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(Full version) Data analytics and digitalisation in off-grid energy with Tobias Engelmeier (Village Data Analytics / VIDA)

57:35
 
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Manage episode 503748460 series 3687142
Distributing Solar에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Distributing Solar 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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

  continue reading

24 에피소드

Artwork
icon공유
 
Manage episode 503748460 series 3687142
Distributing Solar에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Distributing Solar 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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

  continue reading

24 에피소드

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