Adaptive User-Oriented Direct Load-Control of Residential Flexible Devices
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[1] Christos V. Verikoukis,et al. A Survey on Demand Response Programs in Smart Grids: Pricing Methods and Optimization Algorithms , 2015, IEEE Communications Surveys & Tutorials.
[2] Jin-ho Kim,et al. Common failures of demand response , 2011 .
[3] Hartmut Schmeck,et al. Modeling and Valuation of Residential Demand Flexibility for Renewable Energy Integration , 2017, IEEE Transactions on Smart Grid.
[4] Lingfeng Wang,et al. Autonomous Appliance Scheduling for Household Energy Management , 2014, IEEE Transactions on Smart Grid.
[5] Victor O. K. Li,et al. Maximizing aggregator profit through energy trading by coordinated electric vehicle charging , 2016, 2016 IEEE International Conference on Smart Grid Communications (SmartGridComm).
[6] Torben Bach Pedersen,et al. Dependency-based FlexOffers: scalable management of flexible loads with dependencies , 2016, e-Energy.
[7] Jesper Kjeldskov,et al. Aesthetic, Functional and Conceptual Provocation in Research Through Design , 2017, Conference on Designing Interactive Systems.
[8] Jiangfeng Zhang,et al. Optimal scheduling of household appliances for demand response , 2014 .
[9] Jiming Chen,et al. A Survey on Demand Response in Smart Grids: Mathematical Models and Approaches , 2015, IEEE Transactions on Industrial Informatics.
[10] Sousso Kelouwani,et al. Non-intrusive load monitoring through home energy management systems: A comprehensive review , 2017 .
[11] João P. S. Catalão,et al. Optimal Household Appliances Scheduling Under Day-Ahead Pricing and Load-Shaping Demand Response Strategies , 2015, IEEE Transactions on Industrial Informatics.
[12] Torben Bach Pedersen,et al. Aggregating and Disaggregating Flexibility Objects , 2012, IEEE Transactions on Knowledge and Data Engineering.
[13] Torben Bach Pedersen,et al. Generation and Evaluation of Flex-Offers from Flexible Electrical Devices , 2017, e-Energy.
[14] Chris Develder,et al. Quantifying flexibility in EV charging as DR potential: Analysis of two real-world data sets , 2016, 2016 IEEE International Conference on Smart Grid Communications (SmartGridComm).
[15] Geert Deconinck,et al. Potential of Active Demand Reduction With Residential Wet Appliances: A Case Study for Belgium , 2015, IEEE Transactions on Smart Grid.
[16] Torben Bach Pedersen,et al. Data management in the MIRABEL smart grid system , 2012, EDBT-ICDT '12.
[17] Fernando L. Alvarado,et al. Using utility information to calibrate customer demand management behavior models , 2002, 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309).
[18] Jan Schoormans,et al. A real-life assessment on the effect of smart appliances for shifting households’ electricity demand , 2015 .
[19] Bo Thiesson,et al. Towards Flexibility Detection in Device-Level Energy Consumption , 2014, DARE.
[20] Jasper Frunt,et al. Load shifting potential of the washing machine and tumble dryer , 2016, 2016 IEEE International Energy Conference (ENERGYCON).
[21] Torben Bach Pedersen,et al. Aggregating energy flexibilities under constraints , 2016, 2016 IEEE International Conference on Smart Grid Communications (SmartGridComm).
[22] Jesper Kjeldskov,et al. Washing with the Wind: A Study of Scripting towards Sustainability , 2018, Conference on Designing Interactive Systems.
[23] Torben Bach Pedersen,et al. Measuring and Comparing Energy Flexibilities , 2015, EDBT/ICDT Workshops.
[24] Na Li,et al. Optimal demand response based on utility maximization in power networks , 2011, 2011 IEEE Power and Energy Society General Meeting.
[25] Zhe Chen,et al. A novel technique to enhance demand responsiveness: An EV based test case , 2015, 2015 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC).
[26] Karl Aberer,et al. Electricity load forecasting for residential customers: Exploiting aggregation and correlation between households , 2013, 2013 Sustainable Internet and ICT for Sustainability (SustainIT).
[27] Vincent W. S. Wong,et al. Advanced Demand Side Management for the Future Smart Grid Using Mechanism Design , 2012, IEEE Transactions on Smart Grid.
[28] Salil S. Kanhere,et al. Can smart plugs predict electric power consumption?: a case study , 2014, MobiQuitous.
[29] Claire J. Tomlin,et al. Residential demand response targeting using machine learning with observational data , 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).
[30] Lingyang Song,et al. Residential Load Scheduling in Smart Grid: A Cost Efficiency Perspective , 2016, IEEE Transactions on Smart Grid.
[31] Wolf Fichtner,et al. Load-shifting potentials in households including electric mobility - A comparison of user behaviour with modelling results , 2013, 2013 10th International Conference on the European Energy Market (EEM).
[32] Mark W. Newman,et al. Making sustainability sustainable: challenges in the design of eco-interaction technologies , 2014, CHI.
[33] Bo Thiesson,et al. Evaluating the Value of Flexibility in Energy Regulation Markets , 2015, e-Energy.
[34] Jesper Kjeldskov,et al. HeatDial: Beyond User Scheduling in Eco-Interaction , 2016, NordiCHI.
[35] Shing-Chow Chan,et al. Demand Response Optimization for Smart Home Scheduling Under Real-Time Pricing , 2012, IEEE Transactions on Smart Grid.
[36] Gerard J. M. Smit,et al. Generation of flexible domestic load profiles to evaluate Demand Side Management approaches , 2016, 2016 IEEE International Energy Conference (ENERGYCON).