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OBJECTIVE
Large scale advances in remote sensing geospatial technologies have enabled researchers to evaluate and assess the electrification of settlements and communities (High Resolution Electricity Access) in various time intervals and large geographic scales. These datasets are now being used to forecast the electrification process in time and generate insight into the distribution and location of populations at risk of being left behind. The Forecasting Electricity Access (FEA) tool, developed as a web dashboard hosted on UNDP's GeoHub platform, is bringing all these data into one space and will allow users to unearth trends in electrification and evaluate the state of this process in respect to the indicators defining the SDG7. Participants are encouraged to reflect on how this tool can be applied in their specific context and consider the adaptations needed for effective customization.
GUIDING QUESTIONS
- What information/ data/ tools do you use for understanding energy access gaps in your country and portfolio context?
- What information/ data/ tools do you have in place to facilitate microplanning, such as identifying targeted populations for energy access?
- How does the FEA tool align with the energy access needs and objectives of your portfolio/ country context?
- How can the FEA tool be used to support the energy access goals and ambitions in your portfolio/ country context?
- How can the FEA tool be enhanced to provide improved support for your work?
HOW TO CONTRIBUTE?
💬 Use the comment section below to share your perspective.
✍️ Please introduce yourself when responding for the first time.
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↩️ Please indicate the question number(s) in your response!
Any technical issues can be shared with: [email protected]. Any other questions about this consultation can be addressed to: [email protected].
Comments (47)
Colleagues, I welcome you to the discussion room on Electricity Access Forecasting where we will delve into the transformative potential of data generated by the High-Resolution Electricity Access Mapping project. The High-Resolution Electricity Access Mapping project has improved our understanding of the national energy access landscapes by providing granular, geospatial data on electricity access. This resource can support policymakers, researchers, and practitioners with detailed insights into the distribution, quality, and reliability of electricity services at a local level. However, beyond these data sets lies the crucial question: how do we effectively utilize this information to catalyze progress in respect to SDG7?
I invite you to leverage your expertise and practical experience acquired in the field to foster a dialogue and knowledge exchange aiming to chart a course towards inclusive, sustainable, and equitable electrification, ensuring that no community is left in the dark. Feel free to inquire and debate on specific aspects of electricity access and its applications for informing infrastructure investments and policy decisions to enable targeted interventions for underserved communities.
The discussions will be moderated this first week by our colleagues Bheki Bhembe , Inya Nlenanya and [email protected].
Thank you and looking forward to our fruitful conversations.
Ioan
Thanks, you Ioan for the introduction. You have set the tone for this week's public consultations very well, with the question - how do we effectively utilize the wide variety of emerging data and analytics to catalyze progress in respect to SDG7? We are glad to engage in this discussion from the Kenya Country Office. My name is Bheki Bhembe - Senior Economist Kenya CO. Pleasure to meet my fellow moderators @Inya Nlenanya and @Rosine Ouedraogo!.
Hello Dear colleagues, I am Serges-Roberteau TCHOFFO, the Head of Experimentation of the UNDP Cameroon Accelerator Lab (the R&D unit of the country office).
Regarding question N°4 on "How can the FEA tool be used to support energy access goals and ambitions in your portfolio/country context?"
I think that the Forecasting Electricity Access (FEA) tool can be crucial to support the energy access goal in the context of Cameroon (where supply is low compared to demand, despite the high hydropower potential of Cameroon, which is about 12,000 MW, the third in Sub-Saharan Africa according to the World Bank Group). FEA can support energy access in several ways and, of which I will mention three:
1. Data-driven planning: The FEA tool can analyze various data from different sources to provide insights into current energy supply and demand. For example, this can help identify where the GAPS are and to anticipate them accordingly.
2. Scenario modeling: It can model different scenarios for expanding electricity access, taking into account factors such as population growth, urbanization, construction of new hydropower plants, economic development, etc., which are critical for medium- and long-term planning. This can help policymakers in Cameroon to make informed decisions that are consistent with the country's energy access ambitions.
3. Attract investment: By providing a clear picture of the energy access landscape, the FEA tool can help attract investors by highlighting areas with high potential for growth and return on investment. In fact, only half of Cameroon's population has access to electricity, and this percentage is much lower in rural areas.
In summary, the FEA tool can provide a comprehensive analysis to support Cameroon's efforts to bridge the supply-demand gap and achieve its energy access goals.
Thanks,
Roberteau
Greetings Serges-Roberteau and many thanks for your response!
