Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 222222
Loughborough University

Centre for Renewable Energy Systems Technology (CREST)

CREST Demand Model

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About

The CREST Demand Model is a high-resolution stochastic model of domestic thermal and electricity demand. The model produces one-minute resolution demand data, disaggregated by end-use, using a bottom-up modelling approach based on patterns of active occupancy and daily activity profiles derived from time-use survey data.

The model includes a representation of electrical demand and generation (appliances, lighting, and photovoltaics), resident occupancy, solar thermal collector, and thermal models including a low-order building thermal model, domestic hot water consumption, thermostat and timer controls and gas boilers.

The model has been validated and can be used to simulate demand of aggregations of dwellings such that dwelling diversity is duly represented and end-use demand appropriately correlated. The bottom-up development of the model allows changes in appliances and their usage patterns to be represented, allowing quantification of the impact of changes in technology, for example the introduction of more efficient technologies, the electrification of heat, and the impact of demand response, in terms of changes in the timing of occupant activities.

The model has been developed primarily for low-voltage network analysis and the model’s ability to account for demand diversity is of critical importance for this application. The model, however, can also serve as a basis for modelling domestic energy demands within the broader field of urban energy systems analysis.

The model is an open-source development in Excel VBA and is freely available to download for users to configure and extend, or to incorporate into other models.

Download

The model has been developed as a Microsoft Excel work book and has been made available for free. The latest version of the model can be downloaded below.

CREST Demand Model »
(Figshare)

License

This model is open source software and publicly available. It is published under GNU General Public License 3 (http://www.gnu.org/licenses/). The license guarantees you the freedoms to use, study, share (copy), and modify the software. It is a copyleft license, which means that you can distribute derived works only under the same license terms.

Citation

If you use this model for academic research please cite the following paper in your work:

Eoghan McKenna and Murray Thomson. 2016. High-resolution stochastic integrated thermal-electrical domestic demand model. Applied Energy, 165:445. http://dx.doi.org/10.1016/j.apenergy.2015.12.089

CREST demand screenshot

High-level architecture of the model.

 

CREST demand screenshot

Example simulation output of the model for a single day, showing appropriate correlation between variables.

 

CREST demand screenshot

Screenshot of the Excel workbook.

 

The model has been extensively documented in the following publications:

McKenna E., Thomson M. 2016. High-resolution stochastic integrated thermal-electrical domestic demand model. Applied Energy, 165:445. http://dx.doi.org/10.1016/j.apenergy.2015.12.089.

McKenna E., Krawczynski M., Thomson M. 2015. Four-state domestic building occupancy model for energy demand simulations. Energy and Buildings, 96:30. http://dx.doi.org/10.1016/j.enbuild.2015.03.013.

Richardson I., Thomson M. 2013. Integrated simulation of photovoltaic micro-generation and domestic electricity demand: a one-minute resolution open-source model, Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 227 73-81. http://dx.doi.org/10.1177/0957650912454989.

Richardson I. 2010. Integrated High-resolution Modelling of Domestic Electricity Demand and Low Voltage Electricity Distribution Networks (PhD Thesis). Loughborough University. (2010) Available from: https://dspace.lboro.ac.uk/2134/7968.

Richardson I., Thomson M., Infield D., Clifford C. 2010. Domestic electricity use: A high-resolution energy demand model, Energy and Buildings 42 1878-1887. http://dx.doi.org/10.1016/j.enbuild.2010.05.023.

Richardson I., Thomson M., Infield D., Delahunty A. 2009. Domestic lighting: A high-resolution energy demand model, Energy and Buildings 41 781-789. http://dx.doi.org/10.1016/j.enbuild.2009.02.010.

Richardson I., Thomson M., Infield D. 2008. A high-resolution domestic building occupancy model for energy demand simulations, Energy and Buildings 40 1560–1566. http://dx.doi.org/10.1016/j.enbuild.2008.02.006.

