Conference Program

Monday:
Tutorials
Tuesday - Thursday:
Main Conference
Friday:
Workshops

London Mirror / PDT Mirror

Since this year’s conference will be held online, we will stream the replay of each presentation at two different times to accomodate different time zones. Authors will record their presentation in advance and may choose to present live at either one of the mirrors. Q&A will be done either in person (when the author presents live), or offline via chat (when the author is unable to attend due to timezone, and a recording is used instead).

Please note that the weekday of the program reflects the current weekday in the timezone that names the mirror (London / PDT). Example: a presentation in the PDT (US West) mirror at 9:00am on Tuesday will start at 2:00am Wednesday in Australia (AEST).

Best Paper Award Candidates

  • Pareto-optimal energy sharing between battery-equipped renewable generators by Vivek Deulkar (IIT Bombay); Jayakrishnan Nair (IIT Bombay)
  • Discrete and stochastic coalitional storage games by Diego Kiedanski (Télécom Paris); Ariel Orda (Technion); Daniel Kofman (Télécom Paris)
  • Emission-aware Energy Storage Scheduling for a Greener Grid by Rishikesh Jha (University of Massachusetts Amherst); Stephen Lee (University of Pittsburgh); Srinivasan Iyengar (Microsoft Research India); Mohammad Hajiesmaili (University of Massachusetts Amherst); David Irwin (University of Massachusetts Amherst); Prashant Shenoy (University of Massachusetts, Amherst)

  • Monday, June 22, 2020

  • Tutorial: Optimal Power Flow

  • AEST Mirror 0:00-4:00 London | 7:00-11:00 HKT | 16:00-20:00 PDT | 19:00-23:00 EDT | 9:00-13:00 AEST

  • Tutorial: Blockchain and Energy

  • AEST Mirror 9:00-13:00 London | 16:00-20:00 HKT | 1:00-5:00 PDT | 4:00-8:00 EDT | 18:00-22:00 AEST

  • Tuesday, June 23, 2020

  • ACM e-Energy Opening

  • London Mirror 8:15-9:00 London | 15:15-16:00 HKT | 0:15-1:00 PDT | 3:15-4:00 EDT | 17:15-18:00 AEST

  • PDT Mirror 8:15-9:00 PDT | 16:15-17:00 London | 23:15-0:00 HKT | 11:15-12:00 EDT | 1:15-2:00 AEST

  • Session 1: Energy Markets

    Session Chair: Chenye Wu (Tsinghua University)

  • London Mirror 9:00-10:30 London | 16:00-17:30 HKT | 1:00-2:30 PDT | 4:00-5:30 EDT | 18:00-19:30 AEST

  • PDT Mirror 9:00-10:30 PDT | 17:00-18:30 London | 0:00-1:30 HKT | 12:00-13:30 EDT | 2:00-3:30 AEST

  • Long-term electricity market agent based model validation using genetic algorithm based optimization

    Alexander J. M. Kell (Newcastle University); Matthew Forshaw (Newcastle University); A. Stephen McGough (Newcastle University)

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  • Network-aware Participation of Aggregators in NEM Energy and FCAS Markets

    Ahmad Attarha (The Australian National University); Paul Scott (The Australian National University); Sylvie Thiebaux (The Australian National University)

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  • Pareto-optimal energy sharing between battery-equipped renewable generators (nominated)

    Vivek Deulkar (IIT Bombay); Jayakrishnan Nair (IIT Bombay)

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  • Small-Scale Communities Are Sufficient for Cost- and Data-Efficient Peer-to-Peer Energy Sharing

    Romaric Duvignau (Chalmers University of Technology); Verena Heinisch (Chalmers University of Technology); Lisa Göransson (Chalmers University of Technology); Vincenzo Gulisano (Chalmers University of Technology); Marina Papatriantafilou (Chalmers University of Technology)

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  • Session 2: Smart Buildings

