Thermal Modelling and Cost Analysis for Large-Scale Battery Energy Storage System (BESS) in Grid-Connected PV Plant
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Thermal Modelling and Cost Analysis for Large-Scale Battery Energy Storage System (BESS) in Grid-Connected PV Plant Md Mehedi Hasan Bachelor of Engineering (Electrical and Electronic Engineering) A thesis submitted for the degree of Master of Philosophy at The University of Queensland in 2019 School of Information Technology and Electrical Engineering Abstract With the growing renewable energy capacity at an exponential rate every year, energy storage system has become popular. Among available energy storage systems, battery energy storage system (BESS) is widely used technology for its high-power density and fast response in renewable plants such as photovoltaic (PV) farm. The indispensable operation of battery system is to store excess PV generation and utilise it effectively. Fluctuation in PV generation output is a usual incident due to the unpredictable nature of PV generation. Therefore, a storage system is required to smooth its output generation prior to export it to the grid. Despite a lot of advancement in electrochemical storage technology and cost reduction, battery degradation remains a big obstacle for its wider acceptance in large-scale PV plant. Battery degrades because of charging/discharging operation as well as during idle condition. Elevated temperature of battery cell accelerates battery degradation, which indicates an imminent loss of expensive investment on BESS. In addition, elevated temperature is responsible for adding to the cost of battery system operation in the plant by accelerating cooling system operation. A number of research studies have been carried out to model thermal characteristics and be- haviour of battery. However, the majority of studies reported in the literature are conducted on the small-scale battery thermal management where thermal behaviour is investigated using complicated thermo-dynamical models. However, a detailed thermo-dynamical model is not feasible for a large- scale BESS, where thousands of battery cells are installed and thermally interacting with each other. To consider battery degradation cost in the EMS, a solution is required to estimate battery thermal behaviour for any given profile without following any complex computational methods. An accurate battery cell temperature estimation can play a significant role in ensuring BESS optimal operation considering its degradation. In this thesis, the work starts with investigating the thermal behaviour of the battery with respect to its charging/discharging operation along with other possible effective parameters. Identifying the most dominant factors for battery cell temperature is one of the primary steps. A comprehensive ther- mal model will be developed to estimate battery cell temperature with 24 hours horizon in advance ii iii with high accuracy. Finally, an effective cost function will be developed considering dominant pa- rameters. Different simulation strategies are implemented to assess the proposed models. This thesis will consider all pertinent matters and undergo rigorous assessments using real field data to ensure practicality. Scalability of the solution will be kept in mind for future development along with the aforementioned features. Power industries and academia will be benefited from the studies on ther- mal behaviour of battery, battery cell temperature estimation, and cost functions for effective BESS operations in a PV plant. Declaration by Author This thesis is composed of my original work, and contains no material previously published or written by another person except where due reference has been made in the text. I have clearly stated the contribution by others to jointly-authored works that I have included in my thesis. I have clearly stated the contribution of others to my thesis as a whole, including statistical as- sistance, survey design, data analysis, significant technical procedures, professional editorial advice, financial support and any other original research work used or reported in my thesis. The content of my thesis is the result of work I have carried out since the commencement of my higher degree by research candidature and does not include a substantial part of work that has been submitted to qualify for the award of any other degree or diploma in any university or other tertiary institution. I have clearly stated which parts of my thesis, if any, have been submitted to qualify for another award. I acknowledge that an electronic copy of my thesis must be lodged with the University Library and, subject to the policy and procedures of The University of Queensland, the thesis be made available for research and study in accordance with the Copyright Act 1968 unless a period of embargo has been