Overview of Optimized Load Scheduling of Energy Hub under Energy Internet Environment

Abstract

Energy hubs (EH) play a key role in the energy Internet environment, especially in the load optimization scheduling of multi-energy systems. As an input-output port model of multi-energy systems, EH realizes real-time monitoring and intelligent analysis through the Internet of Things, big data and artificial intelligence technologies, promoting the efficient use of energy and the reduction of environmental pollution. This model uses the coupling matrix to describe the conversion, storage and transmission relations between energy sources, which provides strong support for the planning and operation of multi-energy systems. With the development of the energy Internet, the importance of EH is becoming increasingly prominent. By the introduction of EH, the coordinated operation of power, natural gas, heat and other energy systems can be realized, and the flexibility and stability of the system can be improved. Current research focuses on stochastic optimization of energy systems and load optimization scheduling to cope with the uncertainties in energy prediction and price. However, user behavior and demand response still face challenges in energy system planning and scheduling. Future research needs to deeply explore the changes in user behavior and introduce demand response mechanisms to improve the accuracy and effectiveness of energy system planning and scheduling. In the future, the optimal scheduling of energy hub load will develop in the direction of intelligence, self-adaptability and multi-energy collaborative optimization. Using big data, cloud computing and other technologies to achieve higher levels of intelligence and adaptability, in-depth research on the collaborative optimization of various energy sources, to promote the efficient operation of the energy system and green and low-carbon development, to provide strong support for the sustainable development of the energy sector.