You have indeed identified a set of core use cases for FEA. In the instance of data driven planning (1) FEA has the potential to identify the underserved communties at various spatial spaces. The original HREA data was generated at settlement level featuring a spatial resolution of 40 meteres and can be used to microscale disparities the FEA data features a spatial resolution of 1000m or 1 KM and can be employed in data driven planning either directly or by agregating it to administrative units at various levels (provinces, districts, etc).
I find the scenario planning (2) use case to be very interesting as combining FEA with other solutions like Open Source Spatial electrification Tool and policies can constitute a framework for managing and trancking SDG7.
Last but not least using FEA to drive investment at hyperlocal scale is also possible, specially with the historical HREA datasets. The FEA dashboard will feature geospatial admin units with information on electrification levels, both historical and predicted, accounting for population growth and urban area expansion. Thus identification of suitable districts or simple locations for investing into various types of solutions will benefit from this setup. This is absolutely important specially in Africa as the continent is going to experience an exponential population growth in next decades.
At the same time, the original HREA data layers are already consumable and discoverable as you can see here.
Alternatively, using Geohub one can easy generate images from the datasets like this:
https://geohub.data.undp.org/api/datasets/2294a356bcc4888f3d17ad1446bf8…
https://geohub.data.undp.org/api/datasets/2294a356bcc4888f3d17ad1446bf8…The above is a peek into High Resolution Electricity Access in Bertoua, Cameroon generated in real time using the dataset ID and latitude/longitude coordinates.
The potential of the historical HREA as well as the forecasts can be undobtely put to good use for the benefit of the comunities.
Interesting dear Ioan Ferencik
Thank you Serges-Roberteau TCHOFFO for sharing the Camerron perspectives.
Thank you Serges-Roberteau TCHOFFO for your insightful contribution on the potential application of the FEA tool in Cameroon. Your analysis clearly outlines the utility of FEA in addressing the country's energy supply and demand challenges. The points you raised about data-driven planning, scenario modeling, and attracting investment are particularly compelling and align well with the strategic goals of the FEA.
Your mention of Cameroon's untapped hydropower potential and the current electricity access disparity underscores the urgent need for such tools in strategic planning and investment attraction. Your input serves as a strong foundation for further exploring how the FEA tool can be optimized for Cameroon’s context.
To continue our discussion, I would like to ask based on the ability to leverage diverse data sources that you rightly identified, what current data or information or tools do you have in place to facilitate microplanning, such as identifying targeted populations for energy access? Additionally, what strategies or models should be considered to better align with your energy access objectives and strategies?
Thank you once again for your comprehensive analysis and for contributing to this important discussion.
You are welcome Inya Nlenanya and thanks for your questions.
To give you some answers to your questions, I would say the following:
First of all, as far as the data/information and tools already available in the country are concerned, we have to contact the Ministry in charge of Energy or the Electricity Sector Regulatory Agency (ARSEL), and other government agencies/ministries depending on the thematic data. In fact, the reality in Cameroon, as in many other developing countries, is that there isn't yet a common (geographic) database, so for official thematic data, you need to contact the government Agency/Ministry concerned.
Secondly, as far as possible strategies and models are concerned, the Ministry in charge of Energy is in the best position to tell us, as this falls within its prerogatives.
Merci Serges-Roberteau TCHOFFO de nous avoir fourni cet excellent exemple sur le Cameroun. Votre analyse est très pertinente. Il est effet intéressant d’aborder les différentes manières dont l’outil FEA peut accompagner les décideurs politiques dans leurs efforts d’expansion de l’accès à l’énergie aux populations.
Sachant que cette expansion induit une mobilisation importante de ressources, il est tout à fait opportun que l’outil FEA puisse servir de levier pour attirer des investisseurs surtout le secteur privé. Ainsi, quelle appréciation faites-vous de l’engouement du secteur privé au Cameroun pour les investissements dans le domaine de l’électrification ? Des mécanismes éventuellement politiques et financiers sont-ils déjà mis en place pour dérisquer le secteur (s'il y a lieu) et attirer leurs investissements ?
A votre avis, de quelle manière ou à travers l’intégration de quels types de données ou de fonctionnalités, l’outil FEA pourrait-il contribuer davantage à susciter l’intérêt de ces investisseurs privés ?
Merci une fois de plus pour votre contribution et au plaisir de vous lire à nouveau.
Merci pour votre retour et pour vos question Rosine Ouedraogo .