    Session Chair: Romaric Duvignau (Chalmers University of Technology)

  • London Mirror 11:00-12:00 London | 18:00-19:00 HKT | 3:00-4:00 PDT | 6:00-7:00 EDT | 20:00-21:00 AEST

  • PDT Mirror 11:00-12:00 PDT | 19:00-20:00 London | 2:00-3:00 HKT | 14:00-15:00 EDT | 4:00-5:00 AEST

  • MELODY: Adaptive Task Definition of COP Prediction with Metadata for HVAC Control and Electricity Saving

    Zimu Zheng (Huawei Technologies Co., Ltd); Daqi Xie (Huawei Technologies Co., Ltd); Jie Pu (Huawei Technologies Co., Ltd); Feng Wang (Huawei Technologies Co., Ltd)

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  • MARCO - Multi-Agent Reinforcement learning based COntrol of building HVAC systems

    Srinarayana Nagarathinam (Tata Consultancy Services); Vishnu Menon (Tata Consultancy Services); Arunchandar Vasan (Tata Consultancy Services); Anand Sivasubramaniam (Penn State University)

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  • Towards Federated Learning for HVAC Analytics: A Measurement Study

    Yunzhe Guo (Tsinghua University & The Hong Kong Polytechnic University); Dan Wang (The Hong Kong Polytechnic University); Arun Vishwanath (IBM Research Australia); Cheng Xu (The Hong Kong Polytechnic University); Qi Li (Tsinghua University)

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  • Keynote 1 Anuradha Annaswamy, MIT

  • London Mirror 13:30-14:30 London | 20:30-21:30 HKT | 5:30-6:30 PDT | 8:30-9:30 EDT | 22:30-23:30 AEST

  • PDT Mirror 13:30-14:30 PDT | 21:30-22:30 London | 4:30-5:30 HKT | 16:30-17:30 EDT | 6:30-7:30 AEST

  • Significant changes have occurred all over the world even over the past decade in the energy landscape. Globally, there’s a big push towards a 100% incorporation of wind and solar power for electricity production, with synergistic support from various technologies. For example, in the US, natural gas prices have declined, costs of renewable energy technologies have come down, and large-scale battery energy storage technologies have advanced rapidly. There are however a host of challenges, most of which are due to the intermittency and unpredictability of the renewable energy resources. This talk will focus on some of the solutions for the deep integration of these renewable resources for electricity production that are control-centric. A distributed optimization approach that judiciously combines renewable generation with storage and flexible loads has the possibility for ensuring power balance even with growing penetration of renewables. Flexibility in other interdependent infrastructures such as train networks can be integrated with solar and wind power generation nodes, storage sites, and flexible consumption can lead to real-time power balance and optimal power flow. This presentation will cover some of these challenges, highlights of the current research in distributed optimization, and use-case studies that illustrate the role of distributed and dynamic optimization in renewable-rich power grids.

  • Session 3: The Power Grid

    Session Chair: Omid Ardakanian (University of Alberta)

  • London Mirror 15:00-16:30 London | 22:00-23:30 HKT | 7:00-8:30 PDT | 10:00-11:30 EDT | 0:00-1:30 AEST

  • PDT Mirror 15:00-16:30 PDT | 23:00-0:30 London | 6:00-7:30 HKT | 18:00-19:30 EDT | 8:00-9:30 AEST

  • The Long-term Cost of Energy Generation

    Jimmy Horn (Horn Wind LLC); Yutong Wu (University of Texas at Austin); Ali Khodabakhsh (University of Texas at Austin); Evdokia Nikolova (University of Texas at Austin); Emmanouil Pountourakis (Drexel University)

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  • Automated Classification of Power Plants by Generation Type

    Liuzixuan Lin (University of Chicago); Andrew A. Chien (University of Chicago & Argonne National Lab)

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  • Flexible Redundancy Generation for Virtual Network Embedding with an Application to Smart Grids

