Optimal Sizing And Operation Planning Of Microgrids And Operation Analysis Of Charging Stations For Electric Vehicles

Optimal Sizing and Operation Planning of Microgrids and Operation Analysis of Charging Stations for Electric Vehicles

Energy and transportation sectors are going through major changes as a result of technological advances, depletion of fossil fuels and climate change. With regard to the energy sector, the future smart grid is expected to be an interconnected network of small-scale and self-contained microgrids, in addition to a large-scale electric power backbone. By utilizing microsources, such as renewable energy sources, energy storage systems and vehicle-to-grid systems, microgrids target to satisfy the customers' energy demands in a safe, reliable, economic and environmentally friendly way. With regard to the changes in the transportation sector, internal combustion engine vehicles are expected to be gradually replaced by electric vehicles, which are considered to be a promising solution for mitigating the impact of transportation sector on the environment. The presented thesis deals with two main topics; the first one refers to the optimal sizing and operation planning of microgrids comprising various urban building types, while the second one is related to the operation of fast charging stations for electric vehicles that are located in densely populated areas. The first objective of the thesis is to examine the effect of energy exchanges among interconnected buildings with diverse load profiles on the sizes of power equipment to be installed at the buildings. To this end, a mixed integer linear programming optimization framework is presented that determines the optimal capacities of photovoltaic panels, energy storage systems, and inverters, as well as the optimum management of the generated power. As a first step, the benefits of cooperation among buildings that are already interconnected through an existing point of common coupling is examined. The cooperation benefits are derived by comparing the buildings' costs when they participate in the microgrid with their costs when they operate as separate entities. As a second step, a different microgrid topology is proposed where energy exchanges take place through a common DC bus. In this way, neighboring buildings that are not already physically connected can be members of the same microgrid. Moreover, the optimization results for the new topology are obtained by using the Nash bargaining method, through which the benefits of cooperation are equally distributed among the participating members. Finally, the possible integration of new buildings in the existing microgrid at a later time point is also examined. The second objective of the thesis is to provide an accurate operation analysis of fast charging stations for electric vehicles. To this end, a novel queuing theory-based model is presented that classifies the various electric vehicles by their battery size. As a first step, it is analyzed a charging station that contains DC outlets, and the electric vehicles recharge their batteries up to the maximum possible level. The proposed model takes into account the arrival rates and state of charge of the electric vehicles' batteries when arriving at the station, in order to compute the maximum number of customers that can be served, subject to an upper bound for the waiting time in the queue. In addition, a charging strategy is proposed, which allows the charging station to serve more customers without any increase in the queue waiting time. As a second step, it is considered that the charging station can serve both DC and AC electric vehicle classes, while a more flexible way is adopted for denoting the customers' recharging patterns. Based on these additional novelties, the overall profit margin of the charging station operator, and the queue waiting times of the DC and AC classes are calculated under two different pricing policies.

Resilient Community Microgrids

Developments and Applications in SmartRail, Traffic, and Transportation Engineering

This book is a collection of original peer-reviewed contributions from the 2023 International Conference on SmartRail, Traffic, and Transportation Engineering, jointly organized by Beijing Jiaotong University, China Electrotechnical Society, Chinese Institute of Electronics and Central South University. It was held on July 28-30, 2023 in Changsha, China. Topics covered includes SmartRail systems, autonomous vehicles, energy efficiency, sustainable transportation, big data in transportation, and machine learning. Speakers discussed innovative technologies and strategies to improve the efficiency, reliability, and safety of rail networks, while exploring the opportunities and challenges of integrating autonomous vehicles into existing transportation networks. It provides valuable insights into the latest developments and trends in transportation engineering and technology, with a focus on electrification and sustainable transportation. It serves as a valuable resource for professionals, researchers, and students working in the field.