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About the Project
Renewable energy sources (RES) are a proven tool in reducing harmful green house emissions. The usage of RES as well as energy storage have transformed the energy sector and now new topologies such as smart grids are fast replacing traditional power networks. Multi vector energy systems (such as electricity, hydrogen, and transport) can be used to increase the RES penetration as they can offer many advantages over single career energy systems such as purely electrical grids. While a multivector approach can help with the penetration of RES, it imposes several obstacles in the controllability of such systems due to the different structural, temporal and logical features of the different vectors. In the past, the team at Newcastle has proposed several methods to address such issues like graph theory [1-2], graphical methods [3-6] and Automata [7]. In this project we propose the combination of the above methods under a Multi Agent framework that will take into account the system’s scalability and resilience. Candidates should have a strong background on systems theory and programming using Matlab and Python.
Newcastle University is committed to being a fully inclusive Global University which actively recruits, supports and retains colleagues from all sectors of society. We value diversity as well as celebrate, support and thrive on the contributions of all our employees and the communities they represent. We are proud to be an equal opportunities employer and encourage applications from everybody, regardless of race, sex, ethnicity, religion, nationality, sexual orientation, age, disability, gender identity, marital status/civil partnership, pregnancy and maternity, as well as being open to flexible working practices.
Application enquires:
Damian Giaouris, damian.giaouris@ncl.ac.uk
References
[1] Damian Giaouris, Athanasios Papadopoulos; Charalampos Patsios; Sara Walker, Chrysovalantou Ziogou, Phil Taylor, Spyros Voutetakis, Simira Papadopoulou, Panos Seferlis: "A Systems Approach for Management of Microgrids Considering Multiple Energy Carriers, Stochastic Loads, Forecasting and Demand Side Response", Applied Energy, Vol. 226, pp. 546-559, 2018
[2] Damian Giaouris, Athanasios I. Papadopoulos, Chrysovalantou Ziogou, Dimitris Ipsakis, Spyros Voutetakis, Simira Papadopoulou, Panos Seferlis, Fotis Stergiopoulos, Costas Elmasides: "Performance investigation of a hybrid renewable power generation and storage system using systemic power management models", Energy, Vol. 61, pp. 621-635, Nov. 2013.
[3] Nyong-Bassey Bassey Etim, Damian Giaouris, "Probabilistic Adaptive Power Pinch Analysis for Islanded Hybrid Energy Storage Systems", Journal of Energy Storage, Volume 54, 2022
[4] Nyong-Bassey Bassey Etima, Damian Giaouris, Charalampos Patsios, Simira Papadopoulou, Athanasios I. Papadopoulos, Sara Walker, Spyros Voutetakis, Panos Seferlis, Shady Gadoue "Reinforcement Learning Based Adaptive Power Pinch Analysis for Energy Management of Stand-alone Hybrid Energy Storage Systems Considering Uncertainty", Energy,Vol. 193, 15 February 2020
[5] Damian Giaouris, A. I. Papadopoulos, P. Seferlis, S. Voutetakis, S. Papadopoulou: "Power grand composite curves shaping for adaptive energy management of hybrid microgrids", Renewable Energy 95, pp. 433-448, 2016.
[6] Damian Giaouris; Athanasios I. Papadopoulos; Spyros Voutetakis; Simira Papadopoulou, Panos Seferlis: "A Power Grand Composite Curves Approach for Analysis and Adaptive Operation of Renewable Energy Smart Grids", Clean Technologies and Environmental Policy, Vol. 17, No, 5, pp. 1171-1193, April 2015.
[7] Yara Khawajaa, Adib Allahham, Damian Giaouris, Charalampos Patsios, Sara Walker, and Issa Qiqiehr "An Integrated Framework for Sizing and Energy Management of Hybrid Energy Systems Using Finite Automata", Vol. 250, pp. 257-272, 2019, Applied Energy.
[2] Damian Giaouris, Athanasios I. Papadopoulos, Chrysovalantou Ziogou, Dimitris Ipsakis, Spyros Voutetakis, Simira Papadopoulou, Panos Seferlis, Fotis Stergiopoulos, Costas Elmasides: "Performance investigation of a hybrid renewable power generation and storage system using systemic power management models", Energy, Vol. 61, pp. 621-635, Nov. 2013.
[3] Nyong-Bassey Bassey Etim, Damian Giaouris, "Probabilistic Adaptive Power Pinch Analysis for Islanded Hybrid Energy Storage Systems", Journal of Energy Storage, Volume 54, 2022
[4] Nyong-Bassey Bassey Etima, Damian Giaouris, Charalampos Patsios, Simira Papadopoulou, Athanasios I. Papadopoulos, Sara Walker, Spyros Voutetakis, Panos Seferlis, Shady Gadoue "Reinforcement Learning Based Adaptive Power Pinch Analysis for Energy Management of Stand-alone Hybrid Energy Storage Systems Considering Uncertainty", Energy,Vol. 193, 15 February 2020
[5] Damian Giaouris, A. I. Papadopoulos, P. Seferlis, S. Voutetakis, S. Papadopoulou: "Power grand composite curves shaping for adaptive energy management of hybrid microgrids", Renewable Energy 95, pp. 433-448, 2016.
[6] Damian Giaouris; Athanasios I. Papadopoulos; Spyros Voutetakis; Simira Papadopoulou, Panos Seferlis: "A Power Grand Composite Curves Approach for Analysis and Adaptive Operation of Renewable Energy Smart Grids", Clean Technologies and Environmental Policy, Vol. 17, No, 5, pp. 1171-1193, April 2015.
[7] Yara Khawajaa, Adib Allahham, Damian Giaouris, Charalampos Patsios, Sara Walker, and Issa Qiqiehr "An Integrated Framework for Sizing and Energy Management of Hybrid Energy Systems Using Finite Automata", Vol. 250, pp. 257-272, 2019, Applied Energy.
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