The following institutions have cited or used the model in their research (from Scopus as of 19th April 2016):

  • Aalborg University
  • Aalto University
  • Advanced Digital Sciences Center
  • Alstom Grid Ltd
  • Anna University
  • Anvil Semiconductors Ltd
  • Aristotle University of Thessaloniki
  • Arizona State University
  • Arup
  • Athens University of Economics and Business
  • Austrian Institute of Technology
  • Autodesk Research
  • Brunel University
  • Cardiff University
  • Carleton University
  • Catalonia Institute for Energy Research
  • CentraleSupelec
  • Centre for Renewable Energy Sources and Saving
  • Centre for Research and Technology Hellas
  • Changsha University of Science and Technology
  • Chinese Academy of Sciences
  • City University London
  • Columbia University
  • Concordia University
  • Converter Technology Ltd
  • Coventry University
  • Cranfield University
  • CSIRO Ecosystem Sciences
  • Daidalos Peutz bouwfysisch ingenieursbureau
  • De Montfort University
  • Deakin University
  • Denso IT Laboratory
  • DNV GL
  • DTU-Technical University of Denmark
  • Dublin Institute of Technology
  • E3S SUPELEC Systems Sciences
  • Ecole Centrale Paris
  • Ecole Nationale Superieure de Creation Industrielle
  • École Polytechnique de Montréal
  • Ecole Polytechnique Fédérale de Lausanne
  • EDF R&D
  • Eindhoven University of Technology
  • Electricity North West Ltd
  • ENEA
  • EnergyVille
  • EPFL
  • ESIEE
  • ESTIA
  • ETH Zurich
  • Federal University of Western Pará
  • Fraunhofer Institute
  • Gartenmann Engineering
  • Georgia Institute of Technology
  • Glasgow Caledonian University
  • Glasgow School of Art
  • Global Action Plan
  • Hamburg University of Technology
  • Hebei United University
  • Helmut-Schmidt-University,
  • Heriot-Watt University
  • HES-SO Valais
  • Huazhong University of Science and Technology
  • Hunan University
  • IBM Research
  • IMDEA Energy Institute
  • Imperial College
  • Information Technologies Institute
  • Inhouse Engineering GmbH
  • Inst. of Informatics and Telematics - Italian National Research Council
  • Institute for Energy Technology
  • Institute for Infocomm Research
  • Italian National Research Council
  • Karlsruhe Institute of Technology
  • King Saud University
  • King's College
  • Klinik Facility-Management Eppendorf GmbH
  • KTH Royal Institute of Technology
  • KU Leuven
  • Kyung Hee University
  • Lahore University of Management Science
  • Lawrence Berkeley National Laboratory
  • Linköping University
  • London School of Hygiene and Tropical Medicine
  • Midwest Independent Transmission System Operator
  • Mines ParisTech
  • MIT
  • MSR-INIRA Joint Centre
  • Nanyang Technological University
  • National Institute of Informatics
  • National Institute of Standards and Technology
  • National Technical University of Athens
  • Navetas Energy Management Ltd
  • Newcastle University
  • North Carolina State University
  • North China Electric Power University
  • Northumbria University
  • Norwegian University of Science and Technology
  • Oak Ridge National Laboratory
  • Ohio State University
  • Osaka University
  • Ostfalia University of Applied Science
  • Paris Research and Innovation Center, Technicolor
  • Polytechnic of Turin
  • Prairie View A&M University
  • Princeton University
  • PSA Peugeot Citron
  • Public University of Navarre
  • Purdue University
  • Qatar Environment and Energy Research Institute
  • Rensselaer Polytechnic Institute
  • Riga Technical University
  • RMIT University
  • Rochester Institute of Technology
  • RWTH Aachen University
  • Singapore University of Technology and Design
  • SINTEF Building and Infrastructure
  • Southeast University
  • SP Technical Research Institute of Sweden
  • SSE
  • State Grid AC Project Construction Co
  • State University of New York at Stony Brook
  • Sungkyunkwan University
  • Swiss Center for Electronics and Microtechnology
  • Tallinn University of Technology
  • Tampere University of Technology
  • Technical University 'Gheorghe Asachi' of Iasi
  • Technical University of Denmark
  • Technical University of Lisbon
  • Technological Education Institute of Athens
  • Texas A & M University at Qatar
  • The State University of New Jersey
  • Tongji University
  • Towson University
  • Toyota Technological Institute at Chicago
  • Tshwane University of Technology
  • Tshwane University of Technology
  • Tsinghua University
  • UC Berkeley
  • Universidad Autónoma del Estado de Morelos
  • Universidad de Córdoba
  • Universidad de La Laguna
  • Universidade de Lisboa
  • Universidade Federal Do Rio Grande- Furg
  • Universidade Nova de Lisboa
  • Università Degli Studi Del Sannio
  • Università degli Studi eCampus
  • Università di Padova
  • Universita Politecnica delle Marche
  • Universitat Politècnica de Catalunya
  • University College Dublin
  • University College London
  • University of Aberdeen
  • University of Alberta
  • University of Aveiro
  • University of Basra
  • University of Bath
  • University of Birmingham
  • University of Cagliari
  • University of California, Santa Barbara
  • University of Cambridge
  • University of Coimbra
  • University of Colorado
  • University of Edinburgh
  • University of Exeter
  • University of Florida
  • University of Greenwich
  • University of Grenoble
  • University of Guelph
  • University of Leeds
  • University of Liege
  • University of Liverpool
  • University of Manchester
  • University of Mons
  • University of Nebraska-Lincoln
  • University of New South Wales
  • University of North Texas
  • University of Nottingham
  • University of Oldenburg
  • University of Otago
  • University of Oxford
  • University of Palermo
  • University of Pisa
  • University of Pretoria
  • University of Reading
  • University of Regina
  • University of Salerno
  • University of Southampton
  • University of Southern California
  • University of Southern Denmark
  • University of Strathclyde
  • University of Surrey
  • University of Tennessee
  • University of Texas at San Antonio
  • University of the Basque Country
  • University of the Philippines
  • University of Thessaly
  • University of Tokyo
  • University of Toledo
  • University of Ulm
  • University of Waterloo
  • University of Zaragoza
  • Uppsala University
  • Vienna University of Technology
  • Viginia Tech
  • Vrije Universiteit Brussel
  • Western Power Distribution
  • Wuhan University of Technology
  • Xi'An Jiaotong University
  • Yeungnam University
  • Zhejiang University