Il m'est difficile pour le moment de me prononcer sur l'engouement des investisseurs dans le domaine de l'électrification au Cameroun et les mesures incitatives mis en place en l'absence d'évidences à mon niveau. Cependant, la réalité est qu'il y a un seul fournisseur de ce service au Cameroun, et il y a beaucoup de plaintes des ménages et entreprises sur la qualité de service, avec la concurence presque inexistante. Donc il est certain que pour les consommateurs, le besoin d'avoir d'autres fournisseurs est réel et ceci fait appel aux investisseurs, surtout privés. Ca peut être intéressant d'intégrer les données sur le potentiel énergétique des pays, la demande en énergie, l'offre disponible, le GAP, etc.. Bref tout ce qui permet à l'investisseur d'avoir une meilleure connaissance du contexte par un potentiel investisseur.
Merci Serges-Roberteau TCHOFFO pour les détails apportés sur les données requises. Savoir que le secteur n'est pas libéralisé au Cameroun malgré la forte demande de la population m’emmène à faire une analogie avec le contexte du Burkina Faso. En effet, des réformes sur le cadre institutionnel et règlementaire y sont en cours afin de susciter la participation des acteurs du privé. La couverture nationale est assurée par un opérateur public mais la règlementation permet aux opérateurs privés d'intervenir dans les zones non encore couvertes par le réseau national. Malgré cela, on constate toujours un faible engouement du privé qui considère que le modèle et la tarification des mini réseaux proposés au niveau nationale n’est pas assez rentable et que le secteur présente encore beaucoup de risques pour le privé. Pour pallier cela, Le PNUD à travers le projet d’appui à l’électrification rurale dans la région du Liptako Gourma propose des réformes sur le cadre règlementaire aux gouvernements grâce à une étude menée en 2021-2022 sur les risques liées aux investissements dans les mini-réseaux solaires avec batteries (DREI) ; le projet propose également de développer une plateforme de suivi et de modélisation énergétique au niveau national, l’idée étant de permettre entre autres aux acteurs du secteur privé de pouvoir faire des simulations sur la plateforme numérique afin de choisir le modèle le plus rentable en fonction des différents paramètres d’entrées sur une zone ciblée. Le processus est en cours et la Direction générale de l’énergie ainsi que l’agence burkinabè d’électrification rurale fortement impliquées dans le processus ne ménagent aucun effort pour voir l’aboutissement de ces initiatives qui pour eux permettront de susciter d’avantage l’intérêt et la mobilisation de ressources du privé. La stratégie nationale de l’électrification nationale 2024-2028 validée le 19 mars dernier vise d’ailleurs à porter le taux d’électrification national rural qui était de 5,49% en 2022 à 50% en 2028 (respectivement de porter le taux de couverture national qui était de 50% en 2022 à 80, 9% en 2028) et cela est conditionné en autres par une mobilisation de fonds de l’Etat, des partenaires techniques et financiers et du secteur privé avec une contribution du secteur privé estimée à 28%. Ainsi comme vous l'avez si bien dit, il nécessaire pour susciter l'engouement du privé d'intégrer les données sur le potentiel énergétique des pays, la demande en énergie, l'offre disponible, le GAP, etc.. et peut être aussi une fonctionnalité de modélisation permettant d'évaluer ou comparer la rentabilité de différents modèles/systèmes électriques en fonction de la zone ciblée.
Merci une fois de plus pour ce fructueux échange sur l'exemple du Cameroun qui permettra sans aucun doute d'alimenter et d'améliorer les données d'entrée de l'outil FEA.
Rosine Ouedraogo , merci pour ce partage d'expérience du Pays des Hommes Intègres.
Thanks for your response Serges-Roberteau TCHOFFO. We can definitely relate with your responses. We are also more than willing to facilitate that conversation with the relevant government agencies as we explore how this tool can be used in the Cameroonian context.
Greetings Dear Development Consultants,
We have previously engaged the SEforAll Energy Access Tool co Developes by ESMAP at country level but it's limitations has been on the transparency if Government and private sector in releasing data
Merci beaucoup Samuel Adunreke de nous partager votre expérience avec l'outil d'accès à l'énergie SEforALL co-développé par ESMAP au niveau national, il serait également intéressant d'en savoir d'avantage sur ce qui fait le succès de cet outil (les points fortement appréciés).
Hello Samuel,
ESMAP is a World Bank program where they subcontracted at least parts of the work. That means the solar, wind, etc products have been developed by third party entities and in order to get specific details oen has to contact the subcontractors.
I am wondering if you could elaborate on the transparency limitations. As far as I know the ESMAP data is downloadable.
