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(Full version) Data analytics and digitalisation in off-grid energy with Tobias Engelmeier (Village Data Analytics / VIDA)
Manage episode 503748460 series 3687142
We speak to Tobias Engelmeier from TFE Energy and VIDA about data and analytics in the off-grid energy access sector.
Contact us at [email protected]
Visit us at www.distributingsolar.com
Follow us on Twitter and LinkedIn
VIDA website: https://www.villagedata.io/
Show notes:
(1:55) Tobias' background and how he entered the energy sector
(4:00) The reason they produced a report on digitalisation, and the limited progress and adoption thus far within the energy sector in frontier markets
(7:00) The main reasons the industry is not on track to meet SDG7 by 2030 - why scale has not reached the energy sector yet
(9:20) Introduction to digital payments, which is the most developed within the sector; introduction to scratch cards through to blockchain technologies. A lot of solutions deployed are not fully tech-enabled yet; the technology adoption story that is emerging
(15:30) Village Data Analytics and their approach to digitalisation and what the need is for additional data to accelerate the pace of deployment; decisions currently made in data lean environments; VIDA's focus on off-grid areas
(19:00) Intro to VIDA / Village Data Analytics; helping to make decisions on where to build minigrids, extend the grid, etc.
(21:20) Focus on decision making rather than just information provision
(22:30) VIDA's approach to obtaining new sources of data (e.g. from satellite imagery) and using Machine Learning methods to impute data that does not currently exist; specialists developing models with deep industry knowledge
(24:45) Examples of customers: governments (e.g. working in Ethiopia, identifying villages, key characteristics, supporting decision making for governments prioritising which health centres should be electrified as a priority); corporates and companies (e.g. SHS companies and microgrid companies; identifying the best targets for expansion and for site selection, for example with PowerGen)
(32:30) Which factors are the most important for siting mini-grids and new locations: looking at anchor loads, infrastructure information, average income, ability to pay, etc. Villages as their unit of analysis; the cultural boundaries to their analysis
(35:20) The capabilities and analytics that VIDA can provide; the appeal to a broader customer base and other industries (e.g. agriculture, health care etc.)
(38:50) Why a data-driven approach has not quite taken off as quickly as we would expect; the need to embed within business-as-usual processes
(43:00) Their partnerships and relationship with other organisations, e.g. Odyssey Energy Solutions, Applied AI
(48:00) The need to look out for biases that may be integrated in the analytics and models
(49:45) Where the name Village Data Analytics comes from
(51:30) Tobias' book on Indian politics: Nation-Building and Foreign Policy in India
(52:00) Advice: get hands-on experience in the industry; work with funders and financing providers
(55:00) Prediction for next 5 years: Great optimism; lots of entrepreneurship and falling technology costs; improved regulations
24 פרקים
Manage episode 503748460 series 3687142
We speak to Tobias Engelmeier from TFE Energy and VIDA about data and analytics in the off-grid energy access sector.
Contact us at [email protected]
Visit us at www.distributingsolar.com
Follow us on Twitter and LinkedIn
VIDA website: https://www.villagedata.io/
Show notes:
(1:55) Tobias' background and how he entered the energy sector
(4:00) The reason they produced a report on digitalisation, and the limited progress and adoption thus far within the energy sector in frontier markets
(7:00) The main reasons the industry is not on track to meet SDG7 by 2030 - why scale has not reached the energy sector yet
(9:20) Introduction to digital payments, which is the most developed within the sector; introduction to scratch cards through to blockchain technologies. A lot of solutions deployed are not fully tech-enabled yet; the technology adoption story that is emerging
(15:30) Village Data Analytics and their approach to digitalisation and what the need is for additional data to accelerate the pace of deployment; decisions currently made in data lean environments; VIDA's focus on off-grid areas
(19:00) Intro to VIDA / Village Data Analytics; helping to make decisions on where to build minigrids, extend the grid, etc.
(21:20) Focus on decision making rather than just information provision
(22:30) VIDA's approach to obtaining new sources of data (e.g. from satellite imagery) and using Machine Learning methods to impute data that does not currently exist; specialists developing models with deep industry knowledge
(24:45) Examples of customers: governments (e.g. working in Ethiopia, identifying villages, key characteristics, supporting decision making for governments prioritising which health centres should be electrified as a priority); corporates and companies (e.g. SHS companies and microgrid companies; identifying the best targets for expansion and for site selection, for example with PowerGen)
(32:30) Which factors are the most important for siting mini-grids and new locations: looking at anchor loads, infrastructure information, average income, ability to pay, etc. Villages as their unit of analysis; the cultural boundaries to their analysis
(35:20) The capabilities and analytics that VIDA can provide; the appeal to a broader customer base and other industries (e.g. agriculture, health care etc.)
(38:50) Why a data-driven approach has not quite taken off as quickly as we would expect; the need to embed within business-as-usual processes
(43:00) Their partnerships and relationship with other organisations, e.g. Odyssey Energy Solutions, Applied AI
(48:00) The need to look out for biases that may be integrated in the analytics and models
(49:45) Where the name Village Data Analytics comes from
(51:30) Tobias' book on Indian politics: Nation-Building and Foreign Policy in India
(52:00) Advice: get hands-on experience in the industry; work with funders and financing providers
(55:00) Prediction for next 5 years: Great optimism; lots of entrepreneurship and falling technology costs; improved regulations
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