The following is a list of academic citations of the model (from Scopus as of 19th April 2016):

Adolph, M., Kopmann, N., Lupulescu, B. & Müller, D. 2014, "Adaptive control strategies for single room heating", Energy and Buildings, vol. 68, no. PART C, pp. 771-778.

Aerts, D., Minnen, J., Glorieux, I., Wouters, I. & Descamps, F. 2014, "A method for the identification and modelling of realistic domestic occupancy sequences for building energy demand simulations and peer comparison", Building and Environment, vol. 75, pp. 67-78.

Ahmadi-Karvigh, S., Becerik-Gerber, B. & Soibelman, L. 2016, "A framework for allocating personalized appliance-level disaggregated electricity consumption to daily activities", Energy and Buildings, vol. 111, pp. 337-350.

Ahmed, K., Pylsy, P. & Kurnitski, J. 2015, "Monthly domestic hot water profiles for energy calculation in Finnish apartment buildings", Energy and Buildings, vol. 97, pp. 77-85.

Ahn, K.-. & Park, C.-. 2016, "Correlation between occupants and energy consumption", Energy and Buildings, vol. 116, pp. 420-433.

Al-Daraiseh, A., El-Qawasmeh, E. & Shah, N. 2015, "Multi-agent system for energy consumption optimisation in higher education institutions", Journal of Computer and System Sciences, vol. 81, no. 6, pp. 958-965.

Al-Salim, K., Andonovic, I. & Michie, C. 2015, "A finite state based residential demand generator for scarce statistical data scenarios", 2015 6th International Renewable Energy Congress, IREC 2015.

Alzate, E.B., Mallick, N.H. & Xie, J. 2014, "A high-resolution smart home power demand model and future impact on load profile in Germany", Conference Proceeding - 2014 IEEE International Conference on Power and Energy, PECon 2014, pp. 53.

Ancillotti, E., Bruno, R. & Conti, M. 2014, "Smoothing peak demands through aggregate control of background electrical loads", 2014 IEEE PES Innovative Smart Grid Technologies Conference, ISGT 2014.

Ancillotti, E., Bruno, R., Crisostomi, E. & Tucci, M. 2015, "Using electric vehicles to improve building energy sustainability", 2014 IEEE International Electric Vehicle Conference, IEVC 2014.

Ancillotti, E., Bruno, R., Crisostomi, E., Tucci, M. & Conti, M. 2015, "EnergyTest: A tool for assessing building energy sustainability", IEEE PES Innovative Smart Grid Technologies Conference Europe.