Thank you Samuel Adunreke for sharing your experiences with the SEforAll Energy Access Tool co-developed by ESMAP. It's useful to hear about your engagement with the tool at the country level and the challenges encountered, particularly concerning the transparency of government and private sector data release.
We are keen to further discuss and explore potential solutions to these challenges. How do you think we can improve the situation regarding data transparency and accessibility in the context of the FEA Tool and beyond?
Hi Everyone,
This is Diana Mae Calde, together with me is Ioan Ferencik and Stephen Gitonga, welcoming you into the second week of discussion and learning from the different sectors and expertise that is using and will be using the FEA tool.
Last week, Serges raised an interesting point of view in using FEA tool for data driven planning, scenario modeling and attract investment in based on Cameron current energy access status. @Serges-Roberteau, what are the main drivers to attract investment in the Cameron?
Samuel also shared to us a tool ESMAP. Could FEA and ESMAP tool be combined and how does this two tool could assist you in your energy access goal?
I encourage everyone to explore GeoHub Electricity Access tool and let us know your thought in how it could be relevant in your region. Looking forward for insightful discussion.
Thank you, Diana. I am happy that I am back from the long Eid Mubarak Holidays that started on Wednesday last week. Looking forward to the discusions this week.
There are several aspects in the application of the tool that I would like to highlight based on experiences on the ground. Countries may fall under the following categories:
1) Some countries may use the tool to understand, plan and execute decisions about where expansion of access should happen at the least cost.
2) Others on whether to combine the expansion of the existing grid system with micro or mini grids in case of electrification, again based on the lease cost options.
3) In other cases, it is the issue of intermittency. This is in situations where there is the infrastructure, but electricity is shed in specific periods of the day.
4) Other countries exhibit a combination of the above.
It would be interesting to hear opinions relating to these scenarios.
I am impressed with the discussion related to the ESMAP tool. ESMAP came up with the multi-tier approach in determining access. It would be good to hear what information/ data/ tools are used by Countries to understand energy access gaps in a country and portfolio context in situation where the multi-tier approach has to be applied.
Sharing this insight we found when analyzing the data from FEA for Kisumu, Kenya. It is showed in this plot the positive gradient (red) is expansion while the negative gradient (blue) is loss. The size of the bubble indicates the magnitude of increase/decrease. HREA is the high resolution electricity access is compared to the expansion/loss of land use and cover.
In the recent years, it showed that expansion in urbanization is related to the increase in energy access in Kisumu, Kenya that actually make sense, to establish a urban area one of the primary requirement is to have basic necessity available such as affordable food, water, and electricity. There are still many socio-economic and geographic factor affects increase in electricity access.
May I know if this is also true in your areas? What are other socio-economic factor you think affects your region's electricity access?
Hello colleagues, I am Gaijouhn Gaybueh, Solar for Health Project Officer at UNDP Liberia.
With regards to question 4, "How can the FEA tool be used to support energy access goals and ambitions in your portfolio/country context?"
The FEA tool can be used to support energy access goals and ambitions in Liberia's context in the following three ways but not limited to:
Data Harnessing for Optimal Site Selection
A key step in renewable energy projects is to identify suitable locations. FEA tools can aid in collecting and analyzing vast and diverse datasets, including topography, land use, weather patterns, and proximity to infrastructure. This capability enables the identification of the most viable sites for solar PV installations, and other renewable energy installations, optimizing land use and minimizing environmental impact.
Energy Yield Analytics
FEA tools play an essential role in forecasting energy yields by processing historical weather data and real-time satellite imagery that predicts solar irradiance and wind patterns, essential for calculating potential energy production. This information helps in designing more efficient renewable energy systems and in making informed decisions about where and how to deploy the system. In our solar tender, we include the Geographical coordinates of the sites and some of the vendors use the coordinates to design the system. Through the use of SOLARGIS.
Attract Financial Investment:
Liberia faces significant challenges in its energy sector, with limited access to electricity and heavy reliance on traditional biomass and imported fossil fuels. The FEA tool can help in providing a clear picture of sites with maximum energy potential and optimized economic development while minimizing the environmental impact that attracts financial investment. Therefore, FEA plays a vital role in the growth of renewable energy by helping identify optimal locations, model and forecast energy production, and assess the availability of renewable energy sources. The continuous development of FEA technologies will help ensure a sustainable energy future for all.
