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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.
\n\nThe 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.
\n\nIndigo DC planning tool requires following python version and packages:
\n\nAll files in main directory and in all subdirectories are released under the GPL 3.0 license.
", "funding": [ { "award": { "acronym": "INDIGO", "id": "00k4n6c32::696098", "identifiers": [ { "identifier": "https://cordis.europa.eu/projects/696098", "scheme": "url" } ], "number": "696098", "program": "H2020", "title": { "en": "New generation of Intelligent Efficient District Cooling systems" } }, "funder": { "id": "00k4n6c32", "name": "European Commission" } } ], "publication_date": "2018-10-22", "publisher": "Zenodo", "resource_type": { "id": "software", "title": { "de": "Software", "en": "Software" } }, "rights": [ { "description": { "en": "" }, "id": "gpl-2.0-only", "props": { "scheme": "spdx", "url": "https://www.gnu.org/licenses/old-licenses/gpl-2.0-standalone.html" }, "title": { "en": "GNU General Public License v2.0 only" } } ], "title": "INDIGO Planning tool - IndPT", "version": "1.2" }, "parent": { "access": { "owned_by": { "user": 32509 } }, "communities": { "default": "502a69c7-1dbe-44ab-a403-da6dab915d17", "entries": [ { "access": { "member_policy": "open", "record_policy": "open", "review_policy": "open", "visibility": "public" }, "children": { "allow": false }, "created": "2017-03-21T10:15:53.876974+00:00", "custom_fields": {}, "deletion_status": { "is_deleted": false, "status": "P" }, "id": "502a69c7-1dbe-44ab-a403-da6dab915d17", "links": {}, "metadata": { "curation_policy": "Papers and data related to the INDIGO project, funded under EU / H2020 Grant Agreement No.: 696098
\r\n", "page": "The main objective of INDIGO is the development of a more efficient, intelligent, and cheaper generation of District Cooling (DC) systems by improving system planning, control and management involving all components and levels of a DC system.
\r\n\r\nEU / H2020 Grant Agreement No.: 696098
\r\n\r\nTopic: EE-13-2015 - Technology for district heating and cooling
\r\n\r\nStarting date of project: 1st of March 2016
\r\n\r\nDuration: 42 months
\r\n\r\nWebpage: www.indigo-project.eu
\r\n\r\nProject Brief:
\r\n\r\nINDIGO is a Horizon 2020 EU-funded project carried out by 6 partners from across Europe and 1 from the United Arab Emirates that aims to develop a more efficient, intelligent and economical generation of District Cooling (DC) systems by improving the existing system planning, control and management tools. This will be achieved through two specific objectives. The first one is to widen the use of DC systems and motivate the competitiveness of European DC market by the development of two open-source tools: a planning tool for DC systems with the aim of supporting their optimal design; and a modelling library with thermo-fluid dynamic models of DC System components which will provide the designers detailed information about their physical behaviour. The second objective is to reduce primary energy consumption. This will be addressed by a ground breaking DC system management strategy focused mainly on energy efficiency maximization and on energy cost minimization.
\r\n\r\nThe main characteristic of this strategy is a predictive management capability. However, it will also address other challenges, such as the integration of different types of Energy Sources (including Renewables) and suitable coupling between generation, storage and demand. Intelligent and innovative component controllers (Predictive Controllers) will also be developed at all DC system levels. Some of them include embedded self-learning algorithms, allowing components to respond properly to the established set-points. In addition, open source tools and guidelines will be developed within the project in order to provide more confidence and, consequently, more openness when developing and using DC systems. INDIGO developments will be validated in a real District Heating and Cooling installation with appropriate conditions for testing the new functionalities. The project, coordinated by the Spanish institution VEOLIA, started in March 2016 and will last three and a half years.
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