Seasonal Effect on the Flexibility Assessment of Electrical Demand
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Gianfranco Chicco | Roberto Napoli | Intisar Ali Sajjad | Muhammad Waseem | G. Chicco | R. Napoli | M. Waseem | I. A. Sajjad
[1] O. K. Larsen,et al. Household electricity demand profiles – A high-resolution load model to facilitate modelling of energy flexible buildings , 2016 .
[2] Johanna L. Mathieu,et al. Uncertainty in the flexibility of aggregations of demand response resources , 2013, IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society.
[3] Brian Vad Mathiesen,et al. Comparative analyses of seven technologies to facilitate the integration of fluctuating renewable energy sources , 2009 .
[4] David E. Culler,et al. Flexible loads in future energy networks , 2013, e-Energy '13.
[5] Lieve Helsen,et al. Bottom-up Quantification Of The Flexibility Potential Of Buildings , 2013, Building Simulation Conference Proceedings.
[6] N. Menemenlis,et al. Thoughts on power system flexibility quantification for the short-term horizon , 2011, 2011 IEEE Power and Energy Society General Meeting.
[7] G. Chicco,et al. Characterisation of the aggregated load patterns for extraurban residential customer groups , 2004, Proceedings of the 12th IEEE Mediterranean Electrotechnical Conference (IEEE Cat. No.04CH37521).
[8] R. Newcombe. Two-sided confidence intervals for the single proportion: comparison of seven methods. , 1998, Statistics in medicine.
[9] Gianfranco Chicco,et al. Effect of aggregation level and sampling time on load variation profile — A statistical analysis , 2014, MELECON 2014 - 2014 17th IEEE Mediterranean Electrotechnical Conference.
[10] Saifur Rahman,et al. Development of physical-based demand response-enabled residential load models , 2013, IEEE Transactions on Power Systems.
[11] Enrico Carpaneto,et al. Probabilistic characterisation of the aggregated residential load patterns , 2008 .
[12] Regina Lamedica,et al. A bottom-up approach to residential load modeling , 1994 .
[13] Tyrone L. Vincent,et al. Potentials and Economics of Residential Thermal Loads Providing Regulation Reserve , 2014, ArXiv.
[14] Gianfranco Chicco,et al. A probabilistic approach to study the load variations in aggregated residential load patterns , 2014, 2014 Power Systems Computation Conference.
[15] Thomas Demeester,et al. Modeling and analysis of residential flexibility: Timing of white good usage , 2016 .
[16] Birgitte Bak-Jensen,et al. Probabilistic quantification of potentially flexible residential demand , 2014, 2014 IEEE PES General Meeting | Conference & Exposition.
[17] Luigi Martirano,et al. Flexibility assessment indicator for aggregate residential demand , 2017, 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe).
[18] L. Brown,et al. Interval Estimation for a Binomial Proportion , 2001 .
[19] Gianfranco Chicco,et al. Definitions of Demand Flexibility for Aggregate Residential Loads , 2016, IEEE Transactions on Smart Grid.
[20] Sean P. Meyn,et al. Ancillary Service to the Grid Through Control of Fans in Commercial Building HVAC Systems , 2014, IEEE Transactions on Smart Grid.
[21] Thomas E. Carroll,et al. Generalized aggregation and coordination of residential loads in a smart community , 2015, 2015 IEEE International Conference on Smart Grid Communications (SmartGridComm).
[22] Jianzhong Wu,et al. Flexible Demand in the GB Domestic Electricity Sector in 2030 , 2015 .
[23] R. Belhomme,et al. Evaluating and planning flexibility in sustainable power systems , 2013, 2013 IEEE Power & Energy Society General Meeting.