Evgenia Mechleri

Dr Evgenia Mechleri


Lecturer
MSc, PhD
+44 (0)1483 683003
13 BC 02

Academic and research departments

Department of Chemical and Process Engineering.

Biography

Research

Research interests

My teaching

My publications

Publications

Mechleri Evgenia, Arellano-Garcia Harvey (2018) A Mathematical Programming Approach to Optimal Design of Smart Distributed Energy Systems, In: Eden Mario R, Ierapetritou Marianthi G, Towler Gavin P (eds.), Computer Aided Chemical Engineering (Part of volume: 13th International Symposium on Process Systems Engineering (PSE 2018)) 44 pp. 2521-2526 Elsevier
The UK is committed to reducing its greenhouse gas emissions by at least 80% by 2050, relative to 1990 levels. For this to happen, we need to transform the UK economy while ensuring secure, low-carbon energy supplies to 2050. The future electricity distribution system, known as smart grid, will integrate advanced digital meters, distribution automation, communication systems and distributed energy resources. There has been a lot of discussion about the importance of the Internet of Things (IoT) in future smart grids and smart cities stating that IoT offers many applications and can be used to integrate efficiency renewable energy sources in the smart grid by making the electricity grid more robust and scalable.
This study will focus on the development of an integrated IoT-Distributed energy systems (DES) model for the efficient energy management of a microgrid under the integration of the intermittent renewable energy resources. In this work, we expand the definition of flexible options to include demand and supply together with design and operation strategies using internet of things (IoT). Our framework brings weather data and sensor information into a virtual energy plant optimisation model that connects supplier and consumer to optimise potential flexibility gaps arising from supply and demand mismatch. The problem is posed as a hybrid mixed-integer linear programming (MILP) optimisation model combining flexibility analysis and optimal synthesis for integrating energy supply and demand, where environmental information is added to each stage. Finally, we combine traditional mathematical programming approaches such as flexibility analysis and optimal network synthesis and within a single optimisation framework combining IoT and urban DES.
Dorneanu Bogdan, Mechleri Evgenia, Arellano-Garcia Harvey (2018) Towards the cooperative-based control of chemical plants, In: Friedl Anton, Klemea Jiri J, Radl S, Varbanov Petar S, Wallek Thomas (eds.), Computer Aided Chemical Engineering (Part of volume: European Symposium on Computer Aided Process Engineering) 43 pp. 1087-1092 Elsevier
This contribution presents the proof of concept for a consensus-based approach for the design and assessment of control structures in chemical plants. The applicability of the proposed approach is demonstrated on an existing mini-plant. For this purpose, a reduced dynamic model that considers a simplified structure of the plant, consisting of feed preparation, reaction, and downstream processing, is used to assess the control structure of the mini-plant using the consensus algorithm. The reduced model is used to assess the control structure of the mini-plant reactor, considering the relevant operational and safety variables.
Ketabchi Elham, Mechleri Evgenia, Gu Sai, Arellano-Garcia Harvey (2018) Modelling and Optimisation Approach of an Integrated Oil Refinery and a Petrochemical Plant, In: Eden Mario R, Ierapetritou Marianthi G, Towler Gavin P (eds.), Computer Aided Chemical Engineering (Part of volume: 13th International Symposium on Process Systems Engineering (PSE 2018)) 44 pp. 1081-1086 Elsevier
An optimised integration approach connecting a conventional oil refinery with an ethylene production plant is investigated. Using the intermediate materials produced as the connection between the two plants, the use of internally provided feedstocks and blending options removes, at least partially, the reliance on external sourcing. This is also beneficial in terms of increasing profit margins and quality for both production systems. Thus, a mathematical model has been developed and implemented in this work to model the oil refinery and the ethylene production plant while considering their integration as an MINLP problem with the aim of optimising the integrated plants. This work considers the optimisation of each plant individually and later the final integration by modelling the interconnection between the oil refinery and the ethylene production plant. Moreover, a case study using practical data was carried out to verify the feasibility of the integration for an industrial application.