Load management in distribution network using battery energy storage system under high penetration of electric vehicles | |
| Author | Thitanan Prachuab |
| Call Number | AIT RSPR no.SE-23-02 |
| Subject(s) | Electric vehicles--Batteries Storage batteries Energy storage |
| Note | A research study submitted in partial fulfillment of the requirements for the Degree of Master of Engineering in Sustainable Energy Transition |
| Publisher | Asian Institute of Technology |
| Abstract | The increasing adoption of electric vehicles (EVs) represents a significant transformation in the transportation sector, offering numerous environmental benefits and reduced reliance on fossil fuels. However, this paradigm shift also brings challenges for the electrical distribution network, particularly with regards to the emergence of new peak loads in the evening. With the rising popularity of EVs, many individuals prefer to charge their vehicles at home during the evening hours, coinciding with the traditional peak demand period for residential electricity consumption. This convergence of EV charging and residential power demand can strain distribution network, leading to several implications. Metropolitan Electricity Authority (MEA) of Thailand is the electricity utility that has responsible for distributed electricity to customer in three provinces – Bangkok, Nonthaburi, and Samut Prakan. It will impact directly from the disruption of load profiles of electric vehicles charging patterns. The peak shaving solution will be adopted in real distribution system for study and improve methodology for suitable with the system. The battery energy storage system (BESS) will be focused in order to achieve peak shaving during electric vehicles charging. This research is studied the widely used methods such as Enumeration and Mathematical optimization approaches, for evaluating the sizing of battery energy storage system by using MATLAB and GAMS simulation software. The sizing results show that the optimization method is more effective than enumeration method. The electric vehicle penetration scenarios are simulated to ensure the optimization method can be applied in real network to mitigate network congestion. The distribution transformer that integrated with BESS can cope with the 52% EV penetration although in overloading condition without any congestion and keep the utilization factor under the MEA’s operation criteria. |
| Year | 2023 |
| Type | Research Study Project Report (RSPR) |
| School | School of Environment, Resources, and Development |
| Department | Department of Energy and Climate Change (Former title: Department of Energy, Environment, and Climate Change (DEECC)) |
| Academic Program/FoS | Sustainable Energy Transition (SE) |
| Chairperson(s) | Weerakorn Ongsakul; |
| Examination Committee(s) | Loc, Thai Nguyen;Singh, Jai Govind; |
| Scholarship Donor(s) | MEA-AIT Academic Collaborative Program Scholarships;AIT Scholarship; |
| Degree | Research report (M. Eng.) - Asian Institute of Technology, 2023 |