GridWatch Public Data
Access high-resolution power quality and reliability measurements from nLine's sensor networks deployed across Sub-Saharan Africa, monitoring both urban grid infrastructure and healthcare facility electrification.
These comprehensive datasets inform critical policy discussions on energy access, reliability, and infrastructure investments in developing countries, where accurate power quality data has traditionally been scarce. From urban grid performance to healthcare facility electrification, our data provides unprecedented insights into power systems in emerging markets.
Urban Grid Performance Monitoring in Accra, Ghana
The GridWatch Accra Dataset consists of high-resolution endpoint voltage and frequency measurements collected by nLine over five years in Accra, Ghana. This dataset provides unprecedented insights into power reliability and quality in a major urban center during a period of significant infrastructure investment. It can help inform policy decisions, evaluate infrastructure investments, and contribute to filling critical gaps in information for researchers, economists, data scientists, and other stakeholders working to improve grid reliability and performance in similar contexts.
Key Details
- Geographical Coverage: Greater Accra Region, Ghana
- Temporal Coverage: July, 2018 - July, 2023
- Sensors: 1,300+ GridWatch devices
- Resolution: 2-minute intervals
- Scale: 21 electricity districts
- Measurements: Power outages, voltage quality, grid frequency
Project Details
- Focus Areas: Achimota, Dansoman, and Kaneshie districts
- Participants: Households and small businesses
- Measurement: Outage duration, frequency, voltage quality, and grid frequency
- Evaluation: Impact of the $316 million Ghana Power Compact
- Infrastructure Upgrades: Low-voltage line bifurcation and transformer injections
This data was collected as part of the University of California, Berkeley and Mathematica Policy Research independent evaluations of the Millennium Challenge Corporation Ghana Power Compact. The project aimed to increase electricity access and reliability through targeted investments in low-voltage line bifurcation, adding new transformers into the low-voltage grid network and splitting out existing low-voltage lines. The dataset provides a unique opportunity to analyze the impact of these infrastructure investments on power reliability and quality at an unprecedented scale and resolution.
nLine's field team enrolled 1,300+ study participants and ensured proper sensor installation and maintenance throughout the five-year project.
Data Applications and Research Opportunities
The GridWatch datasets offer a wealth of opportunities for researchers, economists, data scientists, and policymakers to gain insights into power reliability and quality in developing contexts. Some potential applications include:
- Evaluating the impact of infrastructure investments on power reliability
- Analyzing trends in power availability and outage frequency over time
- Comparing power quality across different regions and facility types
- Correlating power reliability with other datasets, such as socioeconomic indicators or health outcomes
- Developing and training machine learning models on time series power data
- Studying the effects of seasonal variations on power system performance
Researchers can leverage these datasets to develop new metrics for power reliability, create predictive models for outages, or conduct comparative studies across different contexts in developing countries.
Data Collection Methodology
The GridWatch datasets were collected using nLine's GridWatch technology platform, which consists of plug-in sensing devices installed directly in outlets at various locations. Key features of the data collection process include:
- High temporal resolution: Measurements taken at 2-minute intervals
- Real-time data transmission via cellular network
- Local data storage for periods of network unavailability
- Integrated GPS for precise location data
- Battery backup to capture outage start and end times accurately
This methodology allows for the collection of highly accurate and granular data on power reliability and quality, providing a more comprehensive picture than traditional survey-based methods or utility-provided data.
API Access
We are interested in hearing about novel uses of the data! To access the GridWatch Dataset, please fill out the form below. You will receive an API key that enables access to:
- Our Python utility for programmatic data access and analysis
- The public GridWatch dashboard for data visualization and easy downloads of KPIs and sensor data as CSVs
Potential use cases for this dataset include:
- →Evaluate infrastructure investments' impact on power reliability.
- →Analyze trends in power availability and outage frequency.
- →Compare power quality across Accra's neighborhoods.
- →Identify areas with frequent low-voltage events.
- →Correlate power reliability with socioeconomic indicators.
- →Train machine learning models on time series power data.
The dataset and Python tool are licensed under the CC BY-NC 4.0 license, which allows for non-commercial use and sharing with attribution. Please contact us if you have any use cases that might extend beyond these terms.
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