    Allan Almeida Santos (Technical University of Darmstadt); Amr Rizk (Ulm University); Florian Steinke (Technische Universität Darmstadt)

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  • Fairness in Power Flow Network Congestion Management with Outer Matching and Principal Notions of Fair Division

    Brinn Hekkelman (Centrum Wiskunde & Informatica (CWI)); Han La Poutré (Centrum Wiskunde & Informatica (CWI))

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  • Session 4: Electric Vehicles

    Session Chair: Mohammad Hajiesmaili (UMass Amherst)

  • London Mirror 17:00-18:30 London | 0:00-1:30 HKT | 9:00-10:30 PDT | 12:00-13:30 EDT | 2:00-3:30 AEST

  • PDT Mirror 17:00-18:30 PDT | 1:00-2:30 London | 8:00-9:30 HKT | 20:00-21:30 EDT | 10:00-11:30 AEST

  • Adaptive Control of Plug-in Electric Vehicle Charging with Reinforcement Learning

    Abdullah Al Zishan (University of Alberta); Moosa Moghimi Haji (University of Alberta); Omid Ardakanian (University of Alberta)

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  • FlexAbility - Modeling and Maximizing the Bidirectional Flexibility Availability of Unidirectional Charging of Large Pools of Electric Vehicles

    Jonas Schlund (Friedrich-Alexander-University Erlangen-Nürnberg); Marco Pruckner (Friedrich-Alexander-University Erlangen-Nürnberg); Reinhard German (Friedrich-Alexander-University Erlangen-Nürnberg)

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  • MATE: A Memory-Augmented Time-Expansion Approach for Optimal Trip-Vehicle Matching and Routing in Ride-Sharing

    Ye Tian (Iowa State University); Jia Liu (Iowa State University); Cathy Xia (OSU)

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  • ORC: An Online Competitive Algorithm for Recommendation and Charging Schedule in Electric Vehicle Charging Network

    Bo Sun (The Hong Kong University of Science and Technology); Tongxin Li (California Institute of Technology); Steven Low (Caltech); Danny H.K. Tsang (The Hong Kong University of Science and Technology)

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  • Uberizing the Charging Ecosystem for Electric Vehicles

    Aakash Krishna (TCS Research & Innovation); Ajay Narayanan (TCS Research & Innovation); Sunil Krishnakumar (TCS Research & Innovation); Prasant Misra (TCS Research & Innovation); Arunchandar Vasan (TCS Research & Innovation); Venkatesh Sarangan (TCS Research & Innovation); Anand Sivasubramaniam (Penn State University)

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  • Wednesday, June 24, 2020

  • Keynote 2 David Edwards, Horizon Power, Australia

  • London Mirror 8:30-9:30 London | 15:30-16:30 HKT | 0:30-1:30 PDT | 3:30-4:30 EDT | 17:30-18:30 AEST

  • PDT Mirror 8:30-9:30 PDT | 16:30-17:30 London | 23:30-0:30 HKT | 11:30-12:30 EDT | 1:30-2:30 AEST

  • The Carnarvon DER trials are setting a visionary destination for grid automation in high penetration DER microgrids using VPP technology to optimise network operation through orchestration of customer rooftop solar and battery storage. This presentation covers some of the key learnings so far, highlighting how the project has employed IoT and IoE, forecasting, predictive analytics, machine learning and customer value exchange. The goal is a new operational model using clean energy technology that will assist economic development in regional and remote communities.