Thank you Gaijouhn for detailing the strategic use of the FEA tool in enhancing energy access in Liberia, particularly within the Solar for Health Project. I will highlight 2 of your three key application areas that captures how the FEA can be integrated effectively:
Energy Yield Analytics: Leveraging FEA for energy yield forecasts using historical and real-time data is an excellent strategy. This not only helps in system design but also enhances decision-making processes, ensuring that installations are both efficient and effective. Your mention of using SOLARGIS for precise system design based on geographical coordinates in solar tenders illustrates a practical application of this tool.
Attract Financial Investment: Highlighting how FEA can showcase the potential of sites for energy generation and economic development is vital. In environments like Liberia, where energy needs are critical, and traditional energy sources dominate, presenting clear, data-backed investment opportunities can shift the balance towards more sustainable and renewable energy sources.
To build on your experience and expand our understanding, could you share what support mechanisms do you think are necessary to enhance the effectiveness of the FEA in Liberia? Also, I will encourage you to check out the other side of this engagement that focuses on clean energy equity index via this link: Equity in Clean Energy | SparkBlue.
Hi Gaijouhn,
Thank you for very elaborate response on how FEA tool assisted renewable energy solution in Liberia. I am very interested to know more about the energy yield analytics using SOLARGIS. Do you also used the FEA tool to see the current energy demand? How do we improve FEA tool to give support in your current energy analytics?
Dear Inya Nlenanya,
Thanks for highlighting 2 of our key application areas for the FEA. We need more tutorials and presentations on the use of the FEA tool from the developer which will serve as a basic support mechanism to enhance our usage of the FEA tool. If such a tutorial is available, I would appreciate if you could share it with me. Viewing the current Demo, there is no sound.
gaijouhn.gaybueh
Thank you for your suggestions and observation related to the video.
As both FEA and CEEI are data products (layers), we are developing web based dashboards/apps to leverage this datasests. The apps are going to be part of Geohub ( https://geohub.data.undp.org/ ). For FEA the dashboard will provide several types of actions/functionality:
1. spatio-temporal exploration of electricity acces forecasts aggredated at administrative levels (subnatinoal). This will allow users to observe/query the values of electrcity access at various spatials scales between 2012 and 2030
2. a bivariate map showcasing the distribution of electricity access and relative poverty rates. The goal here si to identify spatial clusters of low/high join distributions of electricity access and relative poverty
3. a tool to peerform location based queries on ouputs of electricity access generated using two methods: a machineb learning method and a data driven method. This would allow users to provode feedback on the properties/quality of these metods.
A similar approach is taken for the other work stream (CEEI) where actions related to input data (replace, edit) and computation (change weights of components for CEEI index) are going to be implemented.
The dashboards are currently being developed in a joint partnership UNDP-IBM and will be made public as soon as a stable prototype is developed.
Let us know what other functionality you could envision in this dashboard that would facilitate your work.
Dear Colleagues,
Thank you for coming up and for the invitation to join this knowledge-sharing platform.
In Zambia, various methodologies, including advanced geospatial technologies, are pivotal in identifying and addressing energy access disparities. Forecasting Electricity Access (FEA) can significantly enhance our collective understanding and strategic planning for scaling up energy access through but not limited to the following applications:
I look forward to further insights and discussions.
Thank you,
Kafula
Construction and Facilities Management Analyst – Zambia CO
Dear Kafula,
Thank you for sharing your insights and the innovative uses of the FEA tool in Zambia. It’s enlightening to learn about the strategic applications you’ve outlined, emphasizing the tool’s impact on enhancing energy access and supporting comprehensive planning efforts.
Given the challenges posed by ongoing droughts, your focus on using FEA to deploy alternative and renewable energy solutions strategically is particularly pertinent. This not only aids in building energy resilience but also in promoting sustainable energy practices across communities.
Also, highlighting how energy data can influence other sectors like agriculture and mining opens up pathways for integrated development strategies that leverage energy access for broader economic growth.
As we continue to exchange knowledge and ideas, I’m interested in hearing how you see the role of UNDP in enhancing the effectiveness of tools like FEA in Zambia?
Inya Nlenanya :
UNDP can play a crucial role in enhancing the effectiveness of FEA in Zambia by improving data collection and analysis capabilities anchored on the FEA data within the local country context. Through strategic partnerships with key stakeholders such as the Ministry of Energy, the Energy Regulation Board (ERB), Zambia Electricity Supply Corporation Limited (ZESCO), the Rural Electrification Authority (REA), local authorities, and the private sector, UNDP can facilitate capacity-building initiatives. These initiatives could equip local partners with the necessary skills to effectively collect and analyse FEA-supported energy-related data and integrate this data into the National Spatial Data Infrastructure (NSDI), thereby optimising energy planning and implementation across Zambia. Therefore, we can facilitate the incorporation of both the energy data collected by local partners and the FEA data into national energy policies and development plans by enhancing people's knowledge, access, and appreciation of FEA data and related technologies. This way, policy and decision-making can be based on accurate predictions and current energy needs. Additionally, the government can receive support in establishing robust monitoring and evaluation frameworks that utilise FEA data and that collected by its local partners to monitor development progress, assess the impact of energy policies, and modify strategies accordingly.
