Section: New Results

A methodological framework to promote the use of renewable energy

Participants : Alexandre Rio, Yoann Maurel [contact] .

This work is in line with projects aimed at optimizing the use of renewable energies. It is carried out in collaboration with OKWind. This compagny designs and supplies its customers with renewable energy generators such as vertical axis wind turbines and solar trackers. OKWind promotes a micro-grid infrastructure development.

Our application domains are those of agriculture and industry in which it is possible to identify and influence consuming processes. We mainly consider local generation for self-consumption purposes (microgrid) as it limits infrastructure costs, minimizes line losses, reduces the need of the Grid and hopefully reduces the electricity bill.

Renewable energies currently benefit from numerous subsidies to promote their use so as to reduce greenhouse gas emissions. Nevertheless, it seems worth considering the cost-effectiveness of these solutions without these incentives, as they are highly dependent on political will and can be questioned. The reduction in manufacturing costs, particularly in solar energy, suggests that these solutions can eventually compete with traditional sources if they are properly used.

Competitive low-carbon energy is hampered by the stochastic nature of these sources. During peak periods, the electricity produced is competitive, but too often, the scheduled consumption is not aligned with production. In practice, process planning was and is still driven by the electricity price from the grid. On average, the profitability of the installations is therefore not certain. In this context, using battery to shift the load looks appealing but is, as of today, far from being economically viable if not done properly.

Consequently, the achievement of a profitable self-production site is, in practice, a question of trade-off that involves several factors: the scaling of energy sources, the sizing of batteries used, the desired autonomy level, the ecological concerns, and the organization of demand. This trade-off analysis is very challenging: to be carried out effectively and comprehensively, it must be supported by tools that help the stakeholders. While much work has been done in the literature on the impacts of different factors, there are few approaches that offer a comprehensive model.

Our objective is to provide a methodological framework to embrace the diversity of knowledge, of production and consumption tools, of farm activities and of prediction algorithms. This should enable an expert to conduct a trade-off analysis and decide on the best option for each individual site under consideration.

In the first two years of this PhD thesis, we argued that model-driven engineering is suited for the development of such a model and we presented some preliminary implementation. In 2019, we were able to test our approaches in the field and continue to expand the model to account for a wider range of resources. This was published in [5].