  • Session 5: Human and Energy

    Session Chair: Yashar Ghiassi-Farrokhfal (Rotterdam School of Management)

  • London Mirror 10:00-12:00 London | 17:00-19:00 HKT | 2:00-4:00 PDT | 5:00-7:00 EDT | 19:00-21:00 AEST

  • PDT Mirror 10:00-12:00 PDT | 18:00-20:00 London | 1:00-3:00 HKT | 13:00-15:00 EDT | 3:00-5:00 AEST

  • Sustainability Choices when Cooking Pasta

    Laura Fiorini (University of Groningen); Linda Steg (University of Groningen); Marco Aiello (University of Stuttgart)

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  • How does Load Disaggregation Performance Depend on Data Characteristics? Insights from a Benchmarking Study

    Andreas Reinhardt (TU Clausthal); Christoph Klemenjak (University of Klagenfurt)

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  • Privacy Measures and Storage Technologies for Battery-Based Load Hiding - an Overview and Experimental Study

    Vadim Arzamasov (Karlsruhe Institute of Technology (KIT)); Rebecca Schwerdt (Karlsruhe Institute of Technology (KIT)); Shahab Karrari (Karlsruhe Institute of Technology (KIT)); Klemens Böhm (Karlsruhe Institute of Technology (KIT)); Tien Bach Nguyen (Karlsruhe Institute of Technology (KIT))

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  • Predictive Multi-Objective Scheduling with Dynamic Prices and Marginal CO$_2$-Emission Intensities

    Laura Fiorini (University of Groningen); Marco Aiello (University of Stuttgart)

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  • Fish and Chips: Converting Fishing Boats for Electric Mobility to Serve as Minigrid Anchor Loads

    June Lukuyu (University of Massachusetts Amherst); Aggrey Muhebwa (University of Massachusetts Amherst); Jay Taneja (University of Massachusetts Amherst)

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  • Day 2 Q&A Social Session (Alpha Session)

  • London Mirror 12:15-13:15 London | 19:15-20:15 HKT | 4:15-5:15 PDT | 7:15-8:15 EDT | 21:15-22:15 AEST

  • PDT Mirror 12:15-13:15 PDT | 20:15-21:15 London | 3:15-4:15 HKT | 15:15-16:15 EDT | 5:15-6:15 AEST

  • Poster Session

  • London Mirror 13:30-15:00 London | 20:30-22:00 HKT | 5:30-7:00 PDT | 8:30-10:00 EDT | 22:30-0:00 AEST

  • PDT Mirror 13:30-15:00 PDT | 21:30-23:00 London | 4:30-6:00 HKT | 16:30-18:00 EDT | 6:30-8:00 AEST

  • Best Paper Award and ACM e-Energy 2021

  • London Mirror 15:00-15:45 London | 22:00-22:45 HKT | 7:00-7:45 PDT | 10:00-10:45 EDT | 0:00-0:45 AEST

  • PDT Mirror 15:00-15:45 PDT | 23:00-23:45 London | 6:00-6:45 HKT | 18:00-18:45 EDT | 8:00-8:45 AEST

  • Session 6: Forecasting and Data

    Session Chair: Jay Taneja (UMAss Amherst)

  • London Mirror 16:15-17:30 London | 23:15-0:30 HKT | 8:15-9:30 PDT | 11:15-12:30 EDT | 1:15-2:30 AEST

  • PDT Mirror 16:15-17:30 PDT | 0:15-1:30 London | 7:15-8:30 HKT | 19:15-20:30 EDT | 9:15-10:30 AEST

  • Forecasting energy time series with profile neural networks

    Benedikt Heidrich (Karlsruhe Institute of Technology); Marian Turowski (Karlsruhe Institute of Technology); Nicole Ludwig (Karlsruhe Institute of Technology); Ralf Mikut (Karlsruhe Institute of Technology); Veit Hagenmeyer (Karlsruhe Institute of Technology)

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  • Permutation-Based Residential Short-term Load Forecasting in the Context of Energy Management Optimization Objectives

    Marcus Voss (Technische Universität Berlin (DAI-Labor))

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  • Peak Forecasting for Battery-based Energy Optimizations in Campus Microgrids

    Akhil Soman (University of Massachusetts Amherst); Amee Trivedi (University of Massachusetts Amherst); David Irwin (University of Massachusetts Amherst); Beka Kosanovic (University of Massachusetts Amherst); Benjamin McDaniel (University of Massachusetts Amherst); Prashant Shenoy (University of Massachusetts Amherst)

