With the aim of preserving our planet and nature, great amount of research is focused on increasing energy savings, especially the one extracted from the fossil fuels. Thus, there is a tendency of increasing the share of renewable energy production in the market, with the final aim of providing completely independent users with their own production, known as (near to zero) energy buildings. Moreover, apart from saving the planet, with the growth in RES production, user’s costs are tended to be decreased.
Unfortunately, because of the high correlation between the stochastic weather conditions and RES production such as photo-voltaic panels (PVs), wind turbines (WT), solar-thermal collectors (STC), etc., as shown in Figure 1, with the increase of the RES share, grid stability is highly jeopardised.
Therefore, it is inevitable to include the advanced optimisation approach in order to shift user’s demand and adjust it with the energy production, so to improve grid stability, decrease CO2 emission and costs. This approach has been explained in our previous blog post Optimising the energy demand of neighbourhoods under DR umbrella.
Taking all of previous into account, within the RESPOND project we have developed energy production forecaster service, which estimates the pilot’s RE production for all of the three pilot sites – PV production forecasters for Aarhus and Aran pilot and STC for the Madrid one. Our models use the one day ahead forecasted weather data from https://www.weatherbit.io, and estimates the production for the next 24 hours, with the hourly resolution. Finally, those results, as mentioned, are used by the optimiser in order to adjust the demand and provide suggestions for our end users.
Additional application of RES production can be correlated with the Demand Response (DR) events. Namely, in order to direct users to adjust their consumption with the RES production, ESCOs can define explicit DR events when renewables are producing or producing above some threshold. The example is shown in Figure 1 where with orange and light blue shades intervals with DR events are indicated. In this way, by providing monetary benefits, the effect on energy savings of the users is the highest.
Dea Pujić, MSc EE & CS
Institute Mihajlo Pupin
Volgina 15, Belgrade, Serbia