Andersen, P.D., Iversen, A., Madsen, H. & Rode, C. 2014, "Dynamic modeling of presence of occupants using inhomogeneous Markov chains", Energy and Buildings, vol. 69, pp. 213-223.

Angrisani, G., Canelli, M., Roselli, C. & Sasso, M. 2015, "Integration between electric vehicle charging and micro-cogeneration system", Energy Conversion and Management, vol. 98, pp. 115-126.

Angrisani, G., Canelli, M., Roselli, C. & Sasso, M. 2015, "Microcogeneration in buildings with low energy demand in load sharing application", Energy Conversion and Management, vol. 100, pp. 78-89.

Arif, M.T., Oo, A.M.T. & Stojcevski, A. 2014, "An investigation for improved home energy management", 2014 Australasian Universities Power Engineering Conference, AUPEC 2014 - Proceedings.

Arshad, N., Ali, U. & Javed, F. 2013, "A highly configurable simulator for assessing energy usage", Energy Procedia, pp. 308.

Babaei, T., Abdi, H., Lim, C.P. & Nahavandi, S. 2015, "A study and a directory of energy consumption data sets of buildings", Energy and Buildings, vol. 94, pp. 91-99.

Bajada, J., Fox, M. & Long, D. 2013, "Load modelling and simulation of household electricity consumption for the evaluation of demand-side management strategies", 2013 4th IEEE/PES Innovative Smart Grid Technologies Europe, ISGT Europe 2013.

Bao, H. & Lu, R. 2015, "A new differentially private data aggregation with fault tolerance for smart grid communications", IEEE Internet of Things Journal, vol. 2, no. 3, pp. 248-258.

Baptista, M., Fang, A., Prendinger, H., Prada, R. & Yamaguchi, Y. 2014, "Accurate household occupant behavior modeling based on data mining techniques", Proceedings of the National Conference on Artificial Intelligence, pp. 1164.

Bayram, I.S., Abdallah, M., Tajer, A. & Qaraqe, K. 2015, "Energy storage sizing for peak hour utility applications", IEEE International Conference on Communications, pp. 770.

Bellido-Outeiriño, F.J., Flores-Arias, J.M., Liñan-Reyes, M., Palacios-García, E.J. & Luna-Rodríguez, J.J. 2013, "Wireless sensor network and stochastic models for household power management", IEEE Transactions on Consumer Electronics, vol. 59, no. 3, pp. 483-491.

Bertocco, M., Giorgi, G. & Narduzzi, C. 2013, "Power profile generator for the test of microgrid measurement and control systems", 19th IMEKO TC4 Symposium - Measurements of Electrical Quantities 2013 and 17th International Workshop on ADC and DAC Modelling and Testing, pp. 166.

Bobmann, T. & Staffell, I. 2015, "The shape of future electricity demand: Exploring load curves in 2050s Germany and Britain", Energy, vol. 90, pp. 1317-1333.

Bondu, A. & Dachraoui, A. 2015, "Realistic and very fast simulation of individual electricity consumptions", Proceedings of the International Joint Conference on Neural Networks.

Botsis, V., Doulamis, N.D. & Varvarigos, E. 2016, "Fair pricing mechanism for coalitions in rural areas", Proceedings - IEEE Symposium on Computers and Communications, pp. 83.

Bruninx, K., Patteeuw, D., Delarue, E., Helsen, L. & D'Haeseleer, W. 2013, "Short-term demand response of flexible electric heating systems: The need for integrated simulations", International Conference on the European Energy Market, EEM.

Cai, H., Hutter, A., Olivero, E., Roduit, P. & Ferrez, P. 2015, "Load shifting for tertiary control power provision", International Conference on Power Engineering, Energy and Electrical Drives, pp. 469.

Candanedo, L.M. & Feldheim, V. 2016, "Accurate occupancy detection of an office room from light, temperature, humidity and CO2 measurements using statistical learning models", Energy and Buildings, vol. 112, pp. 28-39.

Cao, H.-., Wijaya, T.K. & Aberer, K. 2014, "Estimating human interactions with electrical appliances for activity-based energy savings recommendations", BuildSys 2014 - Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings, pp. 206.

