Chance-constrained models for transactive energy management of interconnected microgrid clusters
Transactive energy as an emerging approach and sustainable technology can provide an
exceptional opportunity for microgrids to exchange energy with each other for greater …
exceptional opportunity for microgrids to exchange energy with each other for greater …
A novel data-driven sampling strategy for optimizing industrial grinding operation under uncertainty using chance constrained programming
Multi-objective optimization of an integrated grinding circuit considering various sources of
uncertainties has been targeted in this work using Chance constrained programming (CCP) …
uncertainties has been targeted in this work using Chance constrained programming (CCP) …
Data-driven robust optimization for crude oil blending under uncertainty
Optimization of crude oil blending helps improve the operating efficiency of refineries.
However, widespread uncertainties, such as oil properties, bring difficulty in realizing this …
However, widespread uncertainties, such as oil properties, bring difficulty in realizing this …
A two-level model to define the energy procurement contract and daily operation schedule of microgrids
PL Querini, U Manassero, E Fernádez… - Sustainable Energy, Grids …, 2021 - Elsevier
A two-level energy management model that integrates energy procurement contract,
operation scheduling under uncertainty, and demand response for connected microgrids is …
operation scheduling under uncertainty, and demand response for connected microgrids is …
Enhanced branch-and-bound algorithm for chance constrained programs with Gaussian mixture models
We study a class of chance constrained programs (CCPs) where the underlying distribution
is modeled by a Gaussian mixture model. As the original work, Hu et al.(IISE Trans 54 (12) …
is modeled by a Gaussian mixture model. As the original work, Hu et al.(IISE Trans 54 (12) …
Streaming Submodular Maximization with the Chance Constraint
S Gong, B Liu, Q Fang - International Workshop on Frontiers in …, 2022 - Springer
Submodular optimization plays a significant role in combinatorial problems due to its
diminishing marginal return property. Many artificial intelligence and machine learning …
diminishing marginal return property. Many artificial intelligence and machine learning …
A two‐layer chance‐constrained optimization model for a thickening‐dewatering process with uncertain variables
H Zhang, F Wang, K Li, G Zou… - The Canadian Journal of …, 2022 - Wiley Online Library
The feed mass and the filter‐press mass per cabinet (FMP) are uncertain variables in the
thickening‐dewatering (TD) process. These uncertain variables must be considered for the …
thickening‐dewatering (TD) process. These uncertain variables must be considered for the …