Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Radhakrishnan Angamuthu Chinnathambi"'
Autor:
Daniel Bissing, Michael T. Klein, Radhakrishnan Angamuthu Chinnathambi, Daisy Flora Selvaraj, Prakash Ranganathan
Publikováno v:
IEEE Access, Vol 7, Pp 36833-36842 (2019)
Accurate forecast of the hourly spot price of electricity plays a vital role in energy trading decisions. However, due to the complex nature of the power system, coupled with the involvement of multi-variable, the spot prices are volatile and often d
Externí odkaz:
https://doaj.org/article/319cdb16dd6e4838b7efe5ebfeadd57c
Autor:
Michael T. Klein, Daniel Bissing, Radhakrishnan Angamuthu Chinnathambi, Daisy Flora Selvaraj, Prakash Ranganathan
Publikováno v:
IEEE Access, Vol 7, Pp 36833-36842 (2019)
Accurate forecast of the hourly spot price of electricity plays a vital role in energy trading decisions. However, due to the complex nature of the power system, coupled with the involvement of multi-variable, the spot prices are volatile and often d
Autor:
Alex Marquette, Scott Hanson, Aaron Johnson, Naima Kaabouch, Daisy Flora Selvaraj, Prakash Ranganathan, Tyler Clark, Todd Hanson, Jeff Vaughan, Radhakrishnan Angamuthu Chinnathambi
Publikováno v:
EIT
This paper discusses how visualization and machine learning models can be effectively used to track and forecast trap counts of Culex Tarsalis, female mosquitoes responsible for spreading the West Nile Virus (WNV). This paper applies four different m
Autor:
Prakash Ranganathan, Siby Jose Plathottam, Tareq Hossen, Radhakrishnan Angamuthu Chinnathambi, Arun Sukumaran Nair
Publikováno v:
2018 IEEE Electrical Power and Energy Conference (EPEC).
This work investigates the application of a multilayered Perceptron (MLP) deep neural network for the day-ahead price forecast of the Iberian electricity market (MIBEL) which serves the mainland areas of the Spain and Portugal. The 3-month and 6-mont
Autor:
Prakash Ranganathan, Arun Sukumaran Nair, Radhakrishnan Angamuthu Chinnathambi, Mitch Campion
Publikováno v:
2018 IEEE Electrical Power and Energy Conference (EPEC).
This paper investigates three types of feature selection techniques such as relative importance using Linear Regression (LR), Multivariate Adaptive Regression Splines (MARS), and Random forest (RF) to reduce the forecasts error for the hourly spot pr
Publikováno v:
2018 North American Power Symposium (NAPS).
Forecasting of consumer electricity usages plays an important role to make total smart grid system more reliable. As the activities of individual residential consumers has many uncertain variables, it is hard to accurately forecast the residential lo
Autor:
Radhakrishnan Angamuthu Chinnathambi, Jeremy Lin, Mitch Campion, Hossein Salehfar, Prakash Ranganathan, Anupam Mukherjee, Timothy M. Hansen
Publikováno v:
Forecasting
Volume 1
Issue 1
Volume 1
Issue 1
Forecasting hourly spot prices for real-time electricity markets is a key activity in economic and energy trading operations. This paper proposes a novel two-stage approach that uses a combination of Auto-Regressive Integrated Moving Average (ARIMA)
Publikováno v:
IEEE BigData
Forecasting hourly spot prices for real-time electricity usage is a challenging task. This paper investigates a series of forecasting methods to 90 and 180 days of load data collection acquired from the Iberian Electricity Market (MIBEL). This datase