Cao, S. & Sirén, K. 2014, "Impact of simulation time-resolution on the matching of PV production and household electric demand", Applied Energy, vol. 128, pp. 192-208.

Caputo, P., Gaia, C. & Zanotto, V. 2013, "A methodology for defining electricity demand in energy simulations referred to the italian context", Energies, vol. 6, no. 12, pp. 6274-6292.

Chen, Z., Xu, J. & Soh, Y.C. 2015, "Modeling regular occupancy in commercial buildings using stochastic models", Energy and Buildings, vol. 103, pp. 216-223.

Christiansen, N., Kaltschmitt, M., Dzukowski, F. & Isensee, F. 2015, "Electricity consumption of medical plug loads in hospital laboratories: Identification, evaluation, prediction and verification", Energy and Buildings, vol. 107, pp. 392-406.

Ciabattoni, L., Ferracuti, F., Grisostomi, M., Ippoliti, G. & Longhi, S. 2015, "Fuzzy logic based economical analysis of photovoltaic energy management", Neurocomputing, vol. 170, pp. 296-305.

Ciabattoni, L., Grisostomi, M., Ippoliti, G. & Longhi, S. 2015, Household Electrical Consumptions Modeling and Management Through Neural Networks and Fuzzy Logic Approaches.

Ciabattoni, L., Grisostomi, M., Ippoliti, G. & Longhi, S. 2014, "Fuzzy logic home energy consumption modeling for residential photovoltaic plant sizing in the new Italian scenario", Energy, vol. 74, no. 1, pp. 359-367.

Ciabattoni, L., Grisostomi, M., Ippoliti, G. & Longhi, S. 2014, "Home energy management benefits evaluation through fuzzy logic consumptions simulator", Proceedings of the International Joint Conference on Neural Networks, pp. 1447.

Ciabattoni, L., Grisostomi, M., Ippoliti, G. & Longhi, S. 2013, "A Fuzzy Logic tool for household electrical consumption modeling", IECON Proceedings (Industrial Electronics Conference), pp. 8022.

Ciabattoni, L., Grisostomi, M., Ippoliti, G., Longhi, S. & Bonci, A. 2014, "Fuzzy logic simulator for energy management algorithms testing", MESA 2014 - 10th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, Conference Proceedings.

Clarke, J.A. & Hensen, J.L.M. 2015, "Integrated building performance simulation: Progress, prospects and requirements", Building and Environment, vol. 91, pp. 294-306.

Collin, A.J., Tsagarakis, G., Kiprakis, A.E. & McLaughlin, S. 2014, "Development of low-voltage load models for the residential load sector", IEEE Transactions on Power Systems, vol. 29, no. 5, pp. 2180-2188.

Cooper, S.J.G., Hammond, G.P., McManus, M.C. & Pudjianto, D. 2016, "Detailed simulation of electrical demands due to nationwide adoption of heat pumps, taking account of renewable generation and mitigation", IET Renewable Power Generation, vol. 10, no. 3, pp. 380-387.

Cooper, S.J.G., Hammond, G.P., McManus, M.C., Ramallo-Gonzlez, A. & Rogers, J.G. 2014, "Effect of operating conditions on performance of domestic heating systems with heat pumps and fuel cell micro-cogeneration", Energy and Buildings, vol. 70, pp. 52-60.

Cooper, S.J.G., Hammond, G.P., McManus, M.C. & Rogers, J.G. 2014, "Impact on energy requirements and emissions of heat pumps and micro-cogenerators participating in demand side management", Applied Thermal Engineering, vol. 71, no. 2, pp. 872-881.

Cottone, P., Gaglio, S., Lo Re, G. & Ortolani, M. 2015, "User activity recognition for energy saving in smart homes", Pervasive and Mobile Computing, vol. 16, no. PA, pp. 156-170.

D'Agostino, R., Baumann, L., Damiano, A. & Boggasch, E. 2015, "A Vanadium-Redox-Flow-Battery Model for Evaluation of Distributed Storage Implementation in Residential Energy Systems", IEEE Transactions on Energy Conversion, vol. 30, no. 2, pp. 421-430.

Dang, X.-., Petit, M. & Codani, P. 2015, "Energy optimization in an eco-district with electric vehicles smart charging", 2015 IEEE Eindhoven PowerTech, PowerTech 2015.

