE; Ertekin Bolelli, Şeyda; Karagöz, Pınar; Birtürk, Ayşe Nur; Eren, Sinan; KÜÇÜK, DİLEK (2018-09-10) It is widely known that the generation and consumption of electricity should be balanced for secure operation and maintenance of the electricity grid. In order to help achieve this balance in the grid, the renewable energy resources such as wind and stream-flow should be forecast at high accuracies on the generation side, and similarly, electricity consumption should be forecast using a high-performance system. In this paper, we deal with short-term electricity consumption forecast in Turkey, and conduct va...
Data-driven modeling using deep neural networks for power systems demand and locational marginal price forecasting Jimu, Honest; Fahrioğlu, Murat; Electrical and Electronics Engineering (2022-9) Forecasting electricity demand and locational marginal prices (LMPs) have become critical components for power system security and management. Electricity Demand Forecasting (EDF) aids the utility in maximizing the use of power-generation plants and scheduling them for both reliability and cost-effectiveness. In this thesis, a novel Deep Neural Network Long Short-Term Memory (DNN-LSTM) forecasting model is suggested to improve accuracy and robustness for predicting hourly day ahead power system load and LMP...
Energy efficiency perspectives of femtocells in internet of things: recent advances and challenges Al-Turjman, Fadi M.; Imran, Muhammad; Bakhsh, Sheikh Tahir (Institute of Electrical and Electronics Engineers (IEEE), 2017) Energy efficiency is a growing concern in every aspect of the technology. Apart from maintaining profitability, energy efficiency means a decrease in the overall environmental effects, which is a serious concern in today's world. Using a femtocell in Internet of Things (IoT) can boost energy efficiency. To illustrate, femtocells can be used in smart homes, which is a subpart of the smart grid, as a communication mechanism in order to manage energy efficiency. Moreover, femtocells can be used in many IoT app...

Citation Formats

K. Yumak, G. Tosun, B. Varlik, and M. Bağrıyanık, “Load curve classification for the evaluation of demand side management programs,” Kallithea, GREECE, 2016, vol. 161, p. 0, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/67493.