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26 © Hasan and Airaksinen 2016 | The Role of Energy
- Operational tools that will increase opportu- The CITYOPT project is jointly funded by the
nities for user’s engagement through inhabi- European Commission through the Seventh
tants’ demand response in on-line optimiza- Framework Programme (FP7) - call ICT-2013.
tion and operational visualizations. 6.4 - Optimising Energy Systems in Smart Cities.
Project’s duration Feb. 2014 - Feb. 2017.
Pilots
5. Real Life Testing in the Helsinki and
There are three demonstration sites in the Otaniemi Regions
project: Helsinki-Finland, Vienna- Austria, and
Nice Côte d'Azur- France. For example, The Low-cost active technologies can be applied to
Helsinki case study evaluates electricity storage monitor the performance of new and retrofitted
solutions and business models in the new buildings. They heavily depend on ICT to
residential districts of Kalasatama and Öster- optimize the energy consumption without com-
sundom. In the planning phase of the new promising the level of the occupant’s satis-
districts, CITYOPT applications will examine faction of the indoor environment quality. A
technologies, sizing, placement, and steering of huge amount of data can be collected from
electric and heat storage solutions to find the buildings’ operations and their systems. On a
optimal solutions. The optimization goals in large scale, the problem is of classifying relevant
both study cases of Helsinki are divided into information for various stakeholders and their
two connected parts: 1. design optimization and needs from the big data mass. Project owners’
2. operational optimization. In part 1, the requirements and key performance indicators
optimization will choose the correct type and (KPI) are the starting points for processing the
size of energy storage units and its connections data. At the building level, the problem is the
to the energy producers and consumers, while hidden data in different systems. VTT and
in part 2 the optimization will find the optimum several companies are working together to find
operational modes. The optimization objectives ways to obtain and process the information into
can be minimizing investment cost (€), a usable format (Figure 6).
operational cost (€), CO2 emissions (tons per
year or per life-cycle), energy consumption
(kWh), etc.
Figure 6: Leading with data: from data to end-user applications. (Vesanen et al., 2015)
Science Target Inc. www.sciencetarget.com
