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Optimal Site selection for Hydrogen Storage using GIS
To achieve net zero emission targets replacement of fossil fuels is inevitable. In grand scheme of things Hydrogen plays a grand role in taking a major part of new fuel economy [1]. Techno economic analysis of hydrogen energy systems presents a very bright outlook [2]. The energy transport cost will also play an important role for the ultimate energy pricing. Therefore, it becomes imperative to search for the optimal installation locations for the large/small scale hydrogen storage systems considering the environmental, geological and accidental risk factors. A Multi criteria decision making analysis coupled with GIS data would provide the most economical and safe installation sites [3].
The key steps envisioned for the completion of the project are as follows:
1. Literature Review and Data Collection: Comprehensive review of existing literature on the use of GIS for the selection of sites for (energy) plant installation.
2. Data Extraction and analysis: use of Swiss maps (Maps of Switzerland - Swiss Confederation - map.geo.admin.ch) to collect information about the site and archive the information in usable formats for further use in simulation tool (based in python/MATLAB).
3. Implementation in Optimization Frameworks: Integration of the developed GIS tools to predeveloped simulation tool (in python) to provide the input data for the load demand. And use the simulation result to find the most optimal site for the installation.
4. Results Analysis and Report Writing: Evaluate the outcomes of the GIS based optimization tools, perform sensitivity analysis and draft a comprehensive report detailing the findings and implications of the study.
The key steps envisioned for the completion of the project are as follows: 1. Literature Review and Data Collection: Comprehensive review of existing literature on the use of GIS for the selection of sites for (energy) plant installation. 2. Data Extraction and analysis: use of Swiss maps (Maps of Switzerland - Swiss Confederation - map.geo.admin.ch) to collect information about the site and archive the information in usable formats for further use in simulation tool (based in python/MATLAB). 3. Implementation in Optimization Frameworks: Integration of the developed GIS tools to predeveloped simulation tool (in python) to provide the input data for the load demand. And use the simulation result to find the most optimal site for the installation. 4. Results Analysis and Report Writing: Evaluate the outcomes of the GIS based optimization tools, perform sensitivity analysis and draft a comprehensive report detailing the findings and implications of the study.
develop a GIS tool with the capability to be coupled with other quantitative analysis tools
develop a GIS tool with the capability to be coupled with other quantitative analysis tools