October 2020 Second Opportunity SME-II Grant number: OPPORTUNITY/0916/SME-II/0005, Research & Innovation Foundation, Cyprus HYPPOS receives € 700,000 funding from the Cyprys Research & Innovation Foundation towards further development with project duration of two years (10.2018-10.2020). In June 2020, HYPPOS entered its Beta Testing phase at the state-of-the art polypropylene plant of Hellenic Petroleum petrochemicals unit in Thessaloniki, Greece which was pivotal for the success of the project for two reasons. Despite the challenges due to travel restrictions and prohibition of external visitors to plant floors imposed by COVID-19, even after the lock-down periods, we took the opportunity to develop a dedicated procedure for remote commissioning.

June 2023 Hyperion Systems Engineering Group attended the 33rd European Symposium on Computer Aided Process Engineering (ESCAPE33) which took place in Athens, Greece between 18-21 June 2023. Our company presented two papers, and our participating team had the opportunity to reconnect with colleagues, professors and friends. For more details go to: 33rd EUROPEAN SYMPOSIUM ON COMPUTER-AIDED PROCESS ENGINEERING – 18-21 JUNE 2023, Athens, Greece (www.escape33-ath.gr) Our papers are included in the conference proceedings and we would also be happy to share with anyone interested. If you are please send us your name and contact email so that we can forward you a copy directly. Achieving Operational Excellence by Combining Material Tracking and On-line Polymer Analysis and Classification data in an all-in-one Integrated Decision Support System Prediction of Melt Flow Rate (MFR) in polymer production, with auto-regressive Machine Learning algorithms, for multivariate time-series measured in irregular timestamps

March 2023 Elpedison is the first independent electricity producer in Greece and a leading supplier of electricity and natural gas. The company ensures an environmentally friendly power generation process, with its two plants in Thisvi and Thessaloniki, which use exclusively natural gas as fuel. With innovation deeply rooted in its DNA, the Company has a vision to become the leader in providing leading energy products and solutions. Both plants use AspenTech MES technology for real time information management, KPI reporting and the foundation for several layered applications including integration and data exchange with IPTO/ADMIE, the Greek power grid operator. Hyperion is proud to be a trusted advisor and services provider to Elpedison since 2018 helping the company extract maximum value from its investment in the AspenTech platform and ensuring that the systems work uninterruptedly.

June 2021 Three generators provided to a client in the USA by a well-known manufacturer were not preserved well and suffered considerable damage when water entered the generators during a hurricane. Hyperion Power Services (HPS) provided technical support by a generator design expert to describe the extent of the damage and to support SNC Lavalin in their claim against the manufacturer who were responsible for the preservation of the generators. The issue has now been settled between the two parties.

March 2022 Hyperion Group is proud to announce that its HYPPOS related project Embed-AI was selected for funding for by the Cyprus Research & Innovation Foundation within the context of Research in Enterprises (Bridge Programmes). The main objectives of project EMBED-Al are to validate the scientific and technical targets of HYPPOS-AI prototype v.2 in an operational environment and to intensify Hyperion’s research and development in AI/ML, and innovation activities. Our company successfully released HYPPOS v.1.0 within the framework of the 2nd Opportunity grant from the Cyprus Research & Innovation Foundation. Drawing from the HYPPOS-Machine Learning (ML) Smart Sensors project findings, through Project EMBED-Al, Hyperion has been seeking support towards the technological upscale, optimization, demonstration, and exploitation of HYPPOS-AI as an Industry 4.0 solution. The figure below illustrates the HYPPOS completed projects, deliverables, and technical readiness levels: The Cyprus Institute (CyI) is the participating research partner of Hyperion that will support the project with through its engagement through the technology transfer of AI/ML expertise to Hyperion.

April 2021 Hyperion Power Services (HPS) led the root cause analysis to establish the reason of failure of the Low Pressure Turbine that suffered first stage blade cracks. These rendered the turbine unsafe to operate. HPS engineers, working with the manufacturer, performed forensic engineering and recommended measures to prevent a repeat failure of the repaired turbine. Measures to prevent similar failures from environmental factors were recommended and applied to the site.

May 2022 HYPPOS had a frontline position during the ABB Energy Industries (www.abb.com) special edition webinar on “Improving efficiency, quality and sustainability in polymer production”. HYPPOS solution architect, Symon Doe and Symeon Kassianides presented the solution and the ways in which our digital twin technology can help solve some of today’s biggest challenges in polymer production. The webinar also featured a key contribution by Nicos Perperis from the Hellenic Petroleum Polypropelene production plant who shared experiences and benefits from the use of HYPPOS. Hellenic Petroleum (www.helpe.gr) is Hyperion’s official HYPPOS launching partner and has been using the technology in productive use at the Thessaloniki PP plant for over 18 months. Click here to download the presentation slides and click here to see the video recording of the webinar. (Video Link: https://videopress.com/v/6yxf7YxU?resizeToParent=true&cover=true&preloadContent=metadata&useAverageColor=true)

July 2022 Hyperion Power Services provides expertise to several generating plant Owners and to the Peruvian grid operator (COES) to resolve the Sub Synchronous Resonance (SSR) issue in Peru The SSR phenomenon has been a serious concern to generating companies in Peru following the catastrophic failure of four GE Frame 7 units, all located in a plant in Southern Peru. Our Hyperion Power Services was called to provide a world class expert in SSR remediation who, working with the Grid Operator for Peru, COES and the plant Owners, scientifically modeled the grid and demonstrated the reason for failure. Three of the four turbines and two of the four generators were replaced and/or repaired at great cost. COES issued an RFP and HPS proposed ways to minimize/eliminate the SSR risk on the grid. About the SSR phenomenon Sub-Synchronous Resonance is relevant to various generator types, and proper analysis and control measures are crucial to prevent instability in power grids. It can occur in grids that connect different types of power generators: Wind Turbines: In remote areas, wind farms are connected to the grid via long transmission lines. When DFIG-based wind turbines are integrated into such series-compensated grids, SSR becomes a concern. SSR refers to low-frequency oscillations caused by the interaction between the wind turbine controllers and the series-compensated power grid. Steam Turbines: In power systems with series compensation, steam turbines can experience SSR. The interaction between the mechanical shaft system and the electrical system can lead to sub-synchronous oscillations. Hydroelectric Generators: Hydro generators, especially those with long transmission lines, are susceptible to SSR. The hydro generator’s rotor dynamics and the grid’s impedance play a role in these oscillations. Gas Turbines: Gas turbines connected to series-compensated grids may encounter SSR. The control system and grid characteristics influence the severity of these oscillations.

February 2021 We are pleased to announce our recent collaboration with The Cyprus Institute involving High Performance Computing (HPC) and Artificial Intelligence (AI) which falls under the framework of the EuroCC project. Machine Learning Algorithms Computational scientists at the Computation-based Science and Technology Research Center (CaSToRC) are developing ML algorithms with Hyperion that use vast amounts of production plant measurement data to develop models to predict critical quality parameters of the processed material based on real-time conditions. The models will be embedded in Hyperion’s solutions and serve as virtual instrumentation that will infer measurements that can be used to help isolate low quality material more efficiently and dramatically reduce waste and, thus, costs for a plant.