Bonjour,
Moi c'est Farida depuis les iles Comores.
Les outils généralement utiliser en union des Comores sont les enquêtes de proximité et en utilisant des questionnaires plus précis qui vont nous renseigner en matière de besoins et de pouvoir d’achat dans les ménages
En générale nous utilisons des questionnaires et des collectes de données existants dans le secteur de l’énergies afin de mieux programmer les activités prévues dans le plan de mise en œuvre de planification
L’outil FEA peut nous permettre de mieux planifier le déploiement de l’électricité hors réseau et en réseau et il nous aidera à mieux prévoir les besoins en énergies dans les zones cible
L’outil peut être utilise dans le cadre d’un développement socioéconomique dans les zones identifier, en effet le FEA peut nous permettre de mieux comprendre les ambitions des zones en matière de rendement socioéconomique de la population cible et de mieux prioriser les activités du projet et de leurs faisabilités dans le temps.
La rendre beaucoup plus facile à utiliser pour les utilisateurs et les responsables du projet. Faut aussi avoir une version de l'outil en français pour une meilleure appropriation et utilisation dans les pays francophones.
Thank you Farida for sharing what tools you are currently using in the Comoros Islands and how FEA can allow you to do better planning and targeting solutions to where needed. Also, your emphasis on enhancing the usability of the FEA tool for project managers and making it available in French highlights an essential aspect of any technology adoption—accessibility. Given your experience, it would be valuable to hear from you who are the users that would benefit the most from the FEA tool are and further discuss how we can improve the usability for the identified user? Looking forward to your thoughts and continued conversation on this very important topic.
Greetings colleagues from Malawi, my name is Mathangeni Ngwira working as an Energy Analyst with the Malawi CO.
I will mainly focus on the first two questions, for question 1, since most of our energy interventions deal with mini grid development, an electrification master plan is used is used to pinpoint suitable areas (for min grid development) that are further from the grid and will take a lot more time to get electrified. This master plan was developed by the ministry of energy, and it is the nation guide for grid expansion, it is therefore this tool that is used to identify electrical energy gaps and provides the appropriate selection criteria for mini grid sites.
There is an Integrated Energy Planning (IEP) tool, which is an online platform that has information on energy access, there’s also the Rural Electrification master plan whose custodian is the ministry of energy, and recently through the ACRE project UNDP together with the World Bank supported the Ministry of Energy and the National Statistical Office (NSO) with the Global Tracking Framework (GTF) to conduct a Multi-Tier Framework (MTF) survey which provides the status of both access to electricity and access to modern energy cooking solutions in the country. These are some of the tools used/will be used for microplanning when it comes to energy access.
Greeting Manthageni, thank you for sharing your thoughts. I noted that in Malawi you used different sources of data and tools such as IEP to identify the development of electrification. As Malawi electrification plan is focused on mini-grid, what are the requirements for an areas to be considered into mini grid network? How could the FEA tool assit in Malawi's development plan?
Hello, Diana Mae Calde. The master plan basically works on extending the main national electricity grid, it therefore leaves room for other players (like mini grid developers) with the capacity to develop mini grids, a site qualifies for mini grid development if it is not the masterplan’s list to be electrified in the next 5 years and it should be more that 10km away from the main grid. The FEA tool would for one help providing the demand for electricity and electrification pattern which would help in proper planning from both the public and private sectors.
Hi Everyone. Thankyou Inya Nlenanya for the invitation to join this knowledge-sharing platform. Re: question on "How can the FEA tool be enhanced to provide improved support for your work?". Without a doubt - this is a powerful instrument that can unearth trends in electrification, and believe will be further enhanced to be more robust. I think one significant way to improve the tool is by integrating localized data specific to individual countries. This data can be multi-dimensional, capturing a wide range of factors that influence electricity access. For instance, in the case of a country like South Africa, this data could encompass various dimensions, such as:
By incorporating these localized datasets, the tool would be better equipped to generate forecasts that are not only more accurate but also more relevant to the unique characteristics and needs of a country’s energy landscape. This would enable countries to make more informed decisions and develop strategies that are tailored, ultimately leading to more effective and sustainable energy solutions.
