| 1 |
Bottom-up modelling methodology for urban-scale analysis of residential space heating demand response
Hedegaard RE, Kristensen MH, Pedersen TH, Brun A, Petersen S
Applied Energy, 242, 181, 2019 |
| 2 |
Data-driven classification of residential energy consumption patterns by means of functional connectivity networks
Markovic R, Gosak M, Grubelnik V, Marhl M, Virtic P
Applied Energy, 242, 506, 2019 |
| 3 |
Clustering district heat exchange stations using smart meter consumption data
Tureczek AM, Nielsen PS, Madsen H, Brun A
Energy and Buildings, 182, 144, 2019 |
| 4 |
A domestic operational rating for UK homes: Concept, formulation and application
Lomas KJ, Beizaee A, Allinson D, Haines VJ, Beckhelling J, Loveday DL, Porritt SM, Mallaband B, Morton A
Energy and Buildings, 201, 90, 2019 |
| 5 |
A combination of SOM-based operating time estimation and simplified disaggregation for SME buildings using hourly energy consumption data
Komatsu H, Kimura O
Energy and Buildings, 201, 118, 2019 |
| 6 |
Economic assessment of photovoltaic battery systems based on household load profiles
Schopfer S, Tiefenbeck V, Staake T
Applied Energy, 223, 229, 2018 |
| 7 |
Modeling hourly consumption of electricity and district heat in non-residential buildings
Kipping A, Tromborg E
Energy, 123, 473, 2017 |
| 8 |
Detection of non-technical losses in smart meter data based on load curve profiling and time series analysis
Villar-Rodriguez E, Del Ser J, Oregi I, Bilbao MN, Gil-Lopez S
Energy, 137, 118, 2017 |
| 9 |
A hybrid ICT-solution for smart meter data analytics
Liu XF, Nielsen PS
Energy, 115, 1710, 2016 |
| 10 |
Practical lognormal framework for household energy consumption modeling
Kuusela P, Norros I, Weiss R, Sorasalmi T
Energy and Buildings, 108, 223, 2015 |
