One can draw up a typical electrical demand profile for a rural household and use this in a simulation type model. By shifting the loads in the mornings and evenings for one simulation, a number can be added, while noise can be added to the profile graphs to make it more natural.

A more realistic way is to use datalogged data of energy consumption patterns from a metering website or an onsite metering and weathers station solution. There are a number of rural schools and rural clinics that operate off-grid and these installations are typically fitted with a wireless remote monitoring and metering solution that saves the solar power generation and wind patterns for the site, see link below

http://www.meteocontrol.com/en/industrial-line/portals/safersun-professional/

With the Energylens platform, one can build demand profiles such as those illustrated on this link below

http://www.energylens.com/outputs

trust this helps

FC

I am not sure but you may try World Energy Council (WEC) publications.

Truly yours

karbassi

Perhaps if you contact some national energy producers and explain your motive, they may we willing to share some data for some locations that are on the grid or where the national energy service has decided to invest in some off-grid supply. Get the names of the energy services provider, then email wherever you can through the site that seems relevant, and use the names of the companies/organizations to search LinkedIn for people who work for them who may have authority to find someone with authority to release such data. 

Not sure whether it might be worth trying to cobble together some Spanish or Portuguese requests or if a better-written request in English would be better. Just some thoughts. With a decent process you risk as much as a few hours for unknown gain.

One can draw up a typical electrical demand profile for a rural household and use this in a simulation type model. By shifting the loads in the mornings and evenings for one simulation, a number can be added, while noise can be added to the profile graphs to make it more natural.

A more realistic way is to use datalogged data of energy consumption patterns from a metering website or an onsite metering and weathers station solution. There are a number of rural schools and rural clinics that operate off-grid and these installations are typically fitted with a wireless remote monitoring and metering solution that saves the solar power generation and wind patterns for the site, see link below

http://www.meteocontrol.com/en/industrial-line/portals/safersun-professional/

With the Energylens platform, one can build demand profiles such as those illustrated on this link below

http://www.energylens.com/outputs

trust this helps

FC

To all the question followers, I found this interesting Combined Cycle Power Plant Data Set for Download: Data Folder, Data Set Description form Pınar Tüfekci and Heysem Kaya

https://archive.ics.uci.edu/ml/datasets/Combined+Cycle+Power+Plant#

The same UCI Machine Learning Repository also includes an Individual household electric power consumption Data Set Download: Data Folder, Data Set Description by Georges Hebrail and Alice Barard

http://archive.ics.uci.edu/ml/datasets/Individual+household+electric+power+consumption#

and the same with plotting procedures

https://rpubs.com/dmaurath/24642

https://github.com/rdpeng/ExData_Plotting1

Although not for rural villages and household users, there is also some electricity load demand side data on Matlab 

http://www.mathworks.com/matlabcentral/fileexchange/31877-electricity-load-forecasting-for-the-australian-market-case-study/content/Load/html/LoadScriptNN_aus.html

regards

Gerro

Oliver Parson works in the same field and offer some valuable links on household energy consumption data and breaking this up into individual appliances,  Non-intrusive Appliance Load Monitoring (NIALM) or energy disaggregation 

http://blog.oliverparson.co.uk/2012/06/public-data-sets-for-nialm.html

http://www.mendeley.com/groups/2720021/oliver-parson-s-nialm-library/

Dataset links include the Reference Energy Disaggregation Dataset (REDD) corpus http://redd.csail.mit.edu/

The Building-Level labeled Electricity Disaggregation dataset (BLUED)  http://nilm.cmubi.org/

The UMASS Smart  Home Data Set and repository http://traces.cs.umass.edu/index.php/Smart/Smart

The tracebase repository on individual appliance data https://www.tracebase.org/

The Pecan Street Research Institute databases http://www.pecanstreet.org/

The Almanac of Minutely Power Dataset (AMPds) http://ampds.org/

WikiEnergy data https://dataport.pecanstreet.org/

Berkeley Energy Disaggregation Data Set (BERDS) http://www.eecs.berkeley.edu/~maasoumy/

This may help also.

