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INDIGO Planning tool - IndPT

Räma, Miika; Sokka, Laura; Pursiheimo, Esa; Klobut, Krzysztof; Koponen, Kati

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    <subfield code="a">Main changes:
-	An option has been added for deleting selected scenarios
-	Updating cooling demand time series is possible without redefining each consumer
-	Storage cycles are now calculated correctly 
-	Some corrections have been made to the economic calculations
-	Some changes have been made in default input data specially to price levels</subfield>
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    <subfield code="u">VTT Technical Research Centre of Finland</subfield>
    <subfield code="a">Sokka, Laura</subfield>
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    <subfield code="u">VTT Technical Research Centre of Finland</subfield>
    <subfield code="a">Pursiheimo, Esa</subfield>
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    <subfield code="u">VTT Technical Research Centre of Finland</subfield>
    <subfield code="a">Klobut, Krzysztof</subfield>
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    <subfield code="u">VTT Technical Research Centre of Finland</subfield>
    <subfield code="a">Koponen, Kati</subfield>
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    <subfield code="c">2018-10-22</subfield>
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    <subfield code="u">VTT Technical Research Centre of Finland</subfield>
    <subfield code="a">Räma, Miika</subfield>
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    <subfield code="a">INDIGO Planning tool - IndPT</subfield>
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    <subfield code="a">user-indigo</subfield>
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    <subfield code="c">696098</subfield>
    <subfield code="a">New generation of Intelligent Efficient District Cooling systems</subfield>
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    <subfield code="a">GNU General Public License v3.0 only</subfield>
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    <subfield code="a">&lt;p&gt;Indigo DC planning tool (IndPT) supports the optimal design of new DC systems, the assessment of existing systems&amp;rsquo; 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.&lt;/p&gt;

&lt;p&gt;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.&lt;/p&gt;

&lt;p&gt;Indigo DC planning tool requires following python version and packages:&lt;/p&gt;

	&lt;li&gt;Python 3.4&lt;/li&gt;
	&lt;li&gt;pyside 1.2.4&lt;/li&gt;
	&lt;li&gt;qt 4.8.7&lt;/li&gt;
	&lt;li&gt;oemof 0.2.2&lt;/li&gt;
	&lt;li&gt;matplotlib 2.0.0&lt;/li&gt;

&lt;p&gt;All files in main directory and in all subdirectories are released under the GPL 3.0 license.&lt;/p&gt;</subfield>
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    <subfield code="a">10.5281/zenodo.1407213</subfield>
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