Energy Management for Vehicle-to-Grid Power Sharing System Towards Sustainable Manufacturing

Traditionally, manufacturers paid more attention to the methods that can enhance productivity, including strategies for equipment reliability enhancement, product quality management, and manufacturing operations optimization. On the contrary, the energy-related measures of manufacturing systems were ignored. In recent years, due to the increasing energy demand caused by the industrial sector, the manufacturers are facing increasing pressure on energy consumption and carbon footprints reductions. As a result, increasing research attention has been placed on the control and management methods aiming for reducing energy consumption and cost, as well as the carbon footprints from both the industry and academia. The current knowledge on energy management methods for sustainable manufacturing is limited, which offers considerable research opportunities. However, researchers in this field also face many challenges, including 1) system performance prediction methods for real-time energy management; 2) energy management strategies for integrated production systems and auxiliary systems (e.g., heating, ventilation, and air conditioning system); 3) energy management under demand response pricing using external energy storage devices such as electric vehicles. Considering the aforementioned opportunities and challenges, a comprehensive energy management strategy towards sustainable manufacturing is necessary. This thesis aims to develop a methodological framework to reduce energy costs under the time-of-use (TOU) electricity tariff. A decision-making process and a novel vehicle-to-grid (V2G) bidirectional power communication model are proposed to help system designers and manufacturers address the above challenges and achieve sustainable manufacturing. The outcomes of this thesis can contribute to the design of the manufacturing system coupled with a V2G power-sharing system and accomplish energy reduction by applying a comprehensive real-time energy management strategy.