Poster Sergej Jakovlev

Research on heat transportation efficiency of Low-Temperature District Heating (LTDH) systems

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Introduction

Heat transportation in urban areas is a priority for developing regions. New efficient technologies and methodologies are being developed to increase the efficiency and adaptability of current heat transport systems. Optimal heat transport to urban and rural areas has always been a major concern for governmental agencies. Urban heat treatment systems must adopt new energy sources and transport methods, and deal with sustainability problems for rural areas as well. Water heat losses during transportation due to inefficient pipelines and an overall increase in weather temperatures during winter continues to diminish the sustainability of the new energy-saving regulations. In this paper, we demonstrate the importance of the new Heat transport systems according to the new trends to adopt new heat supply technologies for efficient, environmentally friendly and cost-effective community supply - like Low-Temperature District Heating (LTDH).

The aim of this paper is to present an innovative look at the heat transport system from the ICT perspective in accordance with Baltic Sea Region Program project “LowTemp” aimed to evaluate the possibilities of efficient and sustainable heat transport. The authors demonstrate the relative factors and demonstrate developed IT tools (see Figure 1).

The aim of this paper is to present an innovative look at the heat transport system from the ICT perspective in accordance with Baltic Sea Region Program project “LowTemp” aimed to evaluate the possibilities of efficient and sustainable heat transport. The authors demonstrate the relative factors and demonstrate developed IT tools (see Figure 1).

Method

The data collection methodology and consequential knowledge platform will be a tool to be disseminated and used beyond the project`s lifetime. It will be foreseen the development of training material to better explain the concept of the methodology and its application.

District heating data have different standards and levels of quality in the BSR partner countries. The selected key indicators and relevant information stored in database will have both qualitative and quantitative aspects of the district heating, making possible the evaluation and comparability of data on DH/LTDH in different BSR conditions. The data collection methodology implemented within the knowledge platform will also represents a supporting instrument for the finalization of the pilot energy strategies.

Development

The general structure of database is shown in figure 2. The general information about countries, regions and cities are stored in appropriate tables, and these tables are associated to “Generalized DH Multiple Data” and “DH Models” tables. The “Generalized DH Multiple Data” table is used to store numbers, texts, links and other unstructured data related to Country, Region and City specific DH information. The user from these database tables will be provided with the most relevant information about the country or region of his interest.

Each country has associated geographical data (like latitudes and longitudes of relevant places of the country) which is stored into “Geo Referenced Data” table. To store the country region and city related heat load models and the results of multi-criteria analysis for potential development of LTDH strategy the “DH Models” data table is used. Each DH model is associated to monthly information (see Annex 3) where indicators are stored into “Monthly Data” table and the list and description of parameters are stored into “Parameters” table.

Main results

The set of indicators is created for investigation of the development of LTDH as the result of the second step of the methodology. Some of the non-quantitative information is converted into measurable parameters. Then the experts evaluate reached results with the aim to identify if the represented set of indicators is appropriate for solving research problem. If no, then there is a need to improve the set of indicators. If yes, then the set of indicators are further processed with help of a mathematical tool to obtain results. The end results are in additional evaluated, and if the results are not acceptable the set of indicators is improved.

Indicator include:

• Technical indicators;
• Economical indicators;
• Environmental and climate indicators;
• Institutional-political indicators;
• Social indicators.

Main conclusion