Chanaka Keerthisinghe

Chanaka Keerthisinghe
University of Washington Seattle | UW · Department of Electrical Engineering

PhD (Univ. of Sydney, Australia); B.E. and M.E. (Univ. of Auckland, New Zealand)

About

14
Publications
4,577
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267
Citations
Introduction
Chanaka received the Ph.D. in Electrical Engineering from the University of Sydney, Sydney, New South Wales, Australia in 2017; and B.E. (First Class Hons) and M.E. in Electrical and Electronic Engineering from the University of Auckland, Auckland, New Zealand, in 2011 and 2014, respectively. He has industrial work experience at the Mitsubishi Electric Research Labs (MERL) in Cambridge, Massachusetts, USA; and research and teaching experience at the University of Sydney and University of Auckland.
Additional affiliations
January 2017 - June 2017
Mitsubishi Electric Research Laboratories
Position
  • Research Intern
July 2013 - November 2015
The University of Sydney
Position
  • Tutor/Teaching Assistant
March 2013 - December 2016
The University of Sydney
Position
  • PhD Student
Education
March 2013 - August 2016
The University of Sydney
Field of study
  • Power Engineering
March 2011 - November 2012
University of Auckland
Field of study
  • Power Electronics
March 2007 - November 2010
University of Auckland
Field of study
  • Electrical and Electronic Engineering

Publications

Publications (14)
Conference Paper
Full-text available
In the future, residential energy users can seize the full potential of demand response schemes by using an automated home energy management system (HEMS) to schedule their distributed energy resources. In order to generate high quality schedules, a HEMS needs to consider the stochastic nature of the PV generation and energy consumption as well as...
Article
Full-text available
This paper presents a computationally efficient smart home energy management system (SHEMS) using an approximate dynamic programming (ADP) approach with temporal difference learning for scheduling distributed energy resources. This approach improves the performance of a SHEMS by incorporating stochastic energy consumption and PV generation models o...
Conference Paper
Full-text available
In Australia, the penetration of rooftop photovoltaic (PV) systems with storage is expected to increase in the future because of rising electricity costs, decreasing capital costs and growing concerns about climate change. Residential energy users can seize the full financial benefits of these systems by using an automated energy management system...
Article
Engineering education is undergoing a restructuring driven by the needs of an increasingly multidisciplinary engineering profession. At the same time, power systems are transitioning toward future smart grids that will require power engineers with skills outside of the core power engineering domain. Since including new topics in the existing curric...
Conference Paper
Full-text available
In the future, automated smart home energy management systems (SHEMSs) will assist residential energy users to schedule and coordinate their energy use. In order to undertake efficient and robust scheduling of distributed energy resources, such a SHEMS needs to consider the stochastic nature of the household's energy use and the intermittent nature...
Article
Full-text available
Some balancing authorities give owners of medium to large photovoltaic (PV) generation plants a choice between firming the production of their plants using battery energy storage or paying the balancing authority for the cost that these imbalances impose on the system. If the owner of a PV plant decides to do capacity firming, the net production of...
Article
Full-text available
Dynamic programming (DP) can be used to generate the optimal schedules of a smart home energy management system (SHEMS), however, it is computationally difficult because we have to loop over all the possible states, decisions and outcomes. This paper proposes a novel state-space approximate dynamic programming (SS-ADP) approach to quickly solve a S...
Article
Full-text available
This paper proposes a hierarchical approach for estimating residential PV and electrical demand models using historical data. In brief, the method involves first clustering historical data into different day types, and then estimating PV and demand models using kernel regression. Clustering is done to capture intra-day variations in the PV and dema...
Article
Full-text available
In this paper, we propose a policy function approximation (PFA) algorithm using machine learning to effectively control PV-storage systems. The algorithm uses an offline policy planning stage and an online policy execution stage. In the planning stage, a suitable machine learning technique is used to generate models that map states (inputs) and dec...
Conference Paper
Full-text available
Depletion of fossil fuels and growing concerns about climate change have resulted in an increasing trend towards the use of sustainable technologies such as electric vehicles (EVs). As a result, effective means of charging EVs and managing EVs has become one of the most researched topics in the past few years. Among the many solutions proposed, ind...

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Projects

Projects (2)
Archived project
Natural disasters often leave communities, particu- larly isolated rural communities, without grid connection for a long time, endangering the health and life of people who rely on electrically-powered medical devices. While small systems combining photo-voltaic (PV) generation and battery energy storage could be deployed to help cope with such emergencies, very little reliable data is available on how such systems would actually be used and thus on their design requirements. To fill this gap, our paper reports on field research performed in Puerto Rico in the aftermath of Hurricane Maria. It first discusses the collection and analysis of data on the requirements for electricity for critical medical needs in households located in remote areas that were without grid-connection for months. It then describes the installation, use and field-performance of emergency PV- battery systems installed in these households. Based on this information, the paper then proposes an approach to design effective and cost-efficient systems that would support continuous operation over a year considering battery degradation. The benefits of PV-storage systems are also compared to those of using a diesel generator. Website: https://www.cei.washington.edu/education/global-engagement/puerto-rico/ Our work will be published in IEEE Power and Energy Magazine 2019 January/February version.