{"doc_desc":{"title":"zar-erc-delmh-1994-2014-v1","producers":[{"name":"DataFirst","abbreviation":"","affiliation":"University of Cape Town","role":"Metadata producer"}],"prod_date":"2020-04-15","version_statement":{"version":"Version 4"}},"study_desc":{"title_statement":{"idno":"zaf-erc-delmh-1994-2014-v1","title":"Domestic Electrical Load Metering","sub_title":"Hourly Data 1994-2014","alt_title":"DELMH 1994-2014"},"authoring_entity":[{"name":"Wiebke Toussaint","affiliation":"University of Cape Town"}],"oth_id":[{"name":"Marcus Dekenah","affiliation":"MDekenah Consulting","email":"","role":"[Expert knowledge for] understanding database design and conveying details around data collection"}],"production_statement":{"funding_agencies":[{"name":"South African National Energy Development Initiative","abbreviation":"SANEDI","role":"Funder"}],"grant_no":"CESAR Programme"},"distribution_statement":{"contact":[{"name":"DataFirst Support","affiliation":"University of Cape Town","email":"support@data1st.org","uri":"support.data1st.org"}]},"series_statement":{"series_name":"Service Provision Assessment [hh\/spa]","series_info":"Toussaint, Wiebke.  Domestic Electrical Load Metering, Hourly Data 1994-2014 [dataset]. Version 1. Johannesburg: SANEDI [funders]. Cape Town: Energy Research Centre, UCT [producers], 2014. Cape Town: DataFirst [distributor], 2019. DOI: https:\/\/doi.org\/10.25828\/56nh-fw77"},"version_statement":{"version":"v1: Edited, anonymised data for licensed distribution","version_date":"2019-05-23"},"study_info":{"keywords":[{"keyword":"current","vocab":"","uri":""},{"keyword":"South Africa","vocab":"","uri":""},{"keyword":"rural","vocab":"","uri":""},{"keyword":"electrification","vocab":"","uri":""},{"keyword":"load data","vocab":"","uri":""},{"keyword":"time-of-use","vocab":"","uri":""},{"keyword":"electrical","vocab":"","uri":""},{"keyword":"household","vocab":"","uri":""},{"keyword":"consumption","vocab":"","uri":""},{"keyword":"energy","vocab":"","uri":""},{"keyword":"electricity","vocab":"","uri":""},{"keyword":"domestic","vocab":"","uri":""},{"keyword":"residential","vocab":"","uri":""},{"keyword":"behaviour","vocab":"","uri":""}],"abstract":"This data is an aggregated subset of the 5-minute interval electricity metering data available in the Domestic Electrical Load Metering Data (DELM) 1994-2014 available in DataFirst's secure centre. The large volume and high metering cadence of the DELM 1994-2014 data is unwieldy to access and process. Many applications that do not require the granularity of the DELM 1994-2014 data will be able to extract value more effectively and conveniently from aggregate values. This dataset contains all current (Amps) observations aggregated to hourly values. It can be easily merged with the Domestic Electrical Load Survey Key Variables 1994-2014 data to link socio-demographic varibles with household consumption data. This dataset and similar custom datasets can be produced from the DELM 1994-2014 dataset with the python package delprocess. The data processing section includes a description of how this dataset was created. The development of the tools to create this dataset was funded by the South African National Energy Development Initiative (SANEDI).","coll_dates":[{"start":"1994","end":"2014","cycle":""}],"nation":[{"name":"South Africa","abbreviation":"ZAF"}],"geog_coverage":"The study had national coverage.","geog_unit":"The DELMH 1994-2014 dataset does not contain geographic information. When combined with the DELSKV 1994-2014 dataset, the lowest unit of geographic aggregation is settlement\/suburb. Municipal-level data is also available in the DELSKV data which can be merged with the DELMH data.","analysis_unit":"Households","universe":"The metering study covers electrified households that received electricity either directly from Eskom or from their local municipality. Particular attention was devoted to rural and low income households, as well as surveying households electrified over a range of years, thus having had access to electricity from recent times to several decades.","data_kind":"Observation data","notes":"The scope of the hourly South African Domestic Electrical Load Metering data includes:\nCURRENT: Amperes (A) aggregated over a 60 minute interval defined to start daily at 00:00:00 - 00:59:59."},"method":{"data_collection":{"coll_mode":"Other [oth]","cleaning_operations":"This data has been produced by aggregating all current (Amps) metering data from the DELMS 1994-2014 dataset using the reduceRawProfiles function from the delprocess python package (https:\/\/github.com\/wiebket\/delprocess: release v1.0). Full instructions on how to use delprocess to aggregate metering data are in the README file contained in the package.\n\nINVALID READINGS\nThe 'Valid' indicator of readings was converted to 1 (valid) and 0 (invalid). Missing 'Valid' indicators were filled with 0 values.\n\nMISSING VALUES\nMissing readings were treated as per pandas.dataframe.mean default: skipna = True; i.e. missing values are excluded when computing results.\n\nDATA AGGREGATION (OBSERVATIONS)\nThe following processing steps were performed to produce the aggregate dataset:\n0. 'Datefield' values were converted to integer values, rounded to 9 positions left of the decimal, and converted to a numpy datetime64 object with nano-second units. This was done to coerce the data to consistent time intervals.\n1. readings grouped by RecorderID and ProfileID\n2. grouped data resampled to hourly values ('Datefield' column converted to 'H' offset)\n3. mean meter reading value and 'Valid' indicator calculated over resampled intervals\n4. rows with all missing values removed\n5. aggregated 'Valid' indicator set to 0 unless it was 1 (i.e. if one reading was marked as invalid, the mean 'Valid' indicator would be less than 1 and the aggregate 'Valid' indicator was set to 0, thus marking the aggregated validity as invalid) \n\nDATA AGGREGATION (STUDY CYCLES)\nData was aggregated per year, across temporally overlapping study cycles.","method_notes":"POWER CONVERSION\nTo convert the DELMH 1994-2014 dataset from current readings to power use the formula:\n\nx A * 230V \/ 1000 = y kWh\n\nThis calculation is an approximation of power consumption, not the actual measured value. Power quality varied across households and the measured voltage was not always stable. For an accurate power calculation the voltage readings from the DELMS 1994-2014 dataset should be used."}},"data_access":{"dataset_use":{"contact":[{"name":"DataFirst","affiliation":"University of Cape Town","email":"support@data1st.org","uri":"support.data1st.org"}],"cit_req":"Toussaint, Wiebke.  Domestic Electrical Load Metering, Hourly Data 1994-2014 [dataset]. Version 1. Johannesburg: SANEDI [funders]. Cape Town: Energy Research Centre, UCT [producers], 2014. Cape Town: DataFirst [distributor], 2019. DOI: https:\/\/doi.org\/10.25828\/56nh-fw77","conditions":"Licensed use files, available with restrictions"}}},"schematype":"survey"}