Haifeng Qiu
Southeast University
54 Papers
11 Citations
Haifeng Qiu is an academic researcher from Southeast University. The author has contributed to research in topics: Computer science & Robust optimization. The author has an hindex of 10, co-authored 27 publications. Previous affiliations of Haifeng Qiu include Cornell University.
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Papers
Optimal Planning for Electricity-Hydrogen Integrated Energy System Considering Power to Hydrogen and Heat and Seasonal Storage
TL;DR: A reasonable power to heat and hydrogen (P2HH) model with startup/shutdown constraints and a novel model of seasonal hydrogen storage (SHS) are proposed for the first time, using a combination of stochastic and robust optimization approaches to address the generation-load uncertainties.
442
Bi-Level Two-Stage Robust Optimal Scheduling for AC/DC Hybrid Multi-Microgrids
TL;DR: A bi-level two-stage robust optimal scheduling model for ac/dc hybrid multi-microgrids (HMMs) is proposed and the column-and-constraint generation algorithm is used to convert the Min-Max-Min problem of each level into a two- stage mixed-integer linear programming problem, which can be solved quickly and effectively.
154
Bi-level mixed-integer planning for electricity-hydrogen integrated energy system considering levelized cost of hydrogen
TL;DR: A bi-level mixed-integer planning model is proposed to highlight the role of hydrogen in renewable energy penetration and seasonal complementarity and can achieve the dual goals of optimizing the equipment configuration and reducing the supply price of hydrogen by rationally using resources such as wind, solar, and geothermal energy in the planning stage.
134
Robust Optimal Dispatch of AC/DC Hybrid Microgrids Considering Generation and Load Uncertainties and Energy Storage Loss
TL;DR: A novel two-stage min–max–min robust optimal dispatch model for a representative islanded ac/dc hybrid microgrid that faces uncertainties in renewable energy generation and customer loads is presented.
118
Multi-Time-Scale Rolling Optimal Dispatch for AC/DC Hybrid Microgrids With Day-Ahead Distributionally Robust Scheduling
TL;DR: A novel day-ahead distributionally robust optimization (DRO) model, based on the predicted means, deviations, and confidence probabilities of the source-load power, reduces the conservativeness of the adaptive robust optimization and provides robust day- Ahead scheduling plans.
107