Thankyou Inya Nlenanya
Regards,
Mpumi Ngwenya
Dear Mpumi Ngwenya,
Thanks for your comprehensive narative and interesting sugestion on the localisation of FEA. In the current modeling we use two types of drivers: the cellular automata generated insights and the covariates generated insights.
While the first category is part of a mathematical framework/machinery building on the concept of spatial autocorrelation (things that are closer in space are more likely to be alike), the second category uses independent variables like: population, urban sprawl, distance to roads, distance to electrical grid, land use and terrain slope to guide/drive/constrain the predictions.
Your suggestion to include a series of socio-economic indicators is interesting as well and has potential to create custom local versions of FEA that operage at hyperlocal level. One thing that we must ensure is the availability of the variables in the whole of the spatial domeain. Obviously on local scale this is not an issue but, in general only variabels that cover whole Global South can be considered as this is the modeled area.
Hello colleagues, I am Sambou Nget, Programme Specialist and Head of Environment and Climate Resilience at UNDP Gambia CO.
On the question: How Can We Use Geospatial Innovation and AI to Leave-No-One-Behind in Electricity Access?
The Gambia like many other countries in Sub-Saharan Africa, is seeking to improve living standards and reduce poverty, which is most prevalent in the rural areas. Increasing access to modern forms of energy, particularly electricity, is a key element in poverty reduction, which allows households and communities to increase their productivity and incomes and improve their health and education status, thereby laying the foundations for a stable, inclusive, and brighter future for The Gambia.
The Government of The Gambia considers electrification to be one of its priority areas of intervention and is committed to universal access by 2030. To this end, the promotion of renewable energy (RE) has also become a national priority. The Gambia has subscribed to the international Sustainable Energy for all (SE4ALL) Initiative, and is also committed to increasing the share of renewable energy in electricity generation from around 2% in 2019 to 30% by 2030 as enshrined in the country’s Energy Road Map. With the technological advances in renewable energy, the Gambia’s electrification options have now broadened. Standalone solutions such as solar home systems, solar Multi-functional Platforms, solar mini grids are part of the focus for electricity access and expansion in The Gambia. The CO is currently supporting the Ministry of Petroleum and Energy in the installation of a 120kWp solar mini grid system to connect 115 households in some isolated and hard to reach communities and has finalized a feasibility study for another mini grid in the rural area. The use of Geospatial Innovation and AI can really support these initiatives by determining the location of off-grid and hard-to-reach communities, forecast the demand by area using the forecast number of users by user class and the forecast average consumption of each class as well as determine the likely mini-grid electricity service area and location of the powerhouse site amongst others.
Hello Sambou,
Thank you for sharing the approach that The Gambia is taking to improve electricity access and advance renewable energy initiatives. It's great to see the commitment to achieving universal electricity access by 2030 and the strategic focus on renewable energy as a pillar for national development.
Your comment on how geospatial innovation and AI can aid these efforts highlights the transformative potential of these technologies in making electrification more inclusive and effective.
The ongoing projects, such as the installation of the 120kWp solar mini-grid system and the feasibility studies for further expansions, serve as excellent examples of the potential of how the FEA tool as well as the clean energy equity index (CEEI) tool can help support a strong foundation for reaching the ambitious goals set in your national Energy Road Map. I will highly encourage you to weigh in on the CEEI discussion, your insight will be a great addition to the ongoing engagement.
As The Gambia continues to expand its efforts, I would be interested to learn more about how you see the role of policy and regulatory frameworks evolving to further support the adoption of renewable energy and technology-driven solutions in your electrification strategy and how we can work together to maximise that?
Looking forward to your insights and continued success in your initiatives.
Sambou Nget I'd be keen to hear your thoughts on Inya's question.
Hello Colleagues!
My name is Chibulu Luo, and I'll be moderating this week's discussions.
I can already see some exciting and important contributions from our colleagues in Gambia, Zambia, Cameroon, Liberia, Zambia, and South Africa. Thank you for engaging in this chat, I look forward to continued contributions!
From the discussions so far, the FEA tool could be transformative if applied appropriately at the country level. But I'd like to reflect on question 3 in particular: How does the FEA tool align with the energy access needs and objectives of your portfolio/ country context?
