21 |
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 |
22 |
Making legacy thermal storage heating fit for the smart grid Boait PJ, Snape JR, Darby SJ, Hamilton J, Morris RJR Energy and Buildings, 138, 630, 2017 |
23 |
Vulnerability and resistance in the United Kingdom's smart meter transition Sovacool BK, Kivimaa P, Hielscher S, Jenkins K Energy Policy, 109, 767, 2017 |
24 |
Economics of household wind turbine grid-tied systems for five wind resource levels and alternative grid pricing rates Ghaith AF, Epplin FM, Frazier RS Renewable Energy, 109, 155, 2017 |
25 |
State estimation of medium voltage distribution networks using smart meter measurements Al-Wakeel A, Wu JZ, Jenkins N Applied Energy, 184, 207, 2016 |
26 |
A hybrid ICT-solution for smart meter data analytics Liu XF, Nielsen PS Energy, 115, 1710, 2016 |
27 |
Determining the relationship between a household's lifestyle and its electricity consumption in Japan by analyzing measured electric load profiles Ozawa A, Furusato R, Yoshida Y Energy and Buildings, 119, 200, 2016 |
28 |
An evidence based approach to determining residential occupancy and its role in demand response management Chaney J, Owens EH, Peacock AD Energy and Buildings, 125, 254, 2016 |
29 |
The British public's perception of the UK smart metering initiative: Threats and opportunities Buchanan K, Banks N, Preston I, Russo R Energy Policy, 91, 87, 2016 |
30 |
Shifting Boundary for price-based residential demand response and applications Xu FY, Zhang T, Lai LL, Zhou H Applied Energy, 146, 353, 2015 |