Grid solutions
N-SIDE helps system operators make optimal decisions by providing AI software solutions, from system planning to the control room of the future.
Power exchange solutions
Seamlessly match supply and demand in challenging electricity markets. N-SIDE is the trusted provider of auction-based electricity market clearing algorithms.
Forecasting
N-SIDE uses machine learning to produce a variety of forecasts for system operators, including system imbalance forecast, reserve needs forecast and congestion risk forecast.
Power Matching
This robust market clearing algorithm matches supply and demand bids in a closed-gate auction fashion, considering potential congestion and other constraints.
Outage Planning Optimization
Leverage advanced analytics to determine the optimal strategy and daily schedule for grid interventions and related outages.
Dynamic Reserves Dimensioning
TSOs: dynamically adapt reserves volume based on the real imbalance risk faced by the system using machine learning and advanced analytics.
Professional Services
Whether your challenge can be solved by our existing products or requires the development of new analytics solutions and market design approaches, our team is ready to help.
Resources
The latest insights from N-SIDE
Pauline Martin
On June 24th, the new initiative IO.Energy (Internet Of Energy) facilitated by ELIA, ORES, Fluvius, Sibelga, Resa, has organized the Ideation closing event, a first important milestone. At the end of the day, 8 projects were indeed selected to help shape the energy landscape of the future (Read the press release)
N-SIDE is proud to be part of the nominated IO.Energy (Internet Of Energy) use case Sensa (previously named CheckMyFlex), along with ORES, ELIA, Engie, NRB, One Smart Control and Automation. The project has been designated as preferred use case, following a poll at the closing event of the ideation phase.
The project Sensa, using an implicit market mechanism, will cover the full value chain of flexibility for the power systems, from the end-customer to the distribution and transmission system operators, but also local energy communities and commercial market parties.
The main parts are:
- an application to engage the consumer to provide flexibility and incentivize him/her to invest in flexibility .
- a smart box, installed at your home, that can automatically control your devices according to your comfort level settings, based on a price signal, in order for you to get rewarded.
- Several price engines aiming at sending price signals to smart boxes, for different purposes (e.g. balancing, congestion management, auto-consumption).
In particular, N-SIDE develops, together with ELIA, the algorithms behind the smart pricing approach, using machine learning. The challenge is to constantly adapt the smart pricing algorithms based on the observed market reaction to price signals, compared to the desired reaction.