Dang, X.-., Petit, M. & Codani, P. 2015, "Transformer operating conditions under introduction of PV and EVs in an eco-district", IEEE Power and Energy Society General Meeting.

Dǎnilǎ, E. & Lucache, D.D. 2014, "Runtime optimization of hybrid energy source from an UPS back-upping critical consumer", 2014 International Conference on Optimization of Electrical and Electronic Equipment, OPTIM 2014, pp. 661.

Dar, U.I., Georges, L., Sartori, I. & Novakovic, V. 2015, "Influence of occupant’s behavior on heating needs and energy system performance: A case of well-insulated detached houses in cold climates", Building Simulation, vol. 8, no. 5, pp. 499-513.

Dar, U.I., Sartori, I., Georges, L. & Novakovic, V. 2014, "Advanced control of heat pumps for improved flexibility of Net-ZEB towards the grid", Energy and Buildings, vol. 69, pp. 74-84.

De Coninck, R., Baetens, R., Saelens, D., Woyte, A. & Helsen, L. 2014, "Rule-based demand-side management of domestic hot water production with heat pumps in zero energy neighbourhoods", Journal of Building Performance Simulation, vol. 7, no. 4, pp. 271-288.

Deng, R., Yang, Z., Chen, J., Asr, N.R. & Chow, M.-. 2014, "Residential energy consumption scheduling: A coupled-constraint game approach", IEEE Transactions on Smart Grid, vol. 5, no. 3, pp. 1340-1350.

Dong, B., Li, Z. & McFadden, G. 2015, "An investigation on energy-related occupancy behavior for low-income residential buildings", Science and Technology for the Built Environment, vol. 21, no. 6, pp. 892-901.

Donohoe, M., Jennings, B. & Balasubramaniam, S. 2013, "Context-aware microgrid storage using electric cars", 2013 4th IEEE/PES Innovative Smart Grid Technologies Europe, ISGT Europe 2013.

Erseghe, T., Zanella, A. & Codemo, C.G. 2014, "Optimal and compact control policies for energy storage units with single and multiple batteries", IEEE Transactions on Smart Grid, vol. 5, no. 3, pp. 1308-1317.

Fan, H., MacGill, I.F. & Sproul, A.B. 2015, "Statistical analysis of driving factors of residential energy demand in the greater Sydney region, Australia", Energy and Buildings, vol. 105, pp. 9-25.

Farzan, F., Jafari, M.A., Gong, J., Farzan, F. & Stryker, A. 2015, "A multi-scale adaptive model of residential energy demand", Applied Energy, vol. 150, pp. 258-273.

Fazeli, A. & Gillott, M. 2013, "Analysing the effects of seasonal variation on occupancy in an electricity demand model", International Journal of Low-Carbon Technologies, vol. 8, no. 4, pp. 282-288.

Fazeli, A., Sumner, M., Christopher, E. & Johnson, M. 2014, "Power flow control for power and voltage management in future smart energy communities", IET Conference Publications.

Fazeli, A., Sumner, M., Johnson, C.M. & Christopher, E. 2015, "Investigating the impact of varying the number of distributed energy resources on controlling the power flow within a microgrid", IEEE Power and Energy Society General Meeting.

Fazeli, A., Sumner, M., Johnson, C.M. & Christopher, E. 2015, "Investigating the impact of varying the number of distributed energy resources on controlling the power flow within a microgrid", 2015 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2015.

Fazeli, A., Sumner, M., Johnson, M.C. & Christopher, E. 2015, "Real-time deterministic power flow control through dispatch of distributed energy resources", IET Generation, Transmission and Distribution, vol. 9, no. 16, pp. 2724-2735.

Feng, X., Yan, D. & Hong, T. 2015, "Simulation of occupancy in buildings", Energy and Buildings, vol. 87, pp. 348-359.

Fischer, D., Härtl, A. & Wille-Haussmann, B. 2015, "Model for electric load profiles with high time resolution for German households", Energy and Buildings, vol. 92, pp. 170-179.

Fischer, D., Scherer, J., Flunk, A., Kreifels, N., Byskov-Lindberg, K. & Wille-Haussmann, B. 2015, "Impact of HP, CHP, PV and EVs on households' electric load profiles", 2015 IEEE Eindhoven PowerTech, PowerTech 2015.

