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
Rui Yu
Unlike other European countries performing individual dimensioning, the four Nordic TSOs require a common FRR dimensioning methodology to exploit the synergies of the Nordic synchronous system and they strive for the additional benefits of a common Load-Frequency Control (LFC) Block.
This makes the sizing of reserves particularly challenging, due to the multi-area aspect and the possible congestion in the links connecting these 11 LFC areas.
The Swedish TSO, Svenska kraftnät, has contracted N-SIDE to develop a reference model and a methodology for the sizing of reserves in the Swedish control area, leveraging N-SIDE’s expertise in balancing capacity dimensioning and thorough knowledge of the Swedish context.
During the project, various potential approaches have been identified following a state-of-the-art literature review and a qualitative CBA. The methods have been evaluated against several criteria including computational complexity, data requirements, or regulatory compatibility. In the last phase of the project, N-SIDE has implemented a proof-of-concept model of the dimensioning of aFRR and mFRR reserves for the four LFC areas in Sweden, based on a mixed-integer linear programming (MILP) model. Svenska kraftnät and N-SIDE are currently investigating possibilities to expand the model further, including dynamic approaches for instance.
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