Ishanki Anjana De Mel

Postgraduate Research Student
Master of Engineering - Chemical Engineering

My research project

University roles and responsibilities

  • Associate Tutor - Personal Awareness and Development Module (Jan 2020 - Present)
  • Teaching Assistant - ENG1083 Transferable and Laboratory Skills (May - June 2020)
  • Teaching Assistant - ENG2120 Engineering Systems and Dynamics (Oct - Dec 2019)

    My qualifications

    Master of Engineering - Chemical Engineering (First Class Honours)
    University of Surrey

    In the media


    Research interests

    My publications


    Ishanki De Mel, Oleksiy V. Klymenko, Michael Short (2022)Balancing Accuracy and Complexity in Optimisation Models of Distributed Energy Systems and Microgrids with Optimal Power Flow: A Review, In: Sustainable Energy Technologies and Assessments52(A)102066 Elsevier

    Optimisation and simulation models for the design and operation of grid-connected distributed energy systems (DES) often exclude the inherent nonlinearities related to power flow and generation and storage units, to maintain an accuracy-complexity balance. Such models may provide sub-optimal or even infeasible designs and dispatch schedules. In DES, optimal power flow (OPF) is often misrepresented and treated as a standalone problem. OPF consists of highly nonlinear and nonconvex constraints related to the underlying alternating current (AC) distribution network. This aspect of the optimisation problem has often been overlooked by researchers in the process systems and optimisation area. In this review we address the disparity between OPF and DES models, highlighting the importance of including elements of OPF in DES design and operational models to ensure that the design and operation of microgrids meet the requirements of the underlying electrical grid. By analysing foundational models for both DES and OPF, we identify detailed technical power flow constraints that have been typically represented using oversimplified linear approximations in DES models. We also identify a subset of models, labelled DES-OPF, which include these detailed constraints and use innovative optimisation approaches to solve them. Results of these studies suggest that achieving feasible solutions with high-fidelity models is more important than achieving globally optimal solutions using less-detailed DES models. Recommendations for future work include the need for more comparisons between high-fidelity models and models with linear approximations, and the use of simulation tools to validate high-fidelity DES-OPF models. The review is aimed at a multidisciplinary audience of researchers and stakeholders who are interested in modelling DES to support the development of more robust and accurate optimisation models for the future.

    Ishanki A De Mel, Oleksiy V Klymenko, Michael Short (2021)Levels of Approximation for the Optimal Design of Distributed Energy Systems, In: Computer Aided Chemical Engineering50pp. 1403-1408 Elsevier

    Optimisation models for the design of distributed energy systems (DES) often exclude inherent nonlinearities and constraints associated with alternating current (AC) power flow and the underlying distribution network. This study aims to assess this gap by comparing the performance of linear and nonlinear formulations of DES design models, connected to and trading with an AC grid. The inclusion of the optimal power flow (OPF) constraints within the DES design framework is demonstrated in the methodology. A residential case study is used to test both models and compare the designs obtained from the two formulations. The results highlight that DES designs obtained are different when constraints related to the underlying distribution network are added, particularly when electricity storage is not considered. Overall, this study highlights the need for future modelling efforts to include OPF within DES optimisation frameworks to obtain practically feasible designs, rather than considering them as standalone problems.

    Ishanki De Mel, Panagiotis Demis, Bogdan Dorneanu, Oleksiy Klymenko, Evgenia Mechleri, Harvey Arellano-Garcia (2020)Global Sensitivity Analysis for Design and Operation of Distributed Energy Systems, In: Computer Aided Chemical Engineering48pp. 1519-1524

    Distributed Energy Systems (DES) are set to play a vital role in achieving emission targets and meeting higher global energy demand by 2050. However, implementing these systems has been challenging, particularly due to uncertainties in local energy demand and renewable energy generation, which imply uncertain operational costs. In this work we are implementing a Mixed-Integer Linear Programming (MILP) model for the operation of a DES, and analysing impacts of uncertainties in electricity demand, heating demand and solar irradiance on the main model output, the total daily operational cost, using Global Sensitivity Analysis (GSA). Representative data from a case study involving nine residential areas at the University of Surrey are used to test the model for the winter season. Distribution models for uncertain variables, obtained through statistical analysis of raw data, are presented. Design results show reduced costs and emissions, whilst GSA results show that heating demand has the largest influence on the variance of total daily operational cost. Challenges and design limitations are also discussed. Overall, the methodology can be easily applied to improve DES design and operation.

    H C Burridge, R K Bhagat, MEJ Stettler, P Kumar, I De Mel, P Demis, A Hart, Y Johnson-Llambias, M-F King, O Klymenko, A McMillan, P Morawiecki, T Pennington, MICHAEL SHORT, D Sykes, P H Trinh, S K Wilson, C Wong, H Wragg, M S Davies Wykes, C Iddon, A W Woods, N Mingotti, N Bhamidipati, H Woodward, C Beggs, H Davies, S Fitzgerald, C Pain, P F Linden (2021)The ventilation of buildings and other mitigating measures for COVID-19: a focus on wintertime, In: Proceedings Mathematical, physical, and engineering sciences477(2247)20200855 The Royal Society

    The year 2020 has seen the emergence of a global pandemic as a result of the disease COVID-19. This report reviews knowledge of the transmission of COVID-19 indoors, examines the evidence for mitigating measures, and considers the implications for wintertime with a focus on ventilation.