Energy access contexts are different and quite complex from one country to another. Therefore, beyond mapping electricity access rates and identifying where to deploy technologies, how can we ensure that the technologies account for the local realities at the community level? For example, data around community willingness to pay, electrification and cooking behaviours, and productive use activities, can be important inputs into the FEA tool. What are your thoughts around complementing such data with this tool to ensure better alignment with national contexts?
Also: input from kafula.kamiji, Mathangeni Ngwira indicate the opportunity for the FEA tool to support government policy and planning processes. Our previous moderator (Inya Nlenanya) asks a question linked to this to Gambia (Sambou Nget). How can we practically influence government appetite to promote the uptake and use of the FEA tool? How can we ensure complementarity across different tools that may already exist at the planning level?
Please engage with us, we look forward to your continued contributions!
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Hello dear colleagues,
It is a pleasure to e-meet you! I am Costanza Landini and I work on strategic policy, partnerships and innovation at the Mauritania CO.
Welcome to a new week of discussions on how FEA tool can be applied to your specific context. It is extremely fascinating to read all your considerations and see that last week our China CO also joint the discussion.
Building on Chibulu Luo's post, I would like to hear more on question 3. How does the FEA tool align with the energy access needs and objectives of your portfolio/ country context? It would be great to bring to the discussion colleagues from other regions as well!
Also, it would be interesting to steer our attention to how can the FEA tool be enhanced to provide improved support for COs' work. Do you colleagues think that such a tool could be interesting to help UNDP engage with government counterparts in the energy sector?
I wish all of us a productive week and I look forward to hearing your thoughts!
Bonjour chers collègues,
Je suis Jules Kikanda, conseiller technique principal/électrification rurale PNUD/Mauritanie
Dans la plupart des cas, nous réalisons la prévision de la demande en énergie sur base des données collectées sur terrain à partir d’un questionnaire d’enquête préalablement préparé, des observations visuelles réalisées dans la zone à électrifier et l’utilisation des formules empiriques pour déterminer la demande. L’analyse de la demande a un impact significatif sur la détermination si le projet est bancable ou non et donc son financement par le secteur public ou privé.
La fiabilité de la prévision de la demande est donc d’une importance capitale. L’outil devrait contribuer à fiabiliser la prévision de la demande car la collecte des données dans les zones isolées est très souvent confrontée aux problèmes d’accessibilité. Les résultats de l’analyse influencent beaucoup la bancabilité des projets et donc l’implication du secteur privé. Merci
Thank you Jules for sharing your approach to forecasting energy demand in Mauritania, and for highlighting the challenge of such efforts in the remote areas. We are definitely interested in partnering with you to ensure this tool is able to address these needs for the CO. And also, explore ways that we can work together to validate and improve reliability. Please don't hesitate to share you thoughts on how best to make this collaboration work for you. Thanks.
Hello, I'm Benyoh Kigha, and joining from the UNDP Rome Center for Climate Action and Energy Transition.
Addressing the fourth question: How can the FEA tool be used to support the energy access goals and ambitions in your portfolio/ country context?
First and foremost, ambitions, targets and goals are very specific and employing the tool through the following strategies will be vital in achieving these objectives:
1) Renewable Energy Planning: Utilizing geospatial data to inform national energy development decisions, including both off-grid and grid-connected solutions. By employing empirical methods, we can effectively assess the viability of various energy solutions.
2) Enhance Energy Optimization: Optimizing energy projects with the tool by considering factors such renewable energy potential, energy demand, proximity to grid substations, type and size of energy systems etc. are critical to enhance efficiency and reduce costs.
3) Foster Energy Transition and Climate Ambitions: Utilizing the FEA tool should enable informed decision-making regarding the transition from fossil fuels to clean energy sources. Factors such as cost, efficiency, and timeline are crucial in determining the scale and pace of this transition, aligning with national climate and energy goals and targets."
Thanks!
Hi kigha.benyoh,
Thank you for joining our discussion. You have raised some interesting points and I am on board with you views. Renewable energy planning can for sure leverage FEA because it can be used to derive stastics at specific admin levels (district, province) and this can guide and support crafting adequate intervention policies targeting the populations without access with high priority. However I would like to know if you could give us more details regarding the energy optimization. Do you have concrete idea on how electricity access can shape such aspects? I am thinking for example about using FEA to detect spatial clusters of low/high electricity access and overlay them with the existing grid stations and substations as to optimize the spatial distribution of future stations.
In the last aspect related to green energy transition you mentioned the timelines. I believe FEA can inform on the progress of electrification as the forecasting is done using a yearly time step. This it is possible to track the progress of SDG7 and associated measures.
Let us know your thoughs on the above.