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The potential to generate solar hydrogen for cooking applications: Case studies of Ghana, Jamaica and Indonesia

Abstract This paper evaluates one option to replace traditional cooking fuels in developing economies with a flexible, modular and clean solution of solar hydrogen, based on a numerical and experimentally tested system to address technical and safety issues. The study focuses on Ghana, Jamaica and Indonesia as examples of developing economies using fossil fuels for domestic cooking. Statistical analyses are performed and the domestic cooking demand profiles are created for these countries based on available data and a specific quantitative study in Ghana. The derived cooking demand profiles are used to size solar hydrogen plant case-studies for rural communities based on a TRNSYS numerical model. The results indicate that hydrogen plant sizing and management satisfy annual cooking demands of the communities which are 621.6 kg H2 for Jamaica, 631 kg H2 for Indonesia and 785 kg H2 for Ghana. The effect of the weather data on the simulation is estimated by comparison between TMY and recent weather data for Jamaica. Finkelstein-Schafer statistics indicate differences between the composite and recent weather data, but these prove to have minor effect on simulation results, with 0.9% difference in hydrogen generation. The potential to establish solar hydrogen plants in the countries is further evaluated by creating novel solar hydrogen potential maps.
- Brunel University London United Kingdom
- Brunel University London United Kingdom
- Ho Polytechnic Ghana
- University of Technology Russian Federation
- Ho Polytechnic Ghana
690, 330, Cooking energy in developing economies, Weather data, Solar hydrogen, Renewable energy simulation, Hydrogen potential maps
690, 330, Cooking energy in developing economies, Weather data, Solar hydrogen, Renewable energy simulation, Hydrogen potential maps
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).26 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
