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Motoroil, Greece - One of the largest South-eastern Europe refineries

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Site overview
Motoroil (MOH) refinery at Agioi Theodoroi is located close to city of Corinth and around 60Km west of Athens. MOH owns and operates one of the largest refineries in South-eastern Europe with the highest complexity at European and world-wide level and is also a “Seveso” site. Due to its flexibility it can process crude oils of various characteristics and produce a full range of petroleum products. Within the refinery complex, MOH has an installed storage capacity of 2.5 million cubic meters (crude oil & products). Also, a fully operational truck loading terminal delivers products to continental Greece and the region of South East EU.
  
MOH Refinery is a critical infrastructure for the energy system in South-Eastern Europe that may be exposed to physical and cyber threats. Those threats are continually identified, and related prevention, detection, response and mitigation mechanism are continually developed within the company.

Expected innovation and InfraStress Added Value
InfraStress is strongly in line with MOHs culture and strategy of continuous investigation of new approaches that might mitigate the existing hazards. MOH is located in one of the most earthquake prone areas in Europe and therefore the earthquake is one of the major threats that will be investigated in detail. Interrelationships and cascading effects will be assessed. InfraStress cyber tools will be also evaluated. MOH will provide an area where physical security sensors will be deployed, and cyber/physical detection will be demonstrated, using the National earthquake detection network and the National atmospheric monitoring network data in real time in order to complement the local environmental monitoring. In addition, NOA will make available all real time data of a unique experimental earthquake early warning network that will be installed in the broader area of MOH refinery within 2019 in the frame of a nationally funded project (ARIS). Part of the demonstration scenario will include decision support tools for response (ie. plum modelling) in case of accident.

 

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement n°833088

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