| 1 |
Knowledge discovery of data-driven-based fault diagnostics for building energy systems: A case study of the building variable refrigerant flow system
Liu JY, Li GN, Liu B, Li KN, Chen HX
Energy, 174, 873, 2019 |
| 2 |
Comparative study of posteriori decision-making methods when designing building integrated energy systems with multi-objectives
Jing R, Wang M, Zhang ZH, Liu J, Liang H, Meng C, Shah N, Li N, Zhao YR
Energy and Buildings, 194, 123, 2019 |
| 3 |
Comparison of clustering algorithms for the selection of typical demand days for energy system synthesis
Schutz T, Schraven MH, Fuchs M, Remmen P, Muller D
Renewable Energy, 129, 570, 2018 |
| 4 |
Multiobjective optimisation of energy systems and building envelope retrofit in a residential community
Wu R, Mavromatidis G, Orehounig K, Carmeliet J
Applied Energy, 190, 634, 2017 |
| 5 |
Robust scheduling of building energy system under uncertainty
Wang CS, Jiao BQ, Guo L, Tian Z, Niu JD, Li SW
Applied Energy, 167, 366, 2016 |
| 6 |
Modeling and simulation of the heating circuit of a multi-functional building
Sangi R, Baranski M, Oltmanns J, Streblow R, Muller D
Energy and Buildings, 110, 13, 2016 |
| 7 |
A general multi-agent control approach for building energy system optimization
Cai J, Kim D, Jaramillo R, Braun JE, Hu JH
Energy and Buildings, 127, 337, 2016 |
| 8 |
Fractional order models for system identification of thermal dynamics of buildings
Chen L, Basu B, McCabe D
Energy and Buildings, 133, 381, 2016 |
| 9 |
A comparison of thermal energy storage models for building energy system optimization
Schutz T, Streblow R, Muller D
Energy and Buildings, 93, 23, 2015 |
| 10 |
Implications of weighting factors on technology preference in net zero energy buildings
Noris F, Musall E, Salom J, Berggren B, Jensen SO, Lindberg K, Sartori I
Energy and Buildings, 82, 250, 2014 |