Ford, R., McCulloch, M., Helfer, T. & Surrall, S. 2013, "Suricatta: A platform to model smart grid technologies in the distribution system", 2013 4th IEEE/PES Innovative Smart Grid Technologies Europe, ISGT Europe 2013.

Freeman, J., Hellgardt, K. & Markides, C.N. 2015, "An assessment of solar-powered organic Rankine cycle systems for combined heating and power in UK domestic applications", Applied Energy, vol. 138, pp. 605-620.

Garg, V.K., Jayram, T.S. & Narayanaswamy, B. 2013, "Online optimization with dynamic temporal uncertainty: Incorporating short term predictions for renewable integration in intelligent energy systems", Proceedings of the 27th AAAI Conference on Artificial Intelligence, AAAI 2013, pp. 1291.

Gehsbargs, A., Laicane, I., Blumberga, D. & Blumberga, A. 2015, "Application of Markov chain approach in simulation and analysis of domestic electricity consumption in Latvia", APLIMAT 2015 - 14th Conference on Applied Mathematics, Proceedings, pp. 309.

Gelegenis, J.J., Harris, D., Diakoulaki, D., Lampropoulou, H. & Giannakidis, G. 2015, "Determination of fixed expenses in central heating costs allocation: An arising issue of dispute", Management of Environmental Quality, vol. 26, no. 6, pp. 810-825.

Gkatzikis, L., Iosifidis, G., Koutsopoulos, I. & Tassiulas, L. 2015, "Collaborative placement and sharing of storage resources in the Smart Grid", 2014 IEEE International Conference on Smart Grid Communications, SmartGridComm 2014, pp. 103.

Gonzalez De Durana, J.M., Barambones, O., Kremers, E. & Varga, L. 2014, "Agent based modeling of energy networks", Energy Conversion and Management, vol. 82, pp. 308-319.

Good, N., Karangelos, E., Navarro-Espinosa, A. & Mancarella, P. 2015, "Optimization under Uncertainty of Thermal Storage-Based Flexible Demand Response with Quantification of Residential Users' Discomfort", IEEE Transactions on Smart Grid, vol. 6, no. 5, pp. 2333-2342.

Good, N., Martínez Ceseña, E.A., Zhang, L. & Mancarella, P. 2016, "Techno-economic and business case assessment of low carbon technologies in distributed multi-energy systems", Applied Energy, vol. 167, pp. 158-172.

Good, N., Navarro-Espinosa, A., Mancarella, P. & Karangelos, E. 2013, "Participation of electric heat pump resources in electricity markets under uncertainty", International Conference on the European Energy Market, EEM.

Good, N., Zhang, L., Navarro-Espinosa, A. & Mancarella, P. 2015, "High resolution modelling of multi-energy domestic demand profiles", Applied Energy, vol. 137, pp. 193-210.

Good, N., Zhang, L., Navarro-Espinosa, A. & Mancarella, P. 2013, "Physical modeling of electro-thermal domestic heating systems with quantification of economic and environmental costs", IEEE EuroCon 2013, pp. 1164.

Granell, R., Axon, C.J. & Wallom, D.C.H. 2015, "Impacts of Raw Data Temporal Resolution Using Selected Clustering Methods on Residential Electricity Load Profiles", IEEE Transactions on Power Systems, vol. 30, no. 6, pp. 3217-3224.

Gruber, J.K., Jahromizadeh, S., Prodanović, M. & Rakočević, V. 2014, "Application-oriented modelling of domestic energy demand", International Journal of Electrical Power and Energy Systems, vol. 61, pp. 656-664.

Gu, W., Wu, Z., Bo, R., Liu, W., Zhou, G., Chen, W. & Wu, Z. 2014, "Modeling, planning and optimal energy management of combined cooling, heating and power microgrid: A review", International Journal of Electrical Power and Energy Systems, vol. 54, pp. 26-37.

Guerra, G. & Martinez-Velasco, J.A. 2016, "Optimum allocation of distributed generation in multi-feeder systems using long term evaluation and assuming voltage-dependent loads", Sustainable Energy, Grids and Networks, vol. 5, pp. 13-26.

Guo, W. & Ullah, T. 2015, "Deployment of a load simulator in simulating residential household appliances", ICNSC 2015 - 2015 IEEE 12th International Conference on Networking, Sensing and Control, pp. 570.

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