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Department of Electrical and Electronic Engineering
University of Peradeniya
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Department of Electrical and Electronic Engineering
University of Peradeniya

Research


Investigators : Prof.K.M.Liyanage

Description

Smarter and greener energy technologies are expected replace the legacy power network in near future. Variety of innovative technologies, system architectures and market models are being investigated in order to significantly reduce the carbon footprint of the energy sector. This project investigates the advantages of active participation of customers in energy market through a customer friendly plug & play system architecture. Where, aggregated Distributed Energy Resources (DER) like solar PV, Electric Vehicles and controllable loads in customer domain are controlled in an optimal fashion to minimize carbon emission while ensuring customer satisfaction. In this project, in addition to developing the required optimization algorithm, the study was extended to model the effects of random communication delays on the aggregated output of DERs using applied probability theory.


Research Assistant

Mr. M.A. Mohammed Manaz (M.Phil student)


Amount

None


Duration

3 Years


Collaborators

None


Funding Body

None

Investigators : Prof. J.B. Ekanayake and Dr. J.V. Wijayakulasooriya

Description

In the proposed research, a system that can determine the dynamic line rating is developed using low cost solutions. GPRS communication is used to transmit data from sensors located on the power lines and these data and the parameters of the line will be used to determine the dynamic line rating. The sensors and communication unit will be powered by the electricity harnessed from the power line itself. This dynamic line rating system will be first implemented and tested in the laboratory. Then it is enclosed in a suitable enclosure and suitable field test are carried out on distribution overhead lines.


Research Assistant
Miss. Akila Wijethunga
Amount

LKR. 2 million


Duration

2014 January – to date


Collaborators

Ceylon Electricity Board, Lanka Electricity Company.


Funding Body

National Science Foundation

Investigators : Prof. Janaka Ekanayake, Dr. Prabath Binduhewa Dr. Lilantha Samaranayake Dr. Lidula Widanagama Arachchige


Description

This research is aiming to investigate how dc microgrid could help to reduce the losses in power distribution and be used to integrate PV into power system and how PV could enhance the quality, reliability and security of the power supply. Novel converter topologies related to dc networks will be investigated.


Research Assistant
Mr. Chathuranga Jayarathna
Amount

LKR. 2.2 million


Duration

02/06/2014 – 30/06/2017


Collaborators

University of Moratuwa


Funding Body

National Research Council, Sri Lanka

Investigators : Dr. G.M.R.I. Godaliyadda, M.P.B. Ekanayake, Prof. J.B. Ekanayake and Dr. J.V. Wijayakulasooriya

Description

Load Monitoring techniques determine the appliances that are turned-on within a given period of time in a household. They play a critical role in a variety of smart grid applications such as supply and demand side power control, smart billing and intelligent appliance monitoring and control. Load monitoring can be performed both intrusively as well as non-intrusively.

Intrusive load monitoring estimates the turned-on appliances by attaching individual sensors to each appliance to be monitored. Non-Intrusive Load Monitoring (NILM) attempts to identify the turned-on appliances from the power supply entry point to the household or workplace. The necessity for effective and efficient NILM methods for residential appliance identification has recently escalated due to its application potential for smart grids. Most of the existing NILM methods require very high sampling rates to capture the unique features from the measurement signals. Further, some of these NILM methods require more than one electrical measurement (such as voltage, current, active power, reactive power etc.) for the appliances identification. Further, such methods need multi functional smart meters that are also costly. Considering the above drawbacks, a novel NILM method was proposed based on uncorrelated spectral information of a low frequency (less than 1 Hz) active power consumption signal. Real household active power consumption data from two public databases, i.e. tracebase and REDD, was used to demostrate the robustness of the proposed NILM method under several practical scenarios.


Research Assistant
Mr. H.G.C.P. Dinesh
Duration

2014 May – to date

Investigators : Prof. J.B. Ekanayake, Dr. S.G. Abeyratne, Dr. P.J. Binduhewa

Description

A key aspect of electricity supply quality in a power system is to supply voltages within its limits. In this research an electronically controlled Volt-Var Control (VVC) scheme based on a three winding transformer is investigated. Two configurations based on series and parallel compensation are studied for their relevant merits.


Research Assistant
Miss Lochana Wijayaratne
Amount

LKR. 2.25 million


Duration

2014 January – to date


Collaboration

Lanka Transformers Ltd.


Funding Body

InRC of University of Peradeniya, Lanka transformers Ltd.

Investigators : Dr. J.R.S.S. Kumara, Dr. A.U.A.W. Gunawardena & Prof. M.A.R.M. Fernando

Description

Moisture estimation of transformer pressboard by Microstrip ring resonator at GHz frequencies


Figure 1 : Developed Ring resonator (diameter 25 mm)

Figure 2 : Results on network analyzer for different dielectric materials

Figure 3 : Correlation between moisture and relative permittivity/ loss tangent on impregnated pressboard samples during drying

Figure 4 : Correlation between moisture and relative permittivity/ loss tangent on impregnated pressboard samples during wetting

Figure 5 : Correlation between moisture and relative permittivity/ loss tangent on non-impregnated pressboard samples during wetting


Research Student(s)

Mr. W.M.S.C. Samarasinghe

Mr. A.C.M. Ahamed


Duration

from October 2014


Collaborators

Collaboration between high voltage and microwave research groups.

Investigators : Dr. Janaka Wijayakulasooriya, Dr. Ruwan Ranaweera, Dr. Roshan Godaliyadda, Dr. Parakrama Ekanayake
Classification Method Results: Accuracy
Training Data Test data
1.   Simple linear boundary classification C4_RMS=C3_RMS 80% 80%
2.   Voting using RMS 85% 85%
3.   OPtimized linear boundary classification C4_RMS=m_opt*C3_RMS + C0_opt 82.9% 75%
4.   PCA 82.9% 50%
5.   LDA 77% 80%

Research Student(s)

W.G.K.G. Kumari


Duration

January 2014 – Aug 2015

Professional Organizition

PHES IEEE IESL IET

Where we are

Copyright 2015 - Department of Electrical & Electronic Engineering