40 citations · 220 across the 39 of their papers we have counts for
39 papers
Competitive Online Optimization with Multiple Inventories: A Divide-and-Conquer Approach
Qiulin Lin, Yanfang Mo, Junyan Su +1
We study a competitive online optimization problem with multiple inventories. In the problem, an online decision maker seeks to optimize the allocation of multiple capacity-limited…
Optimal Online Algorithms for Peak-Demand Reduction Maximization with Energy Storage
Yanfang Mo, Qiulin Lin, Minghua Chen +1
The high proportions of demand charges in electric bills motivate large-power customers to leverage energy storage for reducing the peak procurement from the outer grid. Given limi…
DeepOPF+: A Deep Neural Network Approach for DC Optimal Power Flow for Ensuring Feasibility
Tianyu Zhao, Xiang Pan, Minghua Chen +2
Deep Neural Networks (DNNs) approaches for the Optimal Power Flow (OPF) problem received considerable attention recently. A key challenge of these approaches lies in ensuring the f…
DeepOPF: A Deep Neural Network Approach for Security-Constrained DC Optimal Power Flow
Xiang Pan, Tianyu Zhao, Minghua Chen +1
We develop DeepOPF as a Deep Neural Network (DNN) approach for solving security-constrained direct current optimal power flow (SC-DCOPF) problems, which are critical for reliable a…
Efficient and Robust Equilibrium Strategies of Utilities in Day-ahead Market with Load Uncertainty
Tianyu Zhao, Hanling Yi, Minghua Chen +2
We consider the scenario where utilities strategically bid for electricity in the day-ahead market and balance the mismatch between the committed supply and actual demand in th…
A Probabilistic Approach for Demand-Aware Ride-Sharing Optimization
Qiulin Lin, Wenjie Xu, Minghua Chen +1
Ride-sharing is a modern urban-mobility paradigm with tremendous potential in reducing congestion and pollution. Demand-aware design is a promising avenue for addressing a critical…