Section: New Results

Modeling activities and forecasting energy consumption and production to promote the use of self-produced electricity from renewable sources

Participants : Alexandre Rio, Yoann Maurel [contact] .

This work began in 2017 and is carried out as part of a broader collaboration between Tacoma, the Diverse Team and OKWind, a company specialized in the production of renewable sources of energy. OKWind proposes to deploy self-production units directly where the consumption is done. It has developed expertise in vertical-axis wind turbines, photovoltaic trackers, and heat pump. This project aims at building a system that optimizes the use of different sources of renewable energy, choosing the most suitable source for the current demand and anticipating future needs. The goal is to favor the consumption of locally produced electricity and to maximize the autonomy of the equipped sites so as to reduce the infrastructure needed to distribute electricity, to set energy cost, and to reduce the ecological impact of energy consumption.

Modeling and forecasting production and consumption of a site is hard and raises several issues: how to precisely assess the consumption and production of energy on a given site with changing conditions ? How to adequately size energy sources and energy storage (wind turbine, solar panel and batteries) ? And what methods to use to optimize consumption and, whenever possible, act on installations and activities to reduce energy costs ? We aim to propose tools to predict the consumption of a site based on estimation and previous observation, monitor the site in real time and forecast evolution. We propose to build a DSL describing consumption and production processes, and a system providing recommendations based on the derived model at runtime.

The problem of forecasting is known from both a production and consumption point of view. OKWind has developed tools to predict the production of their renewable sources - the same goes for batteries - and a lot of theoretical work has been done on consumption in the literature. In our view little has been done to precisely model activities, their energy consumption and the associated variability. Indeed most of the current approaches are concerned with either large-scale forecasting for the Smart Grid, are based on coarse grain data (total energy consumption of the site), or focuses on modeling specific appliance without describing how and when they are used.

This is paradoxical considering that companies have spent a lot of time modeling their activities from a logistic point of view. Intuitively, the predictable and seasonal nature of a company's activities would allow building activity schedulers that favor the consumption of certain energy sources (the cleanest or least expensive one for instance). The development of a DSL to describe the relationships between activities, their planning, and the production and environmental factors would make possible to simulate a given site at a given location, to make assumptions on sizing, and would be a basis to forecast energy consumption so as to provide recommendations for the organization of activities.

We already have developed part of this DSL that simulates activities and production. In particular, it is capable of simulating consumption and production over a given period based on available environmental data. This tool is in the experimentation phase. In particular, we are collecting information on several sites to measure the consumption of various activities.