Indigo DC planning tool (IndPT) supports the optimal design of new DC systems, the assessment of existing systems’ potential for performance or efficiency improvement and the comparisons with building specific cooling systems. Consumers, distribution, production and storage of the cooling energy in DC system, are linked together in the planning tool to obtain the available solutions. Life cycle analysis (LCA) framework is used for economic feasibility and climate impact assessment. The tool may also be used to estimate the size of energy storages based on the availability of resources and variation of demand and costs. The main input parameters are cooling demand, structure of cooling production, distribution network characteristics and available resources. Secondary input includes data on energy commodity prices, investments and specifications for components e.g. local heat and electricity generation. As an output, the tool provides primary energy consumption, greenhouse gas emissions and costs of the system. The defined potential district cooling system can also be compared with building specific cooling systems delivering the similar cooling service. Indigo DC planning tool requires following python version and packages: Python 3.4 pyside 1.2.4 qt 4.8.7 oemof 0.2.2 matplotlib 2.0.0 All files in main directory and in all subdirectories are released under the GPL 3.0 license.

Includes licence file