Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Arun Sukumaran Nair"'
Publikováno v:
Sādhanā. 47
Publikováno v:
2021 IEEE Kansas Power and Energy Conference (KPEC).
The forecasting of Wind power generation plays a critical role in the safe and stable operation of a power grid. Grid operators rely on the short-term forecasts of load and generation sources to optimize operations such as unit commitment and economi
Autor:
Daisy Flora Selvaraj, Tareq Hossen, Neena Goveas, Prakash Ranganathan, Arun Sukumaran Nair, Naima Kaabouch, Mitch Campion
Publikováno v:
Technology and Economics of Smart Grids and Sustainable Energy. 5
When discussing the development of MAS for Smart Grid and the advantages of distributed MAS over centralized control in the text of this article [1] and describing MAS tools in Table 2, we inadvertently used text from a previous article by Merabet an
Publikováno v:
EIT
The combination of high penetration of distributed energy resources with fusion of unprotected data from several sources such as digital sensors (e.g., synchrophasors, smart meters, digital relays etc.) and controllers of systems of systems (SoS) tha
Autor:
Daisy Flora Selvaraj, Mitch Campion, Tareq Hossen, Naima Kaabouch, Arun Sukumaran Nair, Prakash Ranganathan, Neena Goveas
Publikováno v:
Technology and Economics of Smart Grids and Sustainable Energy. 3
With the increasing integration of Distributed Energy Resources (DER) in the power grid, a decentralized approach becomes essential for scheduling and allocation of resources in a smart grid. Economic Dispatch (ED) and Unit Commitment (UC) are the tw
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).
In this paper, we present a scheduling scheme for household Electric vehicles based on deep neural network based demand forecast. A novel clustering based Short Term Load Forecasting (STLF) using deep neural network (DNN) is presented in this paper t
Publikováno v:
2018 North American Power Symposium (NAPS).
This paper discusses an optimal operation of smart home appliances using deep learning. A yearly dataset was used to predict the day-ahead energy consumption pattern of household appliances. The preliminary findings indicate promising improvement in
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