Research on Multi-Energy Complementary Coordinated Scheduling Optimization Based on the Uncertainty of Source-Load Forecasting

Date: September 13, 2024 (Friday)

Time:15:30-16:10 PM

Venue: B104, Mingli Building, Lihu Campus,SZU

Host: Professor ZHANG Weiguo, College of Management, SZU

Abstract

This presentation focuses on the coordinated scheduling optimization issues in new energy power systems with multi-energy complementarity. Initially, the report quantifies the uncertainty characteristics of source-load forecasting errors by selecting uncertainty analysis methods based on the data distribution characteristics of power generation-load forecasting errors, and generates interval forecasting results. Subsequently, considering the uncertainties in wind power output forecasting on the power supply side and demand forecasting on the load side, a multi-energy complementary coordinated scheduling decision optimization plan is designed to address day-ahead rolling scheduling issues under source-load uncertainty conditions. Furthermore, based on the uncertainty analysis results of source-load forecasting, single-objective optimization models for minimizing generation costs and multi-objective optimization models for "economic efficiency-energy security-environmental protection" are constructed for the multi-energy complementary coordinated scheduling optimization in new energy power systems. Corresponding optimization algorithms are selected for solving these models, and the multi-energy complementary coordinated scheduling optimization plan is validated with actual data. Finally, the report summarizes the multi-energy complementary coordinated scheduling plan, points out its shortcomings, and suggests future research directions.

Speaker's Biography

Professor Yu Le'an is currently a Distinguished Professor and Doctoral Supervisor at Sichuan University, a selected member of the National High-Level Talents Program, an Academician of the International System and Control Academy, a Fellow of the International Information Technology and Quantitative Management Association, and a Fellow of the Asia-Pacific Artificial Intelligence Association. He has published 5 monographs and over 100 high-level papers, and has received awards such as the China Youth Science and Technology Award, the First Prize of the Ministry of Education's Natural Science Award, and the First Prize of the Beijing Science and Technology Award. His main research areas include big data intelligence, economic forecasting, fintech, and energy management.

All interested facultyand studentsare welcome to attend!