RDA P6 Climate Change Data Challenge Application: Meso-Star

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31 August 2015 1798 reads
Meso-Star SAS represented by Benjamin Piaud
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Describe the possible application or solution you are developing and how does it constitute a challenge goal
The Eco-districts the heart of energy and environmental issues.
Residential and commercial buildings and transport account for around 70% of energy costs in a country like France. Thus the design and optimization of eco-districts of the future is unavoidable in the energy and environmental context.
Innovative tools for eco-districts design.
Meso-Star offers an innovative modeling methodology and simulation of complex systems and associated software. We provide expertise in understanding complex systems, with the actors of the concerned field, with an objective of design and optimization. We start by dealing the right question until the implementation with the development of custom software. The originality of the method lies in a statistical model formulation that leaves free the expert to select the required level of complexity.
Our proposal is to develop the tools that will allow the building actors, of renewable energy, of transport infrastructure and networks, the architects and urban planners to design together some more efficient eco-districts using climate data available.
How will your solution involve the proposed datasets?
Mastering the complexity without reducing it.
Modeling and simulation are used to design increasingly energy-efficient buildings and to optimize the energy production processes. The energy and environmental challenges need to go further in the understanding, design and optimization. Going further request a breakthrough in the approach able to master the complexity without reducing it.
In the case of designing an eco-district, this complex system can not be considered as the assembly of buildings, production systems and energy distributions and other components, designed and optimized independently. The standard approach to design and to optimize systems generally requires a simplification of the basic constituent. In the case of an eco-district this means, for example, simplify the geometry or consider an average sunshine forecast for photovoltaic production. These choices imposed by the simplification approach prevents full use of the potential of the available climate data.
A consistent modelling with climate data.
Our proposal is to develop tools with the ability to integrate the required level of complexity of the geometric description of the system studied physical models and the use of climate data without simplifying. Thus our methodology will allow experts to freely choose the right level of consistency in finesse modelling with the richness of data available.
Which are the datasets integrated in your solution demonstration? Select from the dropdown list.
Code: RDA_ClimateChallenge_daymet_07
What is the expected impact?
Ability to integrate multiple scales of time and space
From a technical perspective, the statistical formulation can integrate the dynamics of the model over several decades including the climatic environment without simplifying the building blocks of the model. For example, simulation of power generation integrated photovoltaic panels on their lifecycle be possible without averaging sunshine. If a typical temporal signal of the incident solar power can be generated from the available climate data so it can be integrated into the simulation without simplification such a discretization.
The emergence of an ecosystem.
Economically, the expected impact is the emergence of an ecosystem around a new methodology that will give rise to new services and software tools. These will be developed in close partnership with the actors for whom they are intended: the building actors, of renewable energy, of transport infrastructure and networks, the architects and urban planners.