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  • Powerstrip: High-Performance Compression for Energy Data

    John R. Ward (Okta, Inc.); Sean K. Barker (Bowdoin College)

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  • Day 2 Q&A Social Session (Beta Session)

  • London Mirror 17:30-18:30 London | 0:30-1:30 HKT | 9:30-10:30 PDT | 12:30-13:30 EDT | 2:30-3:30 AEST

  • PDT Mirror 17:30-18:30 PDT | 1:30-2:30 London | 8:30-9:30 HKT | 20:30-21:30 EDT | 10:30-11:30 AEST

  • Thursday, June 25, 2020

  • Keynote 3 Pierluigi Mancarella, University of Melbourne, Australia

  • London Mirror 8:30-9:30 London | 15:30-16:30 HKT | 0:30-1:30 PDT | 3:30-4:30 EDT | 17:30-18:30 AEST

  • PDT Mirror 8:30-9:30 PDT | 16:30-17:30 London | 23:30-0:30 HKT | 11:30-12:30 EDT | 1:30-2:30 AEST

  • Digital energy systems (DES) are highly distributed cyber-physical systems in which small-scale distributed energy resources such as solar PV, different types of storage, controllable loads, etc., can be actively monitored and controlled via pervasive availability of ICT and smart grid technologies. This keynote address will discuss opportunities and challenges for emerging DES platforms in the context of low-carbon electricity grids with deep penetration of renewables. Particular focus will be put on how DES could be intelligently orchestrated to provide grid flexibility services and participate in different energy markets, as well as autonomously controlled to respond to extreme (for example, weather-driven) events, thus enhancing grid resilience. Specific applications that will be shown will cover technical, commercial and regulatory aspects of DES from a number of recent projects in Australia, UK, and Europe. The final aim is to illustrate how development of DES platforms for smart buildings, smart communities, microgrids, virtual power plants, and distributed energy marketplaces can facilitate an affordable, secure and resilient transition towards a low-carbon energy future.

  • Session 7: Energy Transmission and Control

    Session Chair: Jayakrishnan Nair (IIT Bombay)

  • London Mirror 10:00-12:00 London | 17:00-19:00 HKT | 2:00-4:00 PDT | 5:00-7:00 EDT | 19:00-21:00 AEST

  • PDT Mirror 10:00-12:00 PDT | 18:00-20:00 London | 1:00-3:00 HKT | 13:00-15:00 EDT | 3:00-5:00 AEST

  • Transmission Expansion Planning Using Cycle Flows

    Fabian Neumann (Karlsruhe Institute of Technology); Tom Brown (Karlsruhe Institute of Technology)

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  • Preventing Critical Edges when Designing Transmission Networks

    Dorothea Wagner (Karlsruhe Institute of Technology); Matthias Wolf (Karlsruhe Institute of Technology)

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  • Real-time Flexibility Feedback for Closed-loop Aggregator and System Operator Coordination

    Tongxin Li (California Institute of Technology); Steven H. Low (California Institute of Technology); Adam Wierman (California Institute of Technology)

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  • Design and Development of Brownout Control Strategy using End-point Load Control

    Adithya Ramanujam (Indian Institute of Technology, Bombay); Mahesh Parihar (Indian Institute of Technology,Bombay); Suchitra Swain (Indian Institute of Technology, Bombay); Krithi Ramamritham (IIT Bombay)

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  • Negative Cycle Canceling with Neighborhood Heuristics for the Wind Farm Cabling Problem

    Sascha Gritzbach (Karlsruhe Institute of Technology (KIT)); Dorothea Wagner (Karlsruhe Institute of Technology (KIT)); Matthias Wolf (Karlsruhe Institute of Technology (KIT))

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  • Day 3 Q&A Social Session (Alpha Session)

