Battery-Integrated Residential Energy Systems introduces battery energy storage systems (BESS) of residential systems and offers insight into modeling, managing, and controlling them. Apart from survey of different BESS applications, it explains electrochemical simulation models of BESS. It includes performance parameters, economic analysis, sizing, energy management, control, charging and discharging patterns, coordination of the storage system with other devices in the home, and policy-related matters.
Features:
- Covers different aspects of smart residential energy systems with a battery as a key element
- Discusses increasing energy efficiency in residential units by optimal control and management of BESS
- Explores information related to the policy regarding the use of BESS
- Includes chapters on energy trading for implementation of optimal energy management of BESS
- Focuses on a variety of aspects of battery operation and control
This book is aimed at senior undergraduate, graduate students, and researchers in Electrical Engineering, Battery Systems, Energy Engineering, and Sustainable and Renewable Technologies.
Asmae Berrada is an associate professor of Energy in the school of EnergyEngineering at the international University of Rabat (UIR). She holds a PhD degree from the Faculty of Science USMBA. Her PhD work was prepared at Al Akhawayn University within the framework of the EUROSUNMED project (EU- H2020). She obtained a Master’s degree in Sustainable Energy Management, and a Bachelor’s degree in Engineering and Management Science from Al Akhawayn University. Dr. Berrada started her career as a part-time faculty member at Al Akhawayn University from 2014 to 2018.
She has been ranked among the World’s Top 2% Scientists in the Stanford University and Elsevier ranking for 2023. She has also received several research awards and honors from IRESEN, MASEN, and USMBA.
She has led a number of research projects on renewable energy, hybrid energy systems, and energy storage systems such as SHPS, GESYS, and DARNASOL. She has published a variety of articles in leading international energy journals, and two books (Gravity Energy Storage and Hybrid Energy System Models). Her main research focus is on energy systems and their modeling. She has actively been working in the fields of energy storage and renewable energy.
Altaf Q. H. Badar is currently associated with the Electrical Engineering Department of National Institute of Technology Warangal, India. He completed his Bachelor’s and Master’s degrees at Rashtrasant Tukdoji Maharaj Nagpur University, India in 2001 and 2009, respectively. He pursued his PhD at Visvesvaraya National Institute of Technology, India and completed it in 2015. His PhD research dealt with reduction of active power losses by controlling the flow of reactive power in the transmission system through evolutionary optimization techniques. He also has a Diploma in Business Management completed in 2004 from ICFAI, India.
He has approximately 17 years of experience of teaching professional engineering courses and four years of field experience. His research interests include evolutionary optimization techniques, energy management, smart homes, and energy trading. He has published his research work in more than 30 international papers in journals and conferences.He was awarded a project under the RSM scheme of his parent institution on the topic of smart homes. He has also executed a project awarded under GIAN worth $12,000 on the topic of Advanced Energy Conversion and Storage Systems.
He has been a member of the board of studies of different institutions, including RTM Nagpur University, India. He has also chaired a number of international conferences and been a member of various technical committees. He was an editorial member of International Refereed Journal of Engineering Science and Technology and is currently an editorial member of American Journal of Electrical Power and Energy Systems and International Advanced Research Journal of Engineering and Technology. He has to his name a book on Evolutionary Optimization Algorithms and around five book chapters.
He has delivered his services as a reviewer for multiple international journals and conferences and for a book. He has delivered a large number of expert lectures in different engineering institutions across India. He has guided around 30 undergraduate and ten postgraduate projects. Currently, 40 research scholars are working under his guidance. He is a Senior Member of IEEE, Life Member of the Indian Society of Technical Education, and a member of IAENG. He understands seven different languages at various levels.
Mohammad Sanjari (PhD, FHEA) received his PhD in Electrical Engineering in 2013 from Amirkabir University of Technology (AUT), Tehran, Iran after successfully accomplishing the project "Control of Micro-grid using Distributed Object-Oriented Intelligent System with Partial Information" in which he investigated the partial information- based distributed control scheme of a microgrid to increase its reliability in different modes of operation, taking into account the problems of cyber systems.
He then joined the School of Electrical and Electronic Engineering, Nanyang Technological University (NTU), Singapore as a postdoctoral research fellow, where he worked on a project on increasing reliability and economic performance of the microgrid with funding of S$2.78M. After that, he joined the University of Auckland, New Zealand as a postdoctoral research fellow in the Electrical and Computer Engineering Department to work on developing a generalized framework to model cascading propagation in large- scale power grids, especially in low- carbon energy networks, with the help of graph theory and big data analytics to form a platform for studying the initiation, progression, and propagation of events in a largescale power system.
Since January 2019, he has been with the School of Engineering and Built Environment, Griffith University, Australia. From 2015 to 2017, alongside his research project in NTU, he worked with SembCorp Marine (SM), Singapore on the project "Long-Term and Short-Term Load Forecast in Highly Varying Demand Sectors", which resulted in a technical report, user manual, and commercial software used by the company for strategically operating shipyards located in Singapore, Indonesia, the United Kingdom, and Brazil. After that, he organized training sessions for SM’s engineers to work effectively with the load forecast module to gain better insight into appropriate decision- making procedures for network operation. From 2017 to 2019, he was an active member of the Te Pūnaha Matatini (TPM), Whanau, an active trans- disciplinary community with a shared interest in complex systems and networks, comprising postgraduate students, postdocs, and early career researchers from all over New Zealand.
He is the author of more than 70 journal and conference papers. His h- index (Google Scholar metrics) is 24, showing impactful research studies in his areas of interest, which include applying artificial intelligence and data mining in power systems analysis, control, condition monitoring, and assessment. He has conducted research studies on decision making in power systems, considering network security and risk constraints by using machine learning methods and big data analysis techniques. He also has expertise in probabilistic analysis of smart multi-carrier energy systems, including hybrid load demands and renewable energy resources.