Researchers at MIT led the way by releasing The Reference Energy Disaggregation Data Set (REDD) in 2011, J. Zico Kolter and Matthew J. Johnson. REDD, A Public Data Set for Energy Disaggregation Research. In SustKDD workshop on Data Mining Applications in Sustainability.

Smart, An Open Data Set and Tools for Enabling Research in Sustainable Homes . Sean Barker, Aditya Mishra, David Irwin, Emmanuel Cecchet, Prashant Shenoy, J. A. Smart*: An Open Data Set and Tools for Enabling Research in Sustainable Homes. In Proceedings of the 2012 Workshop on Data Mining Applications in Sustainability, 2012.

Pecan Street (Institution), Free Sample Data Set, Pecan Street Research Institute Expands Access to World-Class Energy Use Data to Global University

Researchers (2013). URL http://bit.ly/17t3Ght.

Makonin, S., Popowich, F., Bartram, L., Gill, B. & Bajic, I. V. AMPds: A Public Dataset for Load Disaggregation and Eco-Feedback Research. In The Annual Electrical Power and Energy Conference (EPEC), 1–6 (2013).

Hebrail, G. & Berard, A. Individual household electric power consumption Data Set (2012). URL http://bit.ly/1byLbr0

Kelly, J. & Knottenbelt, W. UKERC Energy Data Centre 18 (2014)

FC

Gerro

Interesting load profiles from disaggregated smartmeter data would also be valuable

http://www.smartmeters.vic.gov.au/about-smart-meters/reports-and-consultations/advanced-metering-infrastructure-customer-impacts-study-volume-2/appendix-e-confidence-intervals-around-electricity-usage-profiles

Ine can also find very interesting information in rural electricity and heat load profiles from a google or bing image search using the phrase

hourly load profile throughout a year

Finally I recommend reading 

Benefits of Decentralised Production of Heat and Power for small energy consumers in the spotlight

http://www.cogeneurope.eu/benefits-of-decentralised-production-of-heat-and-power-for-small-energy-consumers-in-the-spotlight_282293.html

as it provides valuable insights into autonomous and stand-alone remote energy systems, off-grid rural power systems and combined cycle cogeneration heat and power systems (CHP and CCHP) such as in your project. 

FC

This is a good idea. 

I also found another Smart Residential Load Simulator for Energy Management in Smart Grids

https://uwaterloo.ca/power-energy-systems-group/sites/ca.power-energy-systems-group/files/uploads/files/srls.pdf

and a Smart-grid-emulator with Linked Data Generator for emulating data circulation in the Smart Grid

https://code.google.com/p/smart-grid-emulator/wiki/DataGeneration

open energy data

https://blog.semantic-web.at/2012/04/13/reegle-info-linked-open-energy-data-cloud/

Readers may also find this paper interesting

Scoping exercise to determine load profile archetype reference shapes for solar co-generation models in isolated off-grid rural African villages

https://www.researchgate.net/publication/306098038_Scoping_exercise_to_determine_load_profile_archetype_reference_shapes_for_solar_co-generation_models_in_isolated_off-grid_rural_African_villages

The dataset with rural energy consumption data to download excel spreadsheet is on this link

Scoping Rural Load Profile Electricity n Hot Water Energy Profile Reference Datasets and Excel Data Corpus

https://www.researchgate.net/publication/307509610_Scoping_Rural_Load_Profile_Electricity_n_Hot_Water_Energy_Profile_Reference_Datasets_and_Excel_Data_Corpus

Gerro

Article Scoping exercise to determine load profile archetype referen...

Data Scoping Rural Load Profile Electricity n Hot Water Energy Pr...

Data Rural Village Disaggregated Load Profile from Smart Village ...

I too am looking for the same and to be precise

We are working on optimization of small micro grid model and need real time data of power consumption in single house hold in urban as well as PV usage profile of the same house over a year in Europe ?

Looking for more real-time dataset (.xls or .csv time series data or to evaluate matlab simulation models ( daily household load or user). so how do i get that and also your paper on the same has data of house hold in rural area with less consumption which might of less help .