  • London Mirror 12:15-13:15 London | 19:15-20:15 HKT | 4:15-5:15 PDT | 7:15-8:15 EDT | 21:15-22:15 AEST

  • PDT Mirror 12:15-13:15 PDT | 20:15-21:15 London | 3:15-4:15 HKT | 15:15-16:15 EDT | 5:15-6:15 AEST

  • Session 8: Solar PV

    Session Chair: Sean Barker (Bowdoin College)

  • London Mirror 13:30-15:00 London | 20:30-22:00 HKT | 5:30-7:00 PDT | 8:30-10:00 EDT | 22:30-0:00 AEST

  • PDT Mirror 13:30-15:00 PDT | 21:30-23:00 London | 4:30-6:00 HKT | 16:30-18:00 EDT | 6:30-8:00 AEST

  • Using Satellite and Aerial Imagery for Identification of Solar PV: State of the Art and Research Opportunities

    Julian De Hoog (IBM Research Australia); Stefan Maetschke (IBM Research Australia); Peter Ilfrich (IBM Research Australia); Ramachandra Rao Kolluri (IBM Research Australia)

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  • Interaction between coordinated and droop control PV inverters

    Peter Lusis (Monash University); Ariel Liebman (Monash University); Lachlan L. H. Andrew (University of Melbourne); Guido Tack (Monash University)

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  • PV Controller modifications and its Impact on Assisting PV Penetration

    Vishnu Arayamparambil Vinaya Mohanan (The University of Melbourne); Robin John Evans (The University of Melbourne); Iven Mareels (IBM Research Australia); Ramachandra Rao Kolluri (IBM Research Australia)

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  • A Photovoltaic System Investment Game for Assessing Network Hosting Capacity Allocations

    Yiju Ma (The University of Sydney); Daniel Gebbran (The University of Sydney); Archie Chapman (The University of Queensland); Gregor Verbic (The University of Sydney)

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  • Session 9: Energy Storage and Batteries

    Session Chair: Jia Liu (Iowa State University)

  • London Mirror 15:30-17:00 London | 22:30-0:00 HKT | 7:30-9:00 PDT | 10:30-12:00 EDT | 0:30-2:00 AEST

  • PDT Mirror 15:30-17:00 PDT | 23:30-1:00 London | 6:30-8:00 HKT | 18:30-20:00 EDT | 8:30-10:00 AEST

  • Economic Analysis of using Distributed Energy Storage for Frequency Regulation

    Nasir Mehmood (Lahore University of Management Sciences); Naveed Arshad (Lahore University of Management Sciences)

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  • Discrete and stochastic coalitional storage games (nominated)

    Diego Kiedanski (Télécom Paris); Ariel Orda (Technion); Daniel Kofman (Télécom Paris)

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  • Emission-aware Energy Storage Scheduling for a Greener Grid (nominated)

    Rishikesh Jha (University of Massachusetts Amherst); Stephen Lee (University of Pittsburgh); Srinivasan Iyengar (Microsoft Research India); Mohammad Hajiesmaili (University of Massachusetts Amherst); David Irwin (University of Massachusetts Amherst); Prashant Shenoy (University of Massachusetts, Amherst)

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  • Energy Storage as Public Asset

    Jiasheng Zhang (Tsinghua University); Nan Gu (Tsinghua University); Chenye Wu (Tsinghua University)

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  • Day 3 Q&A Social Session (Beta Session)

  • London Mirror 17:30-18:30 London | 0:30-1:30 HKT | 9:30-10:30 PDT | 12:30-13:30 EDT | 2:30-3:30 AEST

  • PDT Mirror 17:30-18:30 PDT | 1:30-2:30 London | 8:30-9:30 HKT | 20:30-21:30 EDT | 10:30-11:30 AEST

  • Friday, June 26, 2020

Please email the TPC Chairs Dan Wang and Ramesh Sitaraman with any questions you may have.

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