approved by the Dean of the Graduate School. I acknowledge that copyright of all material contained in my thesis resides with the copyright holder(s) of that material. Where appropriate I have obtained copyright permission from the copyright holder to reproduce material in this thesis and have sought permission from co-authors for any jointly authored works included in the thesis. iv Publications and Submitted Manuscripts Publications included in this thesis 1. M. M. Hasan, S. A. Pourmousavi, F. Bai, and T. K. Saha. The impact of temperature on battery degradation for large-scale bess in pv plant. In Universities Power Engineering Conference (AUPEC), 2017 Australasian, pp. 16 (IEEE, 2017). This paper is incorporated in Chapter 3. Contributor Statement of contribution Md Mehedi Hasan Simulation and modelling (100%) Result interpretation and discussion (75%) Paper writing (75%) Seyyed Ali Pourmousavi Kani Result interpretation and discussion (10%) Paper writing (10%) Tapan Saha Result interpretation and discussion (10%) Paper writing (10%) Feifei Bai Result interpretation and discussion (5%) Paper writing (5%) v vi 2. Md Mehedi Hasan, S. Ali Pourmousavi and Tapan K. Saha, “Battery Cell Temperature Estima- tion Model and Cost Analysis of a Grid-Connected PV-BESS Plant”. In IEEE Innovative Smart Grid Technologies Asia (ISGT ASIA 2019), (IEEE, 2019). This paper is incorporated in Chapter 4 and 5. Contributor Statement of contribution Md Mehedi Hasan Simulation and modelling (100%) Result interpretation and discussion (75%) Paper writing (75%) Seyyed Ali Pourmousavi Kani Result interpretation and discussion (15%) Paper writing (15%) Tapan Saha Result interpretation and discussion (10%) Paper writing (10%) Submitted manuscripts included in this thesis 1. Md Mehedi Hasan, Ali Pourmousavi, Tapan K. Saha, “A data-driven approach to estimate battery cell temperature using NARX neural network model. (Submitted to Applied Energy). This paper is incorporated in Chapter 4. Contributor Statement of contribution Md Mehedi Hasan Simulation and modelling (100%) Result interpretation and discussion (75%) Paper writing (75%) Seyyed Ali Pourmousavi Kani Result interpretation and discussion (15%) Paper writing (15%) Tapan Saha Result interpretation and discussion (10%) Paper writing (10%) vii Other publications during candidature “No other publications” Contributions by others to the thesis “No contributions by others” Statement of parts of the thesis submitted to qualify for the award of another degree “No works submitted towards another degree have been included in this thesis” Research Involving Human or Animal Subjects “No animal or human subjects were involved in this research” Acknowledgements A few words cannot be enough to express my appreciation for kind guidance and supports of a number of people. This work would not be happened without their supports. Firstly, I would like to express my gratitude and profound respect to Professor Tapan Saha for advising my MPhil work and thesis. His unforgettable help, understanding and supports as principal supervisor helped me to go forward smoothly during my candidature. It was an outstanding journey working with him, as I have not only learnt technical parts of my work but also a lot of lessons from him, which made my MPhil easier and it would be useful for future endeavour. Moreover, I am really grateful to my associate supervisor, Dr. Ali Pourmousavi for his continuous advice and help on my journey to MPhil thesis. I appreciate his time and encouragement, which assisted to generate a fruitful research outcome. I would like to acknowledge the financial support, I received from The University of Queensland through RTP Scholarship. I would like to convey my gratitude to Professor Tapan Saha for his efforts and all supports towards getting financial funding for attending conference. I would like to acknowledge the research facilities, I have received from UQ Gatton Solar Facility (UQ GSRF) to complete this work. I would like to express my appreciation to all of my colleagues from Power and Energy System (PES) Group of the University of Queensland. Advice and valuable time provided by the group members were undoubtedly beneficial throughout my journey to complete MPhil. I would also like to remember my enjoyable time being in the group. Last but not least, I would like to convey my appreciation to my wife and my family for their love and indispensable supports. Their unconditional encouragement in every step of my study helped me a lot to move forward smoothly. viii Financial Support, Keywords and Classifications Financial Support: “This research was supported by an Australian Government Research Training Program Scholar- ship” Keywords: battery energy storage system, cell temperature, neural network, photovoltaic, cost. Australian and New Zealand Standard Research Classifications