Published December 19, 2021 | Version v1.0
Dataset Open

EPSRC-funded Humanitarian Engineering and Energy for Displacement (HEED) datasets

  • 1. University of Connecticut
  • 2. Goldman Sachs
  • 3. Coventry University

Description

This repository contains raw datasets gathered under the EPSRC-funded Humanitarian Engineering and Energy for Displacement (HEED) research project (EP/P029531/1). The project aimed to understand energy needs of displaced communities by creating an evidence base on the usage of seven different energy interventions, and provide recommendations for improved design of future energy interventions to better meet the needs of people. Below is a brief description of the interventions.

  1. Stove-use monitoring systems (July 2019 to October 2019) - Stove-use monitoring systems (SUMs) were deployed on clay stoves in Kigeme camp, Rwanda in July 2019. The aim of the study was to evaluate stove usage patterns by measuring temperature profiles within stove enclosure and on the surface of stoves. The SUMs consisted of 2 sensors - a thermocouple to measure temperature within the stove and a Si7021 sensor to measure temperature outside the stove, connected to an Arduino MKR GSM 1400 board. The data measured by the sensors was stored only if the change in values exceeded a set threshold for either of the readings. The SUMs were powered by a re-chargeable Li-Ion battery of 3.7V and a rating of 7.59Wh.

    The study was conducted in 2 phases. In phase 1 (02 July 2019 to 30 September 2019), data was collected from 15 SUMs and stored locally on SD cards as well as communicated to a remote server via GSM. The time of data collection was recorded using GSM functionality. However, several GSM and MQTT failures were noted leading to loss of timestamp values as well as shorter battery lifetime due to re-transmission tries. In phase 2 (02 October 2019 to 17 October 2019), data was collected from 9 SUMs and only stored locally on SD cards. The time of data collection was recorded using an external RTC clock connected to the Arduino board. The data from both phases of study is deposited here in SUM.zip. The cleaned dataset is available at 10.5281/zenodo.3946999.
     
  2. Mobile Lantern monitoring systems (July 2019 to December 2019) - Mobile lantern monitoring systems (LMSs) were deployed in Nyabiheke camp, Rwanda, in July 2019. The aim of the study was to evaluate lantern usage (static or mobile) and consumption (charge and discharge) patterns. The monitors consisted of a D.light S30 solar lantern fitted with an Arduino-based monitoring device. The most integral part of the device was the Arduino MKR GSM 1400 board connected to an ADXL345 inertial motion unit sensor. The ADXL was used to calculate step count of a user based on activity and freefall interrupts. Additionally, the voltage of lantern battery was measured using an in-house voltage monitor to understand the discharging and charging patterns. The step count and battery voltage data were stored only if a significant change in the step count was detected. The LMSs were powered through a re-chargeable Li-Ion battery of 3.7V and a rating of 7.59Wh.

    The study was conducted in 2 phases. In phase 1 (03 July 2019 to 30 September 2019), data was collected from 60 lanterns and stored locally on SD card as well as communicated to a remote server via GSM. The time of data collection was recorded using GSM functionality. However, several GSM and MQTT failures were noted leading to loss of timestamp values as well as shorter battery lifetime due to re-transmission tries. In phase 2 (09 October 2019 to 18 December 2019), the design of lantern monitors was modified to circumvent these issues. The data was collected from 54 lanterns data and only stored locally on SD cards. The time of data collection was recorded using an external RTC clock connected to the Arduino board. Additionally, an internal watchdog timer was used to reset the device in case of failures. While certain failures persisted, the data yield was considerably higher than phase 1 of the study. The data from both phases of study is deposited here in LMS.zip. The cleaned dataset is available at 10.5281/zenodo.4269809.
     
  3. Individual appliance monitors (December 2018 to January 2020) - Individual appliance monitors (IAMs) were deployed in Uttargaya settlement, Nepal, in December 2018. The IAMs were simple, cost-effective and unobtrusive devices to collect data on the energy usage of connected appliances. The aim of the study was to understand energy consumption and usage patterns of different household appliances in grid-connected sub-metered displaced communities. The monitoring system consisted of 2 types of devices – Energenie MiHome Smart Plugs MIHO005 (referred to as the IAM) to sense data relating to power and voltage drawn by the connected appliance, and gateway nodes to collect data from IAM. The main component of the gateway node was a Raspberry Pi fitted with an Energenie ENER314-RT (receiver-transmitter) add-on board to allow the Pi to communicate with the smart plugs. The data collected by the RPi gateway was stored locally in an SD card as well as sent to a remote server hosted at Coventry University.

    The study was conducted until January 2020. The raw data from the study is deposited here in IAM.zip. The cleaned dataset is available at 10.5281/zenodo.4271714.
     
  4. Footfall monitoring systems (December 2018 to January 2020) - Seven footfall monitoring systems (FMSs)  were deployed alongside seven solar streetlights to measure step count of passers-by in the Uttargaya settlement, Nepal, in December 2018. The aim of the study was to understand the level of pedestrian movement in the area and evaluate the effect of streetlights on the level of activity. Therefore, the footfall monitors were deployed prior to commissioning of streetlights to gather baseline data. The footfall monitors consisted of a Raspberry Pi 3B, PiFace Real Time Clock and CAM008 70º night vision IR sensor to detect footfall. Upon detection, footfall count along with the direction of movement and the timestamp (measured from PiFace RTC) was stored onto an SD card and communicated to a remote server hosted at Coventry University. 

    The study was conducted until January 2020. The raw data from the study is deposited here in FMS.zip. The cleaned dataset is available at 10.5281/zenodo.4271730.
     
  5. Standalone Solar System for a Community Hall (June 2019 to March 2021) - A standalone solar system was deployed in a Community Hall in Nyabiheke camp, Rwanda in June 2019. The aim of the study was to understand the energy consumption behavior within a set location, and create an evidence base on the value of energy and its benefits for growing cooperatives and learning communities. The standalone system comprised of 2kW of solar panels and 12.2 kWh GEL battery storage capacity. Additional components included a Victron 150/35 charge controller and a Venus GX and 48/3000 MultiPlus Inverter. The system powered four AC 2-pin sockets, a 30 W entrance light, and six 30 W indoor lights. Each light and socket were individually metered and controlled via a remote monitoring unit. This allowed for quotas, maximum draws and periods of use to be remotely controlled.

    The study was conducted until March 2021. The raw data from the study is deposited here in Hall.zip. The cleaned dataset until March 2020 is available at 10.5281/zenodo.3949776.
     
  6. PV-battery Microgrid (July 2019 to March 2021) - A PV-battery Microgrid was deployed in Kigeme camp, Rwanda in July 2019. The microgrid powered a playground and two nursery buildings.  The aim of the study was to identify best practice in the construction, control and operation of a micro-grid as a shared resource, understand optimal design features for user interfaces that allow negotiation over energy priorities and needs and understand community priorities for energy in the context of early years education and the rate of growth in energy utilization. The micro-grid system comprised of a 2.5 kW of solar panels and 21.1 kWh GEL battery storage capacity. Additional components included a Victron 250/60 charge controller, Venus GX 48/1200 MultiPlus Inverter and BMV-700 series battery monitor. Each Nursery building had three classrooms (A, B and C) with separate entrances. Each classroom was fitted with an AC socket, five 10 Watt indoor lights and a 10 Watt outdoor entrance light. A spare socket was located in the first classroom of each nursery building (Classroom A). Two outdoor double sockets were installed at the playground, and fifteen 10 Watt lights were located in the roof structure. Three transmission line poles were fitted with three 10 Watt lights for safety and security purposes, which also enabled them to act as streetlights. Each light and socket was individually monitored and controlled via a programmable remote monitoring unit (RMU). Wireless AC smart meters were used to control and measure power consumption at the socket loads. These meters communicated with the RMU to receive commands and notified the RMU when a command had been received and to transmit usage data. Each light was connected to a CPE (customer-premises equipment) unit, with three lights per CPE, which communicated wirelessly with the RMU. The CPEs received information from the RMU on when to turn the lights on/off and set the brightness. The CPE also monitored the power consumption of the three lights. 

    The study was conducted until March 2021. The raw data from the study is deposited here in Microgrid.zip. The cleaned dataset until March 2020 is available at 10.5281/zenodo.3949776.
     
  7. Standalone solar streetlights (Nepal - June 2019 to October 2020; Rwanda - July 2019 to March 2021) - Seven advanced streetlights were installed by HEED in Khalte, Nepal, in July 2019. Four advanced streetlights and eight normal solar streetlights have been installed in Gihembe, Rwanda, in July 2019. Each advanced streetlight consisted of a solar streetlight and an electrical socket box for excess energy use. The aim of the study was to pilot community co-designed solar streetlights with ground-level sockets to demonstrate alternative energy governance models using new technologies to build community resilience and capacity. The solar light comprised a 300 Watt solar panel, Victron charge controller, 2 kWh li-ion batteries, reprogrammable 60 W LED light, Victron Venus GX for data logging, Victron BMV 700 series battery monitor, ground-level sockets/USB ports and a footfall sensor (only in Nepal). A Victron Battery Protect and remote relay on the Venus GX is used to control access to the secondary load to ensure that there is always sufficient energy to power the light. 

    The study was conducted until October 2020 in Nepal and March 2021 in Rwanda. The raw data from the study is deposited here in SL.zip. The cleaned dataset until March 2020 is available at 10.5281/zenodo.3947992.

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