Data analysis in energy

This seminar is free and open to all but places must be booked in advance. To book please email Benedict Doran with your name, occupation and faculty/organisation.

Presentation 1: Dr Chun Sing Lai, EPSRC Research Fellow, School of Civil Engineering, University of Leeds
Title: Daily clearness index profiles cluster analysis for photovoltaic system

Abstract: Due to various weather perturbation effects, the stochastic nature of real-life solar irradiance has been a major issue for solar photovoltaic (PV) system planning and performance evaluation. This talk presents a data analytics technique to discover clearness index (CI) patterns and to construct centroids for the daily CI profiles. This will be useful in being able to provide a standardized methodology for PV system design and analysis. Four years of solar irradiance data collected from Johannesburg, South Africa are used for the case study. The variation in CI could be significant in different seasons. In this paper, cluster analysis with Gaussian mixture models (GMM), K-Means with Euclidean distance (ED), K-Means with Manhattan distance, Fuzzy C-Means (FCM) with ED, and FCM with dynamic time warping (FCM DTW) are performed for the four seasons. A case study based on sizing a stand-alone solar PV and storage system with anaerobic digestion biogas power plants is used to examine the usefulness of the clustering results. It concludes that FCM DTW and GMM can determine the correct PV farm rated capacity with an acceptable energy storage capacity, with 36 and 46 rather than 1457 solar irradiance profiles, respectively.

Biography: Chun Sing Lai received the B.Eng. (1st Hons.) in electrical and electronic engineering from Brunel University London, U.K. and D.Phil. in engineering science from University of Oxford, U.K. in 2013 and 2019 respectively. He is currently an EPSRC Research Fellow with the School of Civil Engineering, University of Leeds and also a Visiting Research Fellow with the Department of Electrical Engineering, School of Automation, Guangdong University of Technology, China. He is Secretary of the IEEE Smart Cities Publications Committee. He organized the IEEE SMC Workshop on Smart Grid and Smart City, SMC 2017 in Canada. His current interests are in power system optimization, energy system modelling, data analytics, and energy economics for renewable energy and storage systems.

Presentation 2: Dr Petros Aristidou, Lecturer in Smart Energy Systems, School of Electronic and Electrical Engineering, University of Leeds
Title: Data-driven control design in electricity distribution networks

Abstract: Advanced monitoring and communication infrastructure allows distribution system operators to design optimal operation strategies through the centralised control of Distributed Energy Resources (DERs). However, most distribution networks today lack such communication infrastructure and in many countries the cost of building the required capacity is prohibitive.  On the contrary, conventional, local DER control schemes offer a robust, cheap, communication-free solution, but with sub-optimal performance. In this presentation, we investigate the use of data-driven control design algorithms to derive local DER controllers that can emulate the optimal behaviour without the need for communication. This is achieved by using historical data to capture expected operating conditions, in combination with off-line optimisation techniques and machine learning methods.

Biography: Petros Aristidou graduated from the National Technical University of Athens (Greece) in 2010 with a degree in Electrical and Computer engineering. In 2015, he completed a PhD at the University of Liege (Belgium) on the topic of domain decomposition and parallel computing techniques for power system dynamic simulations. During his PhD, he received several awards for his research and worked closely with a transmission system operator on the development of real-time security assessment platform. Afterwards, he spent a year as a Postdoctoral Researcher at ETH Zurich (Switzerland) working on the H2020 project MIGRATE, focused on the stability and control of low-inertia power systems. Since 2016, he is a Lecturer at the University of Leeds (UK) where he leads a research group focused on the modelling, simulation, and control of future power systems.

This seminar is free and open to all but places must be booked in advance. To book please email Benedict Doran with your name, occupation and faculty/organisation.