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20212025
most citedData-Driven Distributionally Robust Scheduling of Community Integrated Energy Systems with Uncertain Renewable Generations Considering Integrated Demand Response

261 citations · 917 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025★ 4 cited

ZTFed-MAS2S: A Zero-Trust Federated Learning Framework with Verifiable Privacy and Trust-Aware Aggregation for Wind Power Data Imputation

Yang Li, Hanjie Wang, Yuanzheng Li +2

Wind power data often suffers from missing values due to sensor faults and unstable transmission at edge sites. While federated learning enables privacy-preserving collaboration wi…

eess.SY2023★ 261 cited

Data-Driven Distributionally Robust Scheduling of Community Integrated Energy Systems with Uncertain Renewable Generations Considering Integrated Demand Response

Yang Li, Meng Han, Mohammad Shahidehpour +2

A community integrated energy system (CIES) is an important carrier of the energy internet and smart city in geographical and functional terms. Its emergence provides a new solutio…

eess.SY2021★ 222 cited

Hierarchical Stochastic Scheduling of Multi-Community Integrated Energy Systems in Uncertain Environments via Stackelberg Game

Yang Li, Bin Wang, Zhen Yang +2

An operating entity utilizing community-integrated energy systems with a large number of small-scale distributed energy sources can easily trade with existing distribution markets.…

eess.SY2021★ 201 cited

Optimal Scheduling of Integrated Demand Response-Enabled Community Integrated Energy Systems in Uncertain Environments

Yang Li, Bin Wang, Zhen Yang +2

The community integrated energy system (CIES) is an essential energy internet carrier that has recently been the focus of much attention. A scheduling model based on chance-constra…

cs.LG2021★ 229 cited

Privacy-preserving Spatiotemporal Scenario Generation of Renewable Energies: A Federated Deep Generative Learning Approach

Yang Li, Jiazheng Li, Yi Wang

Scenario generation is a fundamental and crucial tool for decision-making in power systems with high-penetration renewables. Based on big historical data, a novel federated deep ge…