In TEMPO, 6 technologies are developed and tested, namely:
- An automated on-line supervision platform to detect faults in DH substations
- Visualisation tools for expert and non-expert users
- A smart network controller to maximize sustainable energy consumption and minimize the return temperature
- An innovative piping system
- A building installation optimization
- Decentralised storage buffers
The mentioned technologies are developed in two phases. In the first period of the project, a first, intermediate version of every technology will be developed. Then, these technologies will be implemented in the demonstration sites and tested. After evaluation of the performance of the technologies, an updated version v2 will be developed. Again, they will be implemented in the demonstration site and tested once more.
Deliverable D1.1 briefly describes the functionalities of version 1 of all technologies, and suggestions about possible extensions for version 2 (which is reported in the follow-up deliverable D1.2). Also, installation guidelines are added, describing how the technologies should be applied in the demo sites.
The supervision platform to detect faults in DH substations makes use of primary side measurement data (supply and return temperature, flow rate and energy consumption). In v1, a number of performance indicators were deducted from those measurements, which makes it possible to rank the substations amongst their performance. In v2, the focus will shift towards more dynamic fault detection, whereby the performance of an individual substation is tracked over time.
The visualization tools of v1 are tailored for two groups of users. For experts, such as network technicians, a number of visualization tools were developed to analyse the proper behavior of the network. The expert visualisation tools in TEMPO are separated in core performance metric visualisers and combined performance metrics. The core visualisers make it easier to analyse the performance metrics, by relating them to a given context, while the purpose of the combined metrics is to analyse specific things by combining different graphs. When it comes to non-experts, e.g. tenants in apartment buildings, a number of visual tools were implemented giving the users an insight in their energy consumption.
The smart controller tries to control the heat demand in the network, in order to optimize the temperature levels in the network. Three different control strategies were identified for v1, which all will be tested in the demonstration sites. The optimization strategy is aiming to minimize the return temperature of the buildings connected to the network. In the coordinated buffer charging objective charges decentralised buffers in such a way that the peak loads in the network is minimized. This control strategy has been specifically developed for the Enerpipe case. Finally, the supply temperature optimization, makes use of the water in the network pipes itself is used as a virtual storage buffer: by increasing the temperature of the water in the supply pipes when excess heat is available, heat can be stored for a limited time.
The innovative piping system refers to the implementation of a smaller third pipe that should be operated, when necessary, to circulate hot water in the distribution network. Such a design should be able to reduce annual average return temperatures of about 10°C. In current systems, an embedded temperature error exists. This temperature error is small as long as buildings are energy inefficient. However, as buildings are anticipated to become more energy efficient, so are this embedded temperature error of district heating systems. The embedded temperature error occurs due to low flow rates in distribution networks at times of low heat demand (summer). The low flow rates cause temperature drop within the network, which implicates the quality of heat delivery services. To counteract loss of heat delivery quality, supply side water is mixed into return side water, resulting in increased return temperatures, disclosing the very typical characterization of increasing return temperatures in district heating systems during ‘summer’ outdoor temperatures. The innovative piping solution developed in TEMPO prevents this.
As a first step towards the optimization of the building installation, situations leading to high return temperatures have been identified and formalized. A comprehensive list of possible situations leading to high return temperatures was elaborated. The fault list is based on available literature on the subject and knowledge gained in previous national, European and international projects. The fault list currently contains 48 fault types. For each one of them, a short description of the problem, possible symptoms and correcting measures are proposed. Then, based on this list, a practical guide for technical audit of building installations was developed. Some of the situations compiled in the list have been selected for simulation. The selection took into account ease offault modelling, assumed frequency and assumed impact of faults. Simulation scenarios in which these faults are modelled were defined and implemented, leading to the generation of data for the training of fault detection and diagnosis algorithms.
The Deliverable D1.1 finally describes 4 versions of the decentralized buffers tailored for LT-networks. These versions are the result of continuous improvement. After the first version, amongst other, improvements were made on the positioning of components and a passive integrated circulation unit was developed. Also the domestic hot water station, provided by a third party manufacturer was exchanged by a station developed and manufactured inhouse, with extra sensors. Multiple updates were also targeting easier manufacturing, maintenance, transportation and installation of the decentralized buffer tanks.
Deliverable D1.1 “Report innovation installation guidelines 1st version” developed within WP1 of the H2020 TEMPO project, is a confidential deliverable and is therefore not publicly available. However, we will be happy to answer your questions if you are interested in similar solutions.
Please contact: Dirk Vanhoudt (VITO, email@example.com)