Data Analytics, Forecasting, and Optimization of Smart Power and Energy Systems
To tackle the challenges of global warming, countries all around the world set aggressive goals to reduce carbon emission in different industries. As a major carbon emitter, the power and energy industry plays a vital role in decarbonization, where increasing renewable energy integration and improve energy efficiency are two effective approaches. However, high penetration of renewable energy integration challenges the reliability, economy, and flexibility of the power and energy systems. Fortunately, these challenges have come hand-in-hand with the advancements of Internet of Things (IoT), communication technology, and data science, which helps build the smart power and energy systems.
This talk will discuss three approaches to explore the flexibility and boost the efficiency of the power and energy systems. In the first part, this talk will introduce the concept of electricity consumer behavior model and then discuss how to make the best use of the fine-grained smart meter data available to process and translate them into actual information and incorporate into consumer behavior modeling and distribution system operations. In the second part, a systematic research on probabilistic load forecasting will be introduced by investigating how to model the uncertainties of the electrical load. In the third part, the talk will discuss how to model and optimize the gas, heat, and power integrated energy systems as whole so that the flexibility beyond power systems can be exploited. Future works for smart power and energy systems will be prospected.