MNRG · GridEye application on optimal multi-energy system management and optimal grid reconfiguration as flexibility tools
Horizon 2020 — Marie Skłodowska-Curie Actions
- Duration
- 2021-06-01 → 2023-05-31
- EU contribution
- €203,149
- Participants
- 1
- Scheme
- MSCA-IF
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Results in brief
GridEye application on optimal multi-energy system management and optimal grid reconfiguration as flexibility tools
Renewable energy resources and electrification of mobility are key solutions to reduce greenhouse gas emissions. Moreover, the wide penetration of renewable energy sources accelerates occupation in the EU, by job creation in different ‘green’ technologies. Aim behind the European Green Deal (COM(2019) 640 final) is to be the world’s first climate-neutral continent by 2050. However, their proper integration in a power grid encounters several challenges. For instance, the uncertain nature of renewable energy productions as well as stochastic consumptions of electric vehicles introduce remarkable intermittency to a distribution grid and results in bi-uncertain characteristics of both supply and demand sides. One way to verify the secure grid operation within acceptable voltage and loading levels is to assess its required flexibility considering possible boundaries of uncertain variables. In this publication, a flexibility estimation method is proposed which is based on the feasibility study of the uncertain space of load containing electric vehicles and photovoltaic powers. It allows evaluating the flexibility and lack of flexibility. In addition, the reconfiguration of a system including electrical and thermal energy with the objective of maximizing the system flexibility is modeled well.
Data: CORDIS, © European Union
Project objective
To achieve deep emission reductions in the European energy sector and in the heating sector in particular, stronger cross-sectoral linkages among the different energy carriers are needed. The main objective of proposed MNRG is improving operational flexibility by presenting a comprehensive digitalized, distributed and real-time monitoring of heat, mobility and electricity energy sectors which is required to deal with the uncertainty and variability of growing renewable resources and mobility. The main novelties of this project are: 1) MNRG provides an easy deployment and paired with unprecedented modularity for interconnected multi-energy systems by using GridEye's edge computing capabilities. 2) MNRG introduces a more practical way to manage and respond to the complex needs of the multi-energy systems in the presence of numerous energy components and devices. 3) The impact of DERs and EVs on the quality of energy sectors will be monitored in real-time and the flexibility in the operation of CHPs, use of reactive power controlling devices such as SVR and storage capacity of heat network will be considered as alternatives for technical challenges. 4) Real-time preventive and corrective actions based on dynamic feeder reconfiguration against over-voltage and congestion in the grid will be addressed. To determine network topologies optimally, methods based on machine learning or mathematical techniques will be implemented. 5) By MNRG, the behavior of feeders and transformers that are utilized by DERs and EVs will be predicted for DSO’s usage. In this regard, MNRG feeding by updated forecasts based on mathematical methods, like, ARIMA and deep learning methods, such as DRL and LSTM, will provide corrective and preventive actions. 6) MNRG can provide robust strategies for DSOs by using uncertainty modelling techniques such as robust optimization to tackle the volatility of uncertain parameters.
Original text from CORDIS.
Participants
- DEPSYS SA · PUIDOUXCoordinatorSwitzerland
Links